Identification of most suitable in-vehicle position of
mobile-phone as navigation device for minimizing
driver distraction: A study on drivers of Mobile
Application Based Taxi Services (MABTS)
A thesis submitted
in partial fulfilment of the requirements for the degree of
DOCTOR OF PHILOSOPHY
by
Indresh Kumar Verma
Department of Design
Indian Institute of Technology Guwahati
Guwahati-781039, Assam, India
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Identification of most suitable in-vehicle position of
mobile-phone as navigation device for minimizing
driver distraction: A study on drivers of Mobile
Application Based Taxi Services (MABTS)
A thesis submitted
in partial fulfilment of the requirements for the degree of
DOCTOR OF PHILOSOPHY
Submitted by
Indresh Kumar Verma
Roll No. 146105005
Under the supervision of
Dr. Sougata Karmakar
Department of Design
Indian Institute of Technology Guwahati
Guwahati-781039, Assam, India
June 1, 2021
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Dedicated to My Parents
(Shri. Yogeshwar Prasad Verma and Smt. Aruna Verma),
My Brother (Dr. Priyesh Verma)
and My Wife (Aashita Verma)
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Department of Design
Indian Institute of Technology Guwahati
Guwahati, Assam - 781039
DECLARATION
I hereby declare that the work contained in this thesis entitled “Identification of most
suitable in-vehicle position of mobile-phone as navigation device for minimizing driver
distraction: A study on drivers of Mobile Application Based Taxi Services (MABTS)” is
carried out by me, a bonafide student of Department of Design, Indian Institute of Technology
Guwahati, Assam, India under the guidance of Dr. Sougata Karmakar at the Department of
Design, Indian Institute of Technology Guwahati, Assam. This work is done for the award of
Doctor of Philosophy. It has not been submitted elsewhere for any other degree or diploma.
Date: June 1, 2021
Indresh Kumar Verma
Roll No. 146105005
Department of Design
Indian Institute of Technology Guwahati
Guwahati- 781039, Assam, India.
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Department of Design
Indian Institute of Technology Guwahati
Guwahati, Assam - 781039
CERTIFICATE
This is to certify that the work contained in this thesis entitled “Identification of most
suitable in-vehicle position of mobile-phone as navigation device for minimizing driver
distraction: A study on drivers of Mobile Application Based Taxi Services (MABTS)”
has been carried out under my guidance and supervision and is a bonafide work of Indresh
Kumar Verma. This work, submitted for the degree of Doctor of Philosophy is original and
contains no materials previously published or written by any other person for degree or diploma
at IIT Guwahati or any other institute or university. All the requirements including mandatory
coursework as per the rules and regulations as mentioned in the Ph.D. ordinance for submitting
the thesis for Ph.D. degree of Indian Institute of Technology Guwahati have been fulfilled.
Date: June 1, 2021
Dr. Sougata Karmakar, PhD
Associate Professor
Department of Design
Indian Institute of Technology Guwahati
Guwahati- 781039, Assam, India.
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ACKNOWLEDGMENT
Many people have directly or indirectly contributed to the completion of this thesis. Before
presenting this work, I would like to take the opportunity to humbly and solemnly acknowledge
all of them for their constant support and guidance.
First and foremost, I would like to express my sincere gratitude and profound thanks to
my Doctoral supervisor Dr. Sougata Karmakar for his valuable guidance during the past few
years. I will always be indebted to him for his consistent motivation and insightful support.
He showed tremendous confidence in me and was very patient, for which I shall always be
grateful to him. In his active guidance, I have learned a lot, and I express my sincere gratitude
and respect for the same.
I want to express my deepest gratitude to my doctoral committee members Prof. Debkumar
Chakrabarti, Department of Design, Dr. Pratul Kalita, Department of Design, and Dr. Swarup
Bag, Department of Mechanical Engineering, IIT Guwahati for their time, interest and insightful
comments. They consistently gave me valuable suggestions that facilitated the progress of
my research work. I am grateful to all the faculty members of the Department of Design, IIT
Guwahati for their unrelenting support during my research work and studies. I would like to
appreciate and sincerely thank all the participants for their understanding and co-operation
while performing the experimental study. Also, I would like to thank all the taxi drivers who
took part in the survey and gave their valuable feedback and suggestions. My sincere thanks to
faculty, staff, and students at the Department of Design for helping me during my stay at IIT
Guwahati. I also acknowledge the help received from Mr. Akshay Mohankar and Mr. Ayush Kr.
Das, in sketching the concept alternatives and 3D CAD modeling of the final product. I would
also like to thank all the staff members of the workshop facility at the Department of Design,
IIT Guwahati, for helping me and supporting me in creating a prototype of my product. My
friends and colleague at Ergonomics Laboratory, Department of Design, IIT Guwahati, have
contributed immensely to the completion of this thesis. My special thanks go to all my friends
at IIT Guwahati, their advice and co-operation during this research have helped me to become a
better person and stay motivated.
I want to thank my parents (Shri. Yogeshwar Prasad Verma and Smt. Aruna Verma), wife
(Mrs. Aashita Verma), and younger brother (Dr. Priyesh Verma) for their love, support, and
encouragement. They have been a constant source of inspiration and helped me in pursuing my
dreams. Without their support, this journey would not have been this easy.
Lastly, I thank almighty God for giving me strength and guiding my path during the entire
course of this thesis and my life.
Indresh Kumar Verma
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ABSTRACT
The advancement in technology has lead to the use of gadgets in our daily life. There has been
a rapid growth in the use of these gadgets in the past few decades; one such device is mobile
phones. The number of mobile phone subscribers has increased many folds in India recently.
According to the Telecom Regulatory Authority of India (TRAI), there are about 1.13 billion
mobile-phone subscribers in India as of May 2018 (TRAI, 2018b). Mobile phones are used not
only for texting and calling but also for various other purposes, ranging from booking a movie
ticket, calculators, radio, music systems, camera, a navigation system, and many more. There
has been a proliferation of these mobile phones inside the four-wheeler as well. Advancements
in communication and information technologies have led to the use of mobile phones as an
in-vehicle information system (IVIS) (Horrey, Wickens, & Consalus, 2006). These mobile
phones, used as IVIS, provide information to drivers (personal as-well-as hired car) regarding
driving and non-driving tasks (navigation, vehicle status, weather, and entertainment). The use
of mobile phones while driving causes diversion of attention from the primary task of driving,
which is one type of driver distraction (Kircher, 2007). According to Ranney et al. (2001),
driver distraction is “any activity that takes a driver’s attention away from the task of driving”.
Any distraction from rolling down a window, over adjusting a mirror, tuning a radio, and using
a mobile phone can contribute to a crash. Distracted drivers are four times more likely to be in
a crash than non-distracted drivers (Bendak & Al-Saleh, 2010).
In the past decade, there has been a growth in the taxi companies that use mobile phones
to provide their services. In the present research, these taxi service companies are referred
to as Mobile Application Based Taxi Services (MABTS). Although using a mobile phone
while driving causes distraction, its complete elimination is not possible, especially for the
MABTS drivers, since they use mobile phones for rendering their services (booking rides, fare,
navigation, etc.)
Following initial interaction with the MABTS drivers, it was observed that neither there
is a guideline by the taxi service providers nor specific locations followed by the MABTS
drivers for mounting their mobile phones for navigation purposes. The drivers placed their
mobile phones on the dashboard and around the steering wheel according to their perception of
convenience. This behavior may lead the drivers to position the mobile phones at sub-optimal
locations, which may increase their distraction (poor driving), and incidences of accidents and
near-missed chances.
Hence, there is a need to study the suitability of in-vehicle mobile phone position to ensure
the minimum adverse effect on driving performance (lane keeping, error/ lapses, maneuvering)
and minimal effort (bio-mechanical, reachability) while operating/ navigating during driving.
Particular emphasis has been given to the MABTS drivers since they are subjected to the
condition of using mobile phones and driving. Following the literature survey and pilot study,
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(1) Which are the different activities performed by the drivers of Mobile Application
Based Taxi Services (MABTS), that causes distraction?
(2) What are the presently practiced methodologies to measure driver distraction?
(3) Which is the preferred in-vehicle positions/ locations of mobile phone, for navigation
purpose, by majority of MABTS drivers?
(4) Which position (out of the various preferred locations) of mobile device is most
preferred/ optimal for navigation purpose in terms of reducing driver distraction and
enhancing driving performance?
Hence, the research presented in this dissertation aimed to identify the most suitable
in-vehicle position among the various preferred positions for mounting mobile phone (used
as navigational device) by the MABTS drivers, to minimize diver distraction and ensure less
affected driving performance. To achieve the studies’ aim, the following objectives were set.
(1) To identify the various methodologies currently practiced for measurement of driver
distraction.
(2) To identify the factors influencing driver to distract attention from primary task of
driving.
(3) To identify various in-vehicle locations/ positions which are commonly practiced by
MABTS drivers for navigation purpose.
(4) To identify the position/ location preferred by the majority of MABTS drivers for
keeping mobile phones for navigation purposes, using questionnaire survey.
(5) To identify the optimal/ most preferred in-vehicle position for placing mobile phone
for navigation purpose in terms of minimizing the bio-mechanical effort.
(6) To identify the most suitable in-vehicle position in terms of reduced driver distraction
and less affected driving performance for mounting the mobile phone (as navigational
device), among the various preferred positions by MABTS drivers.
To proceed further in research, the following hypothesis has been formulated.
H1: Driver distraction due to use of mobile phone for navigation can significantly
be reduced by identifying optimal/ most preferred position of the mobile phone
considering minimal obstruction of external view field, minimal eye/ neck movement
(to visualize the screen) and easy reach for navigational purpose.
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H2: Reduced driver distraction due to most suited position of mobile phone for navigation
purpose significantly increases the driving performance.
The overall framework of the current research was divided into five phases: problem
identification; questionnaire survey of MABTS drivers; DHM based study of mobile phone
positions; development of a novel mobile phone holder to be mounted at the center of the
steering wheel; and empirical evaluation of the in-vehicle mobile phone positions in a driving
simulator. Phase – I was the problem identification stage, where a review of literature related to
the study of this thesis was carried out, followed by identification of the research gap. During
this phase, research questions were raised, aim & objectives were set, and hypotheses were
formulated for conducting the research.
In the phase – II, a questionnaire-based survey was conducted to understand the drivers’
involvement/ engagement in distracting activities/ tasks and their preferred location for placing
in-vehicle mobile phones for navigation purposes. The study involved MABTS drivers (n =
188). The questionnaire was found to be reliable with a Cronbach’s alpha (α) = 0.72. Inferences
drawn from the outcome of the survey concluded to some interesting findings. The majority
of drivers (48.8%) preferred to keep their mobile phones on the steering wheel’s left side for
navigation purposes. It was also observed that 40.4% of drivers reported that they kept mobile
phones on the steering wheel’s right side, near the A-pillar. A small percent (10.1%) of drivers
mentioned that they change the position of their mobile phones during night/ evening, and
keep it below the dashboard. Additionally, about 22.3% of drivers reported that they reduce
the mobile phone’s screen’s brightness during the night. These behaviors could be seen as an
act of counter measuring glare from the mobile device during night/ evening. A total of ‘nine’
in-vehicle mobile phone positions (on & around the dashboard and the steering wheel) were
used in this study.
In phase – III, a digital human modeling (DHM) based study was conducted using the
CATIA-DELMIA software. This study was carried out to identify the head (rotation, flexion/
extension), torso movement, and hand reachability, required for easy information access from
different in-vehicle mobile phone position. Head rotation and flexion/ extension values were
measured for 5th, 50th, and 95th percentile digital manikins. These measurements were made
for nine different mobile phone placement locations. Reach analysis was also done to identify
which in-vehicle mobile phone positions were easily operable. An overview of all the in-vehicle
mobile phone positions in the car interior is given in figure 3.1. The minimum head rotation
was recorded for the positions ‘8’, ‘5’, and ‘2’, which were on the same vertical line and close
to the line-of-sight. Negligible head rotation (1°, 1°, 1°), and head flexion (5°, 7°, 8°) was also
recorded for position ‘5’, for the three different percentile manikins. Although, the least head
rotation was recorded for position 8, head flexion (17° – 19°) were outside the comfortable
range suggested by Kee and Karwowski (2001). Position 8 had a better hand reach than others,
and it did not obstruct the forward vision of the drivers.
Following DHM study (details in chapter 4) it was noticed that placing in-vehicle mobile
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phone at a straight forward location nearer to normal line-of-sight would reduce the neck/ eye
movement and subsequently reduce distraction. Hence, placing in-vehicle mobile phone at
position ‘5’, and ‘8’ would benefit MABTS drivers in-terms of improved driving performance.
However, no mobile phone holder which could be easily mounted at the steering wheel’s
hub (that maintains the mobile phone in vertically up-right position even when the steering
wheel rotates), could be found in the automobile accessories market. Hence, in phase – IV, an
innovative self-adjusting mobile-phone holder was developed, which can be mounted on the
hub of steering wheel, by adopting a systematic product development process. The product’s
primary requirement were, (a) it could be mounted in the center of the steering wheel, (b)
it should self-adjust and remains vertically upright even when the steering wheel rotates. A
systematic product development process was followed, which included – customer needs
identification, concept generation, concept screening, prototyping, customer feedback. The
entire process is discussed in detail in chapter 5.
To empirically examine the effect of in-vehicle mobile phone position on the drivers’ driving
performance and visual behavior, a simulated driving study in a laboratory setup was conducted
in phase – V. In this study, four highly preferred in-vehicle mobile phone positions (left, right,
front, and middle of the steering wheel) were used (details in chapter 6). The experiment was
conducted in a within subjects design, and the study subjects had to drive in a simulated road
environment, under five driving conditions (one baseline – only driving, and four dual-task
driving – driving + secondary task on mobile phone located at one of the positions mentioned
earlier). The subjects performed four secondary tasks under each of the four dual-task driving
conditions (details in chapter 6).
The hypotheses formulated at the commencement of the research were tested by fulfilling
various objectives. The DHM study’s outcome revealed that the minimum head movement
(rotation: 1°, flexion: 5° – 8°) was achieved for in-vehicle mobile phone placed at the front
position of the steering wheel for 5th, 50th, and 95th percentile manikins. The outcome of
the driving simulator-based experiment revealed that the driver distraction (in-terms of driving
performance) was minimum for front position of in-vehicle mobile phone. A repeated measures
ANOVA was conducted to find the difference (if any) in the M. Dev values, among the dual-task
driving conditions. The results of repeated measures ANOVA revealed that there is a significant
effect of driving condition (F(4,116) = 36.80, p < 0.05,η2 = 0.559, large effect size) on
M.Dev values. Further, a post hoc test using bonferroni correction revealed that significant
difference in M.Dev values exist between front and middle mobile phone positions (p < 0.05).
Among the dual-task driving scenario, the mean deviation (M.Dev = 0.68) value was minimum
for the front mobile phone position. In terms of driving workload, the front mobile phone
position was rated to be the least loading (M = 30.35). Since the front position of the in-vehicle
mobile phone was least distracting and drivers had a high perception of safety for this position,
the fixation (M = 24.64 s) and glance (M = 31.06 s) duration of the drivers was longest at front
mobile phone position. Hence, we can say that the front mobile phone position with minimum
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head rotation, and easy arm reach, has the least distracting effect (better driving performance
and visual behavior). Thus, establishing the hypothesis – 1 of the research.
The simulated driving experiment revealed that the driving performance depends on the
position of in-vehicle mobile phones used for ride-booking, navigation, checking fare, and
calling by the MABTS drivers. A repeated measures ANOVA showed that M.Dev values
differed significantly among the different driving conditions (F(4,116) = 36.80, p< 0.05,η2 =
0.559, large effect size). The best lane keeping performance (low value of mean deviation) was
achieved when an in-vehicle mobile phone was placed at the front position (p < 0.05) compared
to the other dual-task driving scenario. For lane change error, a Friedman test revealed that there
was a significant effect of driving condition (χ2(4) = 14.09, p < 0.05) on lane change errors.
The least amount of lane change error (M = 3.50) was also observed for the front position
among the different mobile phone positions. Hence, the hypothesis – 2 of the research work
was established.
The present dissertation work demonstrated a systematic research approach from the review
of existing literature, field survey to establish the rationale of research, and formulate the
problem statement. Following laboratory-based experimentation in driving-simulator, current
research has identified the most preferred location of mobile phone (as navigation purpose) in
terms of reduced driver distraction and less impact on driving performance. Current research
has employed field survey to understand the MABTS drivers’ behavior and their common
practice to position the mobile phone as navigation device. A systematic product development
strategy developed an innovative self-adjusting steering wheel-mounted mobile phone holder,
need analysis, concept generation using the morphological chart, concept selection via the Pugh
matrix, and user feedback was applied. Use of digital human modeling (DHM) techniques for
evaluating comfortable head movement (flexion/extension and rotation), and reach to various
in-vehicle mobile phone locations was unique and brings novelty in driver distraction research.
The eye-tracking was used for recording drivers’ visual behavior during performing dual-tasks
in a driving simulator in a laboratory setup to understand drivers’ driving performance and
level of driver distraction due to the different mobile phone locations. Drivers’ subjective
workload was measured using the driving activity load index (DALI) questionnaire. Statistical
analysis (repeated measures ANOVA) was performed to identify, significant difference (if any)
in the driving performance (M. Dev and lane change error), visual behavior (fixation, glance,
total-eye-off-road time), and driving workload, among the different in-vehicle mobile phone
positions. The policy-makers/ road-transport authorities can utilize the current research findings
to formulate guidelines for the efficient and safe use of in-vehicle navigation devices. It is
anticipated that this research’s outcomes would be beneficial to the wide spectrum of drivers
(both personal and professional) driving a variety of vehicle classes (auto, truck, buses, etc.)
by giving them a clear perspective on the placement of in-vehicle mobile phones. Further,
the automobile companies can use the present research outcome for judiciously placing the
in-vehicle displays for reduced driver distraction. The knowledge gained from the study about
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visual and driving behavior could be used by the designers and the ergonomists for developing
safer and user-friendly in-vehicle displays. Additionally, the industrial designers can also use
the knowledge to design mobile holders/ space integrated within the dashboard, keeping in
mind smaller visual angles for safety and usability (to guide the driver to place the mobile
device in the correct position).
Key contributions of the thesis
• The current research work addresses the widespread problem of distraction faced by
professional (taxi/ cab/ auto-rickshaw) drivers in particular and personal automobile
drivers.
• Development of in-vehicle mobile phone holder which can be mounted at the center of
the steering wheel.
• Identified the most suitable in-vehicle mobile phone position (from the existing driver
preferred positions), requiring minimal head movement (rotation and flexion/extension),
arm reach, and improved driving performance and visual behavior.
Keywords: Distraction; Driver behavior; Digital human modeling; Safety; Eye-tracking;
Simulated driving; Lane change test (LCT); Driving activity load index (DALI); Visual behavior;
Mobile application based taxi services (MABTS)
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Contents
Dedication i
Declaration iii
Certificate v
Acknowledgement vii
Abstract ix
List of Figures xix
List of Tables xxi
List of Abbreviations xxiv
1 Introduction 1
1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Research gap/ area unexplored . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.3 Research questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.4 Rationale behind the research work . . . . . . . . . . . . . . . . . . . . . . . 8
1.5 Aim and Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.6 Hypothesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.7 Framework of research work . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.8 Organization of the dissertation . . . . . . . . . . . . . . . . . . . . . . . . . 12
2 Review of literature 15
2.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2 Attention, information processing and driving . . . . . . . . . . . . . . . . . 16
2.3 Driver inattention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.4 Driver distraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.4.1 Defining driver distraction . . . . . . . . . . . . . . . . . . . . . . . 20
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2.4.2 Taxonomy and sources of driver distraction . . . . . . . . . . . . . . 21
2.5 Studies on internal sources of distraction . . . . . . . . . . . . . . . . . . . . 22
2.6 Distraction due to external sources . . . . . . . . . . . . . . . . . . . . . . . 27
2.7 Studies on drivers’ characteristics . . . . . . . . . . . . . . . . . . . . . . . 28
2.8 Studies carried out in India . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.9 Studies on location/position of in-vehicle displays . . . . . . . . . . . . . . . 30
2.10 Existing methodologies for measuring distraction . . . . . . . . . . . . . . . 31
2.10.1 Studies on naturalistic driving . . . . . . . . . . . . . . . . . . . . . 32
2.10.2 Studies on driving simulator . . . . . . . . . . . . . . . . . . . . . . 32
2.11 Variables for measuring driving performance . . . . . . . . . . . . . . . . . 39
2.12 Digital human modeling (DHM) in product design and development . . . . . 43
2.13 Innovative product design and development . . . . . . . . . . . . . . . . . . 44
2.13.1 Benefits of product development process . . . . . . . . . . . . . . . 44
2.13.2 Generic process of product development . . . . . . . . . . . . . . . 45
2.14 Conclusion to literature review . . . . . . . . . . . . . . . . . . . . . . . . . 46
3 Subjective evaluation of distracting behavior of the MABTS drivers 49
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
3.2 Material and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.2.1 Respondents of the survey . . . . . . . . . . . . . . . . . . . . . . . 50
3.2.2 Details of the questionnaire used . . . . . . . . . . . . . . . . . . . . 50
3.2.3 Procedure adopted for the survey . . . . . . . . . . . . . . . . . . . . 51
3.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3.3.1 Socio – demographic information . . . . . . . . . . . . . . . . . . . 53
3.3.2 Frequency of engagement in distracting tasks . . . . . . . . . . . . . 53
3.3.3 Preference for placing mobile phones . . . . . . . . . . . . . . . . . 53
3.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
3.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
4 DHM based study to identify comfortable viewing position for mobile-phone 61
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
4.1.1 Human view-field and head movement . . . . . . . . . . . . . . . . . 62
4.1.2 Literature on in-vehicle display position . . . . . . . . . . . . . . . . 63
4.2 Material and methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
4.2.1 Software used . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
4.2.2 Creation of the digital manikin . . . . . . . . . . . . . . . . . . . . . 65
4.2.3 Creation of the digital mock-up of the car/ taxi interior . . . . . . . . 65
4.2.4 Selection of mobile-phones positions and their placement . . . . . . . 66
4.2.5 Selection of reference points for positing driver manikins . . . . . . . 67
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4.2.6 Interfacing manikin with the CAD model of the car dashboard . . . . 70
4.2.7 Creation of the reach-envelope . . . . . . . . . . . . . . . . . . . . . 70
4.3 Experiment procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
4.3.1 Head flexion/ extension and rotation . . . . . . . . . . . . . . . . . . 71
4.3.2 Reach analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
4.4 Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
4.4.1 Head flexion/ extension . . . . . . . . . . . . . . . . . . . . . . . . . 72
4.4.2 Head rotation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
4.4.3 Physical validation involving real drivers . . . . . . . . . . . . . . . 74
4.4.4 Reach analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
4.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
4.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
5 Mounting device development for positioning the mobile phone at steering wheel’s
hub 81
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
5.2 Need/ requirement of a mobile-holder for car . . . . . . . . . . . . . . . . . 82
5.3 Methodology adopted . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
5.3.1 Customers’ need identification . . . . . . . . . . . . . . . . . . . . . 83
5.3.2 Concept generation . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
5.3.3 Concept selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
5.3.4 Creation of virtual mock-up in CAD . . . . . . . . . . . . . . . . . . 85
5.3.5 Prototype development . . . . . . . . . . . . . . . . . . . . . . . . . 85
5.3.6 Usability testing and user feedback . . . . . . . . . . . . . . . . . . 86
5.4 Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
5.4.1 Insights from the field survey . . . . . . . . . . . . . . . . . . . . . . 86
5.4.2 Generated concepts and their descriptions . . . . . . . . . . . . . . . 88
5.4.3 Final concept based on Pugh chart score . . . . . . . . . . . . . . . . 90
5.4.4 Generated CAD model and final physical prototype . . . . . . . . . . 91
5.4.5 Insights from usability testing and user feedback . . . . . . . . . . . 92
5.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
5.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
6 Experimental validation of the preferred in-vehicle mobile-phone position 99
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
6.1.1 In-vehicle display position in the driving context . . . . . . . . . . . 100
6.1.2 Lane change test for assessing driver distraction in dual-task paradigm 102
6.1.3 Research objective . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
6.2 Methods and materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
TH-2774_146105005
xviii Contents
6.2.1 Participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
6.2.2 Apparatus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
6.2.3 Experiment design . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
6.2.4 Driving task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
6.2.5 Secondary task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
6.2.6 Position of the mobile phone . . . . . . . . . . . . . . . . . . . . . . 105
6.2.7 Experimental procedure . . . . . . . . . . . . . . . . . . . . . . . . 106
6.2.8 Experiment variables . . . . . . . . . . . . . . . . . . . . . . . . . . 107
6.2.9 Statistical analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
6.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
6.3.1 Driving performance . . . . . . . . . . . . . . . . . . . . . . . . . . 108
6.3.2 Visual behaviors . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
6.3.3 Subjective workload assessment . . . . . . . . . . . . . . . . . . . . 112
6.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
6.4.1 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
6.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
7 General discussion and conclusion 119
7.1 Overall discussion of the research work . . . . . . . . . . . . . . . . . . . . 119
7.1.1 Summary of findings . . . . . . . . . . . . . . . . . . . . . . . . . . 123
7.1.2 Summary of objectives fulfillment . . . . . . . . . . . . . . . . . . . 123
7.1.3 Testing of hypothesis . . . . . . . . . . . . . . . . . . . . . . . . . . 125
7.1.4 Novelties (key contributions) of the present research . . . . . . . . . 126
7.2 Scope for future research based on limitations . . . . . . . . . . . . . . . . . 128
Appendices 133
A.1 Detailed questionnaire used in field survey . . . . . . . . . . . . . . . . . . . 135
A.2 Consent Form . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
A.3 Driving Activity Load Index (DALI) . . . . . . . . . . . . . . . . . . . . . . 141
A.4 Calculation of the DALI questionnaire . . . . . . . . . . . . . . . . . . . . . 145
A.5 System Usability Scale (SUS) . . . . . . . . . . . . . . . . . . . . . . . . . 146
A.6 Comparison between virtual and real measurements . . . . . . . . . . . . . . 147
A.7 Two-dimensional drafting of the mobile-phone holder . . . . . . . . . . . . . 148
A.8 Institute Human Ethics Committee approval letter . . . . . . . . . . . . . . . 152
A.9 List of publications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
A.10 Patent filed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
References 155
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List of Figures
1.1 Summary of the Research gap/ Area unexplored . . . . . . . . . . . . . . . . 6
1.2 Framework adopted in this research work . . . . . . . . . . . . . . . . . . . 11
2.1 Information processing during driving, adapted from Houtenbos (2008) . . . 16
2.2 Hierarchy of driving according to Michon (1985) . . . . . . . . . . . . . . . 17
2.3 Methods for assessing distraction . . . . . . . . . . . . . . . . . . . . . . . . 31
2.4 A typical classification of driving simulators (a) low-level fidelity, (b) mid-level
fidelity, and (c) high-level fidelity . . . . . . . . . . . . . . . . . . . . . . . . 33
2.5 A simulated LCT roadways with lane change sign . . . . . . . . . . . . . . . 34
2.6 LCT test track with drivers trajectory compared with normative model . . . . 35
2.7 A PLATO occlusion google, Source: (Yuan, Liu, & Fu, 2018) . . . . . . . . . 37
2.8 A time line showing occlusion and viewing interval, adapted from (Foley, 2009) 37
2.9 A summary of literature review . . . . . . . . . . . . . . . . . . . . . . . . . 42
2.10 A generic product development process . . . . . . . . . . . . . . . . . . . . 45
3.1 Vehicle interior with different mobile phone positions shown to the drivers for
ranking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
3.2 Overview of survey administered to the MABTS drivers . . . . . . . . . . . 52
3.3 Schematic diagram of methodology adopted for the questionnaire study . . . 52
3.4 Different positions of mobile phone with respect to steering wheel; (a) left, (b)
others (at the central console), (c) right . . . . . . . . . . . . . . . . . . . . . 53
4.1 Field of view showing different regions . . . . . . . . . . . . . . . . . . . . 62
4.2 Flowchart of the methodology adopted for the experiment . . . . . . . . . . . 66
4.3 Digital mock-up showing the position of a mobile-phone in relation to other
in-vehicle components (seat, steering wheel, and dashboard) . . . . . . . . . 67
4.4 Isometric view of nine different mobile positions around the steering wheel and
dashboard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
4.5 Digital human model (manikin) interfaced with a virtual car dashboard with
reference points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
xixTH-2774_146105005
xx List of Figures
4.6 Comparative visualization of head flexion/ extension for different percentile
manikins at different positions of the mobile-phone . . . . . . . . . . . . . . 73
4.7 Comparative visualization of head rotation for different percentile manikins at
different positions of the mobile-phone . . . . . . . . . . . . . . . . . . . . . 73
4.8 Comparative visualization of head flexion/ extension and rotation for different
percentile (5th, 50th, and 95th) manikins (virtual) and representative drivers
(real) of similar statures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
4.9 Extended reach-envelope from the lumber joint for (a) 5th percentile manikin
(b) 50th percentile manikin, and (c) 95th percentile manikin . . . . . . . . . . 77
4.10 Reach-envelope, with seat belt tied for (a) 5th percentile manikin (b) 50th
percentile manikin, and (c) 95th percentile manikin . . . . . . . . . . . . . . 77
5.1 A generic product development process . . . . . . . . . . . . . . . . . . . . 82
5.2 Possible location of mobile-phone on steering wheel. . . . . . . . . . . . . . 84
5.3 Relative frequency of the mobile-phone holder cost . . . . . . . . . . . . . . 88
5.4 Relative percentage of mobile phone size . . . . . . . . . . . . . . . . . . . 88
5.5 Different concepts of mobile-phone holder developed. . . . . . . . . . . . . . 89
5.6 Different views for the CAD model of mobile-phone holder; (a) rear-view, (b)
top-view, (c) side-view, and (d) perspective view . . . . . . . . . . . . . . . . 91
5.7 Exploded-view of mobile-phone holder . . . . . . . . . . . . . . . . . . . . 92
5.8 Different views of prototype mobile holder. . . . . . . . . . . . . . . . . . . 92
5.9 Two Dimensional drafting of the mobile-phone holder . . . . . . . . . . . . . 93
5.10 Percentage ratings for questions 1, 3, 5, 7, 9 of SUS . . . . . . . . . . . . . . 94
5.11 Percentage ratings for questions 2, 4, 6, 8, 10 of SUS . . . . . . . . . . . . . 94
5.12 Mean rating for different feedback questions. . . . . . . . . . . . . . . . . . 96
6.1 Experimental Setting; (a) Driving simulator (front-view), (b) Experimenter
monitoring the participant . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
6.2 Visual representation of experimental design . . . . . . . . . . . . . . . . . . 104
6.3 A screenshot of the simulated roadway . . . . . . . . . . . . . . . . . . . . . 105
6.4 Diagram showing different positions of the mobile phone w.r.t. the driver . . 106
6.5 Flowchart of the experimental procedure . . . . . . . . . . . . . . . . . . . . 107
6.6 Mean deviation of lane change at different positions . . . . . . . . . . . . . . 110
6.7 Glance duration and glance count at different mobile phone positions . . . . . 111
6.8 Fixation duration and count at different mobile phone positions . . . . . . . . 112
6.9 Total and mean eye-off-road time at different mobile phone positions . . . . . 113
6.10 DALI subjective assessment scores . . . . . . . . . . . . . . . . . . . . . . . 114
6.11 Sub-scales of DALI for driving conditions . . . . . . . . . . . . . . . . . . . 115
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List of Tables
2.1 Sources of driver distraction (internal/ external) . . . . . . . . . . . . . . . . 22
3.1 Demographic profile of the participants . . . . . . . . . . . . . . . . . . . . 54
3.2 Frequency of involvement in distracting activities . . . . . . . . . . . . . . . 55
3.3 Rankings of different mobile phone positions . . . . . . . . . . . . . . . . . 55
3.4 Perception of doing secondary activities while driving . . . . . . . . . . . . . 56
3.5 Perception of comfort and visibility of controls . . . . . . . . . . . . . . . . 57
4.1 Description of the different positions and orientations of the mobile-phone . . 69
4.2 Coordinates of H-Point for 5th, 50th, and 95th percentile driver manikins . . 70
4.3 Joint angles of head/ neck and torso of 5th, 50th, and 95th percentile manikins
when viewing the mobile-phone at nine different positions . . . . . . . . . . 74
4.4 Joint angles of head/ neck and torso of 3 real drivers (representative of 5th,
50th, and 95th percentile statures) when viewing mobile-phone at nine different
positions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
5.1 Morphological chart for Mobile-phone holder for car . . . . . . . . . . . . . 85
5.2 Questions used during user feedback. . . . . . . . . . . . . . . . . . . . . . 86
5.3 SUS scores with corresponding adjective and acceptability rating. . . . . . . 87
5.4 Pugh concept selection matrix for a mobile-phone holder for car . . . . . . . 90
5.5 System Usability Scale items and their ratings . . . . . . . . . . . . . . . . . 95
6.1 Descriptions of the secondary task . . . . . . . . . . . . . . . . . . . . . . . 105
6.2 Descriptions of mobile phones positions . . . . . . . . . . . . . . . . . . . . 106
6.3 Descriptive of the dependent variables for different test conditions . . . . . . 109
6.4 Descriptive of error in lane change at different condition . . . . . . . . . . . 109
6.5 Mean DALI scores for each task condition . . . . . . . . . . . . . . . . . . . 113
xxiTH-2774_146105005
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List of Abbreviations
η2 Effect size
ADAS Advanced Driver Assistant System
ANOVA Analysis of Variance
AOI Area of Interest
CAD Computer-Aided Design
CAGR Compound Annual Growth Rate
CDMA Code-Division Multiple Access
CMS Camera Monitor System
DALI Driver Activity Load Index
DHM Digital Human Modeling
DS Driving Simulator
ECG Electrocardiogram
EEG Electroencephalogram
GOI Government of India
GPS Global Positioning System
GSM Global System for Mobile Communications
HRV Heart-Rate Variability
HUD Head Up Display
IEA International Ergonomics Association
IHEC Institute Human Ethics Committee
ISO International Organization for Standardization
IVER In-Vehicle Event Recorder
IVIS In-vehicle Information System
xxiiiTH-2774_146105005
xxiv List of Abbreviations
LBFTS Looked-But-Failed-To-See
LCT Lane Change Test
LTE Long-Term Evolution
M.Dev Mean lateral Deviation in Lane Change
MABTS Mobile Application Based Taxi Services
MDT Mobile Data Terminal
MORTH Ministry of Road Transportation and Highways
NASA-TLX National Aeronautics and Space Administration Task Load Index
NHTSA National Highway Traffic Safety Administration
PDT Peripheral detection task
POI Point of Interest
RSME Rating Scale Mental Effort
SAGAT Situation Awareness Global Assessment Technique
SDLP Standard Deviation of the Lane Position
SDT Signal Detection Task
SMI Senso-Motric Instrument
SRR Steering Reversal Rate
SUS System Usability Scale
TDT Tactile Detection Task
TEORT Total eye-off road time
TRAI Telecom Regulatory Authority of India
VDT Visual Detection Task
WHO World Health Organization
TH-2774_146105005
— The more thoroughly I conduct scientific research, the more I believe
that science excludes atheism.
Lord Kelvin
1
Introduction
Abstract
The wave of technological advancement has touched every industrial sector. The automobile sector has
also taken advantage of this situation and introduced sophisticated mobile communication and navigation
devices in the vehicles. Unfortunately, these mobile devices have become one of the causes of driver
distraction, forming the base of the research presented in this dissertation. This introductory chapter
includes the background of present research work, research gap formulates the research questions, and
hypothesis. This chapter outlines the aim, objectives, scope, and rationale of the research work. The
framework and organization of this dissertation’s research work have been presented at the end of this
chapter.
1.1 Background
We are using technology every day in each aspect of life. Today’s technology is helping people
to connect 24×7 to their near and dear ones. A communication revolution has come up in
this era and has touched everyone. In modern world, automobiles especially four-wheeler
(passenger cars) has become an important means of commutation. Cars were built about a
century ago and thereafter they have been evolving rapidly, both in style and technology. They
are used as both, public transport (taxi services) and personal means of transportation. The
technological advancement in the field of digital electronics has captured every aspect of our
lives; digital devices and ubiquitous computing have changed the way we communicate with
each other. The automobile industry is of no exception to these events. Out of the many
factors responsible for the rapid development of the automobile industry, electronics is one of
them. With internet-enabled mobile phones and devices, we can do more than before, and their
presence in automobiles has changed the way drivers used to drive. According to MOTOROLA,
“Current production cars contain more computing power than was used to send the Apollo
spacecraft to the moon” (Damiani, Deregibus, & Andreone, 2009). An important motive behind
1TH-2774_146105005
2 1.1. Background
the current evolution process is the ability to “communicate anywhere and anytime” or to be
connected continuously.
Improvement in communication technology has brought about the revolutionary change
of continuous connectivity within the past few decades, where everyone communicates with
each other anytime. There has an escalation in mobile phone usage in the last decade because
of mobile internet connectivity. Automobile companies have taken advantage of this situation
by bringing mobile and wireless technologies into the four-wheeler, which has enriched the
capability of entertainment (infotainment), and navigation system installed in the vehicles.
These assistive technologies/ devices installed inside the car are expected to support the
driver to efficiently maneuvering the vehicle by providing information about road, traffic, and
condition of the vehicle itself (speed, temperature, fuel, etc.). Many ill-effects have also crept
in with these technologies when used inside the vehicle. One of the detrimental effects of the
technology of the 21st century is the distraction caused to the drivers commonly referred to as
‘driver distraction’. Under the condition of distraction, the driver focuses on activities that are
considered secondary or non-essential to the primary task of driving. In most cases, distracted
driving leads to cases of accidents or near-crash situations. One of the prominent causes of
death and injury has been traffic crashes. While many factors lead to crashes, major reason has
been attributed to driver distraction by many researchers (Kircher, 2007; Klauer, Dingus, Neale,
Sudweeks, & Ramsey, 2006; Klauer et al., 2014; Olson, Hanowski, Hickman, & Bocanegra,
2009; Ranney, 2008). With more sophisticated devices and smartphones being used inside the
vehicle these days, it is expected that a new variety of activities may arise that are capable of
diverting the attention of drivers from the primary task of driving. Hence, investigation of their
influence on the behavior of drivers and road safety is very essential.
Sources of driver distraction can vary significantly, however, in the past decade, cell
phone-related distractions have increased dramatically, and their impact on driving performance
is significant. Phone activity records have been used to investigate cell phones’ impact on crash
risk (McEvoy et al., 2005; Redelmeier & Tibshirani, 1997). McEvoy et al. (2005) estimated
that texting and talking on a mobile phone increases the odds of being in a crash by fourfold.
Similarly, Redelmeier and Tibshirani (1997), demonstrated that, the risk of a collision when
using a mobile phone for making or receiving calls, was four times greater than the risk when it
was not used. On the other hand, less complex tasks, such as combing/ fixing hair, retrieving
tapes/ CDs, and eating, increase the odds of being in a crash or near-crash by twofold (Klauer
et al., 2006).
The crash risk associated with driver distraction is already alarming, and this situation
is going to worsen as more technologies are introduced into the vehicles (Regan, Hallett, &
Gordon, 2011). Unfortunately, despite efforts to increase awareness of the consequences,
drivers continue to engage in activities unrelated to driving (Schroeder, Meyers, & Kostyniuk,
2013). It is crucial to understand the motivating factors or facilitators of drivers’ engagement in
distractions to maximize distraction mitigation strategies’ effectiveness.
TH-2774_146105005
1.1. Background 3
Driver distraction and incidences of near crash & accidents
Vehicles in the recent times are getting fitted with numerous instruments due to rapid
advancement in technology and customer needs. However, there is an increasing concern
related to inattention, mental workload and reduction of driving performance. Distraction
occurs when the driver shifts attention from driving (referred to as a primary task) to any other
activity (secondary task), which is not critical for safe driving. Driver Distraction is one form of
inattention. Driver gets distracted when interacting with instruments inside the vehicles, which
are meant to help and support in driving. In recent years, drivers are using mobile phones inside
the vehicle either as an assistive or communication device. Using mobile phone while driving
causes the driver to take their eye-off road, hands-off steering wheel, and mind away from the
road and surrounding situation. Global body like, WHO has recognized driver distraction as a
major cause of road traffic injuries (WHO, 2011).
Global scenario of distraction and accidents
Globally, the concern about driver inattention and distraction is increasing. Studies have shown
that involvement in the secondary task while driving impairs driving performance, leading to
serious road-traffic safety concerns. There has been a gradual increase in the use of mobile
phones while driving and is becoming a common driver distraction. Studies have shown a
four-fold increase in the risk of accidents when mobile-phone (for talking or texting) is used
while driving (Redelmeier & Tibshirani, 1997). According to the ‘100-car naturalistic study’
completed in the US suggests that 80% crashes and 65% of near-crash incidences are accounted
for driver inattention. In Spain, approximately 20% drivers were involved in some kind of
secondary tasks while driving, talking to the passenger (11.1%), smoking (3.7%) and talking
on the handheld phone (1.3%) (Prat, Planes, Gras, & Sullman, 2015). In New Zealand, about
52.3% of driver reported sending and 66.2% reported reading messages while driving (Hallett,
Lambert, & Regan, 2012). In the UK, it was reported that about 14% of drivers send text
messages whereas 25% read text messages while driving (Lansdown, 2012). In a similar
epidemiological study in the US, it was observed that 16.6% of drivers texted or dialed and
31.4% talked on phone (Huisingh, Griffin, & McGwin, 2014). Countries like the United States
have a separate institute like NHTSA, which is heavily investing in studying, understanding,
and developing methods to mitigate the effect of distraction. Sources of driver distraction
can vary significantly. However, in the past decade, mobile-phone related distractions have
increased dramatically and their impact on driving performance has been found significant.
Sources of distraction to drivers can either be external or internal, depending on where they
occur with respect to the vehicle.
External Source: These sources of distraction are those activities/ elements/ things that occur
outside the vehicle. These include roadside advertisements, billboards, pedestrian, signs
in traffic/ highways.
TH-2774_146105005
4 1.1. Background
Internal Source: It consists of all the elements/ activities/ things that occur inside the vehicle.
They include talking/ texting on mobile-phone; talking to passengers; eating, drinking,
smoking; operating in-vehicle instrument; listening to radio/ music/ entertainment system.
Mobile phones subscribers – global overview and scenario in India
According to “Ericsson’s mobility report,” the mobile subscriptions around the world was
around 7.9 bn in the Q3 of 2018, it also estimated 8.9 bn subscribers by 2024 (Ericsson, 2018).
There has been numerous fold increase in the subscribers of mobile phone. About two decades
ago, in 1997, India’s Telecom market was a modest 14.5 million phone connections, with
an initial policy of “telephone on demand.” However, now in July 2018, the Indian Telecom
industry is 2nd largest globally, with over 1.17 billion telecom subscribers, out of which
1.15 billion are wireless (GSM, CDMA & LTE) subscribers, and 22.27 million are wire-line
subscribers (TRAI, 2018a). According to TRAI, the urban telecom subscribers (wireless) are
639.71 million, whereas rural telecom (wireless) subscribers are 517.33 million as of July 2018.
The telecom sector has seen exponential growth because of 4G, inexpensive tariffs, mobile
number portability, and a conducive regulatory environment.
Growth of automobile in India
India has seen a rapid increase in motorized vehicle usage due to sustained economic growth.
According to report of Ministry of Road Transportation and Highways (MORTH), GOI, 2018,
the number of registered vehicles in India is over 253 million, and in the period between 2007 –
2017, it has grown at a compound annual growth rate (CAGR) of 10.11%. During the years
2010 – 17, the number of registered motor vehicles in India increased at a CAGR of 10.3%,
increasing the vehicle density from 28 per km in 2007 to 42.95 per km in 2017. Road users
are at a high risk of accidents since the same road is being used by a variety of motorized,
non-motorized, and pedestrians (MORTH, 2018). During the decade of 2005 – 15, the highest
CAGR of 10.7% was registered for car, taxis, and jeeps combined, followed by 10.1% for
two-wheeler, 8.8% for goods vehicle, and 8.2% for buses. For every 1000 people, the number
of vehicles has increased from 8 in 1981 to 167 in 2015 (MORTH, 2016).
Road accident scenario in India
In 2015, India signed the Brasilia Declaration in the road safety conference held in Brazil.
In 2016, road traffic-related accidents had taken more than 1.35 million lives globally and
continue to be the chief concern of public health (MORTH, 2018). According to the World
Road Statistics 2018, India is ranked 1 out of 199 countries in road accident deaths, followed
by China and the U.S (MORTH, 2018). Road accidents are multi-causal and occur due to a
combined influence of errors by humans, defects in vehicles, roads, external circumstances
like visibility, glare, weather, etc. The rapid expansion of the road network and motor vehicles
TH-2774_146105005
1.1. Background 5
has resulted in a rise in India’s road traffic accidents. These accidents have resulted in injuries,
fatalities, disabilities, and hospitalization with severe socioeconomic costs. According to the
World Health Organization (WHO), among the causality of deaths, accidents are ranked eight
and first among children between 5 – 14. According to the WHO’s “Global Report on Road
Safety 2018”, 11% of the accidents related to death in the world happens in India (WHO, 2018).
In the age group of 15 – 49, deaths due to accidents is ranked fourth in India. Based on the
report, “Road Accidents in India 2018” published by MORTH, during 2018, the total reported
accidents in India was 4,67,044, which injured 4,69, 418, and killed 1,51,417 people (MORTH,
2018). Compared to 2017, there has been an increase of 0.46% in road accidents in the year
2018. The number of persons killed and the number of injuries have increased by 2.37%
and 0.33%, respectively, in 2018. In the year 2018, two-wheeler were responsible for 35.2%
(maximum) of the accidents , killing a total of 31.4% and injuring 32.7% of the people, whereas,
car/taxi/van caused 24.3%, and 12.3% of the accidents were because of truck/ lorry (MORTH,
2018). Wearing a helmet has been made mandatory, and penalties have been increased via the
amended Motor Vehicle Act passed in 2019 (MORTH, 2018). Road accidents happen due to a
variety of reasons and their interplay. In 2018, over- speeding was the prime reason in 66.5% of
the cases, whereas the wrong side/lane indiscipline accounts for 5.3% of accidents. Alcohol
consumption, red-light violation, and using mobile-phone while driving together account for
6.5% of accidents (MORTH, 2018). Distraction while driving can lead to serious road accidents.
The activity of driving and simultaneously talking on mobile phones is of prime concern, and
a cause of road accidents. It is recently being reported as a causal factor for road accidents.
During the year of 2016, using a mobile phone while driving caused 4,976 road accidents,
causing 2,138 fatalities and 4,746 injuries (MORTH, 2016). Whereas in the year 2017, the use
of mobile phones has resulted in 8,526 number of accidents, causing 3,172 deaths and 7,830
number of injuries. It is important to note that during 2018, accidents and deaths decreased due
to red-light violation, over-speeding, lane indiscipline, and drunk driving. However, accidents
and deaths related to mobile phone use increased in 2018 compared to 2017 (MORTH, 2018).
The subscribers of mobile-phones and its use while driving has shown rapid growth in the past
couple of years. During the last decade there has been a rise in the mobile application based
taxi service (MABTS) companies which utilize mobile phones for providing their services.
A few examples of these MABTS companies in India include, ‘OLA’, ‘Uber’, ‘Meru Cabs’,
‘Carzonrent’, ‘Savaari’. The drivers of these MABTS companies are more vulnerable to mobile
phone based distraction, since they use mobile phones for rendering their services (car booking,
navigation, fare, etc.). There is a need to promote, conduct research & development activities,
education, and awareness programs to face the challenges presented by the upcoming in-vehicle
technologies. A recent survey was conducted by the SaveLIFE foundation with the support of
Vodafone India to explore the current scenario of driver distraction due to the use of the mobile
phone in India. The survey took place in eight different cities. It was found that about 47%
of drivers received calls on the mobile phone while driving, whereas 28% made calls while
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6 1.2. Research gap/ area unexplored
driving (SaveLIFE, 2017).
1.2 Research gap/ area unexplored
A good amount of work pertaining to driver distraction has been done in different countries
like the Philippines, Portugal, Germany, Denmark, USA, UK, and Canada (Alconera, Garcia,
Christine Mercado, & Portus, 2017; Cordazzo, Scialfa, Bubric, & Ross, 2014; Ferreira, Simões,
Piccinini, & Rôla, 2013; Martinussen, Hakamies-Blomqvist, Møller, Özkan, & Lajunen, 2013;
Metz & Krueger, 2010; Simons-Morton, Guo, Klauer, Ehsani, & Pradhan, 2014; M. S. Young
& Mahfoud, 2007). It is also evident that research work regarding the influence of age, gender,
experience on distraction of drivers have also been carried out. As compared to the work
carried out in different countries, the amount of work reported in Indian Scenario is very less.
Following literature review, it has been observed that there are various unexplored areas where
further research are needed to be carried out to maximize driver distraction for ensuring safe
and efficient driving. Various research gaps demonstrated in figure 1.1, are listed below.
Driver 
Distraction
Studies in different Countries: Philippines (Alconera et al., 2017), 
Portuguese (Ferreira et al., 2013), Germany (Metz krueger, 2010), 
Denmark (Martinussen et al., 2013), Australia(Hosking et al., 2009), 
Canada(Cordazzo et al., 2014), USA (Simons-Morton et al., 2014), UK 
(Young & Mahfoud, 2007)
Methodologies for measuring driver distraction 
(Xie et al., 2013, Benedetto et al.,2011, Giang et 
al., 2014, Baumann et al., 2004, Harbluk et al., 
2009, Van~Winsum et al., 1999)
Talking on Cell phone (stayer et al., 2003), 
navigation system (Emmerson et al.,2013), 
Conversation with passengers (Drews et al.,2008), 
Music / radio (Hughes et al., 2013), in-vehicle 
information system (Benedetto et al.,2011), Eating, 
drinking, smoking, alcohol (Young et al., 2008)
Drivers Characteristics: Age (Woo & Lin, 2001), Gender 
(Irwin et al., 2011), Experience (Nabatilan et al., 2011), 
Driving behaviour 
Mobile Application 
Based Taxi Services 
(MABTS)
Position of mobile 
phones
Mobile for 
navigation purpose
Taxi drivers
Studies Conducted in Indian Scenario 
(Choudhary and Velaga, 2017a, 2017b, 2017c; 
Radakrishnan et al., 2016; Ganesh et al., 2015; 
Rajesh et al., 2017)
Explored area
Unexplored area
Figure 1.1: Summary of the Research gap/ Area unexplored
• Following the literature review, clear research gap has been identified regarding lack of
guideline/ standard in national/ international scenario for optimal positioning of mobile
phone (as portable navigation system) to minimize distraction. Neither there is a guideline
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1.3. Research questions 7
by the service providers, nor there are specific locations followed by the MABTS drivers
for mounting their mobile for navigation purpose.
• Drivers are exposed to many in-vehicle communication/ navigation devices these days.
Many researches have reported the impact of using mobile phones while driving. However,
there is rarely reported study on distracting effect of using mobile phone for navigation
purpose by MABTS drivers.
• The existing studies on driver distraction are limited only to in-vehicle display (Camera
monitor system, MDTs) positions (Beck, Lee, & Park, 2017; McKinnon, Callaghan,
& Dickerson, 2012) and have not considered positioning of mobile phone (as portable
navigation system) to minimize distraction.
• Large number of research work are being carried out on different types (manual/ voice
control) of navigation systems (Chiang, Brooks, & Weir, 2004; J. Harbluk, Burns,
Lochner, & Trbovich, 2007; Maciej & Vollrath, 2009). There is rarely reported study on
the effect of position of mobile phone (used for navigation) on driving performance as
well as on driver distraction.
• There are research related to influence of driver characteristics on distraction (Irwin,
Chekaluk, & Geaghan, 2011; Nabatilan, Aghazadeh, Nimbarte, Harvey, & Chowdhury,
2012; WOO & LIN, 2001) but rarely any study considering the drivers of MABTS.
• A good deal of research is already going on in other parts of the world (US, UK, Australia,
Canada, Germany, Denmark, Philippines), but significant knowledge base in Indian
scenario is absent.
1.3 Research questions
Based on the above research gaps, and initial interactions with the MABTS drivers, a set of
research questions were raised as listed below.
Q1: Which are the different activities performed by the drivers of MABTS, that causes
distraction?
Q2: What are the presently practiced methodologies to measure driver distraction?
Q3: Which is the preferred in-vehicle positions/ locations of mobile phone, for navigation
purpose, by majority of MABTS drivers?
Q4: Which position (out of the various preferred locations) of mobile device is most preferred/
optimal for navigation purpose in terms of reducing driver distraction and enhancing
driving performance?
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8 1.4. Rationale behind the research work
1.4 Rationale behind the research work
The mobile-phone subscribers in India has risen rapidly in the recent years. According to the
Telecom Regulatory Authority of India (TRAI), there are about 1.13 billion mobile-phone
subscribers in India as of May 2018 (TRAI, 2018b). With technological advancement, most of
the drivers (personal as-well-as hired car) use mobile-phones as a portable navigation device
for cars.
Literature review indicates that distracted driving due to the use of the mobile phone (texting,
talking, navigating, etc.) has been identified as the significant cause of road-accident (Kircher,
2007; MORTH, 2014, 2018). Researchers empirically examined the effect of the positions of car
navigation display on eye movement and braking reaction time (Itoh, Yamashita, & Kawakami,
2005). The earlier studies (Beck et al., 2017; McKinnon et al., 2012) related to the position of
in-vehicle displays (Camera monitor system, MDTs) and infotainment system (Radakrishnan,
Dharmar, Balakrishnan, & Padattil, 2016) showed that positions of displays affect driver
distraction and thereby driving performance. Ishiko et al. (2013) evaluated two different sizes
of navigation systems at three locations for driving safety, based on gaze data and subjective
rating. Wittmann et al. (2006) attempted to determine the relative safety of onboard display
positions and concluded that drivers’ performance is disturbed exponentially as a function of the
distance between the on-road line of sight and the onboard display position. A comparison of 3
different locations and sizes of in-vehicle displays was performed by Doi, Murata, Moriwaka,
and Osagami (2019) to evaluate driving performance as a measure of driver distraction.
According to the Anti-Distracted Driving Act (ADDA), RA 10913 of The Republic of
Philippines, placing navigational devices/ mobile phones beyond the defined safe zone is
prohibited, as this area is around the line of sight region. This act considers only the driver’s
horizontal line of sight and does not specify the ideal location of the navigation device (LTO,
2017).
De Lumen, Lim, Orosa, Paralleon, and Sedilla (2019), based on their study on 3 different
positions of the navigation devices for Transportation Network Vehicle Services (TNVS),
showed that the driver’s distraction level is significantly affected by the position of the navigation
device. In the earlier reported studies, only three or four different locations of the in-vehicle
displays were examined, whereas mobile phones, due to their small size and availability of
diverse types of holders, are being conveniently placed by the drivers at different positions
around the steering wheel, dashboard, mid-console and windshield as the portable navigation
systems. Moreover, the driver’s comfort and safety in biomechanical effort and reachability are
still unexplored.
Stating the aforesaid literature review, it can be concluded that driver-distraction due to the
varied position of the in-vehicle navigational device (like mobile-phone) might impact driving
performance and thereby the possibility of the road accident. Thus, the identified research
problem and its corresponding hypothesis are based on literature review and field observation
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1.5. Aim and Objectives 9
of diverse mobile phone positions as navigational devices. Here, it is worthy of mentioning that
the aim of the present research is to study the influence of mobile-phone positions on driver
distraction and thereby driving performance but not directly related to accident data.
In India, MABTS companies like ‘OLA’ and ‘Uber’, are using mobile-phone applications
for executing their services. Although mobile phone is a major cause of distraction, its complete
elimination is impractical, as it has become an inevitable part of driving, particularly for the
drivers of Mobile Application-Based Taxi Services. It was observed from the field study that
mobile-phone used for navigation purpose was generally mounted at different locations on and
around the dashboard and steering wheel, as per the driver’s perception of convenience (Verma
& Karmakar, 2017). Neither there is a guideline, nor there are specific locations followed by
the MABTS drivers for mounting their mobile-phone for navigation purpose. Positioning the
in-vehicle mobile phone at un-optimal location would reduce the driving performance and
increase the chances of accidents for the drivers. Hence, there is a need to study the suitability of
in-vehicle mobile phone position to ensure the minimum adverse effect on driving performance
(lane keeping, error/ lapses, maneuvering) and minimal effort (bio-mechanical, reachability)
while operating/ navigating during driving.
Delimitations of the thesis
The pinpoint the research scope following constraints have been imposed on the research design.
• The research in this thesis only considered male MABTS drivers.
• The study presented in this thesis deals with only passenger cars used for MABTS
services. Generally, such taxi services do not use high-end cars where facilities like
voice-activated user-interface, Head-Up Display (HUD), advanced driver assistance
system, and satellite navigation system enabled automotive technologies are present.
• The study presented in this thesis only considers the identification of suitable in-vehicle
mobile phone positions based on the laboratory-based experiment in a low-fidelity
simulator.
1.5 Aim and Objectives
Aim
The aim of this study is to identify the most suitable in-vehicle position among the various
preferred positions for mounting mobile phone (used as navigational device) by the MABTS
drivers, to minimize diver distraction and ensure less affected driving performance.
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10 1.6. Hypothesis
Objectives
Following objectives were set to achieve the aim.
1: To identify the various methodologies currently practiced for measurement of driver
distraction.
2: To identify the factors influencing driver to distract attention from primary task of
driving.
3: To identify various in-vehicle locations/ positions which are commonly practiced by
MABTS drivers for navigation purpose.
4: To identify the position/ location preferred by the majority of MABTS drivers for keeping
mobile phones for navigation purposes, using questionnaire survey.
5: To identify the optimal/ most preferred in-vehicle position for placing mobile phone for
navigation purpose in terms of minimizing the bio-mechanical effort.
6: To identify the most suitable in-vehicle position in terms of reduced driver distraction
and less affected driving performance for mounting the mobile phone (as navigational
device), among the various preferred positions by MABTS drivers.
1.6 Hypothesis
To proceed further in research the following hypothesis has been formulated.
H1: Driver distraction due to use of mobile phone for navigation can significantly be reduced
by identifying optimal/ most preferred position of the mobile phone considering minimal
obstruction of external view field, minimal eye/ neck movement (to visualize the screen)
and easy reach for navigational purpose.
H2: Reduced driver distraction due to most suited position of mobile phone for navigation
purpose significantly increases the driving performance.
1.7 Framework of research work
The study presented in the thesis attempted to find the most preferred/ suitable location for
placing the mobile phone, used as a navigation device.
Figure 1.2 shows the research framework adopted to achieve the goals of this dissertation. The
research framework is presented into five phases. Phase – I was the problem identification
stage, where a review of literature related to the study of this thesis was carried out, followed
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1.7. Framework of research work 11
P
h
a
se
 I
P
h
a
se
 I
I
P
h
a
se
 I
II
P
h
a
se
 I
V
 Literature Survey
 Research gap
 Problem Identification
 Defining Research Question
 Hypothesis
 Defining Aim & Objectives
 Data collected from 188 taxi drivers
 Identification of distracting behaviour 
involvement
 Identifying all possible  mobile phone 
positions and relative preference F
ie
ld
 S
u
rv
ey
D
H
M
 b
as
e
d
 S
tu
d
y
Semi-structured 
questionnaire and interview
Digital human modelling 
simulation in DHM 
software
Identification of most suitable mobile 
phone location in-terms of least 
biomechanical load of information access 
by head flexion/ extension and rotation and 
reachability analysis.
E
m
p
ir
ic
al
 s
tu
d
y
in
 l
ab
o
ra
to
ry Empirically identify the most 
suitable in-vehicle mobile phone 
position in terms of driving 
performance and visual behaviour
Driving simulator and 
eye tracking glass
In
n
o
v
at
iv
e 
p
ro
d
u
ct
 
d
ev
e
lo
p
m
e
n
t
Development of an innovative self-
adjusting steering wheel based mobile-
phone holder. 
A systematic product 
development approach 
P
ro
b
le
m
 
id
e
n
ti
fi
ca
ti
o
n
P
h
a
se
 V
Milestones Methodological 
approach
Objective 
fulfilled
Objective 
1 and 2
Objective 
3 and 4
Objective 5
Objective 6
Objective 6
Figure 1.2: Framework adopted in this research work
by identification of the research gap. During this phase research questions were raised, aim &
objectives were set, and hypothesis were formulated for conducting the research.
In phase – II, field study was conducted to identify the extent of MABTS drivers’
involvement/ engagement in distracting task and their preference of location for placing the
in-vehicle mobile phone used as a navigation device. In this phase, data was collected from the
drivers using a semi-structured questionnaire and a few open-ended questions. The questionnaire
survey was used to identify the involvement of drivers in various distracting task while driving.
In this phase, drivers ranked the different mobile phone locations around the dashboard and
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12 1.8. Organization of the dissertation
steering wheel.
In phase – III, a digital human modeling (DHM) based study was conducted using the
CATIA-DELMIA software. This study was carried out to identify the head (rotation, flexion/
extension), torso movement, and hand reachability, required for easy information access from
different in-vehicle mobile phone position. Head rotation and flexion/ extension values were
measured for 5th, 50th, and 95th percentile digital manikins. These measurements were made
for nine different mobile phone placement locations. Reach analysis was also done to identify
which in-vehicle mobile phone positions were easily operable.
In phase – IV, an innovative self-adjusting mobile-phone holder was developed, which
can be mounted on the hub of steering wheel, by adopting a systematic product development
process. The outcome of DHM based study in the previous phase revealed, if the mobile
phone is placed at the center of the steering wheel, there would be minimum head rotation,
flexion/ extension and torso movement. Hence, a steering wheel based mobile-phone holder
was developed so that an empirical study could be carried out to identify the most suitable/
preferred position of mobile phone.
During phase – V, an empirical study was carried out on a driving simulator in a laboratory
setup. In this study, the drivers’ driving performance was measured using the lane change task
(LCT), and visual behavior was measured using the eye-movement recorder. This study was
conducted by placing the mobile phones at four highly preferred locations (left, right, front,
and middle of the steering wheel) to identify the most preferred position.
1.8 Organization of the dissertation
This dissertation comprises seven chapters. A brief description of these chapters is presented
here. Chapter 1 provides the state-of-art literature review in concise form. It deals with
the identification of research gap, raising research questions, setting the aim & objectives,
formulation of hypothesis, and finally description of research framework.
Chapter 2 gives an overview of the literature covering the previous studies relevant to the
study taken up in this dissertation. The topics covered in this chapter include attention and
its importance in driving, theories related to attention allocation, a brief discussion about the
definition of driver distraction, inattention, taxonomy, and sources of distraction. This chapter
presents different methodologies (naturalistic and simulator-based), various objective and
subjective measures of distraction adopted in driver behavior research. A detailed description
of the field, simulated, and experimental studies of this study are in chapters 3, 4, 5, and 6.
Chapter 3 gives a detailed description of the field study conducted on MABTS drivers to
understand their involvement in different distracting activities. This chapter also presents the
drivers’ preference position for placing in-vehicle mobile phones and their justification.
Chapter 4 gives details about digital human modeling (DHM) based study. The work
presented in this chapter tries to understand the most suitable position for placing the in-vehicle
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1.8. Organization of the dissertation 13
mobile-phone based on head rotation, flexion/ extension of percentile manikins (5th, 50th, and
95th). Reach analysis of different in-vehicle mobile-phone positions is also presented.
Chapter 5 discusses the process involved in the development of a novel self-adjusting
steering wheel based mobile phone holder. This chapter gives a detailed description
of the product development process starting from concept generation, concept selection,
morphological, and pugh chart matrix used to develop the mobile phone holder for the steering
wheel’s hub. The developed product was evaluated using the system usability scale (SUS) and
user feedback was taken.
Chapter 6 discusses an empirical study to find the most suitable position of the in-vehicle
mobile phone. Different in-vehicle mobile phone display positions were evaluated based on
driving performance and visual behavior on a driving simulator. Lane change test (LCT) was
used to perform simulated driving, and an eye-tracker was used for measuring visual behavior.
Variations in driving performance and impact of driver distraction due to different mobile phone
positions are graphically presented.
Chapter 7 summarizes the entire research work presented in the thesis (starting from the
questionnaire survey of MABTS drivers, through DHM based virtual ergonomic evaluation
of the different in-vehicle mobile phone position, development of the novel mobile phone
holder for the steering wheel’s hub, and finally the empirical study on a driving simulator in a
laboratory setup to identify the most suitable in-vehicle mobile phone position for minimized
driver distraction and better driving performance). This chapter also presents the key findings
and limitations of the thesis. Furthermore, this chapter also describes the testing of hypothesis
and contributions (knowledge-base, methodology, society, and industry) of the research.
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TH-2774_146105005
— You have to dream before your dreams can come true.
A. P. J. Abdul Kalam
2
Review of literature
Abstract
Before carrying out the research, it is essential to study and understand the existing literature
on the topic under consideration. The chapter presents a comprehensive review of the literature
on driver distraction. Different theories of attention allocation and driving are discussed at
the start, followed by various studies and empirical work previously done in the field of driver
distraction. This chapter also touches a variety of areas related to driver distraction (definition,
taxonomy, sources). Different aspects that may lead to distraction and different methods for
measuring distractions are also presented in this chapter.
2.1 Overview
Driving is a complex task requiring visual and manual senses to be engaged. Drivers draw about
90% of their information from visual senses and process this information, and as a feedback,
they perform manual maneuvering of the vehicle. Drivers are required to focus their attention
on the road to maintain self and other road commuters’ safety. If the driver deviates their focus
from the primary task of driving, then the chances of accidents and near-crash situation arises.
This condition of the driver not focusing on driving tasks is termed as ‘Driver distraction.’ Many
factors fuel this problem of the driver being distracted from driving. For understanding the
domain of driver distraction, a systematic survey of the literature was carried out. Scholarly
databases of ‘Science Direct’, ‘Scopus,’ and ‘Web of Science’ were searched; keywords used in
this search were ‘driver distraction,’ ‘driver behavior,’ ‘driver inattention,’ ‘distracted driving.’
Different theories of attention, information processing, and driving are presented at the
start, followed by the definition of inattention and distraction suggested by various researchers.
Sources of distraction (internal/ external) and their related studies, methodologies for measuring
distraction, and different distraction measurement metrics mentioned in the literature are
presented in vivid detail.
15TH-2774_146105005
16 2.2. Attention, information processing and . . .
2.2 Attention, information processing and driving
To understand distraction the basic understanding of the context of driving task, information
processing, and attention allocation is necessary. Figure 2.1, shows the information processing
during driving. This model was proposed by Houtenbos (2008), and is based on the information
processing model proposed by Endsley (1995); Wickens, Hollands, Banbury, and Parasuraman
(2015) with addition of concept of expectancy. On a basic level, humans take information about
their environment, then process the data and then responds according to the situation (Eysenck,
2000). However, all the information is not processed at the same time. Even though there is a
stimulus, one may not respond to it if another stimulus is answered at the same time.
Short term 
Sensory 
Processing
Perception
(SA1)
Interpretation
(SA2)
Projection
(SA3)
Decision 
Making
Attention
Long Term Memory
Short Term
expectancy
Long Term
expectancy
Road user x
Mental
Models
Figure 2.1: Information processing during driving, adapted from Houtenbos (2008)
The process of attention helps to allocate one’s available resources on a portion of
environment assisting when stimuli are difficult to perceive in the execution of a simultaneous
task, and when people are overloaded with information. Attention can either be directed
voluntarily or drawn by external stimuli. During driving, attention can be guided by the
expectation or by sudden changes in the environment. Thus, attention can be focused (only
listening to music) or divided (listening to music while driving) (Eysenck, 2000).
Driving is made-up of a number of tasks and driver has to allocate attention to all of them.
Michon (1985) depicted driving as a hierarchy. There are three levels; the strategic level,
manoeuvring level and control level. At the strategic level the rout, trip goal, and the modal
choice are planned. At the manoeuvring level, the driver negotiates curves, junctions, and
obstacles by the use of common driving manoeuvres. At the control level the driver performs
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2.2. Attention, information processing and . . . 17
automatic actions, which include braking, gear changes and steering. The time required for
each activity at different levels decrease as we move from strategic to control level.
Strategic Level
Manoeuvring level
Control Level
General Plan
Controlled action 
patterns
Automatic action 
patterns
Route Speed criteria
Feedback 
criteria
Time scale
Long
Seconds
Miliseconds
Environmental 
Input
Figure 2.2: Hierarchy of driving according to Michon (1985)
The Contextual Control Model (COCOM) of driving is mainly focused on performance
rather than information processing (Hollnagel, 1993). Human action cycle is mainly based upon
ideas, which are driver’s knowledge of and assumptions about the situation. Based on these
ideas, driver will perform certain actions, which will invoke an event and there is feedback to
the action. The disturbances in the event and the environment, influence the idea and the cycle
continues. This model is based on role of situational awareness in generating these ideas.
According to Endsley (1995), situational awareness in driving can be described as
1. Perception of elements in the current driving situation.
2. Comprehension of the current driving situation.
3. Projecting the future characteristics of the driving situation.
Thus the driver has to take in information from the environment by ‘attention’, process
the information to understand the situation and foresee how it might change and respond
accordingly.
The driver can allocate attention to two or more things at the same time and also perform
well, if there are sufficient resources to cope up with the requirement of the task. There are
some theories that have tried to explain the human capacity and allocation of resources.
1. Single Resource Theory: This theory suggests that only a single pool of resources
is available for doing the task and task performance is dependent upon whether
or not sufficient capacity is being allocated from this pool for doing this task.
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18 2.3. Driver inattention
Allocation of resources is dependent upon persons strategy, characteristic and his
motivations (Kahneman, 1973; Norman & Bobrow, 1975).
2. Multiple Resource Theory: It suggests that there are separate pools of resources for special
and verbal information processing, different modalities, stages of information processing
and motor versus verbal response. These resources may be jointly or independently
utilized depending upon the task demand (Wickens, 1991).
3. Malleable Attention Resource Theory: According to this theory there is a separate pool
available for information processing and the size is positively dependent upon mental
worked-load up to a certain limit. Hence, a large reduction in mental workload can
temporarily cause shrinkage in this capacity (M. S. Young & Stanton, 2002).
4. Control Architecture: According to this common resources can be shared effectively
between two or more completing tasks true practice. Thus drivers experience of using
certain systems can influence driving performance (Schneider & Detweiler, 1988).
Eysenck (2000) concluded that when task attention is divided between task then the
performance is dependent upon first task similarity second task difficulty third practice. It is
argued that practice can improve the dual task performance. This concept draws its similarity
from the concepts of automatic and controlled processes (Shiffrin & Schneider, 1977).
1. Automatic processes are employed in performing highly practiced task that don’t require
any thought. They place minimal demand on the information processing of the humans.
2. Controlled processes are needed in new situations. Thus task is carried out serially. This
kind of processing is slow and strenuous, but powerful.
In some driving scenarios the driver voluntarily allocates some attention to the secondary task
and in some other situations, their attention is automatically drawn towards certain things or
stimulus. In both the cases, driver is distracted from the primary task of driving. In this way the
safety of the driver as well as other road users is jeopardized.
2.3 Driver inattention
Driver inattention and distraction are the major contributing factor in car crashes and accidents,
and this problem will escalate exponentially as more and more in-vehicle devices/ technologies
find their way into the vehicle. It is essential first to understand what is Inattention and
distraction, to understand the problem of distraction among drivers. Often these two terms are
used interchangeably.
According to Shorter Oxford English Dictionary, 2002, Inattention is defined as “failure
to pay attention or take notice.” However, this definition is devoid of the context of driving.
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2.4. Driver distraction 19
In literature, there are only a few definitions of driver inattention with varying meanings.
According to J. D. Lee, Young, and Regan (2008), driver in-attention is “diminished attention
to activity critical for safe driving in the absence of competing activity.”
Treat (1980), says driver inattention happens “whenever a driver is delayed in the recognition
of information needed to safely accomplish the driving task, because of having chosen to direct
his attention elsewhere for some non-compelling reason.”
Klauer et al. (2006), defines inattention as, “any point in time that a driver engages in a
secondary task, exhibits symptoms of moderate to severe drowsiness, or looks away from the
forward roadway”.
Talbot, Fagerlind, and Morris (2013), defined driver inattention as “low vigilance due to
loss of focus.” Some crash studies have defined driver inattention as “when the driver’s mind
has wandered from the driving task for some non-compelling reason” such as when the driver
is thinking about family problems or daydreaming and not focusing on driving task (Craft &
Preslopsky, 2009).
According to Victor, Engström, and Harbluk (2009), inattention is defined as the improper
selection of information, which can be due to, either lack in the selection of information or by
selection of inappropriate information. Hence, driver inattention is the improper selection of
information, which is critical for safe driving, either by the lack in the selection of relevant
information (e.g., closing of the eye due to fatigue) or selection of irrelevant information which
can be both relevant as well as irrelevant for driving. The latter part of driver inattention is
Driver distraction, in which the driver selects information which is not critical for safe driving.
Driver distraction can be seen as a subset of driver inattention, which includes all the situations
of misallocated attention except for where attention is not at all allocated.
2.4 Driver distraction
In the past decade, driver distraction has become a growing concern for governments, road
safety researchers, and the general public. Empirical studies have shown the deleterious effect
of driver distraction on the driving performance of drivers and a major concern of traffic safety.
As per the reports of NHTSA, a total of 32,675 people were killed in vehicle accidents on U.S.
roads and about 2.3 million injured these accidents in 2014. Distracted driving accounted for
crashes which killed about 3,179 people, making it about 10% of all the fatalities.
Despite the heightened awareness of the issue concerning driver distraction, no consensus
has been reached on its definition. Over the years, numerous definitions have emerged, many
of which are vague or contradictory (Foley, Young, Angell, & Domeyer, 2013). As a result of
this inconsistency, driver distraction studies are often difficult to compare and challenging to
replicate (Savino, 2009). However, efforts to standardize the definition of inattention and driver
distraction have been brought about by the need to reliably operationalize these concepts (Regan
et al., 2011; Trick, Enns, Mills, & Vavrik, 2004).
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20 2.4. Driver distraction
2.4.1 Defining driver distraction
The definition for driver distraction was not properly articulated until recent past. Hence, based
on their study needs and context, different researches have come up with a variety of statements
to define driver distraction in the past few decades. Some definitions have been presented
below:
Treat (1980) argues that driver distraction occurs “whenever a driver is delayed in the
recognition of information needed to safely accomplish the driving task, because some event,
activity, object, or person within (or outside) his vehicle, compelled or tended to induce the
driver’s shifting of attention away from the driving task”.
According to Hoel, Jaffard, and Van Elslande (2010), driver distraction results "from
interference between a driving task and an external stimulation without link with driving (e.g.,
guide a vehicle and tune the radio). This secondary task can be gestural or visuo-cognitive".
According to J. D. Lee et al. (2008), “Driver distraction is the diversion of attention away
from activities critical for safe driving toward a competing activity.”
Ranney et al. (2001), defines driver distraction as “any activity that takes a driver’s attention
away from the task of driving. Any distraction from rolling down a window, over adjusting a
mirror, tuning a radio to using a cell phone can contribute to a crash.”
The common points in all the definitions is that:
• There occurs a diversion of attention away from driving.
• There is a competing activity, either inside or outside the vehicle (either related or
unrelated to driving) which compels driver to divert their attention.
• There is an presumption that this competing activity adversely affect safe driving.
In the 1st International conference on distracted driving the following definition of distraction
driving was adopted by the group of internationally renowned scientists (Hedlund, Simpson, &
Mayhew, 2006)
“Distraction involves a diversion of attention from driving, because the driver
is temporarily focusing on an object, person, task, or event not related to driving,
which reduces the driver’s awareness, decision-making, and/ or performance,
leading to an increased risk of corrective actions, near-crashes, or crashes.”
According to Regan et al. (2011), driver inattention means – “insufficient or no attention to
activities critical for safe driving”, and driver distraction is – “just one form of driver inattention,
with the explicit characteristic of the presence of a competing activity”.
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2.4. Driver distraction 21
2.4.2 Taxonomy and sources of driver distraction
Driver distraction is a phenomenon that occurs due to multiple factors, which may occur either
inside or outside the vehicle. Categorization of these factors is done to clearly identify the key
causal activity leading to distraction. As per literature four types of distraction exist (more than
one can be active at a time).
• Visual (e.g. looking away from roadway)
• Auditory (e.g. responding to ringing cell phone)
• Bio-mechanical/ physical (e.g. adjusting CD player)
• Cognitive (e.g. lost in thought).
Visual distraction: This may take one of the three types – 1) visual field of driver is
blocked by an objects (sticker on windscreen etc.), which hinders the vision and driver
is unable to detect hazards in road environment, 2) when the driver focuses their visual
attention on other targets that are not critical for safe driving (such as in-vehicle navigation
system) for long period of time, 3) when drives’ visual attentiveness is lost, this is referred
to as "looked, but did not see" (Hajime, ATSUMI, Hiroshi, & AKAMATSU, 2001)
Auditory distraction: This type of distraction occurs when driver is focusing their
attention to sounds/ audio signals (momentarily or long duration) instead of primary task
of driving; this can happen while listening to music/ radio/ talking to passengers.
Bio-mechanical (physical) distraction: This type of distraction happens when driver
is physically distracted by removing their hand-off steering wheel or performing any
physical task which is not critical for safe driving (Haigney, 1997).
Cognitive distraction: When driver is thinking about something to an extent that they
are unable to safely maneuver the vehicle in traffic, then cognitive distraction is said
to occur. Reaction to hazardous events occurring on the road environment is reduced.
Talking on mobile-phone while driving has been reported as one of the cause leading to
cognitive distraction.
There are several factors that can distract the driver from primary task of driving. The
NHTSA has found the different sources of driver distraction (Stutts, Reinfurt, Staplin,
& Rodgman, 2001). Causes of distraction can be subdivided into internal and external
sources (Regan, Lee, & Young, 2008). Table 2.1, shows the different sources of distraction,
categorized as internal (those occurring inside the vehicle) sources and external (occurring
outside the vehicle) sources.
There exist an ample evidence of empirical studies that shows the detrimental effect of these
sources on driving performance (speed, lateral position and headway) and road safety (reaction
time and chances of accidents) (Brodsky & Slor, 2013; Strayer, Drews, & Johnston, 2003)
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22 2.5. Studies on internal sources of distraction
Internal sources External Sources
Vehicle systems Seeking location/ destination
Communication Other vehicle
Cell phone talking/ texting Traffic control
Daydreaming Pedestrian/ cyclist
Passengers Advertising signs
Coughing/ sneezing Sun/ other vehicle lights
Animal/ insect in the vehicle Landscape/ architecture
Eating/ drinking Animal
Entertainment systems Accident/ incident
Smoking Signs and markings
Stress Police/ Ambulance/ Fire brigade
Table 2.1: Sources of driver distraction (internal/ external)
It is noteworthy to mention here that Horberry, Anderson, Regan, Triggs, and Brown (2006)
in their study observed that even though the driver’s visual attention (eye glance behavior) is
affected by external sources, these sources don’t significantly affect driver behavior and safety.
2.5 Studies on internal sources of distraction
Distraction that occur due to activities taking place inside the vehicle are termed as internal
sources of distraction. These include those cased due to use of cell phones (smart-phones),
conversation with passengers, listening to radio and music, In-vehicle Information System
(IVIS), eating, drinking, smoking etc. Various studies relating to these sources are discussed
below.
Cell phone
A variety of studies have shown the detrimental effects of mobile phone use on driving
performance and behavior; their use has also resulted in increased cases of accidents.
Mobile-phone can either be used by the drivers for conversing or texting; in both situations,
there is a detrimental effect on the driver’s driving performance.
A driving simulator-based study conducted by Choudhary and Velaga (2017b) examined
the effect of texting and talking over mobile-phone on driving performance. The variables
under investigation were, ability to avoid accident and mean speed. The effect of age on
driving performance was also evaluated by dividing the participants into three age groups
(youngster, middle-aged, old). It was observed that the increase in workload was compensated
by reducing the speed; also, it was seen that chances of accident increased when drivers were
using cell-phone for texting or talking during driving.
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2.5. Studies on internal sources of distraction 23
Using mobile phones while driving results in a damaging effect on the reaction time of the
driver. It is a suitable parameter to measure event detection performance under the influence
of distraction. In a simulator study Choudhary and Velaga (2017c), analyzed and modeled
the effect of mobile phone distraction on the reaction time of event detection; about n = 100,
drivers were chosen for the study, with three different age groups. Two scenarios were used (1)
pedestrian crossing events, (2) road crossing event by parked vehicle. Results revealed that in
both cases, there was a considerable increase in reaction time.
The use of mobile-phone is more prevalent among youngsters. Due to their attitude of taking
risk and inexperience in driving, the risk of accidents for this group of population increases if
the mobile-phone is used while driving. Choudhary and Velaga (2019) comparatively studied
the longitudinal and lateral vehicle control for younger (n=25) and experienced (n=24) age
groups. Results revealed a degradation in driving performance for an in-experienced younger
population during the usage of mobile-phones. However, experienced drivers also showed
driving performance degradation under increased workload conditions.
In another simulator study, Haigney, Taylor, and Westerman (2000) examined the effects of
mobile-phone type (hands-free and hand-held) on driving performances. Results revealed an
increased mean heart rate of drivers during the phone call duration, which could be associated
to increased cognitive load. This doesn’t lead directly to reduced driving performance but
has significance in safety and risk of accidents. However, no significant change in heart rate
were observed for mobile-phone types. It was reported that drivers engaged in compensatory
behavior of reducing the speed during phone-calls as a measure of dealing with the increase
workload; also poor driving performance were observed for hand-held phones (as compared to
hands-free).
Strayer et al. (2003) in a simulator experiment observed that, conversing on a hands-free
phone while driving reduced the reaction time of driver to the braking of vehicle in its front.
This result was found to be more under high traffic condition.
Papadakaki, Tzamalouka, Gnardellis, Lajunen, and Chliaoutakis (2016) examined the
driving performance of experienced drivers under the influence of mobile phone use. This study
was performed using a driving simulator on Greek professional drivers under varying condition.
Results revealed that "variation of the steering position per second" was significantly affected
by texting and text message reading, also significant changes were observed for "following
distance per second" and "variation of lateral lane position per second" when compared with
control time.
In a study by Dozza, Flannagan, and Sayer (2015), data was collected from the naturalistic
driving study and the effect of mobile-phone usage was analyzed on lateral and longitudinal
vehicle control; drivers were divided into three age groups (younger, middle-aged and older).
Results showed that younger drivers were more likely to use mobile-phone while driving than
middle-aged and older drivers. It was also observed that the drivers tend to increase their safety
margin with age and when using phone, this can be to reduce the risk of accidents. It was also
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24 2.5. Studies on internal sources of distraction
observed that drivers tend to terminate the phone calls when driving was more demanding, this
behavior showed the driver’s awareness about the negative effect of mobile phone usage on
driving and their safety.
Talking to passengers
Talking or conversing with the passenger tend to deviate the driver’s attention from the road.
This deviation of attention could increase the chances of accidents. Researches have tried to
comparatively examine the detrimental effect of conversation with passenger and cell phone use.
In a driving simulator experiments conducted by Laberge, Scialfa, White, and Caird (2004),
80 participants were examined under three conditions (driving alone, driving with a passenger,
and driving with a cell-phone). It was observed that lane and speed maintenance variables
were influenced by the demands of driving, also the response time to the incoming pedestrian
increased when driver were talking and driving as compared to when drivers drove without
conversation.
In another study Drews, Pasupathi, and Strayer (2008) comparatively examined talking
with passengers and cell-phone conversation while driving. It was observed that cell phone
conversation differ from talking to passenger in the way that traffic becomes a part of
conversation allowing the sharing of situation awareness between driver and passenger; the
complexity of conversation change according to driving condition. Thus, the negative effect of
conversation on driving is mitigated. On the contrary, driving errors were found to be highest
under cell-phone conversation condition.
White and Caird (2010) conducted a driving simulator based experiment to examine the
effect of conversation with passengers on measures of driving performance (social factors,
hazard detection, and looked-but-failed-to-see (LBFTS) errors). Results of the study revealed
that while conversing with the passengers a higher rate of hazard detection and LBFTS errors
occurred compared to when driving alone.
Listening to radio & music system
Relatively few studies are present which have evaluated the effect of music, radio and
entertainment systems on driving performance. In a simulated driving study conducted by
K. L. Young, Mitsopoulos-Rubens, Rudin-Brown, and Lenné (2012), the effect of using a
portable music player was seen on driving performance. The results showed that when drivers
performed music search tasks while driving, their eye-off-road time increased; time head-way
from the lead vehicle and lane maintaining ability decreased.
Some other researchers have also examined the effect of listening to music while driving
on performance of drivers. Ünal, de Waard, Epstude, and Steg (2013) empirically studied
the influence of music on driving performance, arousal, and mental effort in a driving
simulator-based experiment. Heart rate was also measured to observe the physiological markers
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2.5. Studies on internal sources of distraction 25
of arousal and mental effort. It was observed that listening to music didn’t affect the car-flowing
accuracy. Positive effect on response to speed change of lead vehicle and lateral control
were observed. Additionally, the mental effort (measured by heart rate variability) didn’t
had any significant difference during music and no-music conditions, also, it was seen that
arousal was more during music condition (loud and moderate music had no effect). The results
suggest that listening to music don’t have detrimental effect on car-following task and there are
improvements in some aspects due to increased arousal.
In recent years drivers have also started tot listen to audio-books while driving. Researches
have argued that there may be situation when distractions from secondary task can alleviate
the boredom and fatigue due to monotonous driving. In a simulator study which supported
the above argument, Nowosielski, Trick, and Toxopeus (2018) evaluated driving performance
measure (speed, SD of speed, brake response time, SDLP) under simplex and complex driving
conditions. It was seen that brake response time was higher in complex task than in simple.
It was also seen that the overall driving performance was injurious under complex driving
condition. Faster response to hazards were observed when drivers were listening to audio-books
under simple driving scenario.
In-vehicle information systems (IVIS)
With the technological advancement many new technologies are being used by drivers inside the
vehicle. These so called in-vehicle technologies are supposed to assist the driver by providing
information about traffic, road condition, nearby vehicles and pedestrians. However, it has been
argued by Carsten and Brookhuis (2005) about the safety evaluation of IVIS products and their
effect on driving performance.
In the past few years, product innovation and advancement in GPS technology have made
mobile-phones as navigation device. They provide maps with turn-by-turn directions. Drivers
have started preferring portable (mobile-phone based) navigation device over the conventional
on-board systems. An experiment conducted in real driving scenario by W. C. Lee and Cheng
(2010), compared portable and on-board navigation system in of terms efficiency and car control.
Results reveal that, trip duration were shorter for portable navigation system and car handling
was better in portable system as compared to on-board navigation systems.
In an empirical study conducted by S. Benedetto et al. (2011) in a simulated driving
environment, the effect of using IVIS on blink duration of drivers was examined. LCT was used
in the simulated driving. Results showed that blink duration was more reliable and sensitive
marker of visual workload of driver as compared to blink rate.
Also it is seen in recent years that, use of portable Advanced Driver Assistant System
(ADAS) is raising. An empirical study conducted by Dumitru, Girbacia, Boboc, Postelnicu,
and Mogan (2018), showed that using a smartphone based portable ADAS would improve the
driving performance and reduced the distracting effects of using social media networks during
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26 2.5. Studies on internal sources of distraction
driving. Dumitru et al. developed a smartphone based ADAS system that would give an audio
warning when the drivers are distracted and focusing their attention on non-driving related task.
The ADAS notifications provided during distracted driving ensures that the drivers’ attention is
focused on road and there is minimum driving infractions.
Some researchers have tried to investigate effect of using Surrogate In-Vehicle instrument
system on the driving performance. In a high fidelity simulator experiment carried out by
Jamson and Merat (2005), two modes (visual and cognitive) of secondary task represented the
surrogate IVIS were used to evaluate the primary task (driving) performance in a car following
task. Results showed that no difference of performance were seen between visual and cognitive
tasks. However, the driving performance was decreased as a result of increasing surrogate IVIS
demand, this was shown as reduced time-to-collision and diminished prediction of braking
requirements.
In the recent past, Head-up Displays (HUD) are being employed for providing in-vehicle
information to the drivers in high-end passenger cars. In general these HUDs are displayed on
the windshield. Although, there are certain advantages of using a HUD, that include, reduced
eye-off-road time, elimination of refocusing and eye-axes convergence movements, and more
time available to see on-road scene, there are several disadvantages to using HUDs (Bhise, 2012).
The demerits of using HUDs include, a) attention switching, visual clutter and distraction, b)
the on-road scene may get masked by images from HUD, c) the projected HUD image may not
be visible in bright light and glare, d) requirement of providing additional controls for adjusting
the image brightness, location and switching on/ off, e) possibility to capture driver’s attention
under low demanding visual environment (Bhise, 2012)
Eating, drinking, smoking, and alcohol consumption
Eating while driving can cause safety issues to the drivers and pedestrians on the road since it
causes the driver to reach for the food physically. In a simulated driving study, M. S. Young,
Mahfoud, Walker, Jenkins, and Stanton (2008) evaluated the impact of eating and drinking
alongside driving. In the simulation program, the pedestrian crossing event happened when the
instruction to eat and drink was given. Empirical results suggest that the risk of accidents was
increased as an outcome of physical demand caused due to drinking and eating while driving.
The effect of talking, smoking, and eating on driving performance was analyzed by Yannis,
Papadimitriou, Bairamis, and Sklias (2011) on a simulated driving on a rural road condition. The
participants were instructed to consume snacks and smoke cigarettes at given points. Results
revealed a decrease in speed was associated with talking (simple and complex), smoking, and
eating. However, Complex conversation was associated with increased reaction time and lane
departure. No relationship could be established between increased reaction time and the risk of
accidents due to smoking and eating.
Alcohol intoxication negatively affects the driver’s ability to maneuver the vehicle in traffic
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2.6. Distraction due to external sources 27
successfully. A simulated driving study conducted by Harrison and Fillmore (2011) examined
the effect of alcohol on driving performance under divided attention task. Results showed that
divided attention aggravated alcohol’s impairing effect on driving performance; however, no
detrimental effect of divided attention task was examined for sober drivers.
2.6 Distraction due to external sources
Sources of distraction which occur outside/ external to the vehicle are termed as external
sources of distraction. In many countries, due to development of highways, billboards, roadside
advertisements, increased traffic density, complex roadways signboard together increase the
amount of visual information being presented from outside to the drivers.
Road side advertising signs are the most prominent external sources of distraction which the
drivers come across while driving. In a study conducted by Bendak and Al-Saleh (2010) in a
simulated environment evaluated driving performance on a part of road with advertisement and
other without it. The results of the simulated study showed that the lane excursions and crossing
of intersections were significantly worse in path having advertisements, whereas, indicators
such as over speeding, number of tailgating, and lane changing without signaling were also
worse in advertising paths but not statistically significant. Questionnaire based response to
showed that about 22% drivers were in near-crash situations due to these advertising signs.
In another simulator study M. S. Young et al. (2009) evaluated mental workload, driver
attention and lateral driving performance under the influence of roadside advertisements
(billboard) on varying road conditions (urban, motorway and rural). The results indicated a
deleterious effect of roadside advertisement on driver attention and lateral control by increasing
the mental workload of drivers.
Another empirical study that evaluated the effects of billboards on drivers Edquist, Horberry,
Hosking, and Johnston (2011) examined younger (inexperienced) and older drivers. The results
indicated that drivers response time to road signs and number of errors increased in driving task
due to billboards. A change in drivers’ visual attention was also noted.
With the road side scenery changing every mile, drivers face new kind of distractions
on every mile of highways. Two new kind of external distractions (wind-turbine and video
billboards) were examined by Milloy and Caird (2011) in a simulated driving condition.
Speed maintenance, perception response time, lane keeping were the compared, while driving
alongside the distraction and baseline. The perception response time was not found to be
significantly different from the baseline in the wind-turbine task, however, slow speed were
noted when passing by wind farms. In case of the video billboard task, significant large
collisions to lead-vehicle braking occurred in comparison to conventional billboards and
baseline.
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28 2.7. Studies on drivers’ characteristics
2.7 Studies on drivers’ characteristics (age, gender and
experience) on distraction
Many researchers have shown the effect of age and experience on the drivers’ ability to get
distracted by the secondary task and their perception of hazard while performing in-vehicle
tasks (McKnight & McKnight, 1993; Reed & Green, 1999).
In order to formulate any policy and corrective action plan, it’s important to know the
driver’s understanding and attitude towards the risks associated with usage of mobile phone
while driving. In a study based on the survey of Portuguese drivers carried out by Ferreira et al.
(2013), tried to understand the perception of mobile-phone usage based on gender and age as
an independent variable. The main findings revealed that, as compared to young and middle
age drivers, old drivers, favored less usage of mobile phones while driving on highways. Also,
it was observed that younger drivers send and read text messages more frequently than drivers
of other age groups; the perceived risk was also higher in case of older drivers as compared
to other age groups. The results in terms of gender showed that usage of mobile phone on
highways was mostly favored by males whereas females (although less frequent) engaged more
in sending and reading messages.
Studies similar to those mentioned earlier, McDonald and Sommers (2015) conducted a
focus group study and tried to understand the perception of teenage drivers on inattention due
to cell-phone usage while driving. Novice teenage drivers recognized the innate danger of using
cell-phone while driving, but they still engaged; teens also gave the context or situations where
they would answer a call, text or use social media app.; formulated safe driving behavior which
might reduce accident risks.
The visual and cognitive ability of the old aged driver is decreased, hence their ability to
share attention on coinciding tasks is greatly reduced. Therefore, these drivers are more liable
to get distracted due engagement with secondary task as compared to younger drivers. Similar
to this, a novice (less experienced) driver may be more vulnerable to the distracting effects of
performing secondary task while driving as compared to an experienced one. Training programs
and regimes as proposed by Regan, Triggs, and Godley (2000), would be helpful in training of
novice drivers.
In another study to establish the relationship of internal/ external distraction with age groups,
Lam (2002) concluded that drivers from a particular age group (25-29) were more susceptible
to accidents when using handheld phones as compared to other age groups. This is because of
their increased exposure as compared to other age groups. On the contrary Lam concluded that
the danger of being involved in fatal accidents due to distraction caused by other in-vehicle tasks
increases with age. Similar findings showing high susceptibility of older drivers to distraction
were shown by the studies of McKnight and McKnight (1993); Reed and Green (1999).
Similarly, empirical work by Schreiner, Blanco, and Hankey (2004) on drivers of three
different age groups (young, middle-aged and old) found that the forward and peripheral
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2.8. Studies carried out in India 29
event detection ability of older drivers was degraded while simultaneously performing driving
and phone number dialing using voice commands as compared to normal performance. This
degradation was not significant in younger and middle-aged drivers when performing the same
task as mentioned above.
McPhee, Scialfa, Dennis, Ho, and Caird (2004) in an empirical study revealed that old aged
drivers were slow and inaccurate in identifying the target signs in traffic as compared to young
and middle-aged drivers , when simultaneously engaging in simulated conversation task.
Although many studies on driver distraction have confirmed a degradation in driving
performance due to age, a good deal of other research also indicates that old aged drivers try to
compensate for greater performance degradation by engaging in compensatory (self-regulatory)
behavior. Horberry et al. (2006), in their studies, showed that when interacting with the
entertainment system or mobile phone, the old aged drivers reduced speed to compensate for
the increased workload of simultaneously performing a demanding task.
2.8 Studies carried out in India
As compared to the work which are reported from countries like US, UK, Germany, Canada,
Italy, Australia; very few work have come forward very recently.
A study on Indian drivers analyses and modeled the effect of conversation and texting (each
with two difficulty levels) on driving performance in terms of mean speed and accident avoiding
abilities. A total of 100 drivers participated in the simulator study. The participants were
divided into three different age groups (young, mid-age and old-age) The drivers significantly
compensated the workload by reducing speed and accident probabilities increased when drivers
were conversing or texting on phone during driving (Choudhary & Velaga, 2017b).
The effect of conversation and texting (simple and complex) on Vehicle based performance
parameters such as standard deviation of lane positioning, number of lane excursions, mean
and standard deviation of lateral acceleration, mean and standard deviation of steering wheel
angle and steering reversal rates (1◦,5◦ and 10◦) was studied (Choudhary & Velaga, 2017a).
Reaction time is a suitable parameter to measure the effect of distraction on event detection
performance. A simulator study analyses and modeled the effect of mobile phone distraction on
event detection. N=100, drivers were chosen for the study, with three different age groups. Two
scenarios were used (1) pedestrian crossing events, (2) road crossing event by parked vehicle. In
both the cases there was considerable increase in reaction time (Choudhary & Velaga, 2017c).
Radakrishnan et al. (2016), studied the positioning of infotainment screen inside vehicle
for better visual experience using RAMSIS and SPEOS OPTIS for occupant visibility and
reflection evaluation. Parameters like vision angle, avoiding any obscuration due to vehicle
components, avoiding in-vehicle reflections and avoiding ambient reflections were emphasised.
Visual hindrance such as obscuration, reflection and glare on the instrument cluster which
prevents the vital information flow from vehicle to the driver were studied. Ganesh, Mohammed,
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30 2.9. Studies on location/position of . . .
Krishnan, and Rambabu (2015) described the cluster packaging process flow for in-vehicle
visual hindrance free instrument cluster position.
Rajesh, Srinath, Sasikumar, and Subin (2017) presented safety risk perception model, to
understand how vehicle and driver characteristics influences mobile phone usage while driving
and associated risk perception of road safety. Survey was conducted on 1203 drivers in Kerala.
2.9 Studies on location/position of in-vehicle displays
In recent years, our vehicles are loaded with increasing number of displays and digital systems.
Using in-vehicle displays lead to deviation in normal visual scanning behaviour and attention
of drivers and increase the task completion time (Ali & Bazilah, 2014; Lamble, Laakso, &
Summala, 1999). The position of in-vehicle display plays an essential role in safe commutation.
Researchers empirically examined the effect of the positions of car navigation display on eye
movement and braking reaction time (Itoh et al., 2005). Position is an important factor in
frequently used and high attentional demand in-vehicle displays. Large, Crundall, Burnett,
Harvey, and Konstantopoulos (2016), compared the configuration of CMS to the traditional side
mirrors in a lane change test. They measured eye movement, driving performance, subjective
rating for evaluation. The results showed reduction in decision time and eye off road when
using CMS. the subjective rating showed that, configuration which was close to the traditional
side mirror location were preferred by the drivers. However, they did not discuss about the size
and location of the display.
Recently reported studies tried to evaluate the different positions of in-vehicle displays
empirically in terms of driving performance measures. Radakrishnan et al. (2016) presented
a framework for positioning of infotainment screen inside the vehicle for an improved visual
experience (Radakrishnan et al., 2016).
Another study conducted by Beck et al. (2017), evaluated the in-vehicle side-view display
layouts in critical lane-changing situations. They showed that the spatial arrangement of
mirror/ display significantly affected the dependent measures (response time, eye-off-road time,
perceived safety rating, perceived workload, and preference ratings) (Beck et al., 2017).
Ishiko et al. (2013) evaluated two different sizes of navigation systems at three locations for
driving safety based on gaze data and subjective rating. They found that the 7 – inch display
size was preferable than 4.3 – inch, while among the three locations, the position of the left
side of the steering wheel was more desirable irrespective of display size (Ishiko et al., 2013).
A comparison of different locations and size of in-vehicle display was performed by Doi et
al. (2019), for Camera Monitor System (CMS) used as a replacement of side-view mirror. They
evaluated three different sizes of displays at three different locations inside the vehicle (Doi et
al., 2019).
Gathering behavioral data, eye-tracking, and subjective ratings of the participants in a
driving simulator study; Wittmann et al. (2006), attempted to determine the relative safety
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2.10. Existing methodologies for measuring . . . 31
of on-board display positions, concluded that drivers’ performance is disturbed exponentially
as a function of distance between the on-road line-of-sight and the on-board display position.
Thus, nearer the on-board display to the straight forward line-of-sight, the less detrimental
effect is on the actual driving performance during on-board visuo-motor control of a secondary
task (Wittmann et al., 2006).
2.10 Methodologies for measuring distraction
Distraction is measured in terms of drivers’ driving performance, and there are numerous
methodologies for evaluating the driving performance. The most realistic is the naturalistic
driving method, and lab test give a good amount of experimental control.
Driving performance have largely being measured by the use of instrumented vehicles on the
test tracks or on road (Carney, Harland, & McGehee, 2016), and driving simulators (Horberry
et al., 2006). One of the important naturalistic driving study was conducted on 100 drivers
and the movement of their vehicle was recorded for 20,00,000 miles (Klauer et al., 2006).
There are wide variety of driving performance, driver behavior, task performance and demand
measures. Figure 2.3 shows the different methods of measurement for driving performance. It
is clear from the figure that as the realism of the experiment increases, the experimental control
decreases and vice-versa. The methodologies for assessing distraction has been categorized
as naturalistic studies (those conducted under natural driving condition) and driving simulator
studies (conducted on a simulator in a laboratory).
Low-cost driving simulator (PC with steering and 
pedals) (eg. Lane change test, Occlusion Test, PDT)
Advance fixed base driving simulator with high quality 
display
Advance driving simulator with motion base
Test track studies 
Trails on Road
Naturalistic Study in Instrumented vehicle
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Figure 2.3: Methods for assessing distraction
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32 2.10. Existing methodologies for measuring . . .
2.10.1 Studies on naturalistic driving
For evaluating/ measuring the drivers’ involvement in distracting activities in a real road
scenario, naturalistic driving studies are conducted. During driving, the actions of drivers are
monitored by instruments, cameras, and data loggers fitted into the car/ vehicle (Xie, Zhu,
Guo, & Zhang, 2013). In this method, data is collected in a very discrete manner, and drivers
are permitted to drive naturally without any instructions. Headway from lead vehicle, lateral
and longitudinal controls are measured using sensors in the vehicles. These studies generate a
large amount of data and are time taking (long period). For analysis and quantification of the
drivers’ exposure to a distracting task (personal grooming, adjusting in-vehicle instruments,
drinking, and eating, reading, etc.), trained coders are needed. Carney et al. (2016) conducted a
naturalistic study, and data were collected using an event-triggered IVERs (in-vehicle event
recorder) technology. The accelerometer, audio, and video data were triggered by specific
events and were not continuously recorded. Other sophisticated instruments can also be used in
place of data loggers, such as eye-tracker for measuring visual behavior of the drivers (Xie et
al., 2013; K. L. Young, Salmon, & Cornelissen, 2013).
2.10.2 Studies on driving simulator
Driving simulator (DS) studies utilize a controlled laboratory environment to conduct empirical
studies to evaluate drivers’ driving performance under a variety of test conditions. DS based
research is safe, relatively realistic, and data from various driving performance measures can be
gathered. Fidelity (realism) and validity affect the outcome of these studies. DS based study
has several merits over the on-road/ test track studies. Hazardous/ unethical driving conditions/
environment can be easily and safely evaluated in the DS. Traffic and multi-vehicle scenarios
can be easily simulated. A considerable amount of experimental control can be achieved in
DS than the test on track/ road. A variety of hazardous driving test conditions (road, weather
conditions, day/ night-time) can be easily investigated. In addition to the merits mentioned
above, there are some demerits of DS based studies. Another limitation of DS based research
is the effect of being monitored by the experimenter and the learning effect of using a DS.
Expertise in operating the additional equipment (e.g., eye-tracker) is required in DS based
research in addition to high cost (for high-fidelity) of DS. (Xie et al., 2013). Reports of DS
discomfort are common for females and old-aged drivers, resulting in higher dropout compared
to male drivers. Additionally, in DS, the drivers feel safer than real road scenarios; they may
differently allocate their cognitive resources to secondary and primary tasks than in actual
driving scenarios.
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2.10. Existing methodologies for measuring . . . 33
Driving simulators and its classification
DS is an advanced application of “computer-aided kinematics” and dynamic simulation.
Researchers and engineers typically use them in highway design, vehicle design, and human
factors (driver behavior) studies under hazardous conditions (under the influence of alcohol,
drugs, severe weather condition, distracting activities), which would be illegal in a real road
scenario. Studies in a DS provide safe, cost-effective, repeated measurement and controlled
scenarios for testing driver behavior, vehicle, and highway designs. The DS can be used in
fields ranging from advanced training, research, and entertainment. A fidelity (or utility) of
a DS describes the degree with which the DS can replicate the actual driving scenario/ task.
Thus, DS can be classified according to the degree of realism and subdivided as low-level,
mid-level (Cuenen et al., 2015), and high-level fidelity DS (A. Benedetto, Calvi, & D’Amico,
2011); shown in figure 2.4.
(a) (b) (c)
Figure 2.4: A typical classification of driving simulators (a) low-level fidelity, (b) mid-level fidelity, and
(c) high-level fidelity
A low-level DS typically consists of a fixed-base (FB), and fixed-screen (FS), with audio
and visual cues for the drivers. The horizontal field-of-view of the low-level DS’s display
screen will be narrow and displayed to the driver on a single monitor. There will be a limited
provision of force-feedback through the steering wheel to the driver. These types of simulators
are cost-effective and useful for students in research and dissertation work. A low-level DS is
limited in its fidelity but is cost-effective.
A mid-level DS has an advanced display with wider field-of-view (horizontally), the drivers
sit in a full-body vehicle, which creates a fully immersive virtual environment. In this DS, a
simple motion base simulates tactile cues of road roughness and vibration.
A high-level DS has 360◦ field of view, 6-DoF (degrees of freedom), sophisticated graphics,
full vehicle with motion base, realistic components, layout, and driving environment. The
drivers will sit in a complete vehicle cab that provides full dashboard functionality. These are
costly, but produce results similar to the actual road driving situation.
Apart from academic research, many automobile companies have also developed their DS.
Daimler-Benz pioneered in this field by building its DS in 1985, which has upgraded over time.
Researchers have utilized different test tools combined with the driving simulator to evaluate
the severity of driver distraction caused due to secondary task engagement. Combining these
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34 2.10. Existing methodologies for measuring . . .
test tools with the driving simulator is easy. These test tools include the peripheral detection
task (PDT), visual occlusion method, lane-change test (LCT), and eye-tracker.
Lane change test (LCT)
Lane change test (LCT) is a reliable, inexpensive, and standardized test tool for measurement of
in-vehicle infotainment system (IVIS) demands (Mattes & Hallén, 2009). The entire procedure
of LCT requires minimum equipment and is quickly completed. It requires a simple desktop
computer on which the LCT software is installed, and a simple force feedback steering wheel
with accelerator and brake pedals. The LCT driving simulation consists of a 3 km test track
having three lanes with 18 lane change signs along the track. Each of the sign contain one
upward arrow and two "X"s, indicating the next lane into which to change. These lane change
signs (same) appears on both sides of the simulated roadways. The participants have to perform
lane change manoeuvres alongside maintaining the vehicle at a constant speed of 60 km/hr
(which can not be increased). The mean distance between signs is approximately 150 m, having
a mean duration of 9 s in between subsequent lane changes. It takes approximately 180 s time
duration for each test track to complete. During the LCT, the primary driving performance
measure is called the mean lateral deviation (M.Dev). There are no surrounding traffic in the
driving scenario. The participants have to perform the lane change manoeuvres in a deliberate,
quick, and effective manner when they were able to identify the signs. In the simulation the
lane change signs are always visible, but they remain blank and appear at a distance of 40 m
before the lane change sign. ISO (2010) gives a more detailed description about the LCT.
  
  
  
  
  
Figure 2.5: A simulated LCT roadways with lane change sign
The distracting effects of the using additional in-vehicle, navigation task along with driving
has been successfully demonstrated by using LCT (J. Harbluk et al., 2007; J. Harbluk, Mitroi,
& Burns, 2009; Mitsopoulos-rubens, Young, & Lenné, 2010).
Additionally, Burns, Trbovich, McCurdie, and Harbluk (2005) in an empirical study
differentiated the secondary tasks based on the levels of workload by using the LCT. Higher
values of mean deviation were observed while performing secondary task than when driving
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2.10. Existing methodologies for measuring . . . 35
 
  
 
Figure 2.6: LCT test track with drivers trajectory compared with normative model
without performing it. For change in task type and complexity, the mean deviation values also
showed differences.
Engström and Markkula (2007), performed a re-analysis of lane change test (LCT) data
originally collected by Daimler Chrysler. They used a subset of the collected data. It was found
that visual and cognitive distractions impair driving in different ways. Visual only distraction
leads to reduction in path control, in contrast to cognitive distraction which affect detection and
response selection.
Grane and Bengtsson (2013), used Lane change test (LCT) for empirically examining how
visual and haptic interfaces affect driver performance. Four different interfaces were compared:
visual only, visual-haptic with partly haptic support, visual-haptic with full haptic support, and
haptic-only. The result showed that erroneous crossing of lanes were caused due to visual -only
and visual -haptic with partly haptic support, whereas missed road signs were caused by haptic
-only interface. Least negative effect on driver performance were observed with visual-haptic
with full haptic support.
Although, ISO draft for LCT does not demand or even recommend that subject sample be
balanced for gender. Petzoldt, Bär, and Krems (2009), empirically investigated if there is any
change in lane change performance while engaging in secondary task across the gender. It was
found that gender differences exists in LCT and secondary task performance. They concluded
that the subject samples should be balanced for gender to assure comparability in LCT results.
J. Harbluk et al. (2009), examined three different navigation system with three tasks having
varying complexity. They used LCT to assess the distraction demand. LCT differentiated the
easy task from the difficult task. However, LCT was not able to differentiate two difficult task
(having different task completion time). Hence, it was proposed to include measure of task
duration in LCT since it indicates the amount of time driver deviates attention from driving
(primary task).
Rodrick, Bhise, and Jothi (2013), studied the secondary task and driver characteristics
(age and gender) on lane change test (LCT) performance. Four secondary tasks (data entry,
memory, visual search, tracking), with each having two levels of difficulty were used in
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36 2.10. Existing methodologies for measuring . . .
the study. Results showed that the driving performance were least affected by the task that
required memory scanning, and utilized auditory modalities, whereas, most affected by task
requiring psychomotor coordination, and visual attention. Apart from this age and gender
related differences were also found in LCT performance.
Peripheral detection task (PDT)
An artificial signal detection method which is lately being used in driver distraction studies is
the PDT. Van˜Winsum, Martens, and Herland (1999) developed the first PDT, then after there
has been several variations to it, namely SDT (signal detection task), TDT (tactile detection
task) (Hsieh, Seaman, & Young, 2015), VDT (visual detection task), This method is based
on the hypothesis that as the driving task demand increases, the stimuli’ response time also
increases. Simulator and on-road studies can easily implement PDT and its variants. The
stimuli are presented with the spatial and temporal differences in the visual field of drivers. If an
auditory stimulus is presented in the driving simulator, its referred to as the auditory detection
task (ADT) Merat and Jamson (1999). The only difference between the variants of PDT is the
modality of stimuli presentation; however, in all the cases, the drivers’ response is collected in
the same manner (micro switch attached to index finger) (Victor et al., 2009). Generally, PDT
is implemented in a with-in subject experimental design, where the subjects perform driving
tasks, with and without secondary task along with detecting the stimuli. Hit rate and reaction
time (RT) gives the performance of a study based on PDT.
Visual occlusion method
When the driver’s attention is focused on the primary task of driving, he is expected to look
at the roadways; however, when he is paying attention to an in-vehicle device, his attention is
not on the road. The drivers’ chances to distract from driving have increased since in-vehicle
devices (communication, information, and entertainment) are becoming feature-rich. Although
eye-glance behavior is superior, it is time-consuming to analyze and difficult to collect. Visual
demand of the in-vehicle information system (IVIS) can be measured using the visual occlusion
method in the preliminary product design stage. Many researchers have used visual occlusion
methods in a variety of ways to measure driver distraction.
The basis of this technique is that driving is a visual-manual task (Foley, 2009). This
technique measures the visual demand of a task performed concomitantly with driving and
was initially proposed by Senders, Kristofferson, Levison, Dietrich, and Ward (1967). It
can be used on both simulators and on-road/ naturalistic driving studies. Visual occlusion is
“physical obstruction of vision for a fixed period of time” (Gelau & Krems, 2004). In this
method, the drive’s vision is systematically obscured, and then the obscuration is removed.
Figure 2.8, shows the obscuring and un-obscuring of driver vision. The apparatus used in the
visual occlusion method is the PLATO (portable liquid-crystal apparatus for tachistoscopic
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2.10. Existing methodologies for measuring . . . 37
Figure 2.7: A PLATO occlusion google, Source: (Yuan et al., 2018)
occlusion) googles, shown in figure 2.7. ISO standard 16673 (ISO, 2007) describes the various
Total task time = sum of viewing and occlusion
interval
Total shutter open time = sum of viewing intervals
Viewing 
interval
Occlusion 
interval
Shutter 
open
closed
Figure 2.8: A time line showing occlusion and viewing interval, adapted from (Foley, 2009)
parameters of visual occlusion method. These parameters are; Resumability ratio (R) (ratio of
mean TSOT to the mean TTTUnoccl), TTTUnoccl (total task time for a task completed without
occlusion), and Total shutter open time (TSOT) (total time during which vision is un-occluded).
The driving performance of the participants are measured under no occlusion condition and
when periodically occlusion occurs. Task duration in this method is measured from the point
when instruction ends to when the participants says ‘done’. The acceptable shutter open time
(SOT) acceptable by a standardized occlusion procedure is about 1.5 s. Several researchers
have proposed this method to assess in-vehicle information system (Baumann, Keinath, Krems,
& Bengler, 2004; Burnett, Lawson, Donkor, & Kuriyagawa, 2013; Gelau & Krems, 2004).
Gelau and Schindhelm (2010) conducted research work to improve the sensitivity of the visual
occlusion method. H. Kim and Song (2014), used visual occlusion method to evaluate the
usability and safety of in-vehicle information system (IVIS). Visual occlusion method has also
been used to assess the effect of work profile and age on distraction. Visual workload while
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38 2.10. Existing methodologies for measuring . . .
driving has also been evaluated using occlusion method (Van Der Horst, 2004).
Visual behavior study using eye-tracking
Eye-tracking studies are increasingly becoming popular for evaluating visual performance while
driving. It is also observed from the literature that eye-tracking studies are conducted along
with other driving performance matrices.
In an experiment to assess the changes in visual behavior due to cognitive distraction,
J. L. Harbluk, Noy, and Eizenman (2002) measured mean visual gaze, mean number of saccades,
percentage of time spent looking at central and peripheral area of forward view.
In a simulator based experiment, K. L. Young, Rudin-Brown, Patten, Ceci, and Lenné
(2014) examined the effect of phone type (touch screen vs. numeric keypad) on visual scanning
behavior of drivers. The percent of driver’s total gaze time to the centre of road, frequency and
glance duration to phone were used as a measure of visual behavior.
Zahabi and Kaber (2018) empirically examined visual behavior performance, workload
and situation awareness in a driving simulator based experiment for current and enhanced
mobile computer terminal interface design for police or emergency vehicle point the results
suggest that the use of MCT (mobile computer terminal) while driving reduced perceived level
of driving environment awareness an increased cognitive load of police officers. They utilized
an eye-tracking variables (fixation time, off-road glance frequency, maximum off-road glance
duration) along with other variables (like driver performance, level of awareness, and perceived
workload, secondary task time) as the dependent variables.
Metrics used in eye-tracking studies
The components that form the basics of eye-tracking metrics are described below:
• Point-of-regard: The raw output data of the eye-tracker which indicates where the person
is looking is said to be the point-of-regard (PORs)
• Fixation: A spatially stable PORs forms the fixation, which are defined by duration and
location. Visual processing occurs during fixation.
• Saccades: The rapid eye movement which occurs between successive fixation is called
saccades. There is no occurrence of visual processing during this duration.
• Scanpath: The sequence in which the fixation and saccades occur, through which
visualization of eye-movement is possible is called scan path.
• Area of Interest (AOI): Its an area/ region on the visual display, defined by the
experimenter, at which the data of eye-tracking is analyzed.
• Gaze/ dwell/ glance: It is the sum total of the fixation duration starting with the first
fixation in the particular AOI to the first fixation outside that particular.
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2.11. Variables for measuring driving . . . 39
2.11 Variables for measuring driving performance
Driving performance variables indicate the level/ degree of distraction when a driver performs
a secondary task(s) while driving. Distraction affects the drivers at multiple levels; hence,
a single driving performance measure can’t capture the entire picture. Driving performance
metrics can be categorized as longitudinal (speed, longitudinal control, headway) and lateral
control (SDLP, SRR, lateral acceleration, and lane excursion) variables. While choosing the
driving performance variable, its agreement with the distraction measurement method is of
prime importance. Given below are the brief descriptions of the commonly used indicators of
driving performance.
Longitudinal control
Most commonly used longitudinal control measures are speed and headway.
(a) Speed is an essential and commonly used variable in driver distraction and road safety
research. These variables include maximum, mean, 85th percentile, and variability of
Speed. Both on-road and driving simulator research has shown drivers displaying greater
speed variability while performing a secondary task during driving (A. Benedetto et al.,
2011; Reimer, Mehler, & Donmez, 2014).
(b) Headway is the distance between the front and the following vehicle. It is an indicator
of safety margin and also called as a vehicle following. Standard deviation (SD),
minimum, and mean headway are the most commonly used variables in driver distraction
studies (A. Benedetto et al., 2011; Peng, Boyle, & Lee, 2014).
Lateral control
The steering wheel and lane-keeping metrics are the commonly used lateral control variables
used in driver distraction research.
(a) Lateral position (lane keeping) is the vehicle’s relative position with respect to the center of
the lane in which the vehicle is moving. The lateral position of the vehicle is affected by
the secondary task demands. Commonly used lane-keeping metrics in the driver distraction
research are the number of lane exceedances, SDLP (standard deviation of the lane position),
and mean lane position (Cuenen et al., 2015).
(b) Steering wheel (SW) metrics comprises of steering reversal rate (SRR), SD (standard
deviation) of SW angle, and SW angle (Savino, 2009) Higher SW movements will be
observed when drivers perform visual-manual secondary task compared to when not.
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40 2.11. Variables for measuring driving . . .
Reaction time & event detection
The variables which are representative of the reaction time and event detection parameters
consists of response time and distance (the distance of event when detected), number of incorrect
responses, number of missed/ detected events. Both driving simulator and on-road studies have
shown a decline in drives’ ability to react and identify objects/ events, under the influence of
secondary task (A. Benedetto et al., 2011; Haque & Washington, 2015; Yannis, Papadimitriou,
Karekla, & Kontodima, 2010).
Gap acceptance
The elements of gap acceptance measure are, size of gap accepted, and the number of collisions
initiated. Studies have shown that drivers initiate a higher number of collisions, and take smaller
gaps when interacting with in-vehicle instruments (Ashalatha & Chandra, 2011; Cooper &
Zheng, 2002).
Eye-movement metrics
Researchers have used a number of Eye-movement metrics in their studies as an indicator of
driving performance. These metrics include fixations count, saccades (Wang, Wang, Wang,
& Zhao, 2016) and smooth pursuits which are increasingly becoming popular in driving
simulator studies (J. L. Harbluk, Noy, Trbovich, & Eizenman, 2007; Kujala & Saariluoma,
2011; Zahabi & Kaber, 2018). Eye-tracking metrics can be obtained in combination to other
driving performance variables in either naturalistic or simulated studies. S. Benedetto et al.
(2011) used eye-movement metrics (blink rate, blink duration, Average pupil diameter) as a
measure of drivers’ workload. Details about various studies using eye-movement metrics for
evaluating driving performance has been discussed in section 2.10.2.
Measure of workload
According to Verwey (2000), “mental workload is related to the amount of attention required
for making decisions”. Mental workload is measured by either subjective or physiological
measurement techniques, the following section will briefly discuss these techniques.
1. Subjective workload measurement: These metrics record the participants’ workload after
they have performed a task. In driver distraction research, the primarily used workload
scales include NASA Task Load Index (NASA-TLX) (Horberry et al., 2006), Situation
Awareness Global Assessment Technique (SAGAT) (Gugerty, 2011; Salmon, Stanton, &
Young, 2012), Rating Scale Mental Effort (RSME) (Zijlstra, 1993). Some studies have
also reported using DALI (Driving Activity Load Index) scale (Pauzié, 2008; Pauzié,
Manzan, & Dapzol, 2007; Petzoldt et al., 2009). It is a modified version of NASA-TLX
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2.11. Variables for measuring driving . . . 41
developed to assess the driver’s workload while operating in-vehicle devices. Assessment
using this method is inexpensive, non-invasive, and fast.
2. Physiological workload measurement: These techniques are based on the fact that the
physical response from the body would increase with an increased mental demand (Moray,
1979). Commonly used physiological measures of workload include cardiac, speech
measure, respiratory, and brain activity. Cardiac activity (ECG, heart rate(Haigney
et al., 2000), heart-rate variability (HRV), and blood pressure (BP) (Enokida et al.,
2013)); Respiratory activity is measured by the number of breaths in a given time and
the amount of air intake of a person. Speech measures note the rate, pitch, loudness,
shimmer, and jitter in speech when measuring workload. Brain activity is measured by
electroencephalogram (EEG) (Enokida et al., 2013). Eye-movement matrices such as
blink rate, pupil diameter, and blink duration have also been used to measure drivers’
workload (S. Benedetto et al., 2011; Dlugosch, Conti, & Bengler, 2013).
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42
2.11.
Variables
for
m
easuring
driving
...
Driver inattention
Attention, information processing and driving
Driver distraction
External sources
Methodologies for measuring 
distraction
Mobile phone
Talking to 
passenegers
In-vehicle 
information system
Listening radio, 
music system
Internal sources
Eating, drinking 
alcohol, smoking
Driving performance measure
Simulator based studyNaturalistic Study
Lane Change Task (LCT)
Peripheral Detection 
Task (PDT)
Visual Occlusion Method
Eye Movement Studies
Longitudinal control, lateral control, 
event detection, reaction time, gap 
acceptance, eye-movement matrices, 
Measure of driver workload 
(physiological and subjective 
measurements)
Figure 2.9: A summary of literature review
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2.12. Digital human modeling (DHM) in . . . 43
2.12 Digital human modeling (DHM) in product design and
development
Every day, a wide variety of products come in the market. It is believed that the finished product
will fit the consumer regardless of their physical, cognitive capabilities/ limitations; however, it
is not always true—a mismatch between consumers and the end product is commonly observed
phenomena. Designers of innovative products are aware that using ergonomics considerations
can lead to the product’s overall success.
International Ergonomics Association (IEA) defines Ergonomics (Human Factors) as “the
scientific discipline concerned with the understanding of the interaction among humans and
other elements of a system, and the profession that applies theoretical principles, data and
methods to design to optimize human well-being and overall system performance” IEA (2019).
Human-machine compatibility can be investigated with the traditional ergonomic methods,
which involves physical mock-ups and consequent trails with real human beings. This process
is expensive and time-consuming. With the advancement in computer technology and 3D
visualization techniques, the use of DHM software for virtual ergonomic evaluation has gained
momentum. Specialized Computer-aided Design (CAD) methods utilizing DHM software have
given the possibility to proactively incorporate human factors in designing and developing
a product. In DHM software, digital human (manikin) model of varying body types and
dimensions (mostly 5th, 50th, 95th percentile) can be created which interacts with a CAD
generated product in a virtual environment. With the help of these tools identification of key
design issues and difficulties encountered by the humans in performing task with the product
at an early phase of design is possible. This allows for early changes in configurations and
design (even before making a physical prototype). Using DHM for ergonomics evaluations/
simulations is economical compared to traditional ergonomic evaluation methods in a product
design/ development process (Chaffin, 2005). The need for using physical mock-ups for
ergonomics evaluations is reduced due to the use of DHMs, as simulations/ evaluations are
done in the virtual environment (Hanson, Blomé, Dukic, & Högberg, 2006).
The first digital manikin (called "First Man" later known as Boeman), was developed for
Boeing in 1959 to assess pilot accommodation in the cockpit of Boeing 747. Some popularly
available DHM software packages in the market are Safework, RAMSIS, JACK, SANTOS,
CATIA-DELMIA; These software packages allow creating a complex environment, simulate
tasks, analyze posture and are used by a wide variety of companies. The application ranges
from comfort analysis to ergonomic design of car interior, manufacturing process, and car
ingress/ egress simulation in the automotive domain. Some examples of DHM packages used
by automobile companies include Ramsis by Honda, Audi, Ford, Volkswagen; Jack by BAe
Systems, and John Deere.
Benefits of using DHM in product design and development include reduced design time,
increased productivity, enhanced safety, evaluation with manikins (digital humans) of varying
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44 2.13. Innovative product design and . . .
body types and dimensions, evaluation in a hazardous condition, lower development cost,
loopholes and errors can be identified even before making physical mock-up, repeated trials and
modification based on DHM evaluation (Patel, Sanjog, & Karmakar, 2016; Sanjog, Chowdhury,
& Karmakar, 2012; Sanjog, Patnaik, Patel, & Karmakar, 2016).
DHM has found its application in a wide variety of industries, which include the automobile
sector (Lämkull, Hanson, & Örtengren, 2009), aviation and aerospace, defense research
(Karmakar, Pal, Majumdar, & Majumdar, 2012), health care application, agriculture sector
(Patel et al., 2017), clothing, manufacturing (Sanjog et al., 2016), service and animation industry
for the ergonomic evaluation of their products and workspace.
2.13 Innovative product design and development
The global market is becoming increasingly competitive. The economic success of any firm
depends on their ability to identify needs of customer and quickly make a product which meets
these needs at low cost. To bring a new product in the market, companies have to innovate and
do product development. Customers satisfaction highly depends on the utility being offered by
the product. A customer is willing to pay higher price for the product if it fulfills the desired
utility of the customer. Products are of various types; broadly they can be classified as tangible
(goods like pen, bicycle, soap, phone, car etc.) and intangible (hotels, airlines, doctor, barber
etc.). Another classification could be of a consumer and industrial products; Consumer products
are those which is purchased by individuals for personal or household use; Industrial products
are the ones which are purchased by organizations for their business purposes.
Innovation has many meanings to it, which depend upon the context where its used. The
word ’Innovation’ is an outcome of creative design thinking and problem solving process. It is
related to products as well as designers who conceive new products to serve the needs of the
customers. Published literature show a wide variety of innovation, which can be ranging from —
Product; Service; production; management; organization; process; commercial and marketing
innovation. According to Schumpeter (2017), ‘Innovation’ can be defined as “Introducing a
new product or modifications brought to an existing product; A new process of innovation in an
industry; The discovery of a new market; Developing new sources of supply with raw materials;
Other changes in the organization”.
2.13.1 Benefits of product development process
The sequence of steps employed for conceptualizing, designing, and commercializing a product
is called a systematic product development process. Key benefits of a systematic product
development process include:
Quality Assurance: Quality of the product is assured, if the stages and checkpoints of
the project are chosen wisely according the product development process.
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2.13. Innovative product design and . . . 45
Coordination: A well documented development process defines the role of various
members in the team and tells them when their contribution is needed and with whom
they need to exchange information/ material.
Planning: The development process contains milestones related to the finishing of
different phases. The development process is kept on track by timings of this milestone.
Management: The development process acts as a benchmark for the ongoing efforts.
Actual problem areas can be found out by comparing the ongoing events with the
formulated development process.
Improvement: A well articulated development process helps in finding the improvement
opportunities of the organization.
Morale and satisfaction: It shows the progress of the ongoing project. This, maintains
enthusiasm among the team members.
2.13.2 Generic process of product development
A product is something which is sold by an enterprise to its customers. The sequence of steps
which transforms an input to output is called a process. The Generic product development
process consists of six phases (shown in Figure 2.10); Planning; Concept development; System
level design; detail design; Testing and refinement; Production ramp-up.
Planning
Concept Development
System level design
Detail Design
Testing and Refinement
Production Ramp-Up
Mission Approval
Concept Screening
System specification review
Critical design review
Production approval
Phase ‘0’
Phase ‘1’
Phase ‘2’
Phase ‘3’
Phase ‘4’
Phase ‘5’
Figure 2.10: A generic product development process
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46 2.14. Conclusion to literature review
Planning: Planning is referred to as the "phase zero" of the product development process.
The output of the planning phase is the project mission statement. It specifies the target
market, business goal, key assumptions and constraints.
Concept development: In this phase, the need of the market are identified, alternate
products ideas are generated and evaluated, consequently one or more ideas are selected
for testing and development.
System level design This phase defines the product architecture and further break-down
into subsystems and components. The final assembly scheme is defined in this phase.
The output of this phase is the geometric layout of the product, functional specification
of product’s subsystem and the process diagram for final assembly.
Detail design In this phase the complete specifications of geometry, material and
tolerance of all the parts used in the product are given. Control documentation is the
output of this phase, which describes the geometry, tooling requirements, specifications,
process plan for fabrication of each part used in the product. Production cost and robust
performance are addressed in this phase of detail design.
Testing and refinement In this phase multiple pre – production units of the products are
made. The initial version is called the alpha unit, which is built using the parts intended
for production (with same parts and geometry). Alpha Prototypes are tested to determine
if they work as they are designed and if they satisfy the customer requirements. Later on
the beta prototypes are developed and tested. These prototypes are tested extensively by
the customers in their own environment, with the goal to identify any engineering and
reliability issues. If any issues are found, necessary changes are done in the final product.
Production ramp-up In this phase the products are made using the intended parts to be
used in the production system. The purpose of this phase is to prepare the workforce and
to work out any remaining problems in the production process. There is a slow shift from
the ramp-up to ongoing production process.
2.14 Conclusion to literature review
In the earlier sections, various aspects of driver distraction (types, causal factors, external/
internal sources of distraction, drivers’ characteristics, etc.), driving distraction related studies
in the Indian context. This chapter also classifies the existing methodological perspective of
measuring driver distraction, visual behavior of drivers & its assessment using eye-tracker,
measuring of driving performance, simulation of driver-mobile interaction, etc. have been
highlighted. Each of the existing methodology has its advantages/ merits. With respect to
solving the research problem taken up, the lane changing task (LCT) is a reliable, inexpensive,
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2.14. Conclusion to literature review 47
and standardized test tool for measurement of in-vehicle infotainment system (IVIS) demands.
The entire procedure of LCT requires minimum equipment and is quickly completed. It requires
a simple desktop computer on which the LCT software is installed, and a simple force feedback
steering wheel with accelerator and brake pedals.
Since driving is a visual-manual task it requires focused attention and eye-tracking studies
(using eye-movement recorder) are increasingly becoming popular for evaluating visual
performance while driving. It is also observed from the literature that eye-tracking studies are
conducted along with other driving performance matrices.
The driving simulator (DS) studies utilize a controlled laboratory environment to conduct
empirical studies to evaluate drivers’ driving performance under a variety of test conditions.
DS based research is safe, relatively realistic, and data from various driving performance
measures can be gathered. DS based study has several merits over the on-road/ test track studies.
Hazardous/ unethical driving conditions/ environment can be easily and safely evaluated in the
DS.
Hence, concluding from the literature review, it was decided to utilize driving simulator
along with eye-movement recording to empirically study the driving performance of drivers in
a controlled laboratory environment.
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— Everyone thinks of changing the world, but no one thinks of changing
himself.
Leo Tolstoy
3
Subjective evaluation of distracting
behavior of the MABTS drivers
Abstract
Driving is a complex task where lack of attention can lead to accidents and near-crash incidences.
Smartphone usage (e.g., calling, texting, navigation, etc.) while driving is among the top contributor
to distraction. The number of Mobile Application Based Taxi Services (MABTS) is increasing rapidly
in India. The MABTS drivers are very much dependent on their mobile phones for navigation and
other purposes. Proper guidelines for the usage of mobile phones for navigation purposes are missing
and needs to be formulated. Due importance has not been paid in this field of research in developing
countries like India. Hence, to understand the problem of distraction among the MABTS drivers in India,
a questionnaire-based survey was conducted. This chapter gives a detailed description of the survey
methodology, inferences drawn, and implications for further research work.
3.1 Introduction
At present the drivers of the ‘Mobile Application Based Taxi Services’ (MABTS) have to
rely on mobile application for confirming a booking, taking call, navigating to the desired
destination and getting payment for the ride. The drivers of the MABTS have to look at their
mobile phone from time to time for managing the trip and navigation. There is no conclusive
evidence in the literature regarding the optimal positioning of mobile devices to ensure easy
and comfortable viewing with minimal distraction. The drivers of the MABTS are positioning
the mobile devices as per their own preference. Hence, the aim of the current research was to
identify the most preferred location of positioning mobile phone by drivers of MABTS and to
know if this location is comfortable or convenient for them. A questionnaire based survey is
carried out to fulfil the above mentioned objective.
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50 3.2. Material and methods
3.2 Material and methods
3.2.1 Respondents of the survey
A total of 188 MABTS drivers participated in the survey. They had a mean age of 31.77 yrs (SD
= 5.59), with driving experience of a minimum of 2 yrs (M = 8.19 yrs, SD = 5.13). Only male
participants responded to the questionnaire since only males drove MABTS taxis in the study
area. It was an anonymous survey and the participation in the survey was completely voluntary
in nature without any incentives. The participants had the choice to leave the survey at any
point in time, or when they get a call for ride-booking. The inclusion criteria for participating
in the survey include having a valid Indian driving license for light moving vehicle (LMV) and
driving a MABTS service company vehicle. For selecting the participants, we used a purposive
(non-probability) sampling technique.
3.2.2 Details of the questionnaire used
An initial pilot study was carried out on (n = 30) MABTS drivers, to prepare the final version
of questionnaire used in the field study. Outcome of the pilot study revealed the common
practices of the MABTS drivers for keeping their mobile phones with/ without using holder for
navigation purpose. It was observed that, drivers in the study generally kept their mobile phone
in one of the eight positions (1 to 9, except position ‘8’), as shown in figure 3.1. Upon asking, “
why don’t you keep the mobile phone on the hub of steering wheel ?", they replied that due to
the unavailability of appropriate mobile phone holder for fixing the mobile phone on the hub
(which could maintain the mobile phone in vertically upright position even when the steering
wheel rotates) they never tried. Researcher included position ‘8’ (hub of steering wheel), along
with all other positions practiced by drivers in the final draft of the questionnaire. Justification
for including position ‘8’ was minimal eye & neck movement for accessing visual information
from the mobile phone screen while looking forward for driving. Previously, Alconera et al.
(2017), used similar locations as shown in 3.1. Hence, in the questionnaire study, total nine
mobile phone positions were considered. The questionnaire used for the survey comprised
of five sections To evaluate the reliability of the questionnaire Cronbach’s alpha (α) value
was calculated. It is the most commonly used measure for evaluating the internal consistency
of a survey/ questionnaire, which uses multiple likert questions (Lund Research Ltd, 2018).
The calculated value of Cronbach’s alpha (α) of the questionnaire (for Likert questions) was
0.72. The minimum requirement of calculated Cronbach’s alpha (α) = 0.7, was satisfied (Field,
2018).
The first part of the questionnaire consisted of demographic information (name, age,
education, driving experience, type of vehicle drive, driving speed range) of the drivers. The
second part comprises questions about physical fitness, pain/ surgery/ injury on neck/ shoulder,
and eye-sight condition. Part 3 inquired about the drivers’ involvement in different distracting
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3.2. Material and methods 51
Figure 3.1: Vehicle interior with different mobile phone positions shown to the drivers for ranking
activities and their relative ease/ difficulty with which they can perform these activities. The
fourth part inquired about the drivers’ preference of the positioning the mobile phone display,
the relative ranking of the positions with respect to each other, for the image illustrated in
figure 3.1, and the relative ease of viewing the display.
Nine mobile phone display locations were shown on the car interior used in this study
(shown in figure 3.1). Out of these nine mobile phone positions, three positions (3,2,1) were
above the horizontal plane of the driver’s normal line of sight. Three positions (6, 5, and 4)
were at of top surface level of the dashboard, two positions (7, 8) horizontal level of steering
wheel mid-line, and one (position 9) was located near the gearbox.
Part 5 inquired about the drivers’ preference for mobile device position for navigation
purpose and its relative position to the driving wheel and dashboard. In the end, a few
open-ended questions were asked to the drivers. These include; “justification of their preferred
position of mobile navigation system", “If there are any MABTS company guidelines for
the position of mobile navigation system," and “justification of shifting the mobile device
position during the night-time." A detailed questionnaire used in this study is presented in the
Appendix A.1.
3.2.3 Procedure adopted for the survey
We approached the MABTS drivers at university, airport, railway station, and hospitals, where
these drivers waited for ride-booking. After an initial interaction with the drivers, a questionnaire
survey was conducted. It took on an average of 15–20 minutes to complete the survey. The
questionnaire was administered to the drivers in their vehicle’s comfort to understand the actual
situation. After the initial interaction, the surveyor explained the purpose/ objective of the survey.
All the respondents gave their consent to participate in the survey. They were informed about
their details’ confidentiality and that no part which could recognize them would be published.
The surveyor explained every question to drivers in a language they were comfortable (Hindi/
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52 3.2. Material and methods
Figure 3.2: Overview of survey administered to the MABTS drivers
Initial interaction & 
survey with the 
drivers of MABTS
Questionnaire was 
prepared based on 
interaction
Pilot study with 
N=10 drivers
Questionnaire administered 
to larger sample of drivers 
(n = 188)
Some open ended 
questions asked to 
drivers
Analysis of the 
data obtained
Interaction & 
feedback from 
drivers
Kendall’s Coefficient 
of concordance, 
descriptive statistics, 
reliability of the data
Reliability 
Analysis 
(α = 0.72)
Inclusion criterion (possessing valid 
Indian Driving License, driving for 
MABTS, must have normal or corrected 
to normal vision)
Figure 3.3: Schematic diagram of methodology adopted for the questionnaire study
Assamese). The surveyors marked the responses to the questions themselves to avoid leaving
unanswered questions and errors. A few open-ended questions were asked at the end. Figure 3.3
shows the complete process of developing the questionnaire and its administration to the drivers.
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3.3. Results 53
3.3 Results
3.3.1 Socio – demographic information
Overall 188 MABTS drivers participated in the questionnaire based survey. All the respondents
were males, since in the study area only males drove MABTS. The respondents age ranged
between 21 to 50 years (M = 31.77 yrs, SD = 5.59), whereas the driving experience ranged
between 2 to 32 years (M = 8.19 yrs, SD = 5.13). In terms of vehicle type 71.27 % drivers
reported of driving hatchback, in comparison to 28.72 % driving sedans. Further, when asked
about the driving speed range, 38.8 % drivers reported of driving between 40 to 60 km/h,
whereas, about 60.1 % reported driving between 60 to 80 km/h. The demographic profile of the
survey participants are given in Table 3.1.
(c)(b)(a)
Figure 3.4: Different positions of mobile phone with respect to steering wheel; (a) left, (b) others (at the
central console), (c) right
3.3.2 Frequency of engagement in distracting tasks
The respondents were asked to identify the various distracting tasks they are involved in while
driving. It was recorded that about 97.3 % indicated that they used the navigation system while
driving, whereas 96.8% agreed that they had conversation with the passengers while driving.
About, 91 % of the drivers agreed of using mobile phone (either for talking, texting, navigation,
or weather) in some way while driving. Table 3.2 shows the frequency of engagement in various
distracting activities.
3.3.3 Preference for placing mobile phones
The MABTS drivers were asked to rank the various in-vehicle mobile phone locations shown
in figure 3.1 based on their preference. For determining the most preferred position, Kendall’s
coefficient of concordance (Kendall’s W) was calculated using Statistics package, IBM SPSS
V25. Kendall’s W is used to determine the degree of agreement between rank givers when
working with ranked data (ordinal level of measurement). The average rank of different
positions is shown in Table 3.3. The Kendall’s W test for concordance revealed that (χ2(8) =
1177.36, p < 0.001,W = 0.783), there is a moderate-high level of agreement between the
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54 3.3. Results
Table 3.1: Demographic profile of the participants
Factor Observation Weighted %
Gender
Male 188 100
Female 0 0
Age (in years)
21–30 94 50.00
31–40 87 46.27
41–50 07 03.72
Driving experience
1–12 150 79.78
13–22 34 18.08
23–32 04 02.12
Vehicle Type
hatchback 134 71.27
sedan 54 28.72
Education
secondary 84 44.68
higher-secondary 94 50.00
graduation 10 05.31
Driving Speed (km/hr)
below 40 1 0.50
40–60 73 38.80
60–80 113 60.10
above 80 1 0.50
Mobile-phone
navigation system
w.r.t. steering
Left 91 48.4
Right 76 40.4
Center 1 0.5
No mobile holder 20 10.6
*participants n = 188; w.r.t. – with respect to.
ratings of the drivers. It is clear from Table 3.3, that most of the drivers gave 1st rank to position
6 (left side of steering wheel), and 2nd rank to position 4 (right side of steering wheel), and
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3.3. Results 55
Table 3.2: Frequency of involvement in distracting activities
Activities Frequency, N (%)
Navigation system 183 (97.30)
Radio/ music system 110 (58.5)
Environment control (AC/ Heater) 177 (94.1)
Mobile phone 171 (91)
Look to in-vehicle meters 169 (89.9)
Interact with passengers 182 (96.8)
Adjust seat 10 (5.3)
3rd to position 7 (central console). Also, the least preferred (ranked) were the positions 8
and 9, which were at the center of steering wheel and below the dashboard near to gear box,
respectively.
Table 3.3: Rankings of different mobile phone positions
Position Mean Rank Overall
Rank
1 4.50 5
2 7.12 7
3 3.77 4
4 1.90 2
5 6.89 6
6 1.77 1
7 3.64 3
8 8.22 9
9 7.20 8
Driver’s perception of the ease with which they can perform different secondary activities
while driving is shown in Table 3.4. It was observed that more than 90% of the drivers rated
that it was not easy for them to operate mobile phones while driving. Whereas more than 63%
drivers agreed that operating radio/ music system or Ac/ heater while driving was relatively easy,
and they could comfortably do these activities while driving. Further, 60% of drivers neither
agreed nor disagreed and remained neutral to the notion of a navigation system’s efficient
operation while driving. Also, 52% of the drivers were neutral to adjusting seats while driving.
The MABTS drivers were asked some open-ended questions at the end. These questions
include; “Is there any company guidelines about the location of keeping mobile phone device
for navigation purpose.”, “What is the reason for keeping the mobile phone at the particular
location were it is now? Why don’t you keep it at some other place ?”, “Do you change the
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56 3.3. Results
Table 3.4: Perception of doing secondary activities while driving
Sr.
No.
Secondary
activities
Ratings, %, total n =188
Strongly
Agree
(1)
Agree
(2)
Neutral
(3)
Disagree
(4)
Strongly
Disagree
(5)
1. It is easy to operate mobile
phone while driving
0.8 2.40 6.11 40.95 49.73
2. It is easy to operate radio/ music
system while driving
10.63 63.82 23.93 1.6 0.0
3. It is easy to operate
AC/ heater while driving
13.82 63.82 20.74 1.33 0.26
4. It is easy to look at
in-vehicle meters while driving
3.98 56.38 28.98 10.37 0.26
5. It is easy to do conversation
with passengers while driving
20.47 60.10 18.08 0.79 0.53
6. It is easy to operate navigation
system while driving
2.66 19.95 60.37 17.02 0.0
7. It is easy to adjust seat
while driving
13.29 28.72 52.12 5.32 0.53
mobile phone position at night, or is it in the same position ?”. In response to these questions
as mentioned above, all the drivers reported that they kept the mobile phone for navigation
purposes according to their convenience, and there was no instruction/ guidelines from the
company regarding the location of the mobile phone for navigation purposes while driving.
Further, a small percentage (10.1%) of drivers also reported that they changed the location of
mobile phone at night and placed it below the dashboard. Whereas, about 89% of driver didn’t
change the location of mobile phone at night and reported that they either reduced the screen
brightness (22.3%) or left the phone as it is during the night/ evening.
Regarding the question about using navigation system on known and unknown routes, 48%
of the drivers said that they rarely used the navigation system on known routes, whereas, 16%
of drivers reported having used the navigation system always or almost all the time. Further,
regarding the usage of navigation system on unknown routes, about 92% of drivers agreed that
they used navigation systems all the time. A small portion of drivers (4%) reported that they
never used the navigation systems, even on unknown routes. Additionally, 6.91% of the drivers
reported that they don’t use the navigation system at all, since they do not like it.
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3.4. Discussion 57
Table 3.5: Perception of comfort and visibility of controls
Sr.
No.
Secondary
activities
Ratings, %, total n =188
Strongly
Disagree
(1)
Disagree
(2)
Neutral
(3)
Agree
(4)
Strongly
Agree
(5)
1. Controls are located at
comfortable location and no
head-torso movement is required
0 0.26 15.42 77.66 6.65
2. Discomfort in viewing the
device leading to distraction
6.38 76.06 17.55 0.0 0.0
3. Discomfort in viewing
more than one display
7.44 57.00 35.6 0.0 0.0
4. Viewing auxiliary display
leads to distraction
2.39 67.28 26.60 3.72 0.0
3.4 Discussion
In this study, we conducted a questionnaire survey to understand the drivers’ engagement in
distracting activities and their preferred location for placing mobile phones for navigation
purposes. The study was administered to MABTS drivers (n = 188). The questionnaire was
found to be reliable with a Cronbach’s alpha (α) = 0.72. Inferences drawn from the outcome of
the survey conclude to some interesting findings.
In general terms, although very small, 6.91% of the drivers reported that they did not use
the navigation system during driving. However, this questionnaire was administered only to the
drivers of MABTS, whose primary ride-booking came from mobile applications. The reason
for this was their disliking of using mobile devices during driving. Additionally, another reason
could be their poor technical literacy in using the taxi service mobile application. This kind of
behavior (although observed on a limited number of drivers) could be seen as a countermeasure
to reduce the effects of distraction caused by using mobile phones while driving. Additionally,
about 22.3% drivers reported that they reduce the brightness of mobile phones’ screen during
night. These behaviors could be seen as an act of counter measuring glare from the mobile
device during night/ evening.
More specifically in-terms of positioning of the in-vehicle mobile phones, the majority
of drivers (48.8%) preferred to keep their mobile phones on the steering wheel’s left side for
navigation purposes. The justifications given by drivers include; 1) this is the common behavior
of the other drivers, and they have adopted from them, 2) the co-passenger can easily see
the mobile device at this location and would be able to look for taxi fare and there would be
transparency about the route being followed. Also, some drivers reported that they used to
keep the mobile phones on the right side of the steering wheel (near the A-pillar), but their
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58 3.5. Conclusion
mobile phones were stolen because of the positions’ nearness to the window; hence they started
keeping it on the left side.
It was also observed that 40.4% of drivers reported that they kept mobile phones on the
steering wheel’s right side near the A-pillar. The justifications which the drivers gave include;
1) Easy to access the mobile device for operating, 2) Ease of visibility as they don’t have to
move their head much, 3) The mobile device doesn’t obstruct their visibility of the traffic as
it is against the right A-pillar. About 10.6% of the drivers reported that they did not keep the
mobile phone on the left or right of the steering wheel for navigation as they either don’t have a
mobile holder device or it got broken. These drivers are reluctant to buy a new mobile-holder
since it would break again.
A few percent (10.1%) of drivers mentioned that they change the position of their mobile
phones during night/ evening, and keep it below dashboard.
The result of the ranking of the preferred position of mobile phone (shown in figure 3.1) is
given in Table 3.3 revealed that position 6 (left of steering) had a mean rank of 1.77, and was the
most preferred position, whereas, position 4 (right of steering) was the second most preferred
position (mean rank = 1.90). Similar results were shown in the previous studies conducted
by Alconera et al. (2017); however, the participants of the experiment were Filipino drivers
who were driving ‘left-handed vehicles’. The mean rank of the positions 3 and 7 were 3.77, and
3.64, respectively. Out of the various mobile phone positions shown in figure 3.1, positions 8
and 9 were the least preferred, with mean rank of 8.22 and 7.20, respectively. The disliking
for these positions was because of their relative location around the dashboard; position 8, was
located in the center of the steering wheel which required the drivers to look down by diverting
their attention from the forward on-road scene, and position 9 was below the dashboard near
the gearbox, which again required a head-torso movement by the drivers for focusing their
attention to the mobile phone screen. It is noteworthy, that although position 5 was straight in
front of the drivers’ forward line of sight, this position had a mean rank of 6.89, because, most
of the MABTS drivers refrained from placing mobile phone at this location, and only 1 driver
(0.5%) was found who placed his mobile phone at position 5.
3.5 Conclusion
In the view of the present field study, it was concluded that drivers are engaging in distracting
activities and used to keep the mobile phone for navigation purposes as per their convenience.
The survey was useful in finding the various distracting behavior the drivers indulged while
driving. Apart from that the survey also identified, various positions for placing the in-vehicle
mobile phones and the most preferred among those given positions. The drivers’ preferred
positions were not found to be optimal since, for focusing attention to mobile phones at
these different locations, the drivers would require movement of head, eye or both, and thus
have to deviate from the forward on-road scene, leading to distraction. This could have a
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3.5. Conclusion 59
detrimental effect on the safety of both drivers and other road users. Hence, further studies in
the virtual simulation environment (digital human modeling), and simulated driving studies
utilizing the eye-tracking system is required to empirically suggest the best possible position
for placing mobile phone in-terms of minimum eye/ head movement, best driving performance,
and improved visual behavior. The outcomes of the present study have many implications
for policy and practices for MABTS drivers. An initiative could be to develop an educational
campaign for MABTS drivers, to teach them regarding the ill effects of over usage of mobile
phones while driving.
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— Yesterday I was clever, so I wanted to change the world. Today I am
wise, so I am changing myself.
Rumi
4
DHM based study to identify comfortable
viewing position for mobile-phone
Abstract
The use of mobile phones as a portable navigation system has gained momentum in recent years due
to the advancements in GPS technology. Although mobile phone is a major cause of distraction, its
complete elimination from the Mobile Application Based Taxi Services (MABTS) ecosystem is impractical
since it has become an inevitable part of driving, particularly for the MABTS drivers. Initial interaction
and field survey revealed that drivers placed the in-vehicle mobile phones at different positions on
the dashboard and the steering wheel. This chapter gives a detailed description of a digital human
modeling (DHM) based virtual ergonomics evaluation study which assesses the head (flexion/ extension
and rotation) movement and hand-reach required by the mobile phone at different positions. This chapter
describes the methodology adopted, analysis, and the results of the DHM study.
4.1 Introduction
The number of mobile-phone subscribers in India has increased many folds recently. According
to the Telecom Regulatory Authority of India (TRAI), there are about 1.13 billion mobile-phone
subscribers in India as of May 2018 (TRAI, 2018b). Now-a-days, most of the drivers (personal
as-well-as hired car) use mobile-phones as a navigation device. The use of mobile-phone
while driving causes diversion of attention from the primary task of driving, and this is one
type of driver distraction (Kircher, 2007). Mobile-phone usage while driving has become the
prominent source of driver distraction causing four types of mutually non-exclusive distractions
which include visual, cognitive, auditory, and manual/ physical (Schick, Ascone, Kang, &
Vegega, 2014). Distracted drivers are four times more likely to be in a crash than non-distracted
drivers (Bendak & Al-Saleh, 2010; Klauer et al., 2006). The Ministry of Road Transport and
Highways (MORTH), Government of India, report of 2016 has shown that using mobile-phone
while driving has become a vital cause of road accidents and has resulted in 4976 number
61TH-2774_146105005
62 4.1. Introduction
of road accidents, 2138 number of deaths and injuries to 4746 number of persons (MORTH,
2016). In India, Mobile Application Based Taxi Services (MABTS) companies like ‘OLA’
and ‘UBER’ are using mobile-phone applications for executing their services. Drivers of these
MABTS use the mobile-phone for taking rides, getting information about the fare, and for
navigation. However, it was observed that mobile-phone used for navigation purpose was
generally mounted at different locations on and around the dashboard and steering wheel, as
per the driver’s convenience (Verma & Karmakar, 2017). Neither there is a guideline, nor
there are specific locations followed by the MABTS drivers for mounting their mobile-phone
for navigation purpose. Hence, in this study, we have tried to identify a suitable location
for mounting the mobile-phone, which ensures minimal biomechanical effort in viewing and
operating mobile-phone when driving.
4.1.1 Human view-field and head movement
Unobscured on-road and in-vehicle field of vision is a crucial aspect of the driving task.
During driving, vision plays an important role, as about 90% of the information received by
human-being from ambient environment comes through visual channel (Jung, Shin, & Kee,
2000). Humans have a binocular field of view extending up to 120° in the horizontal field, but
the vision is sharp in a small area ahead corresponding to the foveal area on the retina. An eye
turn is required to focus on an object outside the foveal region. According to Grandjean (1986),
the visual field is the surrounding that is taken in by the eyes when both eye and head are still.
The visual field has three regions (shown in figure 4.1): a) area of distinct vision: viewing angle
of 1°, b) middle field: viewing angle of 40°, c) external field: viewing angle greater than 40°.
distinct vision
Middle field 
 2° to 40°  
External field,  > 40° 
1°Eye
Figure 4.1: Field of view showing different regions
Strasburger, Rentschler, and Juttner (2011) have defined a foveal vision to be below 2°
eccentricity and peripheral vision for anything outside 2° eccentricity. The area beyond distinct
vision (foveal vision) is the peripheral vision. It is sensitive to light and motion but is not capable
of seeing the details sharply (De Lumen et al., 2019). During the field survey, Verma and
Karmakar (2017) observed that even though the mobile-phone is placed within the comfortable
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4.1. Introduction 63
range of eye movement (i.e. 30° horizontally), the drivers shortly turn their head to read and
comprehend the data from mobile-phone for navigation purpose (Verma & Karmakar, 2017).
Thus, it is worthy to note that a head/ neck movement takes place instead of eye-movement
during the distinct foveal vision, even within eye field of 30° around line of sight. Hence, the
movement head/ neck should be kept to a minimum (±15°) from the straight-ahead line of sight.
This means that the visual displays (mirror and instrument panel, mobile-phone, etc.) should
be placed as close to drivers’ forward line-of-sight. In the sitting posture, Kee and Karwowski
(2001), have shown the values for very-good comfort level for neck flexion (4°), extension (7°),
rotation (17°), and lateral bending (13°).
4.1.2 Literature on in-vehicle display position
Although the guidelines for in-vehicle display arrangements for the convenient and safe use of
on-board navigation systems are available in some countries (JAMA, 2004), there is rarely any
clear guideline available for positioning of smart-phones as portable navigation systems which
are different in size and with variable positions (Zheng et al., 2016).
The Department of Transportation, The Republic of Philippines has implemented the
Anti-Distracted Driving Act (ADDA), RA 10913 which prohibits the drivers from using
communication devices, computing gadgets, and electronic entertainment while the vehicle is
moving or temporarily stopped on traffic signals. The ADDA has a provision for a safe zone
(within 4 inches above the vehicle dashboard) where the placement of mobile-phones (with
navigation applications like Waze and Google maps) is allowed. According to the act, placing
navigational devices/ mobile-phones beyond the safe zone is prohibited, as this area is the line
of sight region. This act considers only the driver’s horizontal line of sight and does not specify
the ideal location of the navigation device (LTO, 2017).
Similarly, the National Highway Traffic Safety Administration (NHTSA), US Department
of Transport gives the criteria that the acceptable eye glances away from the road should not be
more than 2 seconds while performing secondary in-vehicle task related activities (NHTSA,
2012).
Although the researchers have attempted to rank the various positions of the displays based
on the different variables under study, they have not considered the suitable display position in
terms of lower biomechanical effort to view and operate the in-vehicle display. During a driving
simulator experiment involving 20 participants, Zheng et al. (2016) analyzed the eye-tracking
data of drivers interacting with displays of different sizes and positions of portable navigation
systems. They noticed that significantly shorter glance time but a significantly higher glance
frequency were required for the convenient display position with a small visual angle (Zheng
et al., 2016). De Lumen et al. (2019) reported that the navigation devices for Transportation
Network Vehicle Services (TNVS) are mounted at different locations, and there is no fixed
position which can be considered as safe or efficient (De Lumen et al., 2019). During their
TH-2774_146105005
64 4.2. Material and methods
study involving ‘Uber’ drivers to identify the optimal location among three different locations
for the navigation device: left side, right side, and middle (speedometer area) of the steering
wheel, researchers adopted the ‘Peripheral Detection Test’ to measure the driver’s distraction
level. The result of the study showed that the driver’s distraction level is significantly affected
by the position of the navigation device, and the position ‘right side of the steering wheel’
with least distracting was identified as ideal location among the three (De Lumen et al., 2019).
Although this study is the first of its kind attempt to identify the ideal location of mobile-phone
as a navigational device, it is infested with various limitations which include (a) considerations
of only 3 horizontal locations above the dashboards out of many others vertical/ horizontal
locations used by TNVS drivers in reality, (b) not measuring the eye glance time away from the
road (straight ahead line of sight) and time to glance at the particular location of navigational
device. In comparison to the onboard displays/ navigation system, the size of mobile-phones
are relatively small and with varying dimensions. Although there are reported literature and
guidelines for conventional onboard display ensuring driving safety, research pertaining to
portable navigation systems like mobile-phones is still less explored (Zheng et al., 2016). In
the previous studies, only three or four different locations of in-vehicle display were examined,
whereas mobile-phones due to their small size and availability of diverse types of holders, were
conveniently placed by the drivers at different positions around the steering wheel, dashboard,
mid-console and windshield as the portable navigation systems. Moreover, the driver’s comfort
and driving safety in terms of biomechanical effort and reachability is still unexplored.
To identify the optimal position for placing mobile-phone, researcher has studied the
requirement of head and/ or torso movement (rotation, flexion/ extension) and fingertip
reachability, at different positions using Digital Human Model (DHM) in a CAD generated
virtual environment. It was presumed that the position of mobile-phone for navigation purpose
could be considered as the most suitable one from the biomechanical point of view if it satisfies
the following criteria:
• Minimal biomechanical load at neck and torso to glance at the mobile.
• Easy reachability (index fingertip) of the mobile-phone to operate/ navigate.
4.2 Material and methods
4.2.1 Software used
As there are numerous advantages of CAD based virtual ergonomics evaluation over the
traditional method of testing and evaluation, digital human modeling (DHM) tools like CATIA
was used for the current research. It has helped in making decisions by ergonomic design
visualizations (De Magistris et al., 2013; Paul & Lee, 2011). Earlier researchers also claimed
that the use of virtual ergonomics evaluations involving DHM could eliminate the development
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4.2. Material and methods 65
of a physical mock-up before the generation of a prototype (Sanjog et al., 2016). DHM
enables lowering development cost, shortening design time, improving quality, increasing
productivity, enhancing safety, and achieving optimal human-machine interface (Chaffin,
2001). DHM finds its extensive technological application in almost all of the industrial
sectors, including automobile industries (Chang & Wang, 2007; Fritzsche, 2010; Lämkull
et al., 2009). In the current research, digital human modeling software facilitated to measure
biomechanical data (angular deviation) of neck/ torso joints corresponding to the visualization
of mobile-phones positioned at different pre-selected locations by the manikins of different
percentile anthropometric values (5th, 50th, and 95th percentile). In the real world situation,
this would require a significant amount of time and incur huge costs. Moreover, finding any
human subject with all the body dimensions of a particular percentile value is nearly impossible.
4.2.2 Creation of the digital manikin
CATIA (V5R19) software was used to build the digital human model (manikin) for virtual
ergonomic evaluation. CATIA digital human modeling software has been extensively used to
implement ergonomic improvements in the automobile sector (Chang & Wang, 2007), proactive
ergonomics for product design innovation (Uday Kumar, Bora, Sanjog, & Karmakar, 2013),
reproducing working posture for task simulation (Brouillette, Thivierge, Marchand, & Charland,
2012), and assessment of risk in car assembly (Fritzsche, 2010). The unavailability of the
Indian anthropometric database of cab/ taxi drivers led the present researchers to use the
anthropometric database of the civilian adult Indian male population (Chakrabarti, 1997) for
generating the manikins for assessment.
As percentile manikins are widely being used in virtual ergonomics assessment of product
and workstation design (Lanzotti et al., 2019; Potvin & Potvin, 2019; Sanjog, Patel, & Karmakar,
2019), hence, in the present research we have used 5th, 50th, and 95th percentile digital human
model (manikin) respectively representing the smallest, average, and the largest anthropometric
dimensions of the user population. MABTS drivers are predominantly male, and there are
rarely any female MABTS drivers in the current Indian scenario. Hence, DHM analysis has
been performed only by generating percentile male driver manikins (Verma & Karmakar, 2017).
A flow chart of the methodology adopted in the current study is shown in figure 4.2.
4.2.3 Creation of the digital mock-up of the car/ taxi interior
The mechanical design feature of CATIA (V5R19) was used to build the car dashboard. CAD
models of the car dashboard (with interior), steering wheel, car seat, and mobile-phone were
prepared (shown in figure 4.3). Passenger seats and exterior of the car were not created, as they
were not required for the intended assessment purpose. In the previous study by Verma
and Karmakar (2017), it was observed that the majority of the drivers were driving the
“Maruti-Suzuki Alto 800” model of the car. Hence, it was decided to create its CAD model using
TH-2774_146105005
66 4.2. Material and methods
Preliminary Survey and data collection from the 
drivers of Mobile Application Based Taxi Services 
(MABTS)
Identification of different positions of keeping 
mobile phones for navigation used by the drivers 
Interfacing of the manikins with the car dashboard and 
giving them proper driving posture
Identification of suitable position of mobile phone for navigation 
purpose in-terms of ease of head movement and reach
Placing the mobile phone in each of the nine 
positions and measuring the head movement 
(flexion/ extension and rotation) for each of the 
three different manikins 
(5th, 50th, and 95th percentile)
Reach Analysis by creating reach envelop (with 
seat belt tied and extended body) of the mobile 
phones placed in nine positions for each of the 
three different manikins 
(5th, 50th, and 95th percentile)
Generation of CAD model of Car 
interior (seat, steering wheel, dashboard) 
based on standard car interior 
dimensions
Generation of manikins (5th, 50th, 95th 
percentile) based on civilian Indian 
anthropometric database
Identification of the reference points (Accelerator 
Heal point (AHP) and H-Point) to place the 
manikin in proper posture
Figure 4.2: Flowchart of the methodology adopted for the experiment
interior dashboard dimensions for the purpose of the current study. The CAD model of a 4.5 –
inch mobile-phone was created and placed at one of the pre-selected nine positions as found in
the actual situation during the earlier reported questionnaire survey (Verma & Karmakar, 2017).
4.2.4 Selection of mobile-phones positions and their placement
In a survey involving MABTS drivers (n=188) (details in chapter 3), nine (09) different positions
(around the steering wheel and on the dashboard) for mounting the in-vehicle mobile-phone
were identified. These positions were generally adopted by the MABTS drivers according to
their own perception of convenience. Relative positions of the mobile-phones in 3D space have
been described based on the midpoint (intersecting point of the two diagonals) of the devices,
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4.2. Material and methods 67
Figure 4.3: Digital mock-up showing the position of a mobile-phone in relation to other in-vehicle
components (seat, steering wheel, and dashboard)
considering midpoint of position ‘8’ as the reference (shown in figure 4.4); position ‘8’ was
selected by the researcher for the purpose of reference as this position is nearest to the line of
sight horizontally. A description of different positions with respect to the reference position is
shown in Table 4.1.
Figure 4.4: Isometric view of nine different mobile positions around the steering wheel and dashboard
4.2.5 Selection of reference points for positing driver manikins
Giving a proper position along with appropriate posture to the manikin, is a difficult task and is
the main source of error. Hence, in the present work for interfacing, the manikin with the CAD
generated mock-up of the car interior and giving it a correct driving posture, H-Point (SAE,
2009), and Accelerator Heal Point (AHP) (SAE, 2009) were chosen as the reference points.
H-point was the referential point for all the manikins, whereas, proper adjustment of manikin
on the driving seat was based on the Accelerator Heal Point (AHP). According to SAE (2009),
the definition of H-Point and Accelerator Heal Point (AHP) are as follows:
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68 4.2. Material and methods
• H – Point: It is the pivot center of the torso and the thigh on the two or three-dimensional
devices used in defining and measuring vehicle seating accommodation.
• Accelerator Heal Point (AHP): is the lowest point of interaction, of the manikin heel
and the depressed floor covering with the shoe on the un-depressed accelerator pedal.
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M
aterialand
m
ethods
69
Table 4.1: Description of the different positions and orientations of the mobile-phone
Position Description of the position WRT
steering
Drivers
preference
(n, % age)
(x,y,z) coordinates (mm) (α,β ,γ) angles (◦) Vector
distance from
reference
(mm)
1 Right side, top of A-pillar R (3, 2.8) (167.29, -102.29, 383.87) (30, 25, -25) 431.05
2 Top of windshield, above the
steering wheel
C (3, 2.8) (9.91, -161.10, 394.09) (30, 3, -5) 425.86
3 Top of windshield, above the
central console
L (7, 6.54) (-272.16, -93.4, 373.45) (30, -25, 10) 471.44
4 Right side, bottom of A-pillar R (36, 33.64) (170.15, 225.96, 161.04) (110, 31, -15) 325.50
5 At the dashboard, behind
steering wheel
C (1, 0.93) (0.515, 225.97, 153.67) (95, 0, 0) 272.94
6 On the dashboard, above the
central console
L (45, 42.05) (-287.05, 243.04, 85.71) (85, 0, 20) 385.77
7 At the central console, over the
AC vent
L (10, 9.34) (-323.93, 191.96, -44.28) (100, -3, 5) 379.13
8 At the center of the steering
wheel
C (N.A., N.A.) (0, 0, 0) (100, 0, 0) 0
9 Below the dashboard, below
central console
L (2, 1.87) (-332.2, 307.77, -348.42) (110, 0, 5) 571.38
*center of the steering wheel (position ‘8’) is taken as the reference point; R – right, L – left, C – center, N.A. – not available, and WRT – with respect to; x, y, and z – coordinates
of intersection point of two diagonals of mobile screen; α,β ,γ – angular orientation of mobile-phone w.r.t. x, y, and z axes.
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70 4.2. Material and methods
4.2.6 Interfacing manikin with the CAD model of the car dashboard
Ergonomic design and analysis feature of CATIA was used to interface manikin with the CAD
model of the car dashboard with seat and steering wheel. A proper driving posture was given to
the manikin, which was same as that of the cab/ taxi driver. A full-scale (1:1) CAD model of
the car-dashboard was interfaced with the full-scale (1:1) manikins to ensure accuracy in the
investigation. Figure 4.5, shows the manikin interfaced with the car dashboard, with reference
points (AHP and H-point). The 3-D coordinates of H-point for 5th, 50th, and 95th percentile
driver manikins are shown in Table 4.2. The distance between the AHP and H-point of all the
three manikins are also shown in the last column of Table 4.2. The AHP for all the manikins in
all the arrangements was kept same: x = 465.83, y = 88.94, z = 567.10 (mm).
Figure 4.5: Digital human model (manikin) interfaced with a virtual car dashboard with reference
points
Table 4.2: Coordinates of H-Point for 5th, 50th, and 95th percentile driver manikins
Percentile H Point (referential) (mm) AHP − H Point
distance (mm)
x y z
5th 306.38 - 598.77 716.56 721.60
50th 327.19 - 677.89 738.28 797.85
95th 299.56 - 770.69 731.01 890.77
4.2.7 Creation of the reach-envelope
Human reach assessment is an important aspect of ergonomic workplace design (Jung, Kee, &
Chung, 1995). To evaluate the reachability of the mobile-phone at different positions on the
dashboard, reach-envelope was created under two conditions; (a) with constrained arm-reach
and (b) with extended arm-reach.
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4.3 Experiment procedure
4.3.1 Head flexion/ extension and rotation
For this study 5th, 50th, and 95th percentile manikins of adult Indian male population were
considered. These manikins were interfaced with the CAD model of the car dashboard with an
appropriate driving posture. CAD model of mobile-phone used for navigation purposes was
placed in one of the locations found in the actual situation during questionnaire survey from the
MABTS drivers. For analysis, binocular vision with 2° view cone was considered, since this
is the region of visual acuity or distinct vision (Miller-Keane, 2003; Strasburger et al., 2011).
Head rotation, flexion/ extension required for focusing on mobile-phone was measured. For
analysis, only rotation, flexion/ extension of head is performed, and all other body joint angles
were kept fixed. During a survey conducted by Verma and Karmakar (2017), it was observed
that the drivers of MABTS placed their mobile-phone for navigation purposes on one of the
nine different positions, as is shown in figure 3.1.
A CAD model of the car dashboard with all the nine positions for mounting mobile-phone
is shown in figure 4.4 (isometric view). These ‘nine’ positions are used in DHM evaluation
in terms of head (flexion/ extension, left/ right rotation) movements of the manikins. Out of
these nine positions, three positions (1, 2, and 3) were at the same horizontal plane above the
normal line of sight of the driver. The other three positions (4, 5, and 6) were at the level of the
top surface of the dashboard. Two positions (7 and 8) were at the horizontal level of midline
of the steering wheel, and one (position 9) was located near the gearbox (Verma & Karmakar,
2017) below central console, as shown in figure 3.1. These positions are similar to the locations
as adopted by Alconera et al. (2017). Firstly, the analysis was done on 5th percentile manikin,
and rotation, flexion/ extension of the head was measured from an initial neutral position for
one of the mobile-phone position. This process was repeated for all the positions as shown in
figure 3.1 and for 50th and 95th percentile manikin. View-cone of 2° was maintained for all the
manikins. Figure 4.5, shows the initial posture of the manikin. The line-of-sight was kept at
0° before starting to rotate and flex the head for focusing on the mobile-phone. AHP for all
the manikins were kept constant. Movement of the thoracic region (rotation, flexion, lateral
bending) was required only for viewing the mobile-phone at position 9. For rest of the other
positions, the thoracic region of the manikin was constant.
4.3.2 Reach analysis
Reach analysis was performed to find out the positions of mobile-phone among the nine
different positions (shown in figure 3.1) which were easy to operate during normal seating
posture. Reach analysis was performed in two configurations; 1) with constrained arm-reach,
2) with extended arm-reach. The envelope for constrained arm-reach was created for manikin
of different percentiles considering seat belt is attached to restrict torso movement, and joint
TH-2774_146105005
72 4.4. Result
kinematics for reach-envelope was driven from the shoulder joint. The envelope for extended
arm-reach was created for manikin of different percentiles considering seat belt was open/ not
tightened to allow torso movement and joint kinematics for reach-envelop was driven, allowing
axial rotation of waist joint. Reach-envelopes (both constrained and extended) were created for
95th, 50th, and 5th percentile manikins while they were seated at the rearmost, middle, and
forward most positions of the seat-track travel, respectively as specified by their corresponding
H-point locations given in Table 4.2. In both cases, reach-envelopes were created for the tip
of the index finger. The reach-envelopes of the drivers with extended arm-reach are shown
with blue color, and the reach-envelopes of the drivers with the constrained arm-reach (without
flexion of upper body) are shown in red color.
4.4 Result
A graph between head flexion/ extension (°) (y-axis) vs. positions of mobile-phone (x-axis) and
head rotation angle (°) (y-axis) vs. positions of mobile-phone (x-axis) for each of the manikins
(5th, 50th, and 95th), is shown in figure 4.6 and figure 4.7 respectively. The joint angles of head/
neck and torso joints of 5th, 50th, and 95th percentile manikins when viewing the mobile-phone
at nine different positions are shown in Table 4.3.
4.4.1 Head flexion/ extension
The graph in figure 4.6 shows the variation of head flexion/ extension against the position of
mobile-phone. Positive value shows head flexion (towards the body), whereas extension (away
from the body) is represented by negative values. Out of the nine positions, head extension
is required in positions ‘1’, ‘2’, and ‘3’, since; these three positions are above the horizontal
line of sight of the drivers. The range of head flexion/ extension varies from 8° (extension)
in position ‘2’ for 5th percentile to 20° (flexion) in position ‘9’ for 95th percentile manikin.
The maximum amount of head flexion is required for position ‘9’ (17°, 19°, 20° for 5th, 50th,
and 95th manikin). Overall, the maximum amount of flexion is observed for 95th percentile
manikin due to its inherent stature, which is opposite in case of extension.
4.4.2 Head rotation
The relation between head rotation and positions of the mobile-phone is shown in figure 4.7.
The total range of head rotation varies from 30° (right side) to 41° (left side), both these extreme
values are reported for 5th percentile manikin. This shows that 5th percentile manikin has to
rotate his head the maximum in order to focus on the mobile-phone. It is also evident from
figure 4.7 that the least head rotation is being observed in positions ‘2’, ‘5’, ‘8’. All these
positions are on the same line and vertical plane, central to the normal seating posture of drivers.
TH-2774_146105005
4.4. Result 73
1 2 3 4 5 6 7 8 9
-20
-15
-10
-5
0
5
10
15
20
Hea
d fle
xion
 / ex
tens
ion 
ang
le (d
eg.)
Position of mobile phone
 5th     50th      95th
Figure 4.6: Comparative visualization of head flexion/ extension for different percentile manikins at
different positions of the mobile-phone
1 2 3 4 5 6 7 8 9-50
-40
-30
-20
-10
0
10
20
30
40  
 
Hea
d ro
tatio
n an
gle 
(deg
.)
Position of mobile phone
 5th     50th     95th
Figure 4.7: Comparative visualization of head rotation for different percentile manikins at different
positions of the mobile-phone
Overall, it is observed that the maximum amount of head rotation (41°, 33°, 27° for 5th, 50th,
and 95th manikin) is required for position ‘3’.
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74 4.4. Result
Table 4.3: Joint angles of head/ neck and torso of 5th, 50th, and 95th percentile manikins when viewing
the mobile-phone at nine different positions
Pos 5th percentile 50th percentile 95th percentile
1 Head(Ex): 7
◦
Head (Ro): 30◦ (R)
Head (Ex): 5◦
Head (Ro): 20◦ (R)
Head (Ex): 3◦
Head (Ro): 18◦ (R)
2 Head (Ex): 8
◦
Head (Ro): 1◦ (L)
Head (Ex): 6◦
Head (Ro): 1◦ (L)
Head (Ex): 3◦
Head (Ro): 2◦ (L)
3 Head (Ex): 6
◦
Head (Ro): 41◦ (L)
Head (Ex): 3◦
Head (Ro): 33◦ (L)
Head (Ex): 1◦
Head (Ro): 27◦ (L)
4 Head (Fl): 7
◦
Head (Ro): 15◦ (R)
Head (Fl): 8◦
Head (Ro): 13◦ (R)
Head (Fl): 9◦
Head (Ro): 12◦ (R)
5 Head (Fl): 5
◦
Head (Ro): 1◦ (R)
Head (Fl): 7◦
Head (Ro): 1◦ (R)
Head (Fl): 8◦
Head (Ro): 1◦ (R)
6 Head (Fl): 10
◦
Head (Ro): 25◦ (L)
Head (Fl): 11◦
Head (Ro): 23◦ (L)
Head (Fl): 12◦
Head (Ro): 18◦ (L)
7 Head (Fl): 16.5
◦
Head (Ro): 29◦ (L)
Head (Fl): 17◦
Head (Ro): 25◦ (L)
Head (Fl): 17.5◦
Head (Ro): 21◦ (L)
8 Head (Fl): 17.5
◦
Head (Ro): 1◦ (L)
Head(Fl): 18.5◦
Head (Ro): 1◦ (L)
Head (Fl): 19◦
Head (Ro): 1◦ (L)
9
Head (Fl): 17◦
Head (Ro): 20◦ (L)
Head (Lat L): 6◦
Thorocic (Fl): 7◦
Thorocic (Lat L): 11◦
Thorocic (Ro): 18◦ (L)
Head (Fl): 19◦
Head (Ro): 18◦ (L)
Head (Lat L): 8◦
Thorocic (Fl): 13◦
Thorocic (Lat L): 6◦
Thorocic (Ro): 9◦ (L)
Head (Fl): 20◦
Head (Ro): 12◦ (L)
Head (Lat L): 10◦
Thorocic (Fl): 13◦
Thorocic (Lat L): 0◦
Thorocic (Ro): 6◦ (L)
*Ro – Rotation, Fl – Flexion, Ex – Extension, Lat – Lateral, R – Right, L – Left, Pos – Position
4.4.3 Physical validation involving real drivers
Three MABTS drivers were identified whose stature approximately matched with 5th, 50th,
and 95th percentile stature data of the Indian anthropometric database (Chakrabarti, 1997).
Head and torso movements were measured for all the mobile-phone mounting position using
goniometer after the participants adopted a comfortable driving posture in a Maruti-Suzuki
Alto 800 car. Table 4.4 shows the head rotation and flexion/ extension for 5th, 50th, and 95th
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4.4. Result 75
percentile participants when looking at the different positions of mobile-phone.
Table 4.4: Joint angles of head/ neck and torso of 3 real drivers (representative of 5th, 50th, and 95th
percentile statures) when viewing mobile-phone at nine different positions
Position 5th percentile 50th percentile 95th percentile
1 Head(Ex): 10◦
Head (Ro): 26◦ (R)
Head (Ex): 7◦
Head (Ro): 18◦ (R)
Head (Ex): 5◦,
Head (Ro): 17◦ (R)
2 Head (Ex): 10◦
Head (Ro): 0◦
Head (Ex): 8◦
Head (Ro): 0◦
Head (Ex): 4◦,
Head (Ro): 0◦
3 Head (Ex): 8◦
Head (Ro): 45◦ (L)
Head (Ex): 5◦
Head (Ro): 35◦ (L)
Head (Ex): 3◦,
Head (Ro): 30◦ (L)
4 Head (Fl): 7◦
Head (Ro): 20◦ (R)
Head (Fl): 8◦
Head (Ro): 17◦ (R)
Head (Fl): 10◦,
Head (Ro): 15◦ (R)
5 Head (Fl): 5◦
Head (Ro): 0◦
Head (Fl): 9◦
Head (Ro): 0◦
Head (Fl): 10◦,
Head (Ro): 0◦
6 Head (Fl): 12◦
Head (Ro): 27◦ (L)
Head (Fl): 13◦
Head (Ro): 25◦ (L)
Head (Fl): 15◦,
Head (Ro): 16◦ (L)
7 Head (Fl): 18◦
Head (Ro): 35◦ (L)
Head (Fl): 20◦
Head (Ro): 30◦ (L)
Head (Fl): 21◦,
Head (Ro): 27◦ (L)
8 Head (Fl): 15◦
Head (Ro): 0◦
Head(Fl): 20◦
Head (Ro): 0◦
Head (Fl): 25◦,
Head (Ro): 0◦
9 Head (Fl): 20◦
Head (Ro): 25◦ (L)
Head (lateral L): 8◦
Thorocic (Fl): 9◦
Thorocic (lateral L): 15◦
Thorocic (Ro): 20◦
Head (Fl): 23◦,
Head (Ro): 22◦ (L)
Head (lateral L): 10◦
Thorocic (Fl): 15◦
Thorocic (lateral L): 8◦
Thorocic (Ro): 12◦
Head (Fl): 25◦,
Head (Ro): 18◦ (L),
Head (lateral L): 12◦,
Thorocic (Fl): 16◦,
Thorocic (lateral L): 2◦,
Thorocic (Ro): 5◦
*Ro - Rotation, Fl - Flexion, Ex - Extension, R - Right, L - Left.
The output (angle of head flexion/ extension and head rotation) of the virtual study and
the real physical measurements were compared for each of the manikins/ representative real
drivers of similar stature (for 5th/ 50th/ 95th percentile) to find out the difference (if any) using
Mann-Whitney U test, conducted in SPSS v.25.0 (IBM, USA) software. Mann-Whitney U test
revealed that there was no significant difference between the virtual and physical measurement
for head flexion/ extension for 5th percentile (U = 32, p = 0.451), 50th percentile (U = 29, p =
0.308), and 95th percentile (U = 30, p = 0.352) manikins/ representative real drivers of similar
stature. Similar observations were also noticed for head rotation of 5th percentile (U = 39, p =
0.894), 50th percentile (U = 39, p = 0.894), and 95th percentile (U = 38, p = 0.859) manikins/
representative real drivers.
TH-2774_146105005
76 4.4. Result
1 2 3 4 5 6 7 8 9
-20
-15
-10
-5
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9
-20
-15
-10
-5
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9
-20
-15
-10
-5
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9-50
-40
-30
-20
-10
0
10
20
30
1 2 3 4 5 6 7 8 9-50
-40
-30
-20
-10
0
10
20
30
1 2 3 4 5 6 7 8 9-50
-40
-30
-20
-10
0
10
20
30
 Virtual Measured
Hea
d fle
xion
/ ex
tens
ion 
ang
le (d
eg.)
5th percentile
 Virtual Measured
50th percentile 95th percentile
 Virtual Measured
Hea
d ro
tatio
n an
gle 
(deg
.)
Position of mobile phone
 Virtual Measured
Position of mobile phone
 Virtual Measured
 Virtual Measured
Position of mobile phone
Figure 4.8: Comparative visualization of head flexion/ extension and rotation for different percentile
(5th, 50th, and 95th) manikins (virtual) and representative drivers (real) of similar statures
Moreover, the comparison of two sets (virtual vs. real physical) measurements for different
body joints (head flexion/ extension and rotation) for each of the manikin/ representative real
driver of similar stature (for 5th/ 50th/ 95th percentile) have been graphically shown (figure 4.8)
for easy understating of the readers. From figure 4.8, it is clear that the differences between
virtually and physically measured values are minimal and almost similar to each other. For a
clear image of figure 4.8, please refer to appendix A.6.
4.4.4 Reach analysis
Reach-envelope was evaluated under two conditions: a) allowing forward flexion of the trunk/
upper body (simulating the scenario of without seat-belt) as shown in figure 4.9. b) constraining
the forward flexion of the trunk/ upper body (simulating the scenario of with seat-belt) as shown
in figure 4.10.
For each of these two scenarios, reach-envelopes were developed for 5th, 50th, and 95th
percentile manikins. In the case of the driver wearing the seat belt, mobile-phone at positions
1, 2, 3, and 8 were within the comfortable reach for 5th, 50th, and 95th percentile manikins
(shown in figure 4.10). On the other hand, in case of without seat belt condition mobile-phone
at positions 1, 2, 3, 4, 5, 6, 7 and 8 were within the comfortable reach for 5th percentile manikin
(figure 4.9 (a)), whereas, for 50th and 95th percentile manikin, mobile-phone at positions 1, 2,
3, and 8 were in comfortable reach (figure 4.9 (b) and 4.9 (c)).
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4.5. Discussion 77
(a) (b) (c)
Figure 4.9: Extended reach-envelope from the lumber joint for (a) 5th percentile manikin (b) 50th
percentile manikin, and (c) 95th percentile manikin
(a) (b) (c)
Figure 4.10: Reach-envelope, with seat belt tied for (a) 5th percentile manikin (b) 50th percentile
manikin, and (c) 95th percentile manikin
4.5 Discussion
The DHM based analysis indicated that the position of the mobile-phone had a noticeable impact
on the neck movement (flexion/ extension and rotation). According to Kee and Karwowski
(2001), the very-good comfort level for the neck is defined within the flexion of 4°, extension of
7°, rotation of 17°, and lateral bending of 13° in a sitting posture. The results of the present study
showed that the head rotation was minimum for positions ‘2’, ‘5’, and ‘8’ as these positions
were nearer to the straight forward line-of-sight of the driver and on the same vertical line. It
was also seen from the results that the position ‘5’ required minimum head flexion (5°, 7°, 8°)
and rotation (1°, 1°, 1°) for all the three (5th, 50th, and 95th percentile) manikins for focusing
on mobile-phone. These values were very close and inside the limit as mentioned by Kee and
Karwowski (2001), for comfortable head movement. Wittmann et al. (2006) found that the
positions which had the least deviation from the forward line-of-sight had the least detrimental
effect on driving. The only limitation of this position was that it created a visual obstruction to
the forward view-field. On the contrary, position ‘9’ required the driver to turn/ rotate their head
as-well-as their trunk/ torso in order to align their line of sight (gaze line) in the center of the
mobile-phone display. This led to a longer off-road time; consequently increasing the chances
of accidents and near-crash incidences. Hence, this position was deemed unfit/ unsuitable for
mounting the mobile-phone. These results were found to be in agreement with the outcome of
the studies conducted by Wittmann et al. (2006). All the positions above the normal line of sight
(position ‘1’, ‘2’, and ‘3’) which required an extension of the head/ neck for focusing attention,
were also considered unsafe for keeping the mobile-phone for navigation. The studies conducted
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78 4.6. Conclusion
by Wittmann et al. (2006), also showed low visibility scores in the focused condition task for
these positions away from the normal line-of-sight. The position ‘3’ was the same position as
that of the rear-view mirror, and it posed severe safety and visibility issues as the rear-view
mirror is frequently used while driving. The above results are supported by the findings of
Doi et al. (2019) who showed increased reaction time for displays at a vertical position and
reported that the vertical eye movement was difficult than the horizontal eye movement, hence
any position above the normal line-of-sight would reduce the driving performance. Although
the position ‘8’ had less amount of head rotation (about 1°) for 5th, 50th, and 95th percentile
manikins, the amount of head flexion was about 17° to 19° for 5th, 50th, and 95th percentile
manikins. This was higher than the very good comfort level of neck flexion mentioned by Kee
and Karwowski (2001), although, placing mobile-phone at this position would be convenient as
there was a comfortable hand reach. Moreover, the position ‘8’ did not obstruct the forward
on-road view and instrument cluster is visible through the steering wheel. The positions ‘6’ and
‘7’, which were on the left side of the steering wheel is shown in figure 3.1. The head rotation
angle for position ‘6’ was 25°, 23°, 18° for 5th, 50th, and 95th percentile manikin. Similarly,
the head rotation angles for position ‘7’ ranged between 21° to 29° for different percentile
(5th, 50th, and 95th) manikins. For both of these positions, the head rotation angles were way
above the comfort level mentioned by Kee and Karwowski (2001). Studies conducted by Doi
et al. (2019) also showed that for display positions where the horizontal neck movement was
larger, there was an increase in off-road glance duration with a subsequent increase in driver
in-attention as compared to where the horizontal neck movement was less. Position‘4’ was at
the right-hand side of the steering wheel, near the A-pillar. The angle of flexion (7°, 8°, 9°)
and rotation (15°, 13°, 12°) for 5th, 50th, and 95th percentile manikin was relatively close and
within the limit for head rotation as mentioned for the comfort level of head movement by Kee
and Karwowski (2001). Placing mobile-phone at this position would cause a small amount
of neck rotation in addition to the extension of arm-reach for mobile-phone operation. Hence,
position ‘4’ is the second-best position for placing the mobile-phone. The experimental study
conducted by Beck et al. (2017) also confirmed that a display located nearer to the steering
wheel on the dashboard was found to be best for response time, eye-off road time, perceived
workload, perceived safety, and preference. Similar results were also shown in the empirical
studies conducted by Ishiko et al. (2013) for in-vehicle navigation systems.
4.6 Conclusion
The present study evaluated the different positions of the mobile-phone in terms of the comfort
of head/ neck and trunk/ torso movement (rotation, flexion/ extension) and ease of arm-reach
using CAD based virtual ergonomics evaluation. The results of the current study suggest that
the mobile-phones are needed to be placed as nearer to or on straight in front of drivers’ normal
line-of-sight, in order to reduce the inherent distraction caused by inappropriate positioning of
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4.6. Conclusion 79
the mobile-phone for navigation purpose. Mobile-phone position ‘5’ (front of steering wheel)
was found to be suitable in terms of comfort of head movement but it obstructed the forward
view field. Thus fulfilling the objective of identifying the most preferred in-vehicle position of
mobile phone, in-terms of minimum bio-mechanical effort. The position ‘4’ (right of steering
wheel on dashboard) was found to be marginally suitable for placing mobile-phones, as this
would cause neck rotation and extended arm-reach for mobile operation. However, it was found
that placing mobile-phone at position ‘8’ (on the hub of steering wheel) would not only require
minimum head rotation but also provide obstruction free visibility of forward view field as well
as instrument cluster through the steering wheel. Moreover, this location is within a comfortable
arm-reach. From the literature review Beck et al. (2017); Wittmann et al. (2006); Zheng et
al. (2016), it is evident that placing the mobile-phone at defined positions (position no. 4 and
8) would reduce the response time, eye-off road, workload, and increase safety due to lesser
head deviation from the normal line of sight. The work presented in this chapter is an initial
study towards developing the guidelines for mounting the mobile-phone (as navigation device)
inside the vehicle, with the aim to minimize the biomechanical effort of information access and
off-road deviation. Thus it can be concluded that objective 5 as mentioned in section 1.5 was
fulfilled by identifying the most preferred in-vehicle mobile phone position in-terms of reduced
bio-mechanical effort.
Further, studies involving human subjects and driving simulator are required, so that factors
like complexity of the task, task completion time, the effect of tilt of mobile-phone, glare,
illumination, drivers’ cognitive load could be taken into consideration to develop guidelines for
well-justified placing of the in-vehicle mobile-phone for navigation purpose.
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— Innovation distinguishes between a leader and a follower.
Steve Jobs
5
Mounting device development for
positioning the mobile phone at steering
wheel’s hub
Abstract
The DHM based study revealed that in-vehicle mobile phone positions placed nearer to the normal
line-of-sight are better in terms of least head movement and easy hand-reach. This chapter describes
a systematic product development process used to develop a novel mobile phone holder for a car that
can be easily mounted on the steering wheel. Different steps involved in the product development and
design process include planning (customer need identification), concept development, concept screening/
selection, prototype development, and testing. These processes are explained in general and specifically
for the developed mobile phone holder.
5.1 Introduction
A product is something that an enterprise sells to its customers based on their needs. A product
may be tangible (like bicycle, television, car, etc.) or intangible (services provided by the
bank, doctors, airlines, etc.); it can be either a consumer (those used by common person) or an
industrial (those used by industries for producing goods) product (Ulrich & Eppinger, 2016).
Product development process is the entire set of activities that an enterprise follows, from
identifying the market opportunity (need identification) to designing and finally commercializing
the product. A generic product development process consists of many phases, which include;
need Identification, concept development, system-level design (define product architecture,
subsystem and components), detailed design (detailed specification about the geometry, material
and tolerance of each part), testing and refinement, and production ramp-up (Ulrich & Eppinger,
2016). Flowchart showing this generic process of product development is shown in figure 5.1.
81TH-2774_146105005
82 5.2. Need/ requirement of a mobile-holder . . .
Ideation
Prototyping
Concept 
generation
Prototype testing 
and Refinements
Figure 5.1: A generic product development process (Adapted from Ulrich and Eppinger (2016)).
5.2 Need/ requirement of a mobile-holder for car
During the initial survey of MABTS drivers, all the positions used for keeping mobile phone
was exhaustively determined. Ranking of the positions was done to find out the most preferred
position (details in chapter 3). Placing the mobile phones on the steering wheel was not found
during the survey and got a lower rating from the drivers. A virtual ergonomic evaluation of
the mobile phone placed at all the different positions using CATIA-DELMIA as a DHM tool
was carried out to determine the biomechanical load of viewing and easy hand-reach (details in
chapter 4). The results revealed that in-vehicle mobile phone positions, which are less eccentric
from the line-of-sight, are more suitable (positions on the steering wheel and behind the wheel
on the dashboard). A market survey showed, non-existence of mobile-holder, which could
be mounted on the steering wheel and simultaneously keep the mobile phone in a vertically
upright position even when the steering wheel rotates.
Hence, to empirically examine the most suitable in-vehicle mobile phone position for
navigation purposes, a mobile phone holder was needed to be developed. The developed mobile
phone holder should facilitate easy mounting on the steering wheel and keep the mobile phone
in a steady-state, even when the steering wheel is rotated.
5.3 Methodology adopted
For this study, the following steps were followed:
(i) Field survey: Initially, semi-structured interview (consisting of both closed and
open-ended questions) was conducted with the drivers who were using the mobile-phone
holder in their car.
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5.3. Methodology adopted 83
(ii) Concept generation: Concepts sketches of the mobile-phone holder were generated based
on customer needs. Morphological chart was used for generating alternate concepts of the
product.
(iii) Concept selection/ screening: Different concept alternatives of the mobile-phone holder
were compared, evaluated, and screened by the design team, using the Pugh concept
selection matrix.
(iv) Prototype development and field trail: A working prototype was developed. The CAD
model was generated before physical prototyping.
Development process of the mobile-phone holder
According to Ulrich et al., a product development process is a set of activities which is employed
to conceptualize, design, and commercialize a new product (Ulrich & Eppinger, 2016). The
process of designing and developing a new product (mobile phone holder in this case) consists
of two broad phases, each of which further divides into three sub-activities. These two phases
are Ideation (consists of customer need identification, concept generation, and concept selection)
and Prototyping (which consists of Detailed design, prototype testing & refinement, and final
production). Generic product development process is shown in figure 5.1.
5.3.1 Customers’ need identification
Careful assessment of market is needed for designing a successful new industrial products
(Piegorsch, 2009). Keeney and Lilien (1987) in their work introduced Multi-attribute analysis,
which they showed to have potential in aiding product design process (Keeney & Lilien, 1987).
For the purpose of this study, to identify customer needs, a total of 107 male drivers were
contacted. Semi-structured interview was conducted and their response was recorded. These
covered the aspects about their usage pattern of the mobile-phone holder, relative placements
around the steering wheel, cost, size etc. Their response was noted and the data was interpreted
in terms of customer needs to formulate the design objectives. It helps in designing the concept
of product. The key features of the design objective are that it manages and controls the design
and is easily understood by both the client and designer.
5.3.2 Concept generation
Brainstorming session was conducted with a small design group to identify the suitable location
for mounting mobile-phone on the steering wheel. Five possible location were identified (shown
in figure 5.2).
• Location ‘A’: It is at the top periphery of the steering wheel; placing here would obstruct
the view of the instrument cluster.
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84 5.3. Methodology adopted
• Location ‘B’ and ‘C’: located at left and the right periphery of the steering wheel; there
would be deviation from the straight forward line of sight.
• Location ‘D’: situated at the bottom periphery of the steering wheel; mobile-phone, if
placed here, would increase the neck and eye movement.
• Location ‘E’: This position is at the center of steering wheel; there will be minimum
deviation from the straight forward line of sight.
Figure 5.2: Possible location of mobile-phone on steering wheel.
Hence, it was decided to design a mobile-phone holder which could be mounted at the
center of steering wheel, as there would be minimal deviation from the straight forward line of
sight. Thereafter, to generate various concepts of mobile-phone holder, a matrix containing all
the possible solutions called the Morphological chart (Norris, 1963) was prepared (shown in
Table 5.1). For this study, the product was divided into the following five functions: 1) Fixing
on the steering wheel, 2) Viewing angle adjustment, 3) Type of clamp opening, 4) Holding
mechanism, 5) Rotating mechanism; and for each of the functions, five alternative options were
made (shown in Table 5.1). Six alternative concepts of the mobile-phone mounting device were
prepared by using one option for each of the function.
5.3.3 Concept selection
Concept selection is a critical stage in the product development process. After various concepts
were developed, appropriate concept was selected or screened out based on the design objective
described earlier. The design team evaluates the concept alternatives and gives scoring based on
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5.3. Methodology adopted 85
Table 5.1: Morphological chart for Mobile-phone holder for car
Functions Options
1 2 3 4 5
(a) Fix to
steering-wheel
Vacuum
suction
Magnet Sticking Clamping Screw
to base
(b) Adjust
viewing angle
Ball and
socket
Swan
neck wire
(c) Attaching
and detaching
Both-side
open
One-side
open
Bottom
open
(d) Holding
mechanism
Clipping Spring
loaded
Rack and
pinion
Elastic
band
Screw
(e) Rotation
mechanism
Gyroscope
(electronic)
Ball bearing
(mechanical)
Hand
adjustment
(manual)
the design objectives. Different concepts of mobile phone holder were evaluated using the Pugh
chart (Otto & Wood, 2001; Pugh, 1991) method for concept selection, and a decision matrix is
prepared. Selecting the DATUM or the reference is of utmost importance in this method. The
design team voted, concept ‘2’, be chosen as ‘DATUM’ or reference, with which other selected
concepts will be evaluated. Concept alternative which received higher score is proceed further
with prototype development.
5.3.4 Creation of virtual mock-up in CAD
A virtual mock-up of the selected mobile-phone holder concept was prepared before making
the prototype. Three-dimensional, Solid CAD model was created using Solid-works (v16)
software; various parts of the product was made and assembled using Solid-works platform.
Two-dimensional drawing of all the part of mobile-phone holder with measurements (in mm)
was drafted.
5.3.5 Prototype development
Various components of the mobile-phone holder were gathered and suitably modified in design
studio as per the requirement of the conceptualized mobile-phone holder. The prototype
consisted basically of three parts: (a) base (b) ball and socket (c) mobile-phone holder. Base
was prepared using Thermoform plastic as material, by Vacuum forming process. A miniature
ball bearing (No. 698zz) was procured from the market. This ball bearing was used to prepare
the mold of the base and was finally fixed inside the base, such that it does not skip out. The
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86 5.4. Observations
second part is the ball with a small stick, made of nylon. It was prepared by turning process in
lathe. For procuring the third part of the mobile-phone holder, which is the holder mechanism,
‘Jugaad’ (Agnihotri, 2015; Prabhu & Jain, 2015) technique was used and was taken from an
already existing product in the market.
5.3.6 Usability testing and user feedback
User feedback was collected to check the efficacy of developed product. Fifteen driver
volunteered to participate in the study. Demonstration was given about fixing of the
mobile-phone holder on the hub of steering wheel, and it’s working during navigation
and driving tasks. Table 5.2 shows the questionnaire for feedback. Usability of the novel
mobile-phone holder was evaluated using System Usability Scale (SUS) (Brooke J. & Brooke,
1996). Fifteen driver volunteered to participate in usability testing and SUS was administered
to them after they interacted with the mobile-phone holder prototype. The SUS scores was
interpreted in terms of adjective rating and acceptability Bangor, Kortum, and Miller (2009,
2008), shown in Table 5.3.
Table 5.2: Questions used during user feedback.
Sr.
No.
Feedback questions Low
(1–2)
Middle
(3)
High
(4–5)
1. How likely is there that you will use this product ?
2. Based on the material and design aspects do you feel
the cost of $5 justified ?
3. How likely do you feel that this product is helpful to
you ?
4. Do you think that the mobile mounting device is
innovative in nature ?
5. How will you rate the Aesthetics of the developed
product ?
6. How likely is there that you will refer this product
to your family members/relatives/ friends ?
5.4 Observations
5.4.1 Insights from the field survey
To understand the customer needs, a semi-structured interview was conducted. A total 107 driver
took part in this survey process. Their responses were noted down, and data was interpreted.
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5.4. Observations 87
Table 5.3: SUS scores with corresponding adjective and acceptability rating.
SUS Score Adjective rating Acceptability
89—100 Best Imaginable
Acceptable84—88 Excellent
71—83 Good
50—70 OK Marginal
32—49 Poor
Unacceptable20—31 Awful
00—19 Worst Imaginable
The relative percentage of drivers and their preference regarding the cost of mobile-phone
holder they use is shown in figure 5.3.
About 50% of the drivers used, mobile-phone holder which ranged from $ 3.5 to $ 7 (approx.
|250 – |500); whereas, 36.45% preferred to use mobile-phone holder, which are below $ 3.5
(approx. |250). For the question, what size of mobile-phone they use for navigation purpose
in their cars, about 24.3% of drivers used mobile-phone having a screen size of 4.5-in. Some
other mobile-phone screen sizes being used by the drivers, recorded during the survey were
4.7-in (19.6%), 5-in (15%), 5.5-in (13.1%), 5.2-in and 5.3-in (each 9.35%). figure 5.4, shows
the frequency curve of mobile phone size, and their relative usage percentage by drivers during
the survey.
Apart from this the drivers were also asked about their preferred position of keeping the
mobile phones (left, right or center). About, 57.9 % preferred keeping their mobile phone on
left side, whereas 36.4 % said they like to keep it on right side, a very small percentage, and 5.6
% said they keep it at center. It was also noted that everyone said that they would like to operate
and install the mobile- phone holder with minimum effort and without any assistance. Hence,
following design objectives are formulated based on customer needs:
1. Size: The mobile-holder easily mounts at the center of steering wheel without hindering
its free movement.
2. Installation: It should be easy to install on the steering wheel.
3. Adjustability: The mobile-holder should provide for a change in the angle of viewing of
mobile phone and keep the phone in upright even while steering wheel movement.
4. Universal: It should be able to adjust to accommodate mobile phones of different size.
5. Cost: The mobile-phone holder is lower in cost than the existing competitors’ products.
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88 5.4. Observations
36.45
49.53
14.02
< 250 250 - 500 500 - 7500
10
20
30
40
50
Rel
ativ
e fre
que
ncy
 (%
)
Cost of mobile holder
Figure 5.3: Relative frequency of the mobile-phone holder cost
4.5 4.7 5 5.2 5.3 5.4 5.5 5.8 6
0
5
10
15
20
25 24.3
19.6
15
9.35 9.35
0.935
13.1
7.48
0.935
Rel
ativ
e fre
que
ncy
 (%
)
Size of mobile phone (inch)
Figure 5.4: Relative percentage of mobile phone size
5.4.2 Generated concepts and their descriptions
Morphological chart was used for generating concepts. Table 5.1, shows the morphological chart
of mobile-phone holder for car, with various options as column, and different functions as each
row. By using the Morphological chart, many concepts were generated (by choosing one option
for each function of the product), out of which the design team selected six concepts which
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5.4. Observations 89
were found to be feasible. The design objectives obtained from customer needs, formulated the
functionality of the novel product. Thus, each of the concept is obtained from combination of
one option for each function; these combinations for each concept is given below in figure 5.5.
These concepts of mobile-phone holder is shown in figure 5.5 (a – f). A brief description of
each concept is given below:
(a) 1a+1b+1c+3d+2e (b) 2a+2b+1c+1d+3e (c) 3a+2b+1c+2d+3e
(d) 5a+1b+3c+5d+3e (e) 2a+1b+1c+2d+2e (d) 3a+1b+1c+3d+2e
Figure 5.5: Different concepts of mobile-phone holder developed.
1. Concept 1: In this concept, the phone is held from the sides, by the arms of the holder,
which come out uniformly by use of rack and pinion mechanism. The phone can be
tightly fixed by pressing the arms of the holder with the phone. A ball bearing is attached
at the back, which in-turn is attached to the steering wheel by stick pad. Hence, the holder
can rotate and stay in an upright position even when the steering is rotated. Shown in
figure 5.5(a).
2. Concept 2: The sketch is shown in figure 5.5(b). The phone can be held from top and
bottom by clipping mechanism. The back side of this is attached to the bearing through
the pivot of the clip. Hence, the angle of the phone can also be adjusted. The bearing can
be attached to steering wheel by stick pad.
3. Concept 3: In this concept, the phone is held from the bottom corners. The jaws open by
a rack and pinion type mechanism. By pressing the jaws we can tighten the mobile-phone.
A bearing is attached at the back of the holder which can be fixed at the centre of the
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90 5.4. Observations
steering wheel by a stick pad.The position of the bearing attachment is not at the center
of the holder but above the horizontal axis — shown in figure 5.5(c).
4. Concept 4: In this the phone is held from the top and bottom. The mobile-phone fits in
by extending the bottom jaw of the holder, which is spring loaded. At the top, a screw
can be tightened to fix the position of mobile-phone. A bearing is attached at the back
which is again attached to the steering wheel stick pad — shown in figure 5.5(d).
5. Concept 5: This concept is shown in figure 5.5(d). This holder consists of three jaw
system- 2 sideways and 1 at bottom. A ball bearing is attached at the back, which can be
fixed to the steering wheel by stick pad. The center of this holder is above the horizontal
axis, to maintain the phone weight to bottom.
6. Concept 6: In this concept (shown in figure 5.5(e)), the mobile phone is held by two
jaws of the mobile holder which opens simultaneously by the press of a button, by rack
and pinion mechanism. The jaws can be closed by pressing them together. A rotating
mechanism is provided with the help of a miniature bearing which maintains the mobile
holder in an upright position when the steering wheel is rotated. The center of this bearing
is attached to the ball and socket joint which provides the facility of changing the angle
of the mobile when it attached to the mobile holder. The entire assembly can be easily
fixed at the center of steering wheel.
5.4.3 Final concept based on Pugh chart score
Based on Pugh chart matrix, the scores of different concepts is shown in Table 5.4. Out of all
the alternatives, concept ‘6’ received the highest score of ‘5’ and it was further taken-up for
physical prototype development.
Table 5.4: Pugh concept selection matrix for a mobile-phone holder for car
Weights Concept
1
Concept
2
Concept
3
Concept
4
Concept
5
Concept
6
Size 1 − D + + − +
Installation 1 + A + + + +
Adjustability 2 − T − − − +
Universal 2 + U + + + +
Cost 1 − M + 0 − −
∑+(Pi) +3 0 +5 +4 +3 +6
∑−(Ni) −4 0 −2 −2 −4 −1
∑ −1 0 +3 +2 −1 +5
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5.4. Observations 91
5.4.4 Generated CAD model and final physical prototype
Three-dimensional solid CAD modeling of different part was made and then assembled in
SOLIDWORKS (v.16) platform. The different views of the product’s CAD model is shown in
figure 5.6. An exploded view of the mobile-phone holder is shown in figure 5.7. The physical
prototype of the conceptualized mobile-phone holder is shown in figure 5.8. It consists of three
parts: (a) mobile-holder (b) ball and socket (c) base. The approximate cost of the developed
prototype is between $4 to $5 (approx. |290 – |350). The two-dimensional drafting (with
measurements in inches) of the mobile-phone holder concept is shown in figure 5.9, detailed
drafting is given in Appendix A.7 (measurements in mm).
(a) (b)
(d)
(c)
Figure 5.6: Different views for the CAD model of mobile-phone holder; (a) rear-view, (b) top-view, (c)
side-view, and (d) perspective view
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92 5.4. Observations
Base
Mobile holder
Ball
Ball bearing
Nut
Figure 5.7: Exploded-view of mobile-phone holder
Figure 5.8: Different views of prototype mobile holder.
5.4.5 Insights from usability testing and user feedback
Fifteen drivers volunteered for usability evaluation and rate the product on System Usability
Scale (SUS) after they were shown and interacted with the product prototype. A SUS score
value of 83.67 was obtained which shows “good” and “acceptable” usability rating, according
to the adjectives shown in Table 5.3. The ratings for various items of SUS is shown in Table 5.5.
Figure 5.10 and figure 5.11 show the ratings for these odd and even-numbered questions
respectively, in a pictorial form. It was observed that, for odd-numbered questions (positively
phrased), the responses were mostly ‘agree’ and ‘strongly agree’; in-contrast to even-numbered
questions (negatively phrased), were high responses percentages lied mostly between ‘disagree’
and ‘strongly disagree’.
The feedback of the users was recorded using the questionnaire (shown in Table 5.2). The
mean ratings by the users is shown in figure 5.12. Overall feedback score of 4.46 out of 5
was obtained. A horizontal line at ‘3’, indicated the median value, the mean score for all
the questions were above it. This indicated the overall positive feedback by the users. The
smart-phone mounting device was tested under naturalistic driving condition and was observed
to move/ rotate about 10° – 15° under sudden jerks and motion (due to rotation of the steering
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5.4. Observations 93
Figure 5.9: Two Dimensional drafting of the mobile-phone holder
wheel) and it returned to its initial vertical position within 600 to 700 milliseconds, after the
sudden motion subsides.
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94 5.5. Discussion
Stronglyagree Agree Neutral Disagree Stronglydisagree
0
10
20
30
40
50
60
70
80
Perc
enta
ge r
atin
g (%
) 
 Q1   Q3   Q5   Q7   Q9
Figure 5.10: Percentage ratings for questions 1, 3, 5, 7, 9 of SUS
Stronglyagree Agree Neutral Disagree Stronglydisagree
0
10
20
30
40
50
60
70
80
Perc
enta
ge r
atin
g (%
) 
 Q2   Q4   Q6   Q8   Q10
Figure 5.11: Percentage ratings for questions 2, 4, 6, 8, 10 of SUS
5.5 Discussion
Literature shows that placing visual displays nearer to the straight forward line of sight (which
have smaller viewing angels), results in improved performance of drivers by reducing the glance
time as well as reaction-time to visual display and consequently reduces driver distraction
(Wittmann et al., 2006; Zheng et al., 2016). Therefore, mounting the mobile-phone as an
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5.5. Discussion 95
Table 5.5: System Usability Scale items and their ratings
Sr.
No.
System usability scale
questions
Ratings, % (n), total n =15
Strongly
Disagree
(1)
Disagree
(2)
Neutral
(3)
Agree
(4)
Strongly
Agree
(5)
1. I think that I would like
to use this product frequently.
00 (0) 00 (0) 00 (0) 60 (9) 40 (6)
2. I found the product
unnecessarily complex.
47 (7) 53 (8) 00 (0) 00 (0) 00 (0)
3. I thought the product
was easy to use.
00 (0) 00 (0) 00 (0) 60 (9) 40 (6)
4. I think that I would need the
support of a technical person
to be able to use this product.
60 (9) 40 (6) 00 (0) 00 (0) 00 (0)
5. I found the various functions
in the product very well
integrated.
00 (0) 00 (0) 07 (1) 60 (9) 33 (5)
6. I thought there was too much
inconsistency in the product.
40 (6) 40 (6) 20 (3) 00 (0) 00 (0)
7. I would imagine that most
people would learn to use
the product very quickly.
00 (0) 00 (0) 13 (2) 20 (3) 67 (10)
8. I found the product
very cumbersome to use.
33 (5) 27 (4) 40 (6) 00 (0) 00 (0)
9. I felt very confident using
the product.
00 (0) 00 (0) 7 (1) 67 (10) 27 (4)
10. I need to learn a lot of things
before I could get going
with this product.
47 (7) 53 (8) 0 (0) 0 (0) 0 (0)
in-vehicle navigation device close to the straight forward line of sight must improve the driving
performance. Middle of the steering wheel for positioning mobile-phone was planned as it is
presumed beneficial. It allows lesser viewing angle and less obscuration of the forward on-road
view field as well as instrument cluster located back-side of steering wheel. Although, based
on earlier research related to position of in-vehicle displays/ navigation screen, it is presumed
that middle of the steering wheel is the best suited location for mounting mobile-phone but
the superiority of selected location should be empirically established. Objective methods of
experimentation using eye-tracking (De Lumen et al., 2019), driving simulator (Doi et al.,
2019), and neck angle (flexion, extension and lateral movement) measurement should be done
for this purpose.
Although there is negligible horizontal/ lateral eye and/or neck movement to visualize the
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96 5.5. Discussion
4.67 4.60 4.73 4.20 4.33 4.20
1 2 3 4 5 60
1
2
3
4
5
6
Feedback questions
Mea
n ra
ting
s
Figure 5.12: Mean rating for different feedback questions.
display of the smart-phone positioned on the hub of steering wheel, there is still requirement
of downward eye and/or neck movement. To avoid this downward eye and/ or neck
movement, mobile-phone could be alternatively positioned on the dashboard or hanging from
the windshield, but these positions lead to obscuration of forward view-field. Another alternative
to avoid downward eye and/ or neck movement is the use of Head-Up Display (HUD), but there
are various limitations of HUD as stated by earlier researchers (Bhise, 2012). Moreover, HUD
are costly, and it is not compatible for various navigation applications. The developed product
(device for mounting smart-phone on steering wheel hub) is innovative in nature due to novelty
in its features as compared to those already existing in the market. The novel features of the
mounting device include (a) provision for fixing the phone/ navigation device at the hub (center)
of the steering wheel, (b) use of ball and socket joint which allows for adjustment of angle
of mobile-phone for better viewing experience (drivers can easily adjust the viewing angle
of the mobile-phone to reduce the glare and better visibility), (c) application of ball bearing
system to the mounting device to facilitate upright position of the mobile-phone even when the
steering wheel is in rotation, (d) lightweight (approx. 200 gm). In the current research, detailed
product development methodology starting from conceptualization to prototype development
has been covered and the adopted methodology is in corroboration to other innovative product
development techniques (Otto & Wood, 2001; Ulrich & Eppinger, 2016).
Brainstorming session with the designers’ group was instrumental in generating optional
ideas for each of the sub-functions of the mounting device. Using Morphological analysis/
chart, large number of concepts was possible in the given time. Additionally, the designers
were able to improve the overall quality of product by a slight change in components to address
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5.6. Conclusion 97
the same function, because all the data is in front of them in the chart (Dandavate & Sarje,
2012). Similar scientific endeavors where morphological analysis were used for generating
results in the fields of smart furniture design (Dragomir, Banyai, Dragomir, Popescu, & Criste,
2016), education (Ritchey, 2010), automotive components (Mansor, Sapuan, Zainudin, Nuraini,
& Hambali, 2014) and architecture (Amorim, 2009). The best solution among the generated
concepts of the mounting device was determined using the Pugh matrix. It is simple and has
been effectively used in comparing the alternative concepts in the diverse product domain of
electrical appliance (Lin & Hsiao, 2019), packaging/ containers (Wu & Hsiao, 2019). For
measuring the perceived usability of the system, multiple standardized questionnaires are
available. Effective use of System Usability Scale (SUS) can be found in evaluating usability
of the system in domains relating to mobile-app development (Kaya, Ozturk, & Gumussoy,
2019; Kortum & Sorber, 2015), healthcare device (Liang et al., 2018), automobile (Deng et al.,
2019) and hand-tool design (Dianat, Asadollahi, & Nedaei, 2017). In current research, SUS
was adopted for checking the usability of the mounting device as this tool were reported to
be the most reliable option even with small number of participants (Tullis & Stetson, 2004).
One of the visible limits of the study is that it takes into account the opinion and feedback only
from male drivers. However, in the future study female drivers may also be included to have a
better understanding of the scenario. Secondly, the final prototype was made using ‘Jugaad’
technique. Future studies could fruitfully explore different material as well as manufacturing
technology for mass production and making the product much affordable. Business plan to
commercialize the developed mounting device are beyond the scope of current study and can be
taken up further. Additionally, as the product is innovative and has market potential, initiative
for protecting the Intellectual property rights (IPR) is needed.
5.6 Conclusion
Following the current research, an innovative smart-phone mounting device was developed
through systematic user-centered product design approach. The developed product is
in-expensive, light-weight, easy to use and has the potential to become a marketable product.
The developed mobile phone holder has a self adjusting feature which can be mounted in
the center of the steering wheel. It is expected that positioning of smart-phone at the hub of
steering wheel with the help of developed mounting device would reduce biomechanical effort
of neck and/or eye movement for information access from the screen and thereby reduction of
driver distraction. However, further experimental study involving this developed mobile-phone
holder in a simulated environment is required to validation this statement.
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— Optimism is the faith that leads to achievement. Nothing can be done
without hope and confidence.
Helen Keller
6
Experimental validation of the preferred
in-vehicle mobile-phone position
Abstract
This chapter presents an empirical study conducted to evaluate the most suitable in-vehicle mobile phone
position. This study uses the construct of lane changing test (LCT) in a simulated driving environment.
The driver has to simultaneously perform secondary task on the mobile phone and lane changes on
a simulated track. Lane change indications are presented to the drivers on the simulator monitor.
Eye-tracking variables were also measured to identify the total number of glances away from the road
and eyes-off-road duration during the simulated driving condition while performing the secondary task
on the mobile phone placed at different positions. The subjective workload of the drivers was assessed
using driver activity load index (DALI). Results, discussion, limitations, and conclusion of the study are
presented at the end in this chapter.
6.1 Introduction
Globally, road traffic accidents are the 8th leading cause of fatalities and injure. An estimated
1.35 million people die due to road traffic accidents annually (WHO, 2018). Driver distraction
is one of the causes of road accidents, and one of the reasons for driver distraction is the use of
mobile phones while driving. Mobile phone use in our daily life has also increased. According
to “Ericsson’s mobility report”, the total number of mobile subscriptions worldwide was around
7.9 billion in Q3 of 2018; it also estimated 8.9 billion subscribers by 2024 (Ericsson, 2018).
Advancements in communication and information technologies have led to mobile phone use
as an in-vehicle information system (IVIS) (Horrey et al., 2006). These mobile phones, used as
IVIS, provide drivers with more information about driving and non-driving tasks (navigation,
vehicle status, weather, and entertainment). It is frequently discovered that drivers place the
mobile phone inside the vehicle at various locations (on the dashboard/ windshield close to
99TH-2774_146105005
100 6.1. Introduction
the central console, close to the base of A-pillar) (Verma & Karmakar, 2020). The use of
mobile-phone-based IVIS is often being associated with inattention to driving, causing driver’s
distraction, thereby impairing road safety (ISO, 2010). According to Ranney et al. (2001),
driver distraction is “any activity that takes a driver’s attention away from the task of driving.”
Any distraction from rolling down a window, over adjusting a mirror, tuning a radio to using a
cell phone can contribute to a crash. It is worthwhile to point out that De Lumen et al. (2019),
in their study, found that the drivers have no idea about the safe and efficient location to mount
their navigation devices.
6.1.1 In-vehicle display position in the driving context
Previous research have evaluated the effect of in-vehicle display positions on various aspects of
driving (De Lumen et al., 2019; Doi et al., 2019; Ganesh et al., 2015; Radakrishnan et al., 2016;
Verma & Karmakar, 2020; Wittmann et al., 2006; Zheng et al., 2016).
Studies have focused on positioning of the infotainment screen inside the vehicle for
better visual experience, emphasis was given to parameters like vision angle, avoiding any
obscuration due to vehicle components, avoiding in-vehicle reflections and avoiding ambient
reflections (Radakrishnan et al., 2016), and cluster packaging process flow for in-vehicle visual
hindrance free instrument cluster position (Ganesh et al., 2015). Some other researchers have
conducted empirical studies to determine the optimal location of in-vehicle displays. In their
study, De Lumen et al. (2019) measured the driver’s visual distraction level by conducting a
peripheral detection test on three locations around the steering wheel to determine the ideal
location for placing mobile navigation device. Further, researchers have also used digital
human modeling to identify the suitable location for mobile navigation device. Verma and
Karmakar (2020), measured head rotation, flexion/extension of the manikins (5th, 50th, and
95th percentile), when mobile phones are placed at nine different locations around the steering
wheel. It is evident that there is a lack of rules or guidelines for the optimal position of mobile
phone-based IVIS. Further, formulating driver distraction policy is an incremental process
as bringing the empirical and theoretical knowledge is a complex process (McGehee, 2011).
However, some countries have enacted laws to prevent distracted driving. One such country is
the Philippines, which has implemented the Anti-Distracted Driving Act (ADDA, RA 10913).
It proposes a safe zone for placement of mobile phone-based IVIS (LTO, 2017).
Further, the research conducted by Wittmann et al. (2006), hypothesized that the primary
task of driving would have a strong degrading effect as the eccentricity of display and workload
condition of secondary task increases. They reported an exponential decrease in driver’s
performance as a function of the distance between the line-of-sight and on-board display
position. Also, the empirical study of Zheng et al. (2016) evaluated the suitability of display
positions based on eye-gaze tracking of drivers, when navigation systems were placed at
different locations around the dashboard. The findings suggest that in-vehicle display positions
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6.1. Introduction 101
with small visual angles have significantly shorter glance time compared to displays with larger
visual angles.
A few researchers have conducted studies to investigate the positioning of mobile data
terminals (MDT) used by the police force for assistance during patrolling duties (Hampton
& Langham, 2005; McKinnon et al., 2012) as an influencing factor for distraction. Hampton
and Langham (2005), have investigated the requirements of MDT installed inside the police
vehicle in terms of safety and the requirements of systems design. McKinnon et al. (2012)
conducted studies on five MDT locations and two types of seats (standard and modified) to find
the best possible MDT locations in terms of reduced physical discomfort. Results reveal that
self-selected MDT locations, along with modified driver seats, reduced the physical discomfort
compared to the traditional arrangement. Some researchers have also studied the effect of
display positions on driving performance, when Camera Monitor System (CMS) replaced
side-view mirrors (Beck et al., 2017; Doi et al., 2019; Large et al., 2016). Studies conducted
by Large et al. (2016) also evaluated five types of layouts for three in-vehicle displays (two
side-view and one rear-view), in comparison to the existing mirror system. Results revealed
that layouts that were similar to the existing mirror locations were subjectively more preferred.
Further, the empirical study conducted by Beck et al. (2017) compared three CMS layouts
to the traditional side-view mirror system. It was concluded that the CMS display position
that was closer on either side of the steering wheel was relatively better in terms of reduced
mean eye-off-road time, higher preference, and perceived safety. The results of the study
conducted by Doi et al. (2019) were in agreement with the previous results, with accurate
and faster reactions to rearward situations when CMS displays were located at a smaller view
angle. Even though previously mentioned studies have evaluated and provided insight to the
in-vehicle display positions, they have some limitations. These studies have mainly considered
the position of the rear-view or side-view mirrors, which were replaced by CMS. The drivers
did not perform any visual-manual task (dual-task scenario) on these displays. Although a few
researchers have studied the interaction of IVIS at different locations, these results can not
be generalized for smaller (in-vehicle mobile phone display). Even the studies conducted on
MDTs did not consider eye-movement while performing tasks on MDTs at different locations.
Since more than 90% of the information to the drivers is gathered from the visual senses,
evaluation of eye-movement becomes an important agenda in driver behavior studies. Also,
the tasks performed on MDTs are different from those on mobile phones. Moreover, these
studies did not consider the drivers’ visual behavior in a dual-task driving scenario. Hence, we
conducted the present study to evaluate the driving performance and the drivers’ visual behavior
when in-vehicle mobile phone are placed at different positions in a dual-task simulated driving
condition.
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102 6.2. Methods and materials
6.1.2 Lane change test for assessing driver distraction in dual-task
paradigm
Lane change test (LCT) is a simple inexpensive, reliable, and standardized test tool for
measuring demand of in-vehicle information system (IVIS) (Mattes, 2003). In the past,
several studies have employed the lane change test (LCT) to successfully examine the effect
of performing secondary tasks on driving performance. Specific focus was given to reaction
time (Fofanova & Vollrath, 2011), driver and task characteristics (complexity) (Rodrick et al.,
2013), and gender (Petzoldt et al., 2009). The LCT driving simulation consists of a 3 km test
track having three lanes with 18 lane change signs along the track. The participants have to
perform lane change manoeuvres while maintaining the vehicle at a constant speed of 60 km/hr.
The mean distance between the signs was approximately 150 m, having a mean duration of 9 s
in between subsequent lane changes. It took approximately 180 s to complete each test track.
During the LCT, the primary driving performance measure is called the mean lateral deviation
(M.Dev). There was no surrounding traffic in the driving scenario. The participants have to
perform the lane change manoeuvres in a deliberate, quick, and effective manner when they
were able to identify the signs.
6.1.3 Research objective
The objective of the current study was to evaluate the effect of mobile phone position on
the driving performance (measured by lane change test), the visual behavior (measured by
eye-tracking), and the perceived driving workload. We expected that as the eccentricity of
mobile phone position increases from the normal line-of-sight, there would be difficulty in
maintaining the lane (higher mean deviation) and thus would also influence the visual behavior.
It was hypothesized that better lane-keeping would result in lower driving workload scores by
the participants.
6.2 Methods and materials
6.2.1 Participants
Thirty participants took part in the study. The participants’ age was 21 to 45 years (M =
27.67 years, SD = 5.03), having a mean driving experience of 6.93 years (SD = 3.94). All of
them declared they had a valid Indian driving license and had prior experience of interacting
with the mobile phone while driving. They were healthy and were not suffering from any
musculoskeletal disorders. The participants were informed that they could choose to leave
(without any consequences) at any stage if they felt uncomfortable during the experiment.
The study objective and the experimental procedure was clearly explained to the participants.
Written informed consent was obtained from each participant before starting the study. The
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6.2. Methods and materials 103
entire data collection was performed following the declaration of Helsinki (Association, 2001).
Since most of the subjects were not well-versed with English, they were explained the questions
in their vernacular language and data were filled in by the interviewer. The inclusion criterion
for participating in the study was: good general health, regularly driving with valid driver’s
license, and having experience of using a mobile phone while driving. Each of them had normal
or corrected to normal vision, and those having glasses were not included in the study.
6.2.2 Apparatus
We used a low-fidelity driving simulator for the experiment. It comprised a separate 42 – inch
display screen, resolution: 1024×768 pixels (SAMSUNG, Model No. PS42A410C1) and a
Logitech G29, racing wheelset (a force-feedback steering wheel, brake pedal, and accelerator),
shown in figure 6.1. The viewing distance between the LCD monitor and the participant was
kept at 70–75 cm depending upon the participant’s stature. The participants could adjust the
position and degree of the seat backrest as per their comfort. It is essential to note that the
simulator set up was for the right-handed driving vehicle. Simulated driving was performed
using the lane-change test (LCT) software (ISO, 2010) installed on the computer system.
(a) (b)
Figure 6.1: Experimental Setting; (a) Driving simulator (front-view), (b) Experimenter monitoring the
participant
A binocular eye-tracker glass, SMI iView X software, and SMI BeGaze (v 3.7) software
by SensoMotric Instrument (SMI) were used to acquire and analyze eye-movement data on a
separate computer system. The eye-tracking device was calibrated using a one-point calibration
technique and was later checked with a laser-pointing device per driving session, per participant.
A 6.3 — inch (diagonally measured) touch screen mobile-phone was used to perform the
secondary task in a dual-task scenario. This mobile-phone was mounted at different positions
(see Table 6.2) using a mobile-holder. Comfortable room temperature and ideal ambient
illumination of about 24 ◦C (75 ◦F) and 500 lux, respectively, were maintained during the
experiment (Bridger, 2017).
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104 6.2. Methods and materials
6.2.3 Experiment design
The study used a within-subject design to measure the driving performance: one baseline
driving (only lane change test), and four dual-task driving (lane change + secondary task, when
mobile-phone is at left, right, front, and middle of the steering wheel). Every participant was
subjected to all the five driving conditions. During each of the five simulated driving sessions,
the participants were instructed to perform the lane change deliberately as-soon-as they saw the
lane change sign-board. The participants had to maintain the vehicle’s speed to 60 km/hr. The
participant had to perform the secondary task on the mobile phone without removing it from
the mobile holder. A visual representation of the experimental design is shown in figure 6.2.
The rest period between the driving session is represented by ‘R’; it was approximately 5 min
and used to collect DALI subjective rating data. Baseline and dual-task driving sessions took 3
min each.
Baseline
Dual-task 
#1
Dual-task 
#2
Dual-task 
#3
Dual-task
#4
3 min
RR R R R
Figure 6.2: Visual representation of experimental design
6.2.4 Driving task
The driving performance was measured using the lane change test (LCT). The LCT is a simple
and low-cost tool used to measure the distracting capabilities of the secondary task performed
during driving. It consists of a 3000 m straight roadway. The driving speed was limited to
a maximum of 60 km/hr, and participants were asked to maintain it, thereby completing the
simulated run in approximately 3 min. There was no traffic or pedestrians. The drivers had to
change the lane purposely as soon as they saw the lane change sign that appeared on both sides
of the road. An image of the simulated road environment is given in figure 6.3.
6.2.5 Secondary task
During each of the four dual-task driving sessions, the participants performed four (4) secondary
tasks (description in Table 6.1). Participants performed these tasks after the experimenter gave
a clap signal to start the secondary task. The sequence of these tasks was counterbalanced for
each dual-task driving sessions to reduce the learning effect. The task chosen to perform during
the experiment resemble the typical tasks that are being performed by the drivers during their
day to day activities.
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6.2. Methods and materials 105
Figure 6.3: A screenshot of the simulated roadway
Table 6.1: Descriptions of the secondary task
Task Category Description
1 Dialing Call a pre-saved number by the name Demo ‘1’
2 Dialing Call a pre-saved number by the name Demo ‘2’
3 POI Address Open google map and finding a POI (point of interest) address (for
ATM, petrol pump, restaurant) and start navigation
4 Dialing Open the telephone dialer and dial your own phone number (ten digit
number)
6.2.6 Position of the mobile phone
During the initial field survey many positions of in-vehicle mobile phone were identified.
However, four positions (left, right, center and front of steering wheel) were shortlisted for this
empirical study which utilized eye-tracking/ driving simulator. Out of the four, two positions
(middle and front) were chosen based on the results of the DHM study, and the remaining two
(left and right) were chosen because they were the most preferred among the drivers (in the
current study), as found from the field study.
Since the simulator setup was for a right-handed driving vehicle, all the mobile phone
positions were accordingly demarcated. The mobile phone was placed at each of the four
positions: left, right, front, middle of the steering wheel. The position of mobile phone w.r.t.
steering wheel is shown in figure 6.4. The dashboard shown represents half of the car’s actual
dashboard, and the left position of the mobile phone is at the center of the actual dashboard.
Dots represent the center of the mobile phones in the figure. The relative positions (shown in
Table 6.2) of the mobile phones are calculated w.r.t. the center of the middle position.
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106 6.2. Methods and materials
42 inch screen 
Front position (visual angle: 0 deg )
Dashboard
Steering wheel
Right position
Left position
Desktop 
computer 
Driver
7
0
 –
 7
5
 c
m
Middle position
Figure 6.4: Diagram showing different positions of the mobile phone w.r.t. the driver
Table 6.2: Descriptions of mobile phones positions
Position Description
Distance w.r.t. middle (mm) Horizontal visual angle (°)
Left 410 58
Right 310 50
Front 260 0
Middle 0 0
6.2.7 Experimental procedure
The experiment was divided into three sessions: screening and briefing, practice, and
experimental session. Upon arrival of the participants in the experiment area, they were
allowed to rest for 5 min. Then they were screened and tested for fitness (for physical pain
or discomfort), visual acuity (using Snellen chart) (Snellen, 1868), and color blindness (using
Ishihara color-blindness type test) (Ishihara, 1917). Subsequently, they were given a brief
introduction about the study and informed about the experimental protocol. Before starting the
session, all participants answered demographic questions regarding their age, gender, driving
experience, license, and visual status. Each of them signed a consent form to participate in the
experiment. After the screening and briefing session, the participants practiced on the driving
simulator with single and dual-task driving. The practice session ended once the participants
were comfortable with the simulated driving environment and completely understood the
task to be performed. In the experimental session, the participant’s driving performance
and eye-movement data were recorded. The participants drove as per the experiment design
(mentioned in 6.2.3). After each driving session, the participants rested for 5 minutes and filled
a subjective rating questionnaire using the driving activity load index (DALI). The entire session
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6.2. Methods and materials 107
took approximately 60 minutes. A flowchart showing the procedure adopted for the study is
given in figure 6.5. Upon completion of the experiment, participants were given refreshments
and a remuneration amount of | 200 to compensate for their time and effort required for taking
part in the experiment. The entire experimental protocol was approved by the Institute Human
Ethics Committee (IHEC) (see Appendix A.8).
Briefing and Scrutiny
 Testing of visual acuity and 
color blindness
 Briefing about the 
experimental protocol
 Filling-up of consent form
E
x
p
er
im
e
n
ta
l 
S
es
si
o
n
Baseline (Driving only)
Primary + Secondary Task 
(mobile-phone at position 1)
Primary + Secondary Task 
(mobile-phone at position 2)
Primary + Secondary Task 
(mobile-phone at position 3)
Primary + Secondary Task 
(mobile-phone at position 4)
Subjective rating (DALI)
Subjective rating (DALI)
Subjective rating (DALI)
Subjective rating (DALI)
Subjective rating (DALI)
C
o
u
n
te
r 
b
al
a
n
c
ed
 o
rd
er
Primary Task (Driving only) Secondary Task (Task on mobile-phone)
Driving task + Secondary task on mobile-phone
P
r
a
c
ti
ce
 
S
es
si
o
n
Figure 6.5: Flowchart of the experimental procedure
6.2.8 Experiment variables
In this study, the independent variable was the position (spatial arrangement of the mobile phone
around the steering wheel), which had five levels: baseline (no mobile phone), and mobile
phone at left, right, front, and middle of the steering wheel. The dependent variables were:
Mean deviation (M.Dev), lane-change error, fixation (duration and count), glance (duration
and count), Total eye-off road time (TEORT), and DALI subjective workload ratings. The
Mean deviation (M.Dev) is defined as the mean deviation between the actual driving course
and the position of normative model. It has been used by many researchers to evaluate driving
performance (Burns et al., 2005; J. Harbluk et al., 2007; Petzoldt et al., 2009; Rodrick et
al., 2013). Lane excursion is the errors performed during the lane change. It was measured
using the LCT simulation software. Glance duration refers to the time duration for which the
drivers looked at a particular area of interest (AOI), and the number of glances to a particular
AOI is defined as glance count (Crundall, Large, & Burnett, 2016; Large et al., 2016; Yang
et al., 2020). Fixation duration is the time duration for which fixation occurred at a particular
area of interest (AOI); the number of fixations occurring at a particular AOI is defined as
fixation count (Cˇegovnik, Stojmenova, Jakus, & Sodnik, 2018; Scialfa, McPhee, & Ho, 2000).
TH-2774_146105005
108 6.3. Results
Total eye-off-road time is defined as the total time when the driver is not looking towards the
road or time spent looking away from the road (Beck et al., 2017; Feng, Liu, & Chen, 2018).
DALI subjective workload scale is a modified version of the NASA-TLX scale measuring the
workload during the driving task. It has six sub-scales; attention, visual, temporal demand,
stress, and interference (Pauzié, 2008).
6.2.9 Statistical analysis
A Shapiro—Wilk’s test (p > 0.05) (Razali, Wah, et al., 2011; Shapiro & Wilk, 1965) and visual
inspection of the histogram, normal Q-Q plot and box plots showed that the eye-movement
variables (fixation and glance duration, fixation, and glance count), TEORT, and mean weighted
DALI subjective rating scores were normally distributed for each of the individual groups. On
the contrary, it was observed that Mean deviation (M.Dev) variable was not normally distributed.
However, an inverse (reciprocal) transform was employed to make all the mean deviation groups
normal for statistical analysis. A one-way repeated measures ANOVA was used to test statistical
significance (if any) by comparing the means of each group in a within-subjects design (Hughes,
Rudin-Brown, & Young, 2013). For controlling the inflation of type-I error, Bonferroni
correction was used (Crundall et al., 2016). Whenever Mauchly’s Test of Sphericity was
violated, Greenhouse-Geisser correction was applied. The statistical analysis was performed
using IBM SPSS 25.0 (SPSS Inc., Chicago, USA) software at a significance level of p = 0.05.
The calculated effect size were reported as being large (0.14≥ η2), medium (0.06≤ η2 < 0.14),
and small (η2 < 0.06) (Cohen, 2013).
6.3 Results
The Mean and SD of the dependent variables are given in Table 6.3.
6.3.1 Driving performance
Mean deviation (M.Dev) of lane change from the normative path (in meters) and the number
of lane change errors were used as a measure of driving performance. The value of M.Dev
was lowest at 0.51 for the baseline and highest at 0.83 for middle position of mobile phone.
A repeated measures ANOVA showed that there was a significant effect of driving condition
(F(4,116) = 36.80, p < 0.05,η2 = 0.559, large effect size) on M.Dev values. A post hoc test
using the Bonferroni correction revealed that there was a significant difference between the
M.Dev values of baseline and all the dual-task driving scenario at p < 0.05. Also, significant
difference in M.Dev values were observed between front and middle mobile phone position
(p < 0.05). However, no significant difference (p > 0.05) were observed in M.Dev values for;
left vs right, left vs front, left vs middle, right vs front, and right vs middle position of steering
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6.3. Results 109
Table 6.3: Descriptive of the dependent variables for different test conditions
Measure Test conditions
Baseline Left Right Front Middle
M.Dev (m) 0.51 (0.26) 0.81 (0.38) 0.76 (0.30) 0.68 (0.30) 0.83 (0.44)
LC error (n) 2.53 (2.37) 4.10 (3.02) 3.83 (2.57) 3.50 (3.10) 4.10 (3.18)
Fixation duration (s) N.A. 19.20 (8.42) 18.00 (6.13) 24.64 (5.40) 17.32 (6.82)
Fixation count (n) N.A. 73.23 (29.55) 71.93 (23.15) 90.26 (22.20) 72.97 (26.23)
Glance duration (s) N.A. 24.67 (10.55) 23.57 (7.89) 31.06 (6.60) 23.47 (9.20)
Glance count (n) N.A. 23.10 (7.88) 24.50 (7.10) 32.70 (8.90) 22.13 (6.53)
TEORT (s) N.A. 27.93 (11.62) 26.86 (8.42) 33.93 (7.09) 25.78 (9.53)
DALI (0 – 100) 23.33 (5.04) 39.24 (7.42) 36.73 (5.69) 30.35 (5.47) 40.97 (4.97)
*Mean (SD); M.Dev – mean deviation, LC – lane change, TEORT – total eye-off road time, DALI – driver activity
load index, N.A.– not applicable.
wheel.
The errors performed during lane change were minimum for baseline (M=2.53), and
maximum for left and middle (M=4.10) positions of the mobile phone. A Friedman test
revealed that there was a significant effect of driving condition (χ2(4) = 14.09, p < 0.05) on
lane change errors. A post hoc analysis with Wilcoxon signed-rank test was conducted with
Bonferroni correction applied, resulting in a significance level set at p < 0.005. The result
revealed that a significant difference exist in lane-change error for mobile phone at middle vs
baseline driving (Z =−3.212, p = 0.001). Median (IQR) error in lane change for baseline, left,
right, front, and middle of steering wheel are shown in Table 6.4. The M.Dev and error in lane
change values for different driving condition is shown in figure 6.6.
Table 6.4: Descriptive of error in lane change at different condition
Condition Mean (SD) Percentile
25th 50th
(median)
75th
Baseline 2.53 (2.41) 1 2 4
Left 4.1 (3.07) 2 3 6
Right 3.83 (2.61) 1.75 4 5.25
Front 3.5 (3.16) 1 3.5 5.25
Middle 4.1 (3.23) 1.75 3 5.25
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110 6.3. Results
Baseline Left Right Front Middle0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
2.2
Positions of mobile phone
M.D
ev (
m)
 Mean deviation   Mean lane change error
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
5.5
Erro
r in 
lane
 cha
nge
Figure 6.6: Mean deviation of lane change at different positions
6.3.2 Visual behaviors
Glance (duration and count), fixation (duration and count), Total eye-off road time (TEORT),
and Mean eye-off road time were used as a measure of visual behavior.
Glance duration and count
The longest glance duration value was observed for front mobile phone position (M = 31.06 s,
SD = 6.60). A repeated measures ANOVA with Greenhouse-Geisser correction revealed that
the difference in glance duration values between the different positions of the mobile phone
was statistically significant (F(2.528,73.304) = 10.339, p < 0.05,η2 = 0.263 large effect size).
Post hoc test with Bonferroni correction determined significantly higher total glance duration
for mobile phone at the front position than left (p = 0.01), right, and middle (p < 0.05).
The glance count values were minimum for middle mobile phone position (M = 22.13,
SD = 6.53). A repeated measures ANOVA revealed that total glance count was significantly
different for mobile phone position (F(3,87) = 23.078, p < 0.05,η2 = 0.443). Post hoc test
with Bonferroni correction revealed that, the total glance count was significantly higher for
the front position (p < 0.05) as compared to left, right, and middle position. The total glance
duration and count for different mobile phone positions is shown in figure 6.7.
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6.3. Results 111
Left Right Front Middle 0
5
10
15
20
25
30
35
40
Gla
nce
 cou
nt (n
)
15
25
35
45
10
20
30
40
50
Position of mobile phone
Gla
nce
 dur
atio
n (s
)
  Glance duration       Glance count
Figure 6.7: Glance duration and glance count at different mobile phone positions
Fixation duration and count
The minimum values for fixation duration were observed for middle mobile phone position (M
= 17.32, SD = 6.82). A repeated measures ANOVA revealed that total fixation duration differed
significantly between the positions of mobile phone (F(3,87) = 16.122, p < 0.05,η2 = 0.357,
large effect size). Post hoc test with Bonferroni correction determined that, the total fixation
duration was significantly higher for mobile phone placed at front as compared with left
(p = 0.005), right (p < 0.01), and middle (p < 0.01).
Least fixation count was recorded for right mobile phone position (M = 71.93, SD = 23.15).
A repeated measures ANOVA with Greenhouse-Geisser correction revealed that position of
mobile phone had a significant main effect on fixation count (F(2.503,72.594) = 7.287, p <
0.05,η2 = 0.201, large effect size), post hoc test with Bonferroni correction showed that, the
fixation count for front position of mobile phone being significantly higher than left (p = 0.019),
right (p < 0.01), and middle (p = 0.008) positions of mobile phone. Fixation duration and
count for different mobile phone positions is shown in figure 6.8.
Total eye-off-road time (TEORT)
The middle mobile phone position recorded the minimum value of TEORT (M = 25.78
s). A repeated measures ANOVA with Greenhouse-Geisser correction revealed that mobile
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112 6.3. Results
Left Right Front Middle
15
25
35
45
10
20
30
40
50
Position of mobile phone
Fixa
tion
 dur
atio
n (s
)
  Fixation duration     Fixation count
30
40
50
60
70
80
90
100
110
Fixa
tion
 cou
nt (n
)
Figure 6.8: Fixation duration and count at different mobile phone positions
phone position had a statistically significant effect on TEORT (F(2.508,72.73) = 8.935, p <
0.05,η2 = 0.236, large effect size). A post hoc test with Bonferroni correction revealed that
TEORT was significantly higher for front than left, right, and middle (p < 0.05) positions
of mobile phone. The variation of Total eye-off-road time (TEORT) under different mobile
phone position is shown in figure 6.9. For mean eye-off-road time, a log transformation was
performed on the data set to make them normal. A repeated measured ANOVA revealed that
mobile phone position did not have a statistically significant effect on the mean eye-off road
time (F(3,87) = 1.974, p = 0.124,η2 = 0.064, low effect size).
6.3.3 Subjective workload assessment
The subjective workload measured using DALI was minimum for baseline task (M = 23.33),
and maximum for middle mobile phone position (M = 40.97). A repeated measures ANOVA,
revealed that position of mobile phone had a statistically significant effect on the subjective
workload ratings (F(4,116) = 61.14, p < 0.05,η2 = 0.678, large effect size). A post hoc test
revealed that the baseline driving condition was significantly different from left, right, front,
and middle (p < 0.05). In addition, front position was found to be significantly different from
baseline, left, right, and middle (p < 0.05).
The graph showing the DALI subjective assessment is shown in figure 6.10. The individual
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6.4. Discussion 113
Left Right Front Middle
10
20
30
40
50
60
Position of mobile phone
Tot
al e
ye-o
ff-ro
ad t
ime
 (s)
 TEORT    Mean eye-off road time
0.4
0.6
0.8
1.0
1.2
1.4
Mea
n ey
e-of
f ro
ad t
ime
 (s)
Figure 6.9: Total and mean eye-off-road time at different mobile phone positions
Table 6.5: Mean DALI scores for each task condition
Dimensions Test conditions
Baseline Left Right Front Middle
Attentional 54.93 70.80 64.53 61.20 67.73
Visual 58.40 55.60 50.40 49.33 57.33
Auditory 04.00 06.93 09.20 01.33 08.67
Stress 11.87 34.40 32.40 21.73 36.53
Temporal 10.00 24.93 19.20 14.93 24.00
Interference 00.80 42.80 44.67 33.60 51.60
sub-scales of DALI for different test conditions is shown in figure 6.11. The mean values of
DALI sub-scale for different driving condition is given in Table 6.5.
6.4 Discussion
In the present study, we empirically examined the influence of in-vehicle mobile phone positions
on the driving performance and the drivers’ visual behavior. The participants performed a
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114 6.4. Discussion
Baseline Left Right Front Middle10
15
20
25
30
35
40
45
50
Driving condition
Glo
bal 
mea
n w
eigh
ted 
scor
e
 Mean   Mean ± 95% CI
Figure 6.10: DALI subjective assessment scores
visual-manual task on the mobile phone and driving task in a simulated environment. The
driving performance results were interpreted in terms of the mean deviation in lane change
(M.Dev) and lane change errors. A smaller value of M.Dev indicates a good lane keeping (better
driving) performance as compared to a larger value, which indicates a poor lane keeping (poor
driving) (J. Harbluk et al., 2007; Mattes, 2003). The best values (M.Dev = 0.51) resulted during
the baseline (only driving) session when compared to all the other driving scenarios, whereas
the worst (M.Dev = 0.83) values were recorded when the mobile phone was placed at the middle
(dual-task) of the steering wheel. When inspecting the dual-task sessions, the values of M.Dev
were better for mobile phone placed at the front when compared to other dual-task scenarios.
Previous studies conducted by Burns et al. (2005); J. Harbluk et al. (2007); K. L. Young, Lenné,
and Williamson (2011) have shown that mean deviation values were smaller for cognitively
and visually easier tasks compared to difficult tasks. The lane excursions (lane-change error)
for dual-task driving were higher for middle and left positions whereas minimum for front
position, indicating that better driving performance was achieved for front and worst for the
middle mobile phone positions. It is important to note that the mobile phone placed on the left
is the farthest from the normal line-of-sight and for looking at the middle position, drivers have
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6.4. Discussion 115
Baseline Left Right Front Middle
0
10
20
30
40
50
60
70
80
90
100
Task conditions
Mea
n w
eigh
ted 
scor
e
 Attentional demand   Visual demand   Auditory demand
 Stress   Temporal demand   Interference
Figure 6.11: Sub-scales of DALI for driving conditions
to shift their attention from the driving scene to the mobile phone. Thus, in terms of driving
performance we can say that the mobile phone positions at the front gave better results than
others.
Further, observing the visual behavior interpreted in terms of the eye-movement measures
(fixation, glance, and TEORT), we note that eye-movement measures were significantly affected
by the in-vehicle mobile phone position.
The glance duration was most prolonged (M = 31.06 s) for the front and smallest (M = 23.47
s) for the middle position. Apart from the front and middle positions, the left position was the
farthest, and right was the nearest from the normal line-of-sight horizontally. The hypothesis
that farther the position of mobile phone away from the normal line-of-sight the longer is the
eye-off-road time holds for left and right positions. Thus, the glance duration values were
higher for left than right, but no significant difference was observed. On the contrary, with the
mobile phone at the front position, the subjects may still use their peripheral vision to observe
the on-road scene. Studies by Summala, Lamble, and Laakso (1998) show that drivers use
peripheral vision for lane and distance keeping. Thus, using the peripheral vision for on-road
monitoring, the drivers tend to spend more time off-road and still maintain better lanes. This
argument holds for the front position where we observe a better mean deviation value and
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116 6.4. Discussion
a longer glance and eye-off road time. Similar conclusions were also drawn in the studies
of Dukic, Hanson, Holmqvist, and Wartenberg (2005), where the button location closer to the
normal line-of-sight resulted in longer eye-off-road time.
In the case of mobile phone at the middle position, the hypothesis mentioned above does
not hold since it is farthest from the normal line-of-sight, located at the center of the steering
wheel, and still has the shortest total eye-off-road time. A potential explanation for this result
could be the driver’s perception of risk. If the drivers have to look at the middle position at
the steering wheel’s center, they have to flex their neck, and they cannot use their peripheral
vision to monitor the on-road scenario. Thus, implying that the drivers consider the middle
position as dangerous, since they cannot look at the on-road situation and are impaired of their
motion-detecting capabilities. Hence, they try to keep the visual off-road time to a minimum.
Similar arguments were also given in the studies conducted by Dukic et al. (2005), for a button
located near the gearbox, showing a shorter eye-off-road time.
The fixation duration for the middle mobile phone position was found to be minimum at
17.32 s, whereas the fixation count was 72.97. The longest fixation duration (24.64 s) was
recorded for front mobile phone position. This can be explained because, while looking at the
front position, drivers were able to monitor the on-road scenario with their peripheral vision
and thus fixated for longer duration at the front mobile phone position, which was opposite in
case of middle position. Similar results were also observed in the studies of Cˇegovnik et al.
(2018), where the fixation duration decreased with the presence of increased cognitive load.
Similarly, a study conducted by Scialfa et al. (2000), which examined the effect of a cellular
phone conversation on the search of a traffic sign, also reported a reduction in fixation duration
as the complexity/ clutter increased.
The DALI subjective workload rating score shows that the baseline task had the lowest
workload score compared to the dual-task driving conditions. Among the dual-task driving
conditions, the front position had the lowest workload compared to the middle position, which
exhibited the highest workload. The above results could be justified because, for performing
tasks on the middle mobile phone position, drivers have to continuously shift their attention
from forward on-road view to the mobile phone located at the center of the steering wheel.
Whereas, for the front position, the drivers did not have to move their heads and performed their
tasks without the fear of committing any driving error, hence resulting in a lesser workload
score.
Studies conducted by Pauzié (2008), have also shown a higher DALI global workload scores
for complex guidance systems than the human co-pilot. Similarly, studies by K. H. Kim and
Wohn (2011) also showed higher DALI workload values for an augmented reality navigation
system than map navigation. Thus, concluding that a high demanding session/ situation
corresponds to a higher value of DALI score.
Observing the details of individual DALI factors, it was noticed that a higher value of
‘interference’ was registered for the middle position compared to other dual-task conditions
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6.4. Discussion 117
since the mobile phone interfered in the unobstructed functioning of the steering wheel. ‘Stress’
was also rated high for middle positions as compared to other dual-task driving conditions. If
we arrange the sub-scales according to their impact on dual-task driving, it was observed that
attention and visual demands were highly rated. In contrast, temporal and auditory demands
were rated low for each of the dual-task conditions. Thus, according to the results of the present
study, in-vehicle mobile phone position at the front seems to be the most suitable in terms
of better driving performance and a lesser amount of driving workload as compared to other
dual-task conditions in the study.
6.4.1 Limitations
The present study is limited in its approach since it was conducted on a fixed-base driving
simulator in a simulated environment where the drivers know that an error or fault in driving
will not lead to an accident. Further, there was a lack of vibration and physical motion in the
simulator vehicle, that may affect the visual and driving performance. Additionally, various
other factors were unaccounted, which may have affected the drivers’ driving and visual
behavior. These factors include the drivers’ characteristics (age, gender, comfort and skill
of driving the simulator, driving experience), environmental characteristics (road condition
(rural/ urban), traffic (high/ low)), and vehicle characteristics (right/ left-hand drive, type of
vehicle). Although utmost care has been taken to match the experimental conditions (position
of the mobile phone) with the real-world scenario, an accurate resemblance may not have been
achieved. An experimental study conducted on an instrumented vehicle may have produced
different outcomes.
This study was primarily aimed at interventions for MABTS drivers as mentioned earlier.
Although DALI was used to measure the driving workload of the drivers, in the real environment,
driver’s behavior may also be affected by psycho-social and organizational factors/ policies.
For example, driver behavior may be influenced by the urgent need for receiving/ booking calls
from a customer while driving and meeting performance targets which is directly linked to
financial factors/ incentives (of reaching the destination on time) which non MABTS drivers
may not be influenced by. These constraints and expectations might put additional load on the
MABTS drivers. Since such factors were not measured, this may be taken up in future research
studies. Apart from the lacunas, as mentioned earlier, future studies should take up research on
an instrumented vehicle and different classes of vehicles (trucks, buses, and auto-rickshaws) for
producing more generalized outcomes.
Future research could also take a comparative study between MABTS drivers who use only
mobile phone and those who use mobile phone with Bluetooth devices (or audio navigation),
since audio input may also influence visual behavior while driving. Future scope also lies in
understanding the optimum position for the mobile phone for drivers suffering from disorders
such as low back pain etc. which is very common among professional drivers and its comparison
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118 6.5. Conclusion
with healthy drivers (present study) and its implications for design.
6.5 Conclusion
In this study, we conducted a driving simulator-based experiment to examine the effect of
in-vehicle mobile phone position on the driving performance and the visual behavior of the
drivers. Results showed that the in-vehicle mobile phone position had a statistically significant
effect on drivers’ driving performance and visual behavior. Placing mobile phones at a smaller
visual angle from the normal line-of-sight resulted in better driving performance and lesser
driving workload scores. However, the drivers’ glance and fixation duration increased, and
they spent more time performing tasks on mobile phones because they felt safer compared
to other in-vehicle mobile phone positions. This study’s observations can be utilized by the
policy-makers and mobile-application-based taxi rental companies to formulate guidelines
for better and safer use of in-vehicle mobile phones. The knowledge gained from the study
about visual and driving behavior could be used by the designers and the ergonomics team for
developing safer and user-friendly in-vehicle displays. Additionally, the industrial designers
can also use the knowledge to design mobile holders/ space integrated with the dashboard,
keeping in mind smaller visual angle for safety and usability (to guide the driver to place the
mobile device in the correct position).
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— The art and science of asking questions is the source of all knowledge.
Thomas Berger
7
General discussion and conclusion
Abstract
This chapter summarizes and presents an overall discussion of the research work, which is being taken
up. Salient findings of the present research, fulfillment of the objective, hypothesis testing, and the
present research’s key contributions are presented in this chapter. Future research directions based on
the limitations of the study have been furnished along with the conclusion at the end.
7.1 Overall discussion of the research work
The present research tried to find the most suitable in-vehicle mobile phone (as a navigational
device) position for navigation purposes in terms of head rotation, flexion/ extension,
reachability, driving performance, visual distraction, and driving workload. The overall
framework of the current research was divided into five phases: problem identification;
questionnaire survey of MABTS drivers; DHM based study of mobile phone positions;
development of a novel mobile phone holder to be mounted at the center of the steering
wheel; and empirical evaluation of the in-vehicle mobile phone positions in a driving simulator.
Phase – I was the problem identification stage, where a review of literature related to the study
of this thesis was carried out, followed by identification of the research gap. During this phase,
research questions were raised, aim & objectives were set, and hypothesis were formulated for
conducting the research.
In the phase – II, a questionnaire based survey was conducted to understand the drivers’
involvement/ engagement in distracting activities/ tasks and their preference location for placing
in-vehicle mobile phones for navigation purposes. The study involved MABTS drivers (n =
188). The questionnaire was found to be reliable with a Cronbach’s alpha (α) = 0.72. Inferences
drawn from the outcome of the survey concluded to some interesting findings. The majority
of drivers (48.8%) preferred to keep their mobile phones on the steering wheel’s left side for
navigation purposes. It was also observed that 40.4% of drivers reported that they kept mobile
119TH-2774_146105005
120 7.1. Overall discussion of the research work
phones on the steering wheel’s right side, near the A-pillar. A small percent (10.1%) of drivers
mentioned that they change the position of their mobile phones during night/ evening, and
keep it below the dashboard. Additionally, about 22.3% of drivers reported that they reduce
the mobile phone’s screen’s brightness during the night. These behaviors could be seen as
an act of counter measuring glare from the mobile device during night/ evening. A total of
‘nine’ in-vehicle mobile phone positions (on & around the dashboard and the steering wheel)
were used in this study (details in chapter 3, see figure 3.1, for visual representation). The
outcome of the ranking of various mobile phone positions as rated by the drivers revealed that
position ‘6’ (left of steering) had a mean rank of 1.77, and was the most preferred position,
whereas, position ‘4’ (right of steering) was the second most preferred position (mean rank =
1.90). Similar observations were reported in the previous studies conducted by Alconera et al.
(2017); however, the participants of this experiment were Filipino drivers who were driving
‘left-handed vehicles’.
Further, in phase – III digital human modeling (DHM) based virtual simulation study was
conducted using the CATIA-DELMIA software to identify the head movement (rotation, flexion/
extension), torso movement, reach-ability required to access information from the different
mobile phone positions. Head movement (rotation and flexion/ extension), and reach-ability
for all the different mobile phone positions identified during the questionnaire survey were
measured, using manikins (5th, 50th, and 95th percentile) with male Indian anthropometric
body dimensions. This experiment showed the influence of mobile phone position on the head
movement. Kee and Karwowski (2001), defined a comfortable angle for neck, with 4° flexion,
7° extension, 17° rotation, and 13° lateral bending in a sitting posture. An overview of all the
in-vehicle mobile phone positions in the car interior is given in figure 3.1. The minimum head
rotation was recorded for the positions ‘8’, ‘5’, and ‘2’, which were on the same vertical line
and close to the line-of-sight. Negligible head rotation (1°, 1°, 1°), and head flexion (5°, 7°, 8°)
was also recorded for position ‘5’, for the three different percentile manikins. These values are
within the comfortable range as given by Kee and Karwowski (2001) for visualizing display.
Earlier studies, by Wittmann et al. (2006), showed that display position closer to line-of-sight
of drivers had a better driving performance. Although, the least head rotation was recorded for
position 8, head flexion (17° – 19°) were outside the comfortable range suggested by Kee and
Karwowski (2001). Position 8 had a better hand reach than others, and it did not obstruct the
forward vision of the drivers.
Following DHM study (details in chapter 4) it was noticed that placing in-vehicle mobile
phone at a straight forward location nearer to normal line-of-sight would reduce the neck/ eye
movement and subsequently reduce distraction. Previous studies by Wittmann et al. (2006);
Zheng et al. (2016) also supported the same. Hence, placing in-vehicle mobile phone at
position ‘5’, and ‘8’ would benefit MABTS drivers in-terms of improved driving performance.
However, no mobile phone holder which could be easily mounted at the steering wheel’s center,
could be found in the automobile accessories market. Hence, the process of developing a
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7.1. Overall discussion of the research work 121
steering-wheel-mounted self-adjusting mobile phone holder was carried out in phase – IV. This
novel product’s primary requirement was, (a) it could be mounted in the center of the steering
wheel, (b) it should self-adjust and remains vertically upright even when the steering wheel
rotates. A systematic product development process was followed, which included – customer
needs identification, concept generation, concept screening, prototyping, customer feedback.
The entire process is discussed in detail in chapter 5.
To empirically examine the effect of in-vehicle mobile phone position on the drivers’ driving
performance and visual behavior, a simulated driving study in a laboratory setup was conducted
in phase – V. In this study, four highly preferred in-vehicle mobile phone positions (left, right,
front, and middle of the steering wheel) were used (details in chapter 6). The experiment was
conducted in a within subjects design, and the study subjects had to drive in a simulated road
environment, under five driving conditions (one baseline – only driving, and four dual-task
driving – driving + secondary task on mobile phone located at one of the positions mentioned
earlier). The subjects performed four secondary tasks under each of the four dual-task driving
condition (details in chapter 6).
The visual behavior was measured using an eye-tracker, and the lane-change test (LCT) in a
simulated environment measured the driving performance. The driving performance results
were interpreted in terms of the mean deviation in lane change (M.Dev) and lane change
errors. A smaller value of M.Dev indicates a good lane keeping (better driving) performance as
compared to a larger value, which indicates a poor lane keeping (poor driving) (J. Harbluk et al.,
2007; Mattes, 2003). To find out the difference (if any) in M.Dev values among the different
driving conditions statistical analysis was performed. A repeated-measures ANOVA showed
that there exists a significant difference in M.Dev values among the different driving conditions
(F(4,116) = 36.80, p < 0.05,η2 = 0.559, large effect size). In the post hoc test, significant
difference in M.Dev value was observed for the driving condition when the mobile phone was
placed at the front and middle of the steering wheel (p < 0.05).
The errors performed during lane change were maximum for left and middle (M=4.10)
mobile phone positions. A significant difference in lane change error among the different driving
conditions (χ2(4) = 14.09, p < 0.05) was observed. Visual behavior was interpreted in terms of
glance (duration and count), fixation (duration and count), total eye-off road time (TEORT), and
mean eye-off road time. The total glance duration (for all the four tasks) for mobile phone placed
at left, right, front, and middle of the steering wheel was 24.67 s, 23.57 s, 31.06 s, and 23.47
s. A repeated-measures ANOVA revealed that the total glance duration differed significantly
among the positions of the mobile phone (F(2.528,73.304) = 10.339, p < 0.05,η2 = 0.263,
large effect size). Similar results were also achieved for fixation duration, glance count TEORT.
The drivers’ subjective workload was measured after each of the simulated driving sessions
using the questions of driver activity load index (DALI). A repeated-measures ANOVA revealed
that position of the mobile phone had a statistically significant effect on the subjective workload
ratings (F(4,116) = 61.14, p < 0.05,η2 = 0.678, large effect size). The front position was
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122 7.1. Overall discussion of the research work
found to be significantly different than baseline, left, right, and middle (p < 0.05).
For the mobile phone display positioned in front of the driver on the dashboard, the drivers
may still use their peripheral vision to observe the on-road scene. Studies by Summala et al.
(1998) showed that drivers use peripheral vision for lane and distance keeping. Thus, using the
peripheral vision for on-road monitoring, the drivers tend to spend more time off-road and still
maintain better lanes. This argument holds for the front position where a better mean deviation
value was observed along with a longer glance and eye-off road time. Similar conclusions were
also drawn in the studies by Dukic et al. (2005), where the button location closer to the normal
line-of-sight resulted in longer eye-off-road time. The mobile phone at the middle position
(located at the steering wheel’s center) is farthest from the normal line-of-sight, and still has
the shortest total eye-off-road time. A potential explanation for this result could be the driver’s
perception of risk. If the drivers have to look at the middle position at the steering wheel’s
center, they have to flex their neck/ glance downwards, and they cannot use their peripheral
vision to monitor the on-road scenario. This, implies that the drivers might consider the middle
position as dangerous because they cannot look at the on-road situation and are impaired of their
peripheral-detection capabilities for moving objects. Hence, they try to keep the visual off-road
time to a minimum. Similar arguments were also given in the studies conducted by Dukic et al.
(2005), for the button located near the gearbox, showing a shorter eye-off-road time.
Observing the individual DALI factors, it was noticed that higher values of ‘interference’
were registered for the middle position compared to other positions since the mobile phone
some times interfered with easy maneuverability of steering wheel. ‘Stress’ was also rated high
for middle positions as compared to other dual-task driving conditions.
Thus, according to the present research, the mobile phone display positioned at the front
seems to be the most suitable (among the driver preferred mobile phone positions) for better
driving performance and a lesser amount of driving workload than other dual-task conditions at
different mobile phone locations under study.
In relation to usability of the methodology being adopted in the present study, the literature
survey identified the advantages/ merits of the various methodologies, and for solving the
research problem, the lane changing task (LCT) was utilized since it is a reliable, inexpensive,
and standardized test tool for measurement of in-vehicle infotainment system (IVIS) demands.
Eye-movement recorder was used to measure the visual demand/ attention of the drivers
while driving. The study was performed in a low fidelity driving simulator in the laboratory
environment, since, a variety of driving conditions/ environment can be easily and safely
evaluated in the driving simulator. The digital human modeling (DHM) software was used
for virtual ergonomics evaluation of various in-vehicle mobile phone position, since physical
mock-ups and consequent trails with real human beings is expensive and time-consuming. In
DHM software, digital human (manikin) model of varying body types and dimensions (mostly
5th, 50th, 95th percentile) can be created which interacts with a CAD generated product in a
virtual environment. Thus, the above mentioned methods were utilize in the present study.
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7.1. Overall discussion of the research work 123
7.1.1 Summary of findings
The following are salient findings of the study regarding mobile applications-based taxi service
(MABTS) drivers, their engagement in distracting tasks, and their placement of in-vehicle
mobile phones around the dashboard and steering wheel.
• Involvement of the MABTS drivers in a wide variety of distracting activities while driving
was explored in the field study.
• Drivers’ preference of the location for placing in-vehicle mobile phone for navigation
and justification of their behavior was established.
• The drivers showed a behavioral change between day and night–time. They either placed
the in-vehicle mobile phone below the dashboard or reduced the screen brightness during
night–time, depicting a mitigation strategy for glare from the mobile devices during
night–time.
• With the digital human modeling study, the association between head movement (flexion/
extension and rotation) and in-vehicle mobile phone location was established.
• Mobile phone located near the gearbox required the driver to turn/ rotate their head and
the trunk/ torso to operate them. The mobile phone located on the dashboard in front
of the steering wheel required minimum head movement (rotation, flexion/ extension),
however, it obstructed the forward view-field. The mobile phone placed at the center of
the steering wheel required minimum head rotation and provided un-obscured visibility
of forward view-field and instrument cluster through the steering wheel.
• The DHM based study established that placing mobile phone at the center of the steering
wheel would minimize head movement. Hence, an innovative, self-balancing mobile
phone holder was developed using a systematic product design and development approach.
The new product could be mounted at the center of the steering wheel.
• An empirical study in a laboratory setup established a statistically significant difference
in driving performance (measured using lane change task on a driving simulator) and
visual behavior (measured using eye tracker) for the in-vehicle mobile phone positions.
• Experimental observations established the superiority of in-vehicle mobile phone at the
front of the steering wheel (on the dashboard) compared to other locations (left, right,
and middle of the steering wheel).
7.1.2 Summary of objectives fulfillment
Objective 1: To identify the various methodologies currently practiced for measurement of
driver distraction.
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124 7.1. Overall discussion of the research work
Various existing methodologies for measuring driver distraction were identified
(details in Chapter 2) by surveying the current driver distraction literature. Thus,
objective – 1 of the research was fulfilled.
Objective 2: To identify the factors influencing driver to distract attention from primary task of
driving.
Objective 3: To identify various in-vehicle locations/ positions which are commonly practiced
by MABTS drivers for navigation purpose.
A questionnaire survey was administered to the MABTS drivers to identify the
various activities that distract the attention of drivers from the primary task of
driving. The questionnaire survey also identified the various locations where the
MABTS drivers keep their mobile phone devices for navigation purposes. Thus,
research objectives – 2 and 3 of the study were fulfilled.
Objective 4: To identify the position/ location preferred by the majority of MABTS drivers for
keeping mobile phones for navigation purposes, using questionnaire survey.
During the questionnaire survey, the MABTS drivers rated their most preferred
location for mounting mobile phones for navigation purposes. Thus, objective –
4 of the research was fulfilled.
Objective 5: To identify the optimal/ most preferred in-vehicle position for placing mobile
phone for navigation purpose in terms of minimizing the bio-mechanical effort.
A digital human modeling (DHM) based virtual simulation was performed to
identify the optimal position of mobile phone location. Digital manikins with
body dimensions of 5th, 50th, and 95th percentile Indian male population was
prepared and interfaced with the car dashboard’s CAD model. Head (rotation,
flexion/ extension, and reachability) movement of each of the 5th, 50th, and 95th
percentile manikins were observed at all the different mobile phone locations
identified during the questionnaire survey (details in chapter 3). The virtual
simulation values were validated by measuring head movements for drivers
representative of 5th, 50th, and 95th percentile male population. An optimal
position for placing a mobile phone for navigation purposes was identified in
terms of minimal biomechanical effort. Thus, research objective – 5 of the
study was fulfilled.
Objective 6: To identify the most suitable in-vehicle position in terms of reduced driver
distraction and less affected driving performance for mounting the mobile phone
(as navigational device), among the various preferred positions by MABTS drivers.
To empirically examine the suitable position of in-vehicle mobile phones, we
conducted a driving simulator based experiment in a laboratory setup. Drivers’
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7.1. Overall discussion of the research work 125
visual behavior and driving performance were measured using an eye-tracking
system and simulated driving (lane change test) environment, respectively. Thus,
research objective – 6 of the study was fulfilled.
7.1.3 Testing of hypothesis
Hypothesis 1: Driver distraction due to use of mobile phone for navigation can significantly
be reduced by identifying optimal/ most preferred position of the mobile phone
considering minimal obstruction of external view field, minimal eye/ neck
movement (to visualize the screen) and easy reach for navigational purpose.
The DHM study’s outcome revealed that the minimum head movement (rotation:
1°, flexion: 5° – 8°) was achieved for in-vehicle mobile phone placed at the
front position of the steering wheel for 5th, 50th, and 95th percentile manikins.
The outcome of the driving simulator-based experiment revealed that the driver
distraction (in-terms of driving performance) was minimum for front position
of in-vehicle mobile phone. A repeated measures ANOVA was conducted to
find the difference (if any) in the M. Dev values, among the dual-task driving
conditions. The results of repeated measures ANOVA revealed that there is a
significant effect of driving condition (F(4,116) = 36.80, p < 0.05,η2 = 0.559,
large effect size) on M.Dev values. Further, a post hoc test using bonferroni
correction revealed that significant difference in M.Dev values exist between
front and middle mobile phone positions (p < 0.05). Among the dual-task
driving scenario, the mean deviation (M.Dev = 0.68) value was minimum for
the front mobile phone position. In terms of driving workload, the front mobile
phone position was rated to be the least loading (M = 30.35). Since the front
position of the in-vehicle mobile phone was least distracting and drivers had
a high perception of safety for this position, the fixation (M = 24.64 s) and
glance (M = 31.06 s) duration of the drivers was longest at front mobile phone
position. Hence, we can say that the front mobile phone position with minimum
head rotation, and easy arm reach, has the least distracting effect (better driving
performance and visual behavior). Thus, establishing the hypothesis – 1 of
the research.
Hypothesis 2: Reduced driver distraction due to most suited position of mobile phone for
navigation purpose significantly increases the driving performance.
The simulated driving experiment revealed that the driving performance depends
on the position of in-vehicle mobile phones used for ride-booking, navigation,
checking fare, and calling by the MABTS drivers. A repeated measures ANOVA
showed that M.Dev values differed significantly among the different driving
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126 7.1. Overall discussion of the research work
conditions (F(4,116) = 36.80, p < 0.05,η2 = 0.559, large effect size). The
best lane keeping performance (low value of mean deviation) was achieved
when an in-vehicle mobile phone was placed at the front position (p < 0.05)
compared to the other dual-task driving scenario. For lane change error, a
Friedman test revealed that there was a significant effect of driving condition
(χ2(4) = 14.09, p < 0.05) on lane change errors. The least amount of lane
change error (M = 3.50) was also observed for the front position among the
different mobile phone positions. Hence, the hypothesis – 2 of the research
work was established.
7.1.4 Novelties (key contributions) of the present research
The current research work promotes the existing knowledge of the visual ergonomics and
cognitive ergonomics in the applied domain of driver distraction to identify the most suitable/
most preferred location for in-vehicle positioning of mobile phone as navigation device. The
key novelties of this research are pin-pointed hereunder.
Contribution to the body of knowledge (ergonomics/HFE)
It has been observed from field-survey that the in-vehicle positioning of mobile phone as
navigational device by MABTS drivers are varied. They generally mount at different locations
on and around the dashboard and steering wheel, as per their convenience. Neither there is a
guideline by the service providers, nor there are specific locations followed by the MABTS
drivers for mounting their mobile for navigation purpose. Following the literature review, clear
research gap has been identified regarding lack of guideline/ standard in national/ international
scenario for optimal positioning of mobile phone (as portable navigation system) to minimize
distraction. Present research has successfully addressed this prominent research gap through
systematic empirical studies. Current research has utilized field survey, virtual simulation, and
driving simulator based laboratory experiments involving LCT, eye-tracking and subjective
workload assessment to identify the most preferred location of mobile phone for navigation
purpose, among various highly preferred/ regularly practiced locations by MABTS drivers.
The current research has not only investigated the commonly practiced locations for
positioning the mobile phone (as in-vehicle navigation device) by the MABTS drivers in
Indian scenario but also attempted to identify the most preferred position in terms of minimal
driver distraction and less affected driving performance. The research work undertaken is
probably the first of its kind that explores the distracting effect of the usage of mobile phone as
in-vehicle navigation device by MABTS drivers in Indian scenario.
The process of ergonomic designing of product (special mobile phone holder for mounting
mobile phone on the hub of the steering wheel) has been described in detail. This research work
has also lead the identification of the most suitable in-vehicle mobile phone position based
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7.1. Overall discussion of the research work 127
on lowest bio-mechanical effort (in-terms of minimum head rotation/ flexion/ extension and
reachability) by applying virtual ergonomic evaluation using digital human modeling software.
Apart from physical ergonomic aspect of reduced bio-mechanical load, suitable in-vehicle
mobile phone position has also been identified based on driver’s cognitive workload (DALI
questionnaire), driving performance (Lane-changing task), and eye-movement study.
Methodological perspective
The present dissertation work demonstrated a systematic research approach from the review of
existing literature, field survey to establish the rationale of research, and formulate the problem
statement. Following laboratory-based experimentation in driving-simulator, current research
has identified the most preferred location of mobile phone (as navigation purpose) in terms
of reduced driver distraction and less impact on driving performance. Current research has
employed field survey to understand the MABTS drivers’ behavior and their common practice
to position the mobile phone as navigation device. A systematic product development strategy
developed an innovative self-adjusting steering wheel-mounted mobile phone holder, need
analysis, concept generation using the morphological chart, concept selection via the Pugh
matrix, and user feedback was applied. Use of digital human modeling (DHM) techniques for
evaluating comfortable head movement (flexion/extension and rotation), and reach to various
in-vehicle mobile phone locations was unique and brings novelty in driver distraction research.
The eye-tracking was used for recording drivers’ visual behavior during performing dual-tasks
in a driving simulator in a laboratory setup to understand drivers’ driving performance and level
of driver distraction due to the different mobile phone locations. Drivers’ subjective workload
was measured using the driving activity load index (DALI) questionnaire. Statistical analysis
(repeated measures ANOVA) was performed to identify, significant difference (if any) in the
driving performance (M. Dev and lane change error), visual behavior (fixation, glance, TEORT),
and driving workload, among the different in-vehicle mobile phone positions.
The research methodology followed in the present research work might be the foremost
of its kind towards exploration from visual and cognitive ergonomics perspective in Indian
MABTS scenario. Researchers, Designers and Engineers involved in design, development of
mobile phone holder or any other in-vehicle control-display unit may adopt a similar strategy
to come up with innovative product design with due consideration of cognitive aspects of the
drivers during real-driving scenario. The standardized methodology as described and adopted
in the present research could serve as the research manual for future researchers.
The complete methodology (starting from identification of research gap and formulating
research problem to providing appropriate solution) used in the present research may be
reproduced by emulating similar control-display scenario to minimize distraction from the
primary task(s) in a scenario of working condition with high demand of attention and thereby
cognitive load.
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128 7.2. Scope for future research based on . . .
Contribution to society
The current research work deals with the widespread problem of visual distraction and
inattention faced by professional (taxi/ cab/ auto-rickshaw) drivers in particular and personal
automobile drivers in general, during their use of mobile phone as navigation device. The
problem of distraction and there by possibility of accidents or near to accidents can be minimized
by optimal position of in-vehicle navigation/ infotainment system like mobile phone. Suitable
position of navigation device/ display would not only reduce the driver distraction largely
by minimizing off-road glances to access information from the display or by decreasing
interaction-time with the device. Moreover, appropriate positioning of navigation/ infotainment
system would minimally affect the driving performance. Findings of the current research can be
utilized by the policy-makers/ road-transport authorities for formulating guidelines for efficient
and safe use of in-vehicle navigation device. It is anticipated that the outcomes of this research
would be beneficial to the wide spectrum of drivers (both personal and professional) driving a
variety of vehicle classes (auto, truck, buses, etc.), by giving them a clear perspective on the
placement of in-vehicle mobile phones. Thus, mitigating the problem of driver distraction and
increasing road safety for drivers and other road commuters.
Contribution to the industry
Current research through systematic research methodology has identified the most preferred
location of mobile phone for navigation purpose, among various highly preferred/ regularly
practiced locations by Indian MABTS drivers. The outcome of the research can be utilized
by the MABTS companies to develop guidelines and standard operating procedures (SOP) for
the drivers for placement of their mobile phone or any other navigation device. Further, the
automobile companies can use the outcome from the present research for judiciously placing
the in-vehicle displays for reduced driver distraction. The knowledge gained from the study
about visual and driving behavior could be used by the designers and the ergonomists for
developing safer and user-friendly in-vehicle displays. Additionally, the industrial designers
can also use the knowledge to design mobile holders/ space integrated within the dashboard,
keeping in mind smaller visual angles for safety and usability (to guide the driver to place the
mobile device in the correct position).
7.2 Scope for future research based on limitations
Although the researcher tried to follow the best possible experimental design and thereby
execution of research as per the set objectives, the overall research is not devoid of limitations.
The inevitable loop-holes and limitations of current research could be taken for further
exploration as the future research scope.
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7.2. Scope for future research based on . . . 129
• The study in chapter 3, was mainly self-reported, which is biased by social desirability
issues. Due to this bias, difficulty in viewing/ operating mobile phones while driving,
health problems, engagement in distracting tasks, and chances/ possible occurrence of
crash/ accident may be under-reported.
• India’s MABTS driver population predominantly consists of males; data from the
female drivers were not feasible due to their unavailability. Apart from this, the survey
respondents were driving right-handed vehicles (hatchback/ sedan); some preferences
regarding the placement of mobile phones might vary for left-handed vehicles, which are
mainly used in the western world. Future studies could consider taking responses and
data from the female population and drivers of left-handed vehicles.
• The study in chapter 4 is based on virtual ergonomic assessment using CATIA-DELMIA
software. This study considers only biomechanical effort in terms of head (rotation and
flexion/ extension) movement, comfort range of motion, and reachability. It does not
consider the subjective evaluation of comfort under prolonged driving conditions.
• The manikins used in the study (chapter 4) were representative of the adult Indian male
population. The results may vary a little and may not apply to the female population.
Moreover, the evaluation was based only on the comfort of head movement (flexion/
extension and rotation), and reachability required for the different in-vehicle mobile
phone positions, using percentile manikins (5th, 50th, and 95th). Use of boundary
manikins may have produced different results. Future studies could build upon these
shortcomings and carry out research to overcome these lacunae.
• Although the researchers have taken the utmost care to match the experimental conditions
(position of the mobile phone) with the real-world scenario (for both DHM and simulated
study), an accurate resemblance may not have been achieved. Further, the empirical
study in chapter 6 used a fixed-base driving simulator in a laboratory environment where
the drivers know that their error/ fault in driving would be inconsequential towards an
accident. An empirical study on an instrumented vehicle on a real road/ traffic condition
may produce a more realistic outcome. The study could further be extended by using
dynamic simulator or in real road conditions.
• Additionally, in the study of chapter 6, various other factors were unaccounted, which
may have affected the drivers’ visual behavior and driving performance. These factors
include the drivers’ characteristics (age, gender, comfort and skill of driving the simulator,
driving experience), environmental characteristics (road condition (rural/ urban), traffic
(high/ low)), and vehicle characteristics (right/ left-hand drive, type of vehicle). Future
research can be planned to study the impact of all these variables in identifying most
preferred mobile phone position.
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130 7.2. Scope for future research based on . . .
• The present study measured driving workload using the DALI scale in a laboratory setup;
however, the driver’s workload may be affected by psycho-social and organizational
factors/ policies. There may be constraints and expectations on the MABTS drivers, such
as meeting the performance targets, directly linked to financial factors/ incentives (of
reaching the destination on time) which don’t influence the non-MABTS drivers. Since
such factors were not measured, there is a scope for future research.
• Future studies should take up research on an instrumented vehicle and different classes
of vehicles (trucks, buses, and auto-rickshaws) for producing more generalized outcomes.
The future scope also lies in understanding the optimum position for mobile phones for
drivers suffering from low back pain, which is very common among professional drivers,
its comparison with healthy drivers (present study), and its implications for design. Future
research could also take a comparative study between MABTS drivers who use only
mobile phones and those who use mobile phones with Bluetooth devices (or voice based
user interface), since audio input may also influence visual behavior while driving.
Indian MABTS drivers mainly employ mobile phones for rendering their services (car
booking, navigation, and fare). Complete elimination of mobile phone’s use by them while
driving is not possible since it is an essential part of taxi services. There is no guideline by the
service providers, nor are there specific locations followed by the MABTS drivers for mounting
their mobile for navigation purposes. MABTS drivers generally mount their mobile phones at
different locations on and around the dashboard and steering, as per their convenience. Thus,
self-justified positioning of the mobile phone by MABTS driver might cause greater visual
distraction, higher biomechanical effort (neck/ eye movement, reachability, etc.), and reduced
driving performance leading to an increased chance of error and accident. Thus, the need of
the hour is to address the issue of identifying the most preferred/ best suitable position of the
mobile phone (as a navigation device). The current research has successfully investigated the
commonly practiced locations for positioning the mobile phone by the MABTS drivers in the
Indian scenario and identified the most preferred position out of the various commonly practiced
positions by the MABTS drivers, in terms of minimal driver distraction and less affected driving
performance. Although the current research has various limitations, it is probably the first of
its kind that explores the distracting effect of mobile phone usage as an in-vehicle navigation
device by MABTS drivers in the Indian scenario. The automobile companies can use the
present research outcome for judiciously placing the in-vehicle displays for reduced driver
distraction. MABTS companies can develop guidelines and standard operating procedures
(SOP) for the drivers for placement of their mobile phone or any other navigation device for
mitigating driver distraction caused by inappropriate positioning of mobile phone for their
services. The policy-makers/ road-transport authorities could utilize the findings of the current
research for formulating guidelines for the efficient and safe use of in-vehicle navigation devices.
The designers and ergonomists could use the knowledge gained from driving simulator-based
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7.2. Scope for future research based on . . . 131
laboratory experiments involving LCT, eye-tracking, and subjective workload assessment for
developing safer and user-friendly in-vehicle displays.
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Appendices
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A.1. Detailed questionnaire used in field survey 135
A.1 Detailed questionnaire used in field survey
PARTICIPANT INFORMED CONSENT 
 
Project Title:    Driver Distraction Questionnaire 
Researcher’s Name:  Indresh Kumar Verma 
Supervisor’s Name:  Dr. Souagata karmakar 
 
DECLARATION BY THE PARTICIPANT 
I hereby declare that 
 I have received information about this research project. 
 I understand the purpose of the research project and my involvement in it. 
 I understand that I may withdraw from the research project at any stage. 
 I understand that whatever information gained during the study may be published, I will not 
be identified and my personal results will remain confidential.  
 
Participants under the age of 18 yrs. require parental consent to be involved in research. The 
consent form should allow for those under the age of 18 yrs. to agree to their involvement and for 
a parent to give consent. 
 
Name: ________________________________ Signed: _________________ Date: ___/__/2015 
Education: ____________________ Corrected Vision: ____ (______) Age / Sex: _____ yr. / ___ 
Address: ______________________________________________________________________ 
DECLARATION BY THE RESEARCHER 
I hereby declare that I have provided requisite information about the research participant; and confirmed that s/he 
has understood the experimental details and his / her role therein. 
 
Researcher’s Name: Indresh Verma  Signed: _________________ Date: ___/__/2015 
 
Demographic Questions 
Name:      Age:  Gender: 
Height (cm) _______________ Driving Experience: _______________________ in yrs 
Type of vehicle you drive:  a.) Personal Vehicle  b.)  Others vehicle professionally  
License type:  a.) learners license   b.) Commercial LMV   c.) Commercial HMV license  
Have you met with an accident while driving (period – past 1 / 2 / 3 / 5 etc yr)    
a. Yes, (if yes, give details)    b. No 
Vehicle you drive is: Hatchback / Sedan / SUV 
Driving Speed Range 
 < 40 kmph   40 – 60 kmph   60 – 80 kmph   > 80 kmph 
 
Physical Fitness Questions: 
1. Have you at any time during the past 12 months had trouble (ache, pain, discomfort) in: 
a. Neck          Yes / No 
b. Shoulder 
i. Right Shoulder       Yes / No 
ii. Left Shoulder       Yes / No 
2. Have you undergone some kind of surgery / operation of shoulder or neck in the past 12 
months          Yes / No 
3. Are you under some kind of Medication / Drug     Yes / No 
4. Do you have a spectacles, if yes 
a. For Long Distance 
b. For Short distance 
5. Do you have problem in recognising the colours      Yes / No 
6. Do you have undergone any kind of eye operation in the past 12 months  Yes / No 
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136 A.1. Detailed questionnaire used in field survey
Section A 
1. Please select from the list of following activities you do while driving 
a. Use of navigation system 
b. Use of Radio/ Music system 
c. Use of Environment control in vehicle 
d. Use of mobile phone 
e. Looking to the in-vehicle meters 
f. Interaction with passengers 
g. Adjusting the seat. 
 
2. On a scale of 1 to 5 please rate the level of distraction you feel when performing these 
activities along with driving. 
Least     most 
     1    2    3    4     5 
a. Talking on phone  
b. Radio/ music system 
c. Environment control (AC / Heater) 
d. Looking to in-vehicle meters 
e. talking with passengers 
f. using navigation system 
g. seat adjustment 
 
Section B    (Strongly disagree – Strongly agree) 
1. It is easy for me to adjust Radio/ music system while driving 
2. I have no difficulty in looking at  in-vehicle meters while driving 
3. It is comfortable for me to talk to the passenger and drive at the same time. 
4. When driving I can easily adjust the environment control system (AC / Heater) 
5. It is easy for me to drive and use navigation system at the same time 
6. I have no difficulty in adjusting seats while driving my car 
7. I can comfortably use my mobile phone while driving 
Section C 
1. The location of Radio / music system is at a comfortable position in my car. 
2. I do not use navigation system in my cars as it is at an uncomfortable position. 
 
Section D 
Questions related to Display and Visual exploration of the display 
1. Where do you generally place the mobile device for navigation purpose while driving? 
_______________________________________________________________________ 
 
 
 
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A.1. Detailed questionnaire used in field survey 137
2.  
a. How often do you look at the navigation display during a trip (known destination) 
Never Rarely Sometimes / Occasionally Almost every time every time 
     
 
b. How often do you look at the navigation display during a trip (un-known destination) 
Never Rarely Sometimes / Occasionally Almost every time every time 
     
 
3. Display visible from the normal operating posture. 
Strongly disagree Disagree Neutral Agree Strongly Agree 
     
 
4. Display located in the expected region? 
Strongly disagree Disagree Neutral Agree Strongly Agree 
     
 
5. Head or Head- torso movements are required to see the display. 
Strongly disagree Disagree Neutral Agree Strongly Agree 
     
 
6. There is visual discomfort in viewing the target area / device, leading to distraction?  
Strongly disagree Disagree Neutral Agree Strongly Agree 
     
 
7. There is discomfort with more than one visible interference, leading to distraction? 
Strongly disagree Disagree Neutral Agree Strongly Agree 
     
 
 
Display Location 
8. Which Region do you prefer to keep the mobile phone when you are using it for navigation? 
a. Left Region of Steering Wheel   
b. Right Region of Steering Wheel 
c. Centre Region of Steering Wheel 
 
9. Where do you generally place mobile for navigation in the car?  
a. Left Portion 
b. Right Portion 
c. Middle Portion 
d. No mobile holder 
 
10. Do you change the position of the car mount mobile holder during different time of the day?
       Yes / No 
 If Yes, 
a. Position at Day time  _____________________________________ 
b. Position at Night time ____________________________________ 
 
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138 A.1. Detailed questionnaire used in field survey 
 
 
 
11. Rank the location (based on preference of use) of keeping the mobile device for navigation 
purpose (1 being most preferred and 9 is least preferred) as shown in picture. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Fig 1 
 
Position 1 2 3 4 5 6 7 8 9 
Rank          
 
12. Do you somehow keep the mobile in any place other than those shown in Fig 1? Please 
share your views towards the same. 
___________________________________________________________________________
___________________________________________________________________________ 
 
13. Display is located at a comfortable viewing distance. 
Strongly disagree Disagree Neutral Agree Strongly Agree 
     
 
14. Display is located close to the driver’s Primary / binocular field of Sight. 
Strongly disagree Disagree Neutral Agree Strongly Agree 
     
 
15. Auxiliary display lead to distraction from driving. 
Strongly disagree Disagree Neutral Agree Strongly Agree 
     
 
16. To view the auxiliary display you have to distract from the primary visual area of driving. 
Strongly disagree Disagree Neutral Agree Strongly Agree 
     
 
17. Display confuse with other visible objects present laterally to the driving visual area. 
Strongly disagree Disagree Neutral Agree Strongly Agree 
     
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A.2. Consent Form 139
A.2 Consent Form
Consent and Basic information Form 
 
Experiment Id: Name: 
 
Age: 
 
Gender:  
  
Driving Experience: 
About the Experiment:  
 In this experiment, your driving performance will be tested under dual task scenario 
(performing secondary task along with the primary task of driving), in a fixed base 
driving simulator, when the mobile-phone is placed at four different locations.  
 
 Your eye-movement and gaze data will be recorded using the eye-tracking equipment. 
 
 
 After completion of the driving test, subjective assessment of workload will be measured 
using Driver Activity Load Index (DALI) questionnaire. 
 
Confidentiality:   
 The data collected during the experiment will be used for research and education 
purpose. 
 
 
 Your personal details will be kept confidential at all times and no part will be made 
public. 
              
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140 A.2. Consent Form
 
Statement of Consent:   
 Your signature indicates that you are at least 18 years of age. 
 
 
 You have read this consent form along with purpose and procedure of the experiment. 
 
Right to Withdraw and Questions:  
 Your participation in this experiment is completely voluntary.  
 
 You may choose not to take part at any time. 
 
 
Signature and Date:  
Signature:  ____________________________________________ 
 
Date:       ___________________________________________ 
TH-2774_146105005
A.3. Driving Activity Load Index (DALI) 141
A.3 Driving Activity Load Index (DALI)
Driving Activity Load Index (DALI) 
 
During the test you have just completed, you may have experienced some difficulties and constraints with 
regard to the driving task.  
 
 
 
 
You are required to rate the experience through 6 different factors (described below). Please read each 
factor and its description carefully and ask the experimenter to explain anything you do not fully understand. 
 
 
 
 
 
 
 
Participant Id _________________________________________ Track No. ______________________ 
 
Please rate each of the following factors according to the experience of your driving activity for this 
particular session on a scale of 0 (low level of constraint) to 5 (high level of constraint). 
 
Attention demand: 
Think about the overall (mental, auditory, visual) demand required during the test to perform the whole 
activity.  
 
 
 
 
Low 
0 
 
1 
 
2 
 
3 
 
4 
High 
5 
 
 
TH-2774_146105005
142 A.3. Driving Activity Load Index (DALI)
Visual demand: 
Think about the visual demand required during the test to perform the whole activity. 
Low 
0 
 
1 
 
2 
 
3 
 
4 
High 
5 
 
Auditory demand: 
Think about the auditory demand required during the test to perform the whole activity. 
 
Low 
0 
 
1 
 
2 
 
3 
 
4 
High 
5 
 
Stress: 
Think about the level of stress (fatigue, insecurity, irritation) during the test to perform the whole 
activity. 
 
 
 
 
Low 
0 
 
1 
 
2 
 
3 
 
4 
High 
5 
 
 
 
 
 
TH-2774_146105005
A.3. Driving Activity Load Index (DALI) 143
Temporal demand: 
Think about the pressure and specific constraint felt due to time pressure of completing task during the 
whole activity. 
 
Low 
0 
 
1 
 
2 
 
3 
 
4 
High 
5 
 
Interference: 
Think about disturbance to the driving task when completing secondary task. 
 
Low 
0 
 
1 
 
2 
 
3 
 
4 
High 
5 
 
 
 
 
 
 
 
 
 
 
 
 
 
TH-2774_146105005
144 A.3. Driving Activity Load Index (DALI)
Pair Wise Comparison 
 
Attention demand 
or 
Visual demand 
 
 
Auditory demand 
 
or 
Stress 
 
 
Attention demand 
or  
Stress 
 
Auditory demand 
 
or 
Interference 
 
Visual demand 
 
or 
Temporal demand 
 
Attention demand 
or 
Temporal demand 
 
Attention demand 
or 
Auditory demand 
 
Visual demand 
 
or 
Auditory demand 
 
Attention demand 
or 
Interference 
 
Visual demand 
 
or 
Interference 
 
Auditory demand 
 
or 
Temporal demand 
 
Visual demand 
 
or 
Stress 
 
Temporal demand 
 
or  
Interference 
 
Stress 
 
 
or 
Interference 
 
 
Temporal demand 
 
or 
Stress 
 
TH-2774_146105005
A.4. Calculation of the DALI questionnaire 145
A.4 Calculation of the DALI questionnaire
Computation of the Weighted DALI Score is calculated by Equation 1
Wi = αi×Ri; (1)
αi =Ci/(n−1); (2)
Ri = li×20; (3)
where,
Wi = Weighted Score of each factor,
Ci = no. of times a given factor has been selected during the pairwise comparison;
(n−1) = no. of pairs for this factor, in this case its 5.
li = rating of each of the factor on a scale of 0 to 5.
The Global workload score for DALI is calculated as shown in equation 4
Wglobal = (
6
∑
i=1
αiRi)/n (4)
n = 6, in this case.
TH-2774_146105005
146 A.5. System Usability Scale (SUS)
A.5 System Usability Scale (SUS)
System Usability Scale (SUS) 
 
 
Instructions  
Based on your experience today, with the product, check the box that reflects your immediate response 
to each statement. Make sure you respond to every statement. If you don’t know how to respond, 
simply check box “3”. 
 
Comments:  
 
 
Project/Release/Study: Date: 
Participant: 
 
 
 
Strongly 
disagree 
1 2 3 4 
Strongly 
agree 
5 
1 I think that I would like to use this product frequently. ☐ ☐ ☐ ☐ ☐ 
2 I found the product unnecessarily complex. ☐ ☐ ☐ ☐ ☐ 
3 I thought the Product was easy to use. ☐ ☐ ☐ ☐ ☐ 
4 
I think that I would need the support of a technical person to 
be able to use this product. ☐ ☐ ☐ ☐ ☐ 
5 
I found the various functions in the Product were well 
integrated. ☐ ☐ ☐ ☐ ☐ 
6 I thought there was too much inconsistency in the Product. ☐ ☐ ☐ ☐ ☐ 
7 
I would imagine that most people would learn to use the 
Product very quickly. ☐ ☐ ☐ ☐ ☐ 
8 I found the Product very cumbersome to use. ☐ ☐ ☐ ☐ ☐ 
9 I felt very confident using the Product. ☐ ☐ ☐ ☐ ☐ 
10 
I need to learn a lot of things before I could get going with 
this Product. ☐ ☐ ☐ ☐ ☐ 
TH-2774_146105005
A
.6.
C
om
parison
betw
een
virtualand
real...
147
A.6 Comparison between virtual and real measurements
1 2 3 4 5 6 7 8 9
-20
-15
-10
-5
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9
-20
-15
-10
-5
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9
-20
-15
-10
-5
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9-50
-40
-30
-20
-10
0
10
20
30
1 2 3 4 5 6 7 8 9-50
-40
-30
-20
-10
0
10
20
30
1 2 3 4 5 6 7 8 9-50
-40
-30
-20
-10
0
10
20
30
 Virtual Measured
H
e
a
d
 
f
l
e
x
i
o
n
/
 
e
x
t
e
n
s
i
o
n
 
a
n
g
l
e
 
(
d
e
g
.
)
5th percentile
 Virtual Measured
50th percentile 95th percentile
 Virtual Measured
H
e
a
d
 
r
o
t
a
t
i
o
n
 
a
n
g
l
e
 
(
d
e
g
.
)
Position of mobile phone
 Virtual Measured
Position of mobile phone
 Virtual Measured
 Virtual Measured
Position of mobile phone
TH-2774_146105005
148 A.7. Two-dimensional drafting of the . . .
A.7 Two-dimensional drafting of the mobile-phone holder
(a) Mobile holder
 10 
 5 
 40 
 30 
 120 
 18 
 40 
 25 
 12 
 6 
 30 
 15 
 10 
 R5 
 R2  R5 
 R5 
 R2 
 22 
 2 
 R0.50 
 15 
 14  2.80 
 14 
 15 
 15 
 R5 
 70 
 18 
 25 
 12 
 6 
 10  5 
 10  75 
 15 
 10 
 R10 
 R2 
 R2 
 22 
 2 
 R0.50 
 18.49  16.71 
 15 
 14 
 R1 
 2.80 
 2.50 
 15 
A A
B B
C C
D D
E E
F F
4
4
3
3
2
2
1
1
DRAWN
CHK'D
APPV'D
MFG
Q.A
UNLESS OTHERWISE SPECIFIED:
DIMENSIONS ARE IN MILLIMETERS
SURFACE FINISH:
TOLERANCES:
   LINEAR:
   ANGULAR:
FINISH: DEBURR AND 
BREAK SHARP 
EDGES
NAME SIGNATURE DATE
MATERIAL:
DO NOT SCALE DRAWING REVISION
TITLE:
DWG NO.
SCALE:1:2 SHEET 1 OF 1
A4
WEIGHT: 
drwMobile Holder
All measurements in mm.
TH-2774_146105005
A.7. Two-dimensional drafting of the . . . 149
(b) Base
 35  35 
 R5 
 20 
 10 
 35 
 2 
 20 
 4 
 R1 
 35  2 
 20 
 4 
 R1 
A A
B B
C C
D D
E E
F F
4
4
3
3
2
2
1
1
DRAWN
CHK'D
APPV'D
MFG
Q.A
UNLESS OTHERWISE SPECIFIED:
DIMENSIONS ARE IN MILLIMETERS
SURFACE FINISH:
TOLERANCES:
   LINEAR:
   ANGULAR:
FINISH: DEBURR AND 
BREAK SHARP 
EDGES
NAME SIGNATURE DATE
MATERIAL:
DO NOT SCALE DRAWING REVISION
TITLE:
DWG NO.
SCALE:2:1 SHEET 1 OF 1
A4
WEIGHT: 
dwgBase1
All measurements in mm.
TH-2774_146105005
150 A.7. Two-dimensional drafting of the . . .
(c) Ball
 15.72 
 15 
 10 
 R5 
 15.72 
 15 
 10 
 10 
 R5 
 15.72 
A A
B B
C C
D D
E E
F F
4
4
3
3
2
2
1
1
DRAWN
CHK'D
APPV'D
MFG
Q.A
UNLESS OTHERWISE SPECIFIED:
DIMENSIONS ARE IN MILLIMETERS
SURFACE FINISH:
TOLERANCES:
   LINEAR:
   ANGULAR:
FINISH: DEBURR AND 
BREAK SHARP 
EDGES
NAME SIGNATURE DATE
MATERIAL:
DO NOT SCALE DRAWING REVISION
TITLE:
DWG NO.
SCALE:2:1 SHEET 1 OF 1
A4
WEIGHT: 
dwgBall
All measurements in mm.
TH-2774_146105005
A.7. Two-dimensional drafting of the . . . 151
(d) Screw
 R2 
 
22
 
 
21
 
 R
2 
 22 
 1
0 
 2
.8
0 
 1
4 
 21 
 16 
 1
 
 20 
 21 
 2
 
 R2 
 R1 
 1
0 
 R1 
 10 
 
22
 
 10 
 2.80 
 14 
 
21
 
 
16
 
 1 
 
20
 
 
21
 
 2 
 R2 
 R1 
 R
1 
A A
B B
C C
D D
E E
F F
4
4
3
3
2
2
1
1
DRAWN
CHK'D
APPV'D
MFG
Q.A
UNLESS OTHERWISE SPECIFIED:
DIMENSIONS ARE IN MILLIMETERS
SURFACE FINISH:
TOLERANCES:
   LINEAR:
   ANGULAR:
FINISH: DEBURR AND 
BREAK SHARP 
EDGES
NAME SIGNATURE DATE
MATERIAL:
DO NOT SCALE DRAWING REVISION
TITLE:
DWG NO.
SCALE:2:1 SHEET 1 OF 1
A4
WEIGHT: 
nut^Assem2
All measurements in mm.
TH-2774_146105005
152 A.8. Institute Human Ethics Committee . . .
A.8 Institute Human Ethics Committee approval letter
TH-2774_146105005
A.9. List of publications 153
A.9 List of publications
Conferences
1. Verma, I. K., & Karmakar, S. (2017). Driver Distraction: Methodological Review. In A.
Chakrabarti & D. Chakrabarti (Eds.), Research into Design for Communities, Volume 1.
ICoRD 2017 (Vol. 65, pp. 849–859). Springer, Singapore. https://doi.org/10.1007/
10.1007/978-981-10-3518-0_73
2. Verma, I., Nath, S., & Karmakar, S. (2018). Research in Driver–Vehicle Interaction:
Indian Scenario. In G. G. Ray, R. Iqbal, A. K. Ganguli, & V. Khanzode (Eds.),
Ergonomics in Caring for People (pp. 353–361). Springer, Singapore. https://doi.org/
10.1007/10.1007/978-981-10-4980-4_43
3. Verma, I., & Karmakar, S. (2021). Subjective evaluation of driver-distraction caused
during use of mobile phone for navigation purpose. In: Proceedings of International
conference on Humanizing Work and Work Environment, 2017. 8th – 10th Dec, 2017.
Journals
1. Verma, I.K., & Karmakar, S. (2020). Positioning of the Mobile Phone to Minimize
Driver’s Biomechanical Effort During Navigation: DHM-Based Approach. Journal of
The Institution of Engineers (India): Series C. https://doi.org/10.1007/s40032-020
-00580-9
2. Verma, I. K., & Karmakar, S. Mounting smart-phone on steering-wheel to facilitate
ease of visibility of navigation screen: Systematic product design approach. WORK: A
Journal of Prevention, Assessment & Rehabilitation. [Accepted]
3. Verma, I. K., Nayak, B. K., & Karmakar, S. Effect of mobile-phone position on the
visual and driving behavior: A LCT based study. Human Factors. [Communicated]
TH-2774_146105005
154 A.10. Patent filed
A.10 Patent filed
Design patent:
• Self-balancing mobile holder for steering wheels. [FER Issued]
Design Registration Number: 329864-001, Class: 08-08, Filed on 08th June, 2020.
Members: Mr. Indresh Kumar Verma, Dr. Sougata Karmakar, Mr. Gurdeep Singh
Utility patent:
• Design of steering wheel-hub mounted self-balancing universal mobile phone holder for
reducing biomechanical effort for display-navigation by vehicle drivers. [Published],
Application No.: 202031030298
Date of Filing: 16th July, 2020, Kolkata
Published on: 14th August, 2020.
The Patent Office Journal No. 33/2020
Members: Mr. Indresh Kumar Verma, Dr. Sougata Karmakar, Mr. Gurdeep Singh.
TH-2774_146105005
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