Table Of ContentDriver Adaptation to
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Driver information and assistance systems have emerged Alan Stevens is Chief Research Scientist and t
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as an integral part of modern road vehicles in order to Research Director, Transportation, at the Transport
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support the driver while driving. They make use of the Research Laboratory (TRL), in the UK, where he has i
newest information technologies in order to enhance driver been working on the application of new technology S o
awareness, safety and comfort, and thereby avoiding driver to transport for 25 years. He is an internationally y n
errors and accidents. Driver Adaptation to Information and recognised expert in human-machine interaction (HMI) s
Assistance Systems brings together recent work by the in the driving environment and his consultancy activities t to
focus on providing advice on policy and interoperability e
Marie-Curie Initial Training Network ADAPTATION. The project
has studied drivers’ behavioural adaptation to these new iasnsdu ecsa rtory iGngo voeurnt mspeencti,f icd etevcehlonpicinalg arnedse haurcmh apnro fgarcatomrss m In
technologies from an integrative perspective working under studies in Intelligent Transport Systems. He is Editor-in- s f
a joint conceptual theoretical framework of behavioural Chief of The Journal of Intelligent Transport Systems. o
adaptation that can be used to generate research hypotheses Corinne Brusque is Research Manager and Scientific r
m
about how drivers will adapt to information and assistance Director in charge of evaluation at Ifsttar (French
systems and to derive guidelines for the design and Institute of Science and Technology for Transport, a
deployment of such systems. Development and Networks). Her main research topics t
concern the factors affecting in-vehicle technology i
The book aims to provide the reader with a better o
adoption, drivers’ exposure to distraction related to
understanding of drivers’ adaptation processes over time in-vehicle technologies and the impact of in-vehicle n
in response to information and assistance system use at
technologies on drivers’ behaviour. Driver Adaptation to
different levels (energetic, cognitive and motivational levels);
Josef Krems is Professor of Cognitive and Industrial
an appreciation of the impact of specificities of drivers
Psychology at Chemnitz University of Technology. His
population on technology use and skill acquisition; insights current research projects focus on three areas: traffic
on the effects of system functionality, design and reliability and transport (safety, driver assistance, green driving
as important system characteristics influencing drivers’ and sustainability); human factors (human-machine Information and
adaptation; and recommendations on research methods and interaction, usability); and user acceptance.
appropriate tools to investigate adaptation processes.
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The Institution of Engineering and Technology Kv Edited by Alan Stevens,
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ISBN 978-1-84919-639-0 s,
Driver Adaptation.indd 1 02/12/2013 18:34:13
Driver Adaptation to
Information and
Assistance Systems
Driver Adaptation to
Information and
Assistance Systems
Edited by Alan Stevens, Corinne Brusque
and Josef Krems
The Institution ofEngineeringand Technology
PublishedbyTheInstitutionofEngineeringandTechnology,London,UnitedKingdom
TheInstitutionofEngineeringandTechnologyisregisteredasaCharityin
England&Wales(no.211014)andScotland(no.SC038698).
†TheInstitutionofEngineeringandTechnology2014
Firstpublished2014
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Contents
AbouttheEditors xv
EarlyStageResearchersandExperiencedResearchersinthe
ADAPTATIONProject xvii
Acknowledgements xxiii
Introduction xxv
1 The ADAPTATIONproject 1
Abstract 1
1.1 The motivation and objective of the project 1
1.2 ADASand adaptation: The background 2
1.3 Scientific and technological objectives 3
1.3.1 Research methodology 4
1.3.2 The research programme 4
1.4 The partners 6
1.5 The training and research programme 6
Acknowledgement 10
References 10
2 Behavioural adaptationinresponseto driving assistance
technologies: Aliterature review 13
Abstract 13
2.1 Introduction 13
2.2 Historical background 14
2.3 Definition and assumptions 16
2.4 Theories accounting forbehavioural adaptation effects 18
2.4.1 Behavioural adaptation and learning theories 18
2.4.2 Behavioural adaptation and driver risk models 19
2.4.3 Integrative models onbehavioural adaptation 20
2.5 Behavioural adaptation over an extended period of time 22
2.6 Behavioural change transfer 24
2.7 A‘Joint Conceptual Theoretical Framework (JCTF)of Behavioural
Adaptation in Response to Advanced Driver Assistance Systems’ 26
2.8 Conclusion and further research needs 29
Acknowledgements 30
References 30
vi Driveradaptationto informationand assistance systems
3 Methodsto assessbehavioural adaptationover time as
aresult of ADASuse 35
Abstract 35
3.1 Introduction 35
3.2 The useof long-term studies to assessbehavioural change
with ADASuse 36
3.2.1 Cognitive adaptation to ADAS 36
3.2.2 Advantages of long-term studies 38
3.2.3 Inconveniences of long-term studies 39
3.2.4 Conclusion onlong-term studies 40
3.3 Long-term studies usingdriving simulators 40
3.3.1 Introducing driving simulators 40
3.3.2 Utility of driving simulators 41
3.3.3 Advantages of driving simulators 42
3.3.4 Disadvantages of driving simulators 43
3.3.5 Conclusion ondriving simulator studies 44
3.4 Long-term studies inreal traffic conditions 45
3.4.1 Utility of naturalistic methods 46
3.4.2 Naturalistic driving study(NDS)versus field
operational test (FOT) 47
3.4.3 Data from naturalistic methods 48
3.4.4 Conclusion onnaturalistic methods 50
3.5 Conclusion 51
Acknowledgement 51
References 51
4 Effect of ADASuse ondrivers’ information processing
andSituationAwareness 57
Abstract 57
4.1 Behavioural adaptation and higher cognitive processes 57
4.2 Mental models 58
4.2.1 Definition 58
4.2.2 Mental model construction and update 58
4.2.3 Discussionof existing mental model measures
and requirements 59
4.2.4 Development of the mental model questionnaire 60
4.3 Situation Awareness 60
4.3.1 Definition 60
4.3.2 Relationship between mental models and
Situation Awareness 61
4.3.3 Situation Awareness as comprehension process 61
4.3.4 Discussionof existing Situation Awareness measures
and requirements 62
4.3.5 Development of the Situation Awarenessmeasurement
technique 63
Contents vii
4.4 Study 1: Driving simulator study 64
4.4.1 Aimsand research questions 64
4.4.2 Method and material 65
4.4.3 Results 67
4.5 Study 2: On-road study 69
4.5.1 Aimsand research questions 69
4.5.2 Method and material 71
4.5.3 Results 73
4.6 Discussionand conclusions 75
4.6.1 Mental model questionnaire 75
4.6.2 Situation Awareness measurement 76
Acknowledgement 77
References 77
5 Earlyadopters’ mental model of Adaptive Cruise
Control (ACC)andits influence onbehavioural adaptation
to thesystem 81
Abstract 81
5.1 Introduction 81
5.1.1 Adaptive Cruise Control (ACC)and behavioural
adaptations 81
5.1.2 Mental models 83
5.1.3 Scope of the research 84
5.2 Focusgroupsdiscussions 86
5.2.1 Procedure 86
5.2.2 Results 87
5.2.3 Discussion 89
5.3 Naturalistic Field Operational Test 90
5.3.1 Procedure 90
5.3.2 Results 92
5.3.3 Discussion 97
5.4 Discussionand conclusions 98
Acknowledgements 99
References 99
6 Intelligent driver supportsystems:Effects of learning
andaging 103
Abstract 103
6.1 Introduction 103
6.2 Dual-task performance 104
6.2.1 Models of dual-task interference 105
6.2.2 Effects of aging on dual-task interference 107
6.3 Learning in dual-task situations 108
6.3.1 Models of learning 108
6.3.2 Effects of aging on learning in dual-task situations 110
viii Driver adaptation to informationand assistance systems
6.4 Anempirical study 111
6.4.1 Hypotheses 111
6.4.2 Experimental setup 112
6.4.3 Summaryof major findings 114
6.5 Conclusion 116
Acknowledgment 116
References 117
7 Researching safety issueswithintersection assistance
systemsfor theolder driver 123
Abstract 123
7.1 Introduction 123
7.2 Road traffic safety 124
7.3 Intersectionsand the older driver 127
7.3.1 Demographic change and its consequences 127
7.3.2 Age-related impairments, diseases/disorders
and intersection performance 129
7.3.3 Crossingan intersection: Amulti-level task 131
7.3.4 New developments, potential benefitsand problems 132
7.3.5 Previous research relevant to intersection assistance 134
7.3.6 Drawbacks,unanswered questions and the need for
further research 136
7.4 Summary and conclusion 138
Acknowledgement 138
References 139
8 Motivational factors wheninvestigating ADASimpacts on
driver behaviour 145
Abstract 145
8.1 Understanding driver behaviour: Models and approaches
that attempt to explain driving behaviour 145
8.1.1 The Hatakka hierarchical model 148
8.1.2 Howperformance onthe particular levelsmay
influence drivers’ performance onother levels 150
8.2 Motivational factors 152
8.2.1 Physiological needs 153
8.2.2 Safety needs 154
8.2.3 Social needs 154
8.2.4 Esteem needs 154
8.2.5 Self-actualisation needs 154
8.3 Motivation and driving 155
8.3.1 Physiological needs and driving 155
8.3.2 Safety needs and driving 156
8.3.3 Social needs and driving 156
8.3.4 Esteem needs and driving 156
8.3.5 Self-actualisation needs and driving 156
Contents ix
8.4 Motivational driver behaviour models 157
8.5 Motivational influence factors based on the theory of
planned behaviour 158
8.6 The role of motivation in behavioural adaptation 159
8.6.1 Vehicle manoeuvring level and ADAS 162
8.6.2 Mastering traffic situations level and ADAS 162
8.6.3 Goals and context of driving and ADAS 163
8.6.4 Goals for life and skills for living and ADAS 163
8.7 Ashort view onimpacts of various ADASon driving 164
8.8 Conclusion 165
Acknowledgement 166
References 166
9 Drivers’adaptationto mobile phoneuse:Interaction
strategies, consequencesondriving behaviour andpotential
impact onroad safety 173
Abstract 173
9.1 Introduction 173
9.2 Regulating the exposure to phone usewhile driving 175
9.2.1 Exposure regulation strategies 175
9.2.2 Factors influencing exposure regulation 177
9.3 Seeking after compatibility of driving and mobile phone use 179
9.3.1 Driving situation 180
9.3.2 Assisted driving 182
9.3.3 Useof hands-free devices 183
9.4 Adapting driving behaviourin response to distractive effects
of mobile phone use 185
9.4.1 Impairment of driving performance due to distraction 185
9.4.2 Compensation strategies to mitigate effects of distraction 187
9.5 Conclusions on potential safety impact 188
Acknowledgement 189
References 189
10 Evaluatingthe potential for workload baseddriving
assistancesystems from apsychological, technological
andphysiological perspective 197
Abstract 197
10.1 Introduction 197
10.2 Theoretical foundation 199
10.2.1 The Yerkes–Dodsonlaw 199
10.2.2 The adapted Yerkes–Dodsonlaw 199
10.2.3 The flower model 199
10.3 Measuringworkload 200
10.3.1 Workload induction bysecondary task:
The n-back task 200
10.3.2 Measuringarousal over physiology 201
