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E-raamat: Driver Distraction: A Sociotechnical Systems Approach [Taylor & Francis e-raamat]

(University of Southampton), (University of Southampton, UK), (University of Southampton, UK)
  • Formaat: 250 pages, 33 Tables, black and white; 29 Illustrations, black and white
  • Sari: Transportation Human Factors
  • Ilmumisaeg: 26-Nov-2018
  • Kirjastus: CRC Press
  • ISBN-13: 9780429466809
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  • Taylor & Francis e-raamat
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Driver Distraction: A Sociotechnical Systems ApproachSuurem pilt
  • Formaat: 250 pages, 33 Tables, black and white; 29 Illustrations, black and white
  • Sari: Transportation Human Factors
  • Ilmumisaeg: 26-Nov-2018
  • Kirjastus: CRC Press
  • ISBN-13: 9780429466809
Teised raamatud teemal:
Taylor & Francis e-raamatudRohkem infot Taylor & Francis e-raamatute kohta
Raamatu kodulehekülg: https://www.taylorfrancis.com/books/9780429466809
Driver Distraction: A Sociotechnical Systems Approach promotes a sociotechnical systems approach to driver distraction. This perspective focuses on analysis of the whole system, its values, and the interactions between human and technical elements at all organisational levels. The book covers the role that the sociotechnical system plays in the theory, study and mitigation of driver distraction. The book will be of interest to accident and incident investigation researchers and practitioners.











Provides a review of the current state of driver distraction research Describes the development, application, and validation of a novel model of driver distraction that accounts for the sociotechnical system Discusses a new, systems-based, driver distraction definition Explains AcciMap analysis of the current legislation on driver distraction from technological devices Offers novel approaches to understanding why driver distraction occurs Presents a extensive framework of the causal factors that lead to distraction informed by drivers
Preface xiii
Acknowledgements xv
List of Abbreviations xvii
Authors xix
Chapter 1 Introduction 1(6)
1.1 Background
1(2)
1.2 Aim and Objectives
3(1)
1.3 Structure of the Book
4(3)
Chapter 2 Driver Distraction, Technology and the Sociotechnical Systems Approach 7(12)
2.1 Introduction
7(1)
2.2 Driver Distraction
7(9)
2.2.1 In-Vehicle Technology Developments and Driver Distraction
9(7)
2.2.1.1 Crash Statistics
12(2)
2.2.1.2 Legislation
14(1)
2.2.1.3 Design Guidelines
15(1)
2.3 The Sociotechnical Systems Approach to Accident Analysis
16(2)
2.3.1 The Sociotechnical System Approach to Driver Distraction
17(1)
2.4 Conclusion
18(1)
Chapter 3 Driver Distraction Methodology 19(22)
3.1 Introduction
19(2)
3.1.1 Driver Distraction Methodological Challenges
19(2)
3.2 Classification of Methodologies
21(12)
3.2.1 Objective Quantitative Methods: Measuring Behaviours
30(1)
3.2.2 Objective Qualitative Methods: Observing Behaviours
31(1)
3.2.3 Subjective Quantitative Methods: Measuring Opinions
31(1)
3.2.4 Subjective Qualitative Methods: Observing Opinions
32(1)
3.3 Systems Methodology and Driver Distraction
33(5)
3.4 The Way Forward
38(1)
3.5 Conclusion
39(2)
Chapter 4 Exploring the Mechanisms of Driver Distraction: The Development of the PARRC Model 41(22)
4.1 Introduction
41(5)
4.1.1 A Case of Driver Distraction
41(2)
4.1.2 What Causes Driver Distraction?
43(2)
4.1.3 Modelling the Sociotechnical System
45(1)
4.2 Methodological Approach
46(2)
4.2.1 Grounded Theory
46(2)
4.2.1.1 Document Analysis
47(1)
4.3 Results and Discussion
48(6)
4.3.1 Causal Factors
49(2)
4.3.1.1 Factor 1: Adapt to Demands
49(1)
4.3.1.2 Factor 2: Behavioural Regulation
50(1)
4.3.1.3 Factor 3: Goal Conflict
50(1)
4.3.1.4 Factor 4: Goal Prioritisation
51(1)
4.3.1.5 Factor 5: Resource Constraints
51(1)
4.3.2 Interconnections
51(3)
4.4 Application of the PARRC Model: A Case Study of Distracted Driving
54(6)
4.4.1 The Systems Approach and the PARRC Model
56(4)
4.4.1.1 Goal Conflict
57(1)
4.4.1.2 Resource Constraints
58(1)
4.4.1.3 Adapt to Demands
59(1)
4.4.1.4 Goal Priority
59(1)
4.4.1.5 Behavioural Regulation
60(1)
4.5 General Discussion
60(2)
4.5.1 Theoretical Implications
60(1)
4.5.2 Practical Implications
61(1)
4.6 Conclusion
62(1)
Chapter 5 What's the Law Got to Do with It? Legislation Regarding In-Vehicle Technology Use and Its Impact on Driver Distraction 63(26)
5.1 Introduction
63(2)
5.1.1 The Role of Legislation in the Road Transport Domain
63(2)
5.2 Method
65(5)
5.2.1 Application of the Risk Management Framework to In-Vehicle Technology Use
65(3)
5.2.2 Application of the AcciMap Analysis to In-Vehicle Technology Use
68(1)
5.2.3 AcciMap Analysis
69(1)
5.3 Results and Discussion
70(12)
5.3.1 AcciMap of Phone Use
70(5)
5.3.2 AcciMap of Other Technology Use
75(2)
5.3.3 Comparison between Mobile Phone Use AcciMap and Other Technology Use AcciMap
77(2)
5.3.4 Application to Specific Events
79(3)
5.3.4.1 Scenario 1
79(1)
5.3.4.2 Scenario 2
80(2)
5.4 General Discussion
82(5)
5.4.1 Recommendations
84(1)
5.4.2 Evaluation and Future Research
84(3)
5.5 Conclusion
87(2)
Chapter 6 Creating the Conditions for Driver Distraction: A Thematic Framework of Sociotechnical Factors 89(32)
6.1 Introduction
89(3)
6.1.1 Voluntary Distraction: Theory and Methodology
89(3)
6.1.2 Objectives
92(1)
6.2 Study 1
92(11)
6.2.1 Aim
92(1)
6.2.2 Method
92(3)
6.2.2.1 Participants
92(1)
6.2.2.2 Data Collection
93(2)
6.2.3 Data Analysis
95(3)
6.2.3.1 Inductive Thematic Coding
96(1)
6.2.3.2 Inter-Rater and Intra-Rater Reliability Assessment
97(1)
6.2.4 Results
98(3)
6.2.5 Discussion
101(2)
6.3 Study 2
103(11)
6.3.1 Aim
103(1)
6.3.2 Method
103(1)
6.3.3 Results
104(9)
6.3.3.1 Adapt to Demands
106(1)
6.3.3.2 Behavioural Regulation
106(1)
6.3.3.3 Goal Conflict
106(1)
6.3.3.4 Goal Priority
107(1)
6.3.3.5 Resource Constraints
107(1)
6.3.3.6 Interconnections
108(5)
6.3.4 Discussion
113(1)
6.4 General Discussion
114(6)
6.4.1 Recommendations to Practise
115(4)
6.4.1.1 Driver
117(1)
6.4.1.2 Infrastructure
117(1)
6.4.1.3 Task
117(1)
6.4.1.4 Context
118(1)
6.4.2 Evaluation and Future Work
119(1)
6.5 Conclusion
120(1)
Chapter 7 What Technologies Do People Use When Driving and Why? 121(26)
7.1 Introduction
121(2)
7.1.1 Factors Linked to Technology Engagement
121(2)
7.2 Method
123(3)
7.2.1 Semi-Structured Interview Study
123(1)
7.2.1.1 Interview Participants
123(1)
7.2.1.2 Interview Procedure
123(1)
7.2.2 Online Survey Study
124(1)
7.2.2.1 Online Survey Participants
124(1)
7.2.2.2 Online Survey Procedure
125(1)
7.2.3 Data Analysis
125(1)
7.3 Results and Discussion
126(14)
7.3.1 Interview and Online Survey Sample Correlation
126(1)
7.3.2 Likelihood Ratings
127(4)
7.3.2.1 Younger Age Category
128(1)
7.3.2.2 Middle Age Category
129(1)
7.3.2.3 Older Age Category
130(1)
7.3.3 Likelihood Reasoning
131(16)
7.3.3.1 Satnav
131(1)
7.3.3.2 Hands-Free Phone
132(2)
7.3.3.3 In-Vehicle Infotainment Systems
134(1)
7.3.3.4 Voice Command System
135(2)
7.3.3.5 Mobile Phone
137(2)
7.3.3.6 Road Type
139(1)
7.3.3.7 Legislation
140(1)
7.4 Implications
140(4)
7.5 Evaluation and Future Work
144(1)
7.6 Conclusion
145(2)
Chapter 8 Good Intentions? Willingness to Engage with Technology on the Road and in a Driving Simulator 147(30)
8.1 Introduction
147(4)
8.1.1 Naturalistic Decision Making
147(2)
8.1.2 Experimental Setting
149(2)
8.2 Method
151(7)
8.2.1 Participants
151(1)
8.2.2 Experimental Design
152(1)
8.2.3 Equipment
152(1)
8.2.3.1 Vehicles
152(1)
8.2.4 Procedure
153(4)
8.2.4.1 Verbal Protocol Methodology
153(1)
8.2.4.2 Task Scenarios
154(2)
8.2.4.3 Route
156(1)
8.2.4.4 NASA-TLX
156(1)
8.2.5 Data Analysis
157(1)
8.3 Results
158(13)
8.3.1 Scenario Responses
159(4)
8.3.1.1 Pre-Trial Interview
159(1)
8.3.1.2 Stated Intention
159(1)
8.3.1.3 Road Type and Task Type
160(1)
8.3.1.4 Reasons for Stated Intention
161(2)
8.3.2 Matrix Queries
163(5)
8.3.3 Driving Speed
168(2)
8.3.3.1 Mean Speed
168(2)
8.3.3.2 Speed Variability
170(1)
8.3.4 Workload
170(1)
8.4 Discussion
171(5)
8.4.1 Experimental Condition
171(1)
8.4.2 Factors Affecting Naturalistic Decision Making
171(3)
8.4.2.1 Task Type
172(1)
8.4.2.2 Road Type
173(1)
8.4.3 Using Verbal Protocol to Capture Naturalistic Decision Making
174(1)
8.4.4 Future Research
175(1)
8.5 Conclusion
176(1)
Chapter 9 Evolution of the PARRC Model of Driver Distraction: Development, Application and Validation 177(18)
9.1 Introduction
177(3)
9.2 Developing the PARRC Model
180(5)
9.2.1 Stage
1. Grounded Theory: Model Development
180(1)
9.2.2 Stage
2. AcciMap Analysis: Model Application
181(1)
9.2.3 Stage
3. Semi-Structured Interviews: Model Validation
181(1)
9.2.4 Stage
4. Driving Study: Model Validation
182(3)
9.3 A Sociotechnical Systems Definition of Driver Distraction
185(1)
9.4 Discussion
185(1)
9.5 Recommendations
186(7)
9.5.1 International Committees, National Committees and Government
187(1)
9.5.2 Regulators
188(1)
9.5.3 Industrialists
189(1)
9.5.4 Resource Providers
190(1)
9.5.5 End Users
191(1)
9.5.6 Equipment and Environment
192(1)
9.6 Conclusion
193(2)
Chapter 10 Conclusions 195(12)
10.1 Introduction
195(1)
10.2 Summary of Findings
195(4)
10.3 Future Work
199(6)
10.3.1 Theoretical Implications
200(3)
10.3.1.1 Sociotechnical Systems Theory and Definition of Driver Distraction
200(1)
10.3.1.2 Further Exploration of the PARRC Model
200(1)
10.3.1.3 Cultural Differences
200(1)
10.3.1.4 Context and Road Environment
201(1)
10.3.1.5 Automated Driving
201(2)
10.3.1.6 Applications to Other Domains
203(1)
10.3.2 Methodological Implications
203(2)
10.3.2.1 Qualitative Research
203(1)
10.3.2.2 Experimental Setting
204(1)
10.3.2.3 Eye Tracking
204(1)
10.3.3 Practical Implications
205(1)
10.3.3.1 Recommendations to Practise for Alternative Countermeasures
205(1)
10.4 Closing Remarks
205(2)
Appendix A 207(10)
Appendix B 217(4)
References 221(22)
Author Index 243(4)
Subject Index 247
Dr. Katie J. Parnell studied for her Engineering Doctorate at the University of Southampton and holds a First class BsC Psychology degree from the University of Reading. Her research interests include applying, developing and reviewing accident causation from a sociotechnical systems viewpoint. Katie is also interested in the advancements in technological interfaces and how they can be utilised safely. She has published a number of journal articles on applying the sociotechnical systems approach to the study, and mitigation of, driver distraction.

Professor Neville A. Stanton, PhD, is a Chartered Psychologist, Chartered Engineer and a Chartered Ergonomist, and holds the Chair in Human Factors in the Faculty of Engineering and the Environment at the University of Southampton. He has degrees in Psychology, Applied Psychology and Human Factors and has worked at the Universities of Aston, Brunel, Cornell and MIT. His research interests include modelling, predicting and analysing human performance in transport systems as well as designing the interfaces between humans and technology. Professor Stanton has worked on cockpit design in automobiles and aircraft over the past 25 years, working on a variety of automation projects. He has published 40 books and over 300 journal papers on Ergonomics and Human Factors, and is currently an editor of the peer-reviewed journal Ergonomics. In 1998 he was awarded the Institution of Electrical Engineers Divisional Premium Award for a co-authored paper on Engineering Psychology and System Safety. The Institution of Ergonomics and Human Factors awarded him The Otto Edholm Medal in 2001, The President¹s Medal in 2008 and The Sir Frederic Bartlett Medal in 2012 for his contribution to basic and applied ergonomics research. The Royal Aeronautical Society awarded him and his colleagues the Hodgson Prize and Bronze Medal in 2006 for research on design-induced flight-deck error published in The Aeronautical Journal. The University of Southampton has awarded him a Doctor of Science (DSc) in 2014 for his sustained contribution to the development and validation of Human Factors methods.

Dr Katherine L. Plant, BSc, PhD, is New Frontiers Fellow in Human Factors Engineering in the Transportation Research Group (TRG) within the Faculty of Engineering and the Environment at the University of Southampton, UK. She is the technical lead for aviation and road safety research within the group. In 2014 Katie was awarded the Honorable Company of Air Pilots Prize for Aviation Safety for her research exploring aeronautical critical decision making. Her primary research interests center on understanding how the interaction of the environment we work in and the mental schema that we hold influence our actions and decision-making processes. Katie is passionate about teaching Human Factors and runs the module Human Factors in Engineering, which is offered to undergraduate and MSc Engineering students across the faculty. In addition to this, Katie supervises a number of PhD, MSc and undergraduate student projects.
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