Handbook of Human Factors for Automated, Connected, and Intelligent Vehicles
Automobile crashes are the seventh leading cause of death worldwide, resulting in over 1.25 million deaths yearly. Automated, connected, and intelligent vehicles have the potential to reduce crashes significantly, while also reducing congestion, carbon emissions, and increasing accessibility. Howeve...
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| Language: | English |
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Boca Raton
CRC Press
2020
Taylor & Francis Group |
| Edition: | 1 |
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| ISBN: | 9781138035027, 1138035025, 9781138748804, 1138748803 |
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| Abstract | Automobile crashes are the seventh leading cause of death worldwide, resulting in over 1.25 million deaths yearly. Automated, connected, and intelligent vehicles have the potential to reduce crashes significantly, while also reducing congestion, carbon emissions, and increasing accessibility. However, the transition could take decades. This new handbook serves a diverse community of stakeholders, including human factors researchers, transportation engineers, regulatory agencies, automobile manufacturers, fleet operators, driving instructors, vulnerable road users, and special populations. The handbook provides information about the human driver, other road users, and human–automation interaction in a single, integrated compendium in order to ensure that automated, connected, and intelligent vehicles reach their full potential.
Features
Addresses four major transportation challenges—crashes, congestion, carbon emissions, and accessibility—from a human factors perspective
Discusses the role of the human operator relevant to the design, regulation, and evaluation of automated, connected, and intelligent vehicles
Offers a broad treatment of the critical issues and technological advances for the designing of transportation systems with the driver in mind
Presents an understanding of the human factors issues that are central to the public acceptance of these automated, connected, and intelligent vehicles
Leverages lessons from other domains in understanding human interactions with automation
Sets the stage for future research by defining the space of unexplored questions |
|---|---|
| AbstractList | Handbook of Human Factors for Automated, Connected, and Intelligent Vehicles
Subject Guide: Ergonomics & Human Factors
Automobile crashes are the seventh leading cause of death worldwide, resulting in over 1.25 million deaths yearly. Automated, connected, and intelligent vehicles have the potential to reduce crashes significantly, while also reducing congestion, carbon emissions, and increasing accessibility. However, the transition could take decades. This new handbook serves a diverse community of stakeholders, including human factors researchers, transportation engineers, regulatory agencies, automobile manufacturers, fleet operators, driving instructors, vulnerable road users, and special populations. It provides information about the human driver, other road users, and human–automation interaction in a single, integrated compendium in order to ensure that automated, connected, and intelligent vehicles reach their full potential.
Features
Addresses four major transportation challenges—crashes, congestion, carbon emissions, and accessibility—from a human factors perspective
Discusses the role of the human operator relevant to the design, regulation, and evaluation of automated, connected, and intelligent vehicles
Offers a broad treatment of the critical issues and technological advances for the designing of transportation systems with the driver in mind
Presents an understanding of the human factors issues that are central to the public acceptance of these automated, connected, and intelligent vehicles
Leverages lessons from other domains in understanding human interactions with automation
Sets the stage for future research by defining the space of unexplored questions
Donald L. Fisher is a Principal Technical Advisor at the Volpe National Transportation Systems Center in Cambridge, MA, a Professor Emeritus and Research Professor in the Department of Mechanical and Industrial Engineering at the University of Massachusetts Amherst, and the Director of the Arbella Insurance Human Performance Laboratory in the College of Engineering. He has published over 250 technical papers, including recent ones in the major journals in transportation, human factors, and psychology. While at the Volpe Center he has worked extensively across the modes on research designed to identify the unintended consequences of automation and, when such are identified, to develop and evaluate countermeasures. Additionally, he has developed a broad, interdisciplinary approach to understanding and remediating functional impairments in transportation, including distraction, fatigue, and alcohol. While at UMass Amherst, he served as a principal or co-principal investigator on over 30 million dollars of research and training grants, including awards from the National Science Foundation, the National Institutes of Health, the National Highway Traffic Safety Administration, MassDOT, the Arbella Insurance Group Charitable Foundation, the State Farm Mutual Automobile Insurance Company, and the New England University Transportation Center. He is a former Associate Editor of Human Factors and editor of both the recently published Handbook of Driving Simulation for Engineering, Medicine and Psychology (2011) and the Handbook of Teen and Novice Drivers (2016). He currently is a co-chair of the TRB Committee on Simulation and Measurement of Vehicle and Operator Performance. He has chaired or co-chaired a number of TRB workshops and served as a member of the National Academy of Sciences Human Factors Committee, the TRB Younger Driver Subcommittee, the joint National Research Council and Institute of Medicine Committee on the Contributions from the Behavioral and Social Sciences in Reducing and Preventing Teen Motor Crashes, and the State Farm® Mutual Automobile Insurance Company and Children’s Hospital of Philadelphia Youthful Driver Initiative. Over the past 25 years, Dr. Fisher has made fundamental contributions to the understanding of driving, including the identification of those factors that: the determine how most safely to transfer control from an automated vehicle to the driver; increase the crash risk of novice and older drivers; impact the effectiveness of signs, signals, and pavement markings; improve the interface to in-vehicle equipment, such as forward collision warning systems, back over collision warning systems, and music retrieval systems; and influence drivers’ understanding of advanced parking management systems, advanced traveler information systems, and dynamic message signs. In addition, he has pioneered the development of both PC-based hazard anticipation training (RAPT) and PC-based attention maintenance training (FOCAL) programs, showing that novice drivers so trained actually anticipate hazards more often and maintain attention better on the open road and in a driving simulator. This program of research has been made possible by the acquisition in 1994 of more than half a million dollars of equipment, supported in part by a grant from the National Science Foundation. He has often spoken about his results, including participating in a congressional science briefing on the novice driver research sponsored several years previous. The Human Performance Laboratory was recognized by the Ergonomics Society, receiving the best paper award for articles that appeared in the journal Ergonomics throughout 2009. The paper described the work in the Human Performance Laboratory on hazard anticipation. Most recently, he published with his Volpe colleagues a review of human factors issues critical to the development of intelligent vehicles in the inaugural volume of IEEE Transactions on Intelligent Vehicles . Dr. Fisher received an AB from Bowdoin College in 1971 (philosophy), an EdM from Harvard University in 1973 (human development), and a PhD from the University of Michigan in 1982 (mathematical psychology).
William J. Horrey , PhD, is the traffic research group leader at the AAA Foundation for Traffic Safety. Previously, he was a principal research scientist in the Center for Behavioral Sciences at the Liberty Mutual Research Institute for Safety. He earned his PhD in engineering psychology from the University of Illinois at Urbana–Champaign in 2005. He has published over 50 papers on numerous topics including visual (selective) and divided attention, automation, driver behavior, and distractions from in-vehicle devices. He chairs the Transportation Research Board Standing Committee on Vehicle User Characteristics (AND10) and the Publications Division at the Human Factors and Ergonomics Society. He is an Associate Editor of the Human Factors Journal and has served on several national and international committees related to transportation safety and human factors.
John D. Lee , PhD, is the Emerson Electric professor in the Department of Industrial and Systems Engineering at the University of Wisconsin, Madison and director of the Cognitive Systems Laboratory. Dr Lee’s research seeks to better integrate people and technology in complex systems, such as cars, semi-autonomous systems, and telemedicine. His research has led to over 400 publications and presentations, including 13 books. He helped to edit The Oxford Handbook of Cognitive Engineering, the Handbook of Driving Simulation for Engineering, Medicine, and Psychology, and two books on distraction Driver Distraction: Theory, Effects, and Mitigation and Driver Distraction and Inattention. He is also the lead author of a popular textbook: Designing for People: An introduction to Human Factors Engineering.
Michael A. Regan , is Professor of Human Factors with the Research Centre for Integrated Transport Innovation at the University of New South Wales in Sydney, Australia. He has BSc (Hons) and PhD degrees in engineering psychology from the Australian National University and has designed and led more than 200 research projects in transportation human factors and safety -spanning aircraft, motorcycles, cars, trucks, buses, and trains. Mike is the author/co-author of around 200 peer-reviewed publications, including three books on driver distraction and inattention, and driver acceptance of new technologies. He was the 25th President of the Human Factors and Ergonomics Society of Australia and is a Fellow of the Australasian College of Road Safety.
Preface. Editors. Contributors. 1. Introduction. 2. Automated Driving: Decades of Research and Development Leading to Today’s Commercial Systems. 3. Driver’s Mental Model of Vehicle Automation. 4. Driver Trust in Automated, Connected, and Intelligent Vehicles. 5. Public Opinion About Automated and Self-Driving Vehicles: An International Review. 6. Workload, Distraction, and Automation. 7. Situation Awareness in Driving. 8. Allocation of Function to Humans and Automation and the Transfer of Control. 9. Driver Fitness in the Resumption of Control. 10. Driver Capabilities in the Resumption of Control. 11. Driver State Monitoring for Decreased Fitness to Drive. 12. Behavioral Adaptation. 13. Distributed Situation Awareness and Vehicle Automation: Case Study Analysis and Design Implications. 14. Human Factors Considerations in Preparing Policy and Regulation for Automated Vehicles. 15. HMI Design for Automated, Connected, and Intelligent Vehicles. 16. Human–Machine Interface Design for Fitness-Impaired Populations. 17. Automated Vehicle Design for People with Disabilities. 18. Importance of Training for Automated, Connected, and Intelligent Vehicle Systems. 19. Connected Vehicles in a Connected World: A Sociotechnical Systems Perspective. 20. Congestion and Carbon Emissions. 21. Automation Lessons from Other Domains. 22. HF Considerations When Testing and Evaluation ACIVs. 23. Techniques for Making Sense of Behavior in Complex Datasets. 24. Future Research Needs and Conclusions. Automobile crashes are the seventh leading cause of death worldwide, resulting in over 1.25 million deaths yearly. Automated, connected, and intelligent vehicles have the potential to reduce crashes significantly, while also reducing congestion, carbon emissions, and increasing accessibility. However, the transition could take decades. This new handbook serves a diverse community of stakeholders, including human factors researchers, transportation engineers, regulatory agencies, automobile manufacturers, fleet operators, driving instructors, vulnerable road users, and special populations. The handbook provides information about the human driver, other road users, and human–automation interaction in a single, integrated compendium in order to ensure that automated, connected, and intelligent vehicles reach their full potential. Features Addresses four major transportation challenges—crashes, congestion, carbon emissions, and accessibility—from a human factors perspective Discusses the role of the human operator relevant to the design, regulation, and evaluation of automated, connected, and intelligent vehicles Offers a broad treatment of the critical issues and technological advances for the designing of transportation systems with the driver in mind Presents an understanding of the human factors issues that are central to the public acceptance of these automated, connected, and intelligent vehicles Leverages lessons from other domains in understanding human interactions with automation Sets the stage for future research by defining the space of unexplored questions This new handbook provides both ordinary and vulnerable road users the information about the human driver that they need in a single, integrated compendium in order to ensure that automated, connected and intelligent vehicles reach their full potential of reduced crashes, congestion, and carbon emissions. Handbook of Human Factors for Automated, Connected, and Intelligent Vehicles Subject Guide: Ergonomics & Human Factors Automobile crashes are the seventh leading cause of death worldwide, resulting in over 1.25 million deaths yearly. Automated, connected, and intelligent vehicles have the potential to reduce crashes significantly, while also reducing congestion, carbon emissions, and increasing accessibility. However, the transition could take decades. This new handbook serves a diverse community of stakeholders, including human factors researchers, transportation engineers, regulatory agencies, automobile manufacturers, fleet operators, driving instructors, vulnerable road users, and special populations. It provides information about the human driver, other road users, and human-automation interaction in a single, integrated compendium in order to ensure that automated, connected, and intelligent vehicles reach their full potential. Features Addresses four major transportation challenges-crashes, congestion, carbon emissions, and accessibility-from a human factors perspective Discusses the role of the human operator relevant to the design, regulation, and evaluation of automated, connected, and intelligent vehicles Offers a broad treatment of the critical issues and technological advances for the designing of transportation systems with the driver in mind Presents an understanding of the human factors issues that are central to the public acceptance of these automated, connected, and intelligent vehicles Leverages lessons from other domains in understanding human interactions with automation Sets the stage for future research by defining the space of unexplored questions |
| Author | Donald L. Fisher John D. Lee William J. Horrey Michael A. Regan |
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| Copyright | 2020 Taylor & Francis Group, LLC |
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| Editor | Lee, John D. Horrey, William J. Regan, Michael A. Fisher, Donald L. |
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| Keywords | Driving Simulator ADAS System Vice Versa Driver’s Mental Model Driver Distraction SA Driving Task Driver Drowsiness SA Global Assessment Technique HMI Designer High Fidelity Driving Simulator Vehicle Automation Driver’s SA Automated Driving Systems Acc Lead Vehicle SA Requirement Non-driving Tasks Active Safety Systems Automated Driving Driver State Monitoring Situation Awareness Requirements Situation Awareness Adaptive Automation Electronic Stability Control |
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| Notes | Other editors: William J. Horrey, John D. Lee, Michael A. Regan Includes bibliographical references and index |
| OCLC | 1157090588 |
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| Snippet | Automobile crashes are the seventh leading cause of death worldwide, resulting in over 1.25 million deaths yearly. Automated, connected, and intelligent... Handbook of Human Factors for Automated, Connected, and Intelligent Vehicles Subject Guide: Ergonomics & Human Factors Automobile crashes are the seventh... This new handbook provides both ordinary and vulnerable road users the information about the human driver that they need in a single, integrated compendium in... |
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| SubjectTerms | AEB Automated Systems automated vehicles Automatic control Automatic Emergency Braking Systems Automobile driving Automobile driving -- Human factors Automobiles Automobiles -- Automatic control Automotive Technology & Engineering carbon emissions connected vehicles Driver assistance systems Driver State Driver-Vehicle Interfaces ENGnetBASE ERGONOMICSnetBASE GENERALENGINEERINGnetBASE Human Computer Interaction Human factors intelligent vehicles MechanicalEngineeringnetBASE SCI-TECHnetBASE STMnetBASE Systems & Control Engineering traffic congestion Traffic safety Traffic safety -- Technological innovations Transfer of Control |
| TableOfContents | 9.2.1.3 Effects of Automation on Distraction -- 9.2.1.4 Effects of Distraction on Driver-Automation Coordination -- 9.2.2 Detection -- 9.2.3 Remediation -- 9.3 Sleepiness -- 9.3.1 Definitions and Effects -- 9.3.1.1 What Is Sleepiness? -- 9.3.1.2 Potential Sources of Sleepiness and Their Effects on Non-Automated Driving -- 9.3.1.3 Effects of Automation on Sleepiness -- 9.3.1.4 Effects of Sleepiness on Driver-Automation Coordination -- 9.3.2 Detection -- 9.3.2.1 Detecting and Predicting Sleepiness -- 9.3.2.2 Detecting and Predicting Microsleeps -- 9.3.2.3 Detecting and Predicting Sleep -- 9.3.3 Remediation -- 9.3.3.1 Technologies and Practices: Opportunities to Develop, Test, and Implement Solutions -- 9.3.3.2 Gaps in Knowledge and Related Opportunities -- 9.4 Alcohol and Other Drugs (AOD) -- 9.4.1 Definitions and Effects -- 9.4.1.1 Alcohol Prevalence and Crash Risk -- 9.4.1.2 Other Drugs Prevalence and Crash Risk -- 9.4.1.3 Prevalence vs. Impairment -- 9.4.1.4 Varying Drug Impairing Behaviors -- 9.4.1.5 Effects of Automation on AOD-Impaired Driving -- 9.4.1.6 Effects of AOD-Impaired Driving on Driver-Automation Coordination -- 9.4.2 Detection -- 9.4.2.1 Alcohol Breath Testers and Sensors, Alcohol-Ignition Interlocks, and DADSS -- 9.4.2.2 Breathalyzers for Drugs Other than Alcohol -- 9.4.2.3 Transdermal Sensors and Other Biosensors for Alcohol and Drug Detection -- 9.4.2.4 Behavioral Indicators for AOD-Impaired Driving -- 9.4.3 Remediation -- 9.5 Motion Sickness -- 9.5.1 Definitions and Effects -- 9.5.1.1 What Is Motion Sickness and What Are Its Symptoms? -- 9.5.1.2 Contributors to Motion Sickness Experienced by Drivers of Automated Vehicles -- 9.5.1.3 Effects of Motion Sickness on Drivers of Automated Vehicles -- 9.5.2 Detection -- 9.5.2.1 Self-Report Measures -- 9.5.2.2 Other Measures -- 9.5.3 Remediation -- 9.6 Conclusion -- Acknowledgments Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Editors -- Contributors -- Chapter 1 Introduction -- Key Points -- 1.1 Background -- 1.2 Definitions -- 1.2.1 Levels of Automation and Active Safety Systems -- 1.2.1.1 Levels of Automation -- 1.2.1.2 Active Safety Systems -- 1.2.2 Automated, Connected, and Intelligent Vehicles -- 1.2.2.1 Automated Vehicles -- 1.2.2.2 Connected Vehicles -- 1.2.2.3 Intelligent Vehicles -- 1.2.3 Operational Design Domain -- 1.3 The Handbook: A Quick Guide -- 1.3.1 The State of the Art: ACIVs (Chapter 2) -- 1.3.2 Issues in the Deployment of ACIVs (Problems) -- 1.3.2.1 Driver's Mental Model of Vehicle Automation (Chapter 3) -- 1.3.2.2 Driver Trust in ACIVs (Chapter 4) -- 1.3.2.3 Public Opinion about ACIVs (Chapter 5) -- 1.3.2.4 Workload, Distraction, and Automation (Chapter 6) -- 1.3.2.5 Situation Awareness in Driving (Chapter 7) -- 1.3.2.6 Allocation of Function to Humans and Automation and the Transfer of Control (Chapter 8) -- 1.3.2.7 Driver Fitness in the Resumption of Control (Chapter 9) -- 1.3.2.8 Driver Capabilities in the Resumption of Control (Chapter 10) -- 1.3.2.9 Driver State Monitoring for Decreased Fitness to Drive (Chapter 11) -- 1.3.2.10 Behavioral Adaptation (Chapter 12) -- 1.3.2.11 Distributed Situation Awareness (Chapter 13) -- 1.3.2.12 Human Factors Issues in the Regulation of Deployment (Chapter 14) -- 1.3.3 Human-Centered Design of ACIVs (Solutions) -- 1.3.3.1 HMI Design for ACIVs (Chapter 15) -- 1.3.3.2 HMI Design for Fitness Impaired Populations (Chapter 16) -- 1.3.3.3 Automated Vehicle Design for People with Disabilities (Chapter 17) -- 1.3.3.4 Importance of Training for ACIVs (Chapter 18) -- 1.3.4 Special Topics -- 1.3.4.1 Connected Vehicles in a Connected World: A Sociotechnical Systems Perspective (Chapter 19) 6.3 Types of Automation and Workload Implications -- 6.3.1 Effect of Different Levels of Automation on Workload -- 6.3.2 The Interaction of Distraction, Workload, and Automation -- 6.3.2.1 Automation Creating Distraction Directly -- 6.3.2.2 Automation Creating Distraction Indirectly -- 6.3.2.3 The Interaction of Other Mechanisms of Inattention, Workload, and Automation -- 6.3.3 Summary -- 6.4 Managing Workload and Distraction in Automated Vehicles -- 6.5 Conclusion -- References -- Chapter 7 Situation Awareness in Driving -- Key Points -- 7.1 Introduction -- 7.2 SA Requirements for Driving -- 7.3 SA Model -- 7.3.1 Individual Factors -- 7.3.1.1 Limited Attention -- 7.3.1.2 Limited Working Memory -- 7.3.1.3 Goal-Driven Processing Alternating with Data-Driven Processing -- 7.3.1.4 Long-Term Memory Stores -- 7.3.1.5 Expertise -- 7.3.1.6 Cognitive Automaticity -- 7.3.2 Vehicle and Driving Environment -- 7.3.2.1 Information Salience -- 7.3.2.2 Complexity -- 7.3.2.3 Workload, Fatigue, and Other Stressors -- 7.3.2.4 Distraction and Technology -- 7.3.3 Automation and Vehicle Design -- 7.4 Conclusions -- References -- Chapter 8 Allocation of Function to Humans and Automation and the Transfer of Control -- Key Points -- 8.1 Introduction -- 8.2 Defining FA -- 8.2.1 Allocating Responsibility -- 8.2.2 Allocating Authority to Take Responsibility for a Function -- 8.3 Defining the Driving Task: How Automation Changes FA -- 8.4 The Can and Why of Allocating Functions -- 8.5 The Consequences of Inappropriate FA -- 8.6 Transfer of FA in AVs -- 8.7 Summary and Conclusions -- References -- Chapter 9 Driver Fitness in the Resumption of Control -- Key Points -- 9.1 Introduction -- 9.2 Distraction -- 9.2.1 Definitions and Effects -- 9.2.1.1 What Is Driver Distraction? -- 9.2.1.2 Potential Sources of Distraction and Their Effects on Non-Automated Driving 1.3.4.2 Congestion and Carbon Emissions (Chapter 20) -- 1.3.4.3 Automation Lessons from Other Domains (Chapter 21) -- 1.3.5 Evaluation of ACIVs -- 1.3.5.1 Human Factors Considerations in Testing and Evaluating ACIVs (Chapter 22) -- 1.3.5.2 Techniques for Making Sense of Behavior in Complex Datasets (Chapter 23) -- 1.4 Conclusion -- Acknowledgments -- References -- Chapter 2 Automated Driving: Decades of Research and Development Leading to Today's Commercial Systems -- Key Points -- 2.1 Introduction -- 2.1.1 Automated Driving: From Vision to the Launch of a New Industry in 70 Years -- 2.1.2 Advent of Active Safety Systems -- 2.1.3 Addressing Safe Testing and Deployment of Automated Driving -- 2.1.4 Pursuit of Nascent "Holy Grails" -- 2.2 Distinctions within SAE Levels of Automation -- 2.3 Automated Driving: Technology Basis -- 2.3.1 Understanding the World to Make Proper Driving Decisions -- 2.3.2 Perception, Mapping, and Localization -- 2.3.3 Motion Planning and Control -- 2.3.4 Artificial Intelligence -- 2.3.5 Off-Board Information Sources -- 2.3.6 Driver Monitoring as Key to Safety Case -- 2.3.7 Behavioral Competencies and Remote Support -- 2.3.8 Design and Test Processes to Ensure Safety -- 2.3.8.1 Functional Safety -- 2.3.8.2 Cybersecurity -- 2.3.8.3 ADS Validation Processes -- 2.4 Automated Driving Commercial Development and Deployment -- 2.4.1 Automated Fleet Services for Freight and Parcels -- 2.4.2 Automated Fleet Services for People -- 2.4.3 Private Ownership: Automation Features in Mass-Market Passenger Cars -- 2.5 Regulatory Considerations -- 2.6 Going Forward: ADS Implications for Human Factors -- References -- Chapter 3 Driver's Mental Model of Vehicle Automation -- Key Points -- 3.1 Importance and Relevance of Mental Models in Driving and Automation -- 3.2 Defining Mental Models -- 3.3 Mental Models under Uncertainty References 3.4 General and Applied Mental Models -- 3.5 Measurement of General and Applied Mental Models -- 3.6 Supporting Accurate and Complete Mental Models -- 3.7 Conclusion -- References -- Chapter 4 Driver Trust in Automated, Connected, and Intelligent Vehicles -- Key Points -- 4.1 Introduction -- 4.2 Trust and Types of Automation -- 4.3 Definition and Mechanisms Underlying Trust -- 4.4 Promoting Appropriate Trust in Vehicle Automation -- 4.4.1 Calibration and Resolution of Trust -- 4.4.2 Trustable Automation: Create Simple Use Situations and Automation Structure -- 4.4.3 Trustable Automation: Display Surface and Depth Indications of Capability -- 4.4.4 Trustable Automation: Enable Directable Automation and Trust Repair -- 4.4.5 Trustworthy Automation and Goal Alignment -- 4.5 Trust and Acceptance of Vehicle Technology -- 4.6 Ethical Considerations and the Teleology of Technology -- 4.7 Conclusion -- Acknowledgements -- References -- Chapter 5 Public Opinion About Automated and Self-Driving Vehicles: An International Review -- Key Points -- 5.1 Introduction -- 5.2 Overall Acceptability -- 5.2.1 Perceived Benefits -- 5.2.2 Perceived Concerns -- 5.2.3 Activities When Riding in an AV -- 5.3 Public Opinion Towards AVs as a Function of Sociodemographic Characteristics -- 5.4 Country Differences in Public Opinion Towards AVs -- 5.5 WTP for AVs -- 5.6 Acceptance of AVs after Experiencing the Technology -- 5.7 Conclusion -- Acknowledgement -- References -- Chapter 6 Workload, Distraction, and Automation -- Key Points -- 6.1 Introduction -- 6.2 Workload, Distraction, and Performance -- 6.2.1 Workload -- 6.2.1.1 Workload and the Yerkes-Dodson Law -- 6.2.1.2 Active Workload Management -- 6.2.2 Distraction -- 6.2.2.1 Distraction and Types of Inattention -- 6.2.2.2 The Process of Driver Distraction -- 6.2.3 Driver Workload and Driver Distraction -- 6.2.4 Summary |
| Title | Handbook of Human Factors for Automated, Connected, and Intelligent Vehicles |
| URI | https://www.taylorfrancis.com/books/9781315269689 https://www.taylorfrancis.com/books/9781351979801 https://cir.nii.ac.jp/crid/1130010301140866970 https://ebookcentral.proquest.com/lib/[SITE_ID]/detail.action?docID=6214809 https://www.vlebooks.com/vleweb/product/openreader?id=none&isbn=9781351979818 |
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