Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Preface
Acknowledgements
Editors
Contributors
Abbreviations
Part I: Modelling
Chapter 1 UCEID – The Best of Both Worlds: Combining Ecological Interface Design with User-Centred Design in a Novel Human Factors Method Applied to Automated Driving
1.1 Introduction
1.1.1 Why Use UCEID?
1.2 The UCEID Method
1.2.1 Literature Review
1.2.2 Data Collection
1.2.3 Thematic Analysis
1.2.4 Cognitive Work Analysis
1.2.5 Consolidation and Ideas Generation
1.2.6 Filtering and Checking
1.3 Methodological Considerations
1.3.1 Advantages
1.3.2 Disadvantages
1.3.3 Training and Application Time
1.3.4 Tools
1.4 Summary
Acknowledgements
References
Chapter 2 Using UCEID to Include the Excluded: An Autonomous Vehicle HMI Inclusive Design Case Study
2.1 Introduction
2.1.1 This Case Study: Designing an HMI for Level 3/ 4 Autonomous Car Takeover
2.1.1.1 Ageing Population
2.1.1.2 Ageing and Capability Impairment
2.1.1.3 Ageing and Digital Technological Interface Capability
2.1.1.4 Inclusive Design
2.2 Approach and Activities
2.2.1 Overview of Explore and Evaluate Stage
2.2.2 Evaluate Activity: Generation and Processing of Requirements – Method
2.2.3 Evaluate Activity: Generation and Processing of Needs Lists – Results
2.2.4 Create Activity: Design Workshop 1
2.2.4.1 Input
2.2.4.2 Activity
2.2.4.3 Results
2.2.5 Create Activity: Iterative Design Development
2.2.6 Evaluate Activity: Testing with Experts and Users – Overview
2.2.7 Create Activity: Design Workshop 2
2.2.7.1 Input
2.2.7.2 Outputs
2.2.8 Create Activity: Final Concepts and Refinement
2.3 Discussion and Conclusions
Acknowledgements
References
Chapter 3 Designing Autonomy in Cars: A Survey and Two Focus Groups on Driving Habits of an Inclusive User Group, and Group Attitudes towards Autonomous Cars
3.1 Introduction
3.2 Related Work
3.2.1 User Views
3.2.2 Inclusiveness
3.3 Survey
3.3.1 Description
3.3.2 Results
3.4 Focus Groups
3.4.1 Description
3.4.2 Results
3.5 Discussion
3.6 Conclusions
Acknowledgements
References
Part II: Lo-Fi and Hi-Fi Simulators
Chapter 4 An Evaluation of Inclusive Dialogue-Based Interfaces for the Takeover of Control in Autonomous Cars
4.1 Introduction
4.1.1 Dialogue-Based Interfaces Designed
4.2 Experiment
4.2.1 Participants
4.2.2 Equipment
4.2.3 Procedure
4.2.4 Results
4.3 Discussion
4.4 Conclusions
Acknowledgements
References
Chapter 5 The Design of Takeover Requests in Autonomous Vehicles: Low-Fidelity Studies
5.1 Introduction
5.1.1 Inclusive Design
5.1.2 Background and Motivation
5.1.3 The UCEID: Project Design Context
5.1.4 Theoretical Background
5.1.5 Definition of the Scenario, Aims, and Boundaries of Analysis
5.1.6 Initial Data Collection: Experts’ Semi-structured Interview
5.1.6.1 Technology Analysis and Benchmarking
5.1.6.2 Thematic Analysis 1
5.1.6.3 Focus Groups
5.1.6.4 Thematic Analysis 2
5.1.6.5 Preferences and User Themes Interpreted
5.1.6.6 Work Domain Analysis ( WDA) Abstraction Hierarchy
5.1.6.7 Control Task Analysis
5.1.6.8 Social Organisation and Cooperation Analysis
5.1.6.9 Design Workshop
5.1.6.10 Concept Refinement and Filtering
5.2 The Design and Formative Development Process
5.2.1 Automotive Takeover Requests ( TORs)
5.2.1.1 TOR Timing
5.2.1.2 TOR Interfaces
5.2.2 The Design Concepts
5.3 The Summative Trials
5.3.1 Experiment 1
5.3.1.1 Trials
5.3.1.2 Results
5.3.1.3 Discussion: Experiment 1
5.3.1.4 Conclusion
5.3.2 Experiment 2
5.3.2.1 Trials
5.3.2.2 Results
5.3.2.3 Discussion: Experiment 2
5.4 Conclusions
Acknowledgements
References
Chapter 6 How Was It for You? Comparing How Different Levels of Multimodal Situation Awareness Feedback Are Experienced by Human Agents during Transfer of Control of the Driving Task in a Semi-Autonomous Vehicle
6.1 Introduction
6.2 Method
6.2.1 Participants and Study Design
6.2.2 Equipment
6.2.3 Procedure
6.2.4 Method of Analysis
6.3 Results and Discussion
6.3.1 Workload
6.3.2 Usability
6.4 Conclusion
Acknowledgements
References
Chapter 7 Human Driver Post-Takeover Driving Performance in Highly Automated Vehicles
7.1 Introduction
7.2 Method
7.2.1 Participants
7.2.2 Experimental Design
7.2.3 Equipment
7.2.4 Procedure
7.2.5 Analysis
7.3 Results
7.3.1 Speed
7.3.2 Steering
7.3.3 Lane Deviation
7.4 Discussion
7.5 Conclusion
Acknowledgements
References
Chapter 8 Validating Operator Event Sequence Diagrams: The Case of Automated Vehicle-to-Human Driver Takeovers
8.1 Introduction
8.1.1 OESD Development
8.2 Study 1 – Validation of OESD-Modelled Driver Behaviour in a Lower-Fidelity Driving Simulator
8.2.1 Method
8.2.1.1 Participants
8.2.1.2 Experimental Design
8.2.1.3 Equipment
8.2.1.4 Procedure
8.2.1.5 Analysis
8.2.1.6 Inter-Rater Reliability Method
8.2.2 Results
8.3 Study 2 – Validation of OESD-Modelled Driver Behaviour in a Higher-Fidelity Driving Simulator
8.3.1 Method
8.3.1.1 Participants
8.3.1.2 Experimental Design
8.3.1.3 Equipment
8.3.1.4 Procedure
8.3.1.5 Analysis
8.3.2 Results
8.4 Discussion
8.5 Conclusions
Acknowledgements
References
Part III: Benchmarking
Chapter 9 Breaking the Cycle of Frustration: Applying Neisser’s Perceptual Cycle Model to Drivers of Semi-Autonomous Vehicles
9.1 Introduction
9.1.1 The Perceptual Cycle Model
9.2 Method
9.2.1 Participants
9.2.2 Equipment
9.2.3 Procedure
9.2.4 Data Analysis
9.3 Results and Discussion: Three Case Studies of Driver Frustration
9.3.1 Case Study 1: ‘ That was scary ….’ – The Risk of an Inappropriate Schema
9.3.1.1 Evidence of Counter Cycle in Case Study 1
9.3.2 Case Study 2: ‘ Oh, I’ve just done the Distronic again ….’ – Impeding Intended Actions
9.3.2.1 Evidence of Counter Cycle in Case Study 2
9.3.3 Case Study 3: ‘ I think it’s green now, … no it’s not!’ – Ineffective World Information
9.3.3.1 Evidence of Counter Cycle in Case Study 3
9.3.4 Implications for Interaction Design
9.3.5 Evaluation of Applying PCM to On-Road Concurrent VP Dialogue
9.4 Conclusions
Acknowledgements
References
Chapter 10 Semi-Automated Driving Has Higher Workload and Is Less Acceptable to Drivers than Manual Vehicles: An On-Road Comparison of Three Contemporary SAE Level 2 Vehicles
10.1 Introduction
10.1.1 Research Gap and Aim
10.2 Method
10.2.1 Experiment Design
10.2.2 Participants
10.2.3 Procedure
10.2.4 Data Analysis
10.3 Results and Discussions
10.3.1 Comparisons between Manual and Automated Driving
10.3.2 The Effects of Complexity in the Driving Condition
10.3.3 The Effects of Drivers’ Prior Experience
10.3.4 Qualitative Investigation of Instances Which May Have Influenced Drivers’ Workload and Acceptance in Automated Driving
10.3.5 Considerations for Designing Driver–Autonomous Vehicle Interaction in Highway Environment
10.3.6 Considerations for Designing Driver–Autonomous Vehicle Interaction in Urban Environment
10.3.7 Recommendations for Designing Driver–Autonomous Vehicle Interaction
10.3.8 Overall Summary
10.4 Conclusions
Acknowledgements
References
Chapter 11 The Iconography of Vehicle A utomation – A Focus Group Study
11.1 Introduction
11.2 Method
11.2.1 Participants
11.2.2 Design
11.2.3 Equipment
11.2.4 Procedure
11.2.5 Method of Analysis
11.3 Results
11.3.1 Exercise One
11.3.1.1 Icons Indicating Automation Mode Active
11.3.1.2 Icons Indicating Manual Mode or Automation Ending/ Inactive
11.3.1.3 Colour
11.3.1.4 Size and Text Labels
11.3.2 Exercise Two
11.3.3 Exercise Three
11.3.3.1 ADAS Experience
11.4 Discussion
11.5 Conclusion
Acknowledgements
References
Part IV: HMI Simulator
Chapter 12 Customisation of Takeover Guidance in Semi-Autonomous Vehicles
12.1 Introduction
12.2 Method
12.2.1 Participants
12.2.2 Experimental Design
12.2.3 Equipment
12.2.4 HMI Design and Customisation
12.2.5 Procedure
12.2.6 Analysis
12.3 Results
12.3.1 Speed
12.3.2 Throttle
12.3.3 Lane Position
12.3.4 Steering Angle
12.3.5 Takeover Time
12.4 Discussion
12.4.1 Speed and Throttle
12.4.2 Lane Position and Steering Angle
12.4.3 Takeover Time
12.4.4 Limitations
12.5 Conclusions
Acknowledgements
References
Chapter 13 Effects of Interface Customisation on Drivers’ Takeover Experience in Highly Automated Driving
13.1 Introduction
13.1.1 Driver Experience during Takeover
13.1.2 Related Work
13.2 Method
13.2.1 Participants
13.2.2 Experimental Design
13.2.3 Equipment
13.2.4 HMI Design and Customisation
13.2.5 Procedure
13.2.6 Analysis
13.2.6.1 Workload
13.2.6.2 Usability
13.2.6.3 Acceptance
13.2.6.4 Trust
13.2.6.5 Data Analysis
13.3 Results and Discussions
13.3.1 Workload
13.3.2 Usability
13.3.3 Acceptance
13.3.4 Trust
13.4 Conclusion
Acknowledgements
References
Chapter 14 Accommodating Drivers’ Preferences Using a Customised Takeover Interface
14.1 Introduction
14.1.1 User-Tailorable Interfaces
14.1.2 Purpose
14.2 Method
14.2.1 Equipment and Driving Simulator
14.2.2 Study Interface Design
14.2.3 Selectable Customisation Settings
14.2.4 Experimental Design
14.2.5 Procedure
14.2.5.1 Pre-Trial
14.2.5.2 Trial
14.2.5.3 Post-Trial
14.2.6 Hypotheses
14.2.6.1 Hypothesis 1
14.2.6.2 Hypothesis 2
14.2.6.3 Hypothesis 3
14.2.6.4 Hypothesis 4
14.2.7 Data Analysis
14.2.7.1 Binary Settings
14.2.7.2 Ordinal Settings and Takeover Time
14.2.7.3 Cluster Analysis
14.2.7.4 Post-Task Questionnaire
14.2.8 Participants
14.3 Results
14.3.1 Customisation Settings
14.3.1.1 Binary
14.3.1.2 Ordinal
14.3.1.3 Cluster Analyses
14.3.2 Takeover Time
14.3.3 Post-Task Questionnaire
14.4 Discussion
14.4.1 Hypotheses
14.4.2 Driver Experience
14.4.3 Limitations of the Study
14.5 Conclusion and Future Work
Acknowledgements
References
Chapter 15 Modelling Automation–Human Driver Interactions in Vehicle Takeovers Using OESDs
15.1 Introduction
15.1.1 Development of the OESD for Automation–Human Driver Takeover
15.1.2 Validation of Methods
15.2 Methods
15.2.1 Participants
15.2.2 Study Design
15.2.3 Equipment
15.2.4 Procedure
15.2.5 Data Reduction and Analysis
15.3 Results
15.4 Discussion
15.5 Conclusions
Acknowledgement
References
Chapter 16 Feedback in Highly Automated Vehicles: What Do Drivers Rely on in Simulated and Real-World Environments?
16.1 Introduction
16.1.1 Challenges of Customisable Interfaces
16.1.2 What is Reliance?
16.1.3 Measuring Reliance
16.1.4 Development of a New Reliance Scale
16.2 Experiment 1 – Simulator Study
16.2.1 Method
16.2.1.1 Participants
16.2.1.2 Design
16.2.1.3 Apparatus
16.2.1.4 Procedure
16.2.2 Method of Analysis
16.2.3 Results
16.3 Experiment 2 – On-Road Study
16.3.1 Method
16.3.1.1 Participants
16.3.1.2 Design
16.3.1.3 Apparatus
16.3.1.4 Procedure
16.3.2 Method of Analysis
16.3.3 Results
16.4 Discussion
16.5 Conclusion
Acknowledgements
References
Part V: On-Road and Design Guidelines
Chapter 17 Can Allowing Interface Customisation Increase Driver Confidence and Safety Levels in Automated Vehicle TORs?
17.1 Introduction
17.2 Method
17.2.1 Participants
17.2.2 Experimental Design
17.2.3 Equipment
17.2.4 Procedure
17.3 Analysis
17.4 Results
17.4.1 Throttle
17.4.2 Speed
17.4.3 Longitudinal Acceleration
17.4.4 Steering Angle
17.4.5 Steering Speed
17.4.6 Lateral Acceleration
17.4.7 Takeover Protocol Time
17.4.8 Takeover Reaction Time
17.5 Discussion
17.6 Conclusions
Acknowledgements
References
Chapter 18 Effects of Customisable HMI on Subjective Evaluation of Takeover Experience on the Road
18.1 Introduction
18.2 Method
18.2.1 Participants
18.2.2 Experimental Design
18.2.3 Equipment
18.2.4 Procedure
18.2.5 Sample and Data Screening
18.2.6 Data Analysis
18.3 Results and Discussions
18.3.1 Comparison between Trials
18.3.1.1 Workload
18.3.1.2 Usability
18.3.1.3 Acceptance
18.3.1.4 Trust
18.3.2 Comparison between Genders
18.3.2.1 Workload
18.3.2.2 Usability
18.3.2.3 Acceptance
18.3.2.4 Trust
18.3.3 Comparisons between Age Groups
18.3.3.1 Workload
18.3.3.2 Usability
18.3.3.3 Acceptance
18.3.3.4 Trust
18.3.4 Benefits and Effects of Customisation
18.3.5 Information Settings for Safe and Timely Takeover
18.4 Conclusion
Acknowledgements
References
Chapter 19 Accommodating Drivers’ Preferences Using a Customised Takeover Interface on UK Motorways
19.1 Introduction
19.2 Methods
19.2.1 System Description
19.2.1.1 Study Vehicle
19.2.1.2 Human–Machine Interface
19.2.1.3 Customisation Settings
19.2.2 Study Design
19.2.3 Procedure
19.2.3.1 Pre-trial
19.2.3.2 Trial
19.2.3.3 Post-trial
19.2.4 Participants
19.2.5 Data Analysis
19.2.5.1 Customisation Settings
19.2.5.2 Cluster Analysis
19.3 Hypotheses
19.4 Results
19.4.1 Overview Customisation Settings
19.4.1.1 Binary Customisation Settings
19.4.1.2 Ordinal Customisation Settings
19.4.2 Cluster Analysis of Customisation Settings
19.4.2.1 Clustering Participants
19.4.2.2 Clustering Binary Interfaces
19.4.2.3 Comparing Simulator and On-Road Study
19.5 Discussion
19.5.1 Hypotheses
19.5.2 Study Limitations
19.6 Conclusion
Acknowledgements
References
Chapter 20 Validating OESDs in an On-Road Study of Semi-Automated Vehicle- to-Human Driver Takeovers
20.1 Introduction
20.2 Construction of OESDs
20.3 Method
20.3.1 Participants
20.3.2 Experimental Design
20.3.3 Equipment
20.3.4 Procedure
20.3.5 Data Reduction and Analysis
20.4 Results
20.5 Discussion
20.6 Conclusions
Acknowledgements
References
Chapter 21 Design Constraints and Guidelines for the Automation–Human Interface
21.1 Design Constraints
21.1.1 Allow Driver to Take Control at Any Point during Takeover, Be Sure Hands on Wheel and Feet on Pedals
21.1.2 Personalise Takeover Based on Driver Preferences (and Situation)
21.1.3 Allow Option to Complete Non-driving Task (Even If It Means Missed Takeover for Junction/Exit)
21.1.4 Allow Sufficient Time for Takeover (Big Individual Differences in Our Studies)
21.1.5 Customise Takeover Based on Duration of Being Outside of the Control Loop and Frequency of Takeover (and Context: Road, Weather, Other Road Users, Infrastructure, Signage) – Multimodal Human–Machine Interface (HMI)
21.1.6 Querying Situation Awareness of Driver by ‘Vehicle Avatar’
21.1.7 Make Explicit Who Is in Control of Vehicle – Mode Awareness HMI (Light-up Steering Wheel)
21.1.8 Recommended Settings Based on Customer Profiles for Customisation
21.1.9 Pre-set Defaults for Takeover
21.1.10 Graduated Alert to Takeover Visual, Audio, Haptic (Escalating)
21.1.11 Cue Driver to ‘Grab’ Steering Wheel
21.1.12 Make ‘Takeover Button’ Easy to Access (e.g. Put on Gear Stick)
21.1.13 ‘Repeat’ Button and ‘OK’ Button?
21.1.14 Encourage (Facilitate) Visual Checks in Environment and Controls of Vehicle
21.1.15 Display the Vehicle Status and Intention
21.1.16 Driver’s HMI Actions Need to Be Clearly Fed Back (Link to 1 – Volvo Hands on Wheel to Flip Both Paddles)
21.1.17 Eyes Out
21.1.18 Use System to Aid Manual Driving
21.1.19 Some Level of Personalisation and Setting of Levels
21.1.20 Longer Automated Vehicle-to-Human Driver Takeover in Urban Environment (Compared to Motorway)
21.1.21 Takeover Strategy That Guides Visual Search
21.1.22 Feedback to Every Driver Action (Process Needs Adapting to Driver and Situation)
21.1.23 Checklist
21.1.24 Option to Request Specific Information of Importance to Driver (If Not in Protocol)
21.1.25 Education of Drivers in Rationale and Technique
21.1.26 Training (Video) before Being Able to Use Autopilot on Roads
21.1.27 Older Drivers Do Not Like to Constantly Monitor Automation for Takeover (Timer Only) Trend Only
21.1.28 Differences between User Preference and Rankings of Usefulness
21.1.29 Characteristics of Modality
21.1.30 Synchronise Multimodal Cues – Combining or Single Modality
21.1.31 Longitudinal Studies
21.2 Design Guidelines
21.2.1 Design Methodological Guidelines (DMG)
21.2.2 Interface and Interaction Design Guidelines (IDG)
21.2.3 User Trials Guidelines (UTG)
Acknowledgements
Index
Subject Index
Inclusivity Index