Designing Interaction and Interfaces for Automated Vehicles: User-Centred Ecological Design and Testing

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