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E-raamat: Handbook of Automotive Human Factors [Taylor & Francis e-raamat]

Edited by (Institute of Human Science & Biomedical, Japan)
  • Formaat: 358 pages, 39 Tables, black and white; 18 Illustrations, color; 202 Illustrations, black and white
  • Ilmumisaeg: 19-Jun-2019
  • Kirjastus: CRC Press
  • ISBN-13: 9780429261060
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  • Taylor & Francis e-raamat
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Handbook of Automotive Human FactorsSuurem pilt
  • Formaat: 358 pages, 39 Tables, black and white; 18 Illustrations, color; 202 Illustrations, black and white
  • Ilmumisaeg: 19-Jun-2019
  • Kirjastus: CRC Press
  • ISBN-13: 9780429261060
Teised raamatud teemal:
Taylor & Francis e-raamatudRohkem infot Taylor & Francis e-raamatute kohta
Raamatu kodulehekülg: https://www.taylorfrancis.com/books/9780429261060

Thanks to advances in computer technology in the last twenty years, navigation system, cabin environment control, ACC, advanced driver assistance system (ADAS) and automated driving have become a part of the automobile experience. Improvement in technology enables us to design these with greater flexibility and provide greater value to the driver (human centered design). To achieve this, research is required by laboratories, automobile and auto parts manufacturers. Although there has been a lot of effort in human factors research and development, starting from basic research to product development, the knowledge and experience has not been integrated optimally. The aim of this book is to collect and review the information for researchers, designers and developers to learn and apply them for further research and development of human centered design of future automotive technologies. Automotive human factors include psychological, physiological, mathematical, engineering and even sociological aspects. This book offers valuable insights to applying the right approach in the right place.

Foreword iii
Preface v
1 Overview of Automotive Ergonomics and Human Factors 1(31)
1.1 Ergonomics and Human Factors for Making Products and Systems Compatible with Humans
1(1)
1.2 Beginning of Human-compatible Automobile Design
1(2)
1.3 Vehicle Cabin Design
3(1)
1.4 Instruments and Displays
4(3)
1.4.1 Instrument Arrangement
4(1)
1.4.2 Meters and Displays
5(1)
1.4.3 Controls
6(1)
1.5 Riding Comfort and Fatigue
7(2)
1.5.1 Fatigue
7(1)
1.5.2 Vibration
8(1)
1.5.3 Arousal Level
9(1)
1.6 Vehicle Interior Environment
9(1)
1.7 Driving Tasks and Non-driving Tasks
10(3)
1.7.1 In-vehicle Systems
10(1)
1.7.2 Non-driving Activities like Using Mobile Phones
11(1)
1.7.3 Visual Distraction
11(1)
1.7.4 Mental Workload and Cognitive Distraction
12(1)
1.8 Driver Model and Driving Behavior Measurement
13(2)
1.8.1 Driver Model
13(1)
1.8.2 Driving Behavior Measurement
13(2)
1.8.2.1 Site-based Measurement
13(1)
1.8.2.2 Driving Simulators
14(1)
1.8.2.3 Equipped Vehicles and Naturalistic Driving Study
15(1)
1.9 Driving-assistance Systems/Automated Driving Systems
15(2)
1.9.1 ACC/Lane-keeping Systems
15(1)
1.9.2 Automated Driving Systems
16(1)
1.10 Elderly Drivers
17(1)
1.11 Positive Aspects of Automobile Driving
18(3)
1.11.1 Enjoyment and Growth
18(2)
1.11.2 Stress Relief
20(1)
1.12 Future of Automobile Ergonomics: Viewpoint of Service Engineering for Providing Value to Users
21(1)
References
22(10)
2 Ergonomic and Human Factors in Automobile Design and Development Process 32(30)
2.1 Ergonomists' Roles and Responsibilities in Automobile Design and Development
32(5)
2.1.1 Ergonomics for Automobiles
32(1)
2.1.2 Development Process
33(1)
2.1.3 Identifying Out User Requirements
33(1)
2.1.4 Ergonomics in Design Stage
34(1)
2.1.5 Ergonomics in Assessment Stage
35(1)
2.1.6 Feedback from Users
35(1)
2.1.7 Designing User's Manual
36(1)
2.2 Surveys for Understanding Users in Design Stage
37(7)
2.2.1 Viewpoints for Considering Target Users
37(1)
2.2.2 Observation-based Approach
38(3)
2.2.2.1 Knowing User Requirements
38(1)
2.2.2.2 Behavior Observation
38(1)
2.2.2.3 Ethnographical Methods
38(2)
2.2.2.4 Task Analysis
40(1)
2.2.3 Questionnaire and Interview Approach
41(3)
2.2.3.1 Objectives of Questionnaires and Interviews
41(1)
2.2.3.2 Selecting Survey Methods
41(1)
2.2.3.3 Designing Paper Questionnaires and Interviews
42(1)
2.2.3.4 Depth Interview Method
43(1)
2.2.3.5 Group Interview
44(1)
2.3 Driving Behavior Measurement
44(15)
2.3.1 Driving Behavior Measurement Using Driving Simulators
44(6)
2.3.1.1 Objectives of Using Driving Simulators
44(1)
2.3.1.2 Basic Configuration of Driving Simulators
45(1)
2.3.1.3 Classification of Driving Simulators
46(2)
2.3.1.4 Driving Simulator Sickness
48(1)
2.3.1.5 Other Tips for Use in Driving Simulators
49(1)
2.3.2 Driving Behavior Measurement Using Instrumented Vehicles
50(3)
2.3.2.1 Instrumented Vehicle
50(2)
2.3.2.2 Measurement Environment
52(1)
2.3.2.2.1 Measurement on a Test Track
52(1)
2.3.2.2.2 Measurement on Real Roads
52(1)
2.3.2.3 FOT and NDS
53(1)
2.3.3 Driving Behavior Analysis Using Drive Recorders
53(9)
2.3.3.1 Drive Recorder Specifications
53(1)
2.3.3.2 Recording Driving Behavior
54(2)
2.3.3.2.1 Face Direction
54(2)
2.3.3.2.2 Recording Traffic Conditions
56(1)
2.3.3.3 Data Recording Methods
56(1)
2.3.3.3.1 Event Trigger Methods
56(1)
2.3.3.3.2 Continuous Recording Methods
56(1)
2.3.3.4 Examples of Drive Recorder Data Analysis
56(6)
2.3.3.4.1 Time Series Analysis Using Variation Tree Analysis
56(2)
2.3.3.4.2 Analyzing a Series of Background Factors
58(1)
References
59(3)
3 Comfort and Quality 62(40)
3.1 Occupant Comfort During Vehicle Run
62(13)
3.1.1 Vibration and Comfort
62(3)
3.1.1.1 Basic Vibration Measurement and Evaluation Methods
63(1)
3.1.1.2 Riding Comfort Evaluation by Phenomenon
64(1)
3.1.1.3 Method for Estimating the Vibration of the Seat when an Occupant is Sitting
64(1)
3.1.2 Comfort of the Seat
65(5)
3.1.2.1 Seat Structure and Vibration Absorption Properties
66(2)
3.1.2.1.1 Transmission of Vibration through the Seat
66(1)
3.1.2.1.2 Issues on the Measurement of the Vibration of the Seat
66(1)
3.1.2.1.3 Seat Structure and Specific Characteristics of Vibration
66(1)
3.1.2.1.4 Vibration Characteristics of the Parts of Seat
67(1)
3.1.2.1.5 Changes in the Characteristics of Vibrations on People
68(1)
3.1.2.2 Body Movements Caused by Acceleration
68(1)
3.1.2.3 Support Performance of the Seat
69(6)
3.1.2.3.1 Lateral Movements
69(1)
3.1.2.3.2 Movements of the Head
70(1)
3.1.2.3.3 Support by the Seat during Driving
70(1)
3.1.3 Vibration and Driving Performance
70(5)
3.2 Acoustic Comfort
75(8)
3.2.1 Design of the Engine Sound
75(4)
3.2.1.1 Acoustic Characteristics that Influence Sound Design
75(1)
3.2.1.2 Order Composition of Sounds
75(2)
3.2.1.2.1 Orders and Generation Mechanism
75(1)
1 Engine sound
75(1)
2 Suction sound
76(1)
3 Exhaust sound
77(1)
3.2.1.2.2 Relationship of the Order Composition and the Impression of the Sound
77(1)
3.2.1.3 Control of the Sound
77(2)
3.2.1.3.1 Method that Uses Components of the Vehicle
78(1)
3.2.1.3.2 Method that Uses Devices for Creating Sounds
78(1)
3.2.1.4 Sound Evaluation Methods
79(1)
3.2.2 Sound of the Door Closing
79(4)
3.2.2.1 Need for Research on Door Sounds
79(1)
3.2.2.2 Mechanism of Door Closing Sounds
80(1)
3.2.2.3 Conditions for Good Door Closing Sound
81(1)
3.2.2.3.1 Arranging the Distribution of Frequency
81(1)
3.2.2.3.2 Adding Reverberation Effects: It is Effective to give Two Sounds with the Same Frequency Components
81(1)
3.2.2.4 How to Realize It
82(1)
3.2.2.4.1 Method of Producing Sounds of Low Frequency
82(1)
3.2.2.4.2 How to Produce the Two Successive Sounds
82(1)
3.2.2.5 Other Considerations
83(1)
3.3 Cabin Air Quality
83(5)
3.3.1 Smells in the Interior of the Vehicle
83(3)
3.3.1.1 Sensory Evaluation
83(1)
3.3.1.2 Instrumental Analysis
84(1)
3.3.1.3 Odor Sensors
85(1)
3.3.1.4 Odor Control
85(1)
3.3.2 Effects of Fragrance
86(2)
3.3.2.1 Perception Mechanism of Smells
86(1)
3.3.2.2 Emotional and Physiological Effects of Fragrances
87(1)
3.3.2.3 Future of Vehicles and Smells
88(1)
3.4 Visual Environment of Vehicle Interior
88(6)
3.4.1 Function and Design of Vehicle Interior Lighting
88(3)
3.4.1.1 Types of Lighting
88(1)
3.4.1.2 Requirements for Functional Lighting Design and a Study Example
89(1)
3.4.1.3 Map and Reading Lamps
90(1)
3.4.1.4 Vanity Lamps
90(1)
3.4.2 Comfort Provided by Vehicle Interior Lighting
91(3)
3.4.2.1 Effect of Shape and Brightness of Light Source on People's Impression of Vehicle Comfort and Spaciousness
91(2)
3.4.2.2 Poor Visibility of Vehicle Interior from Outside
93(1)
3.5 Interior Materials
94(4)
3.5.1 Evaluation Criteria for Interior Material
94(1)
3.5.2 Gripping Functions
94(1)
3.5.2.1 Functions of Vehicle Operation System
94(1)
3.5.2.2 Grips that Support Drivers/Passengers with Physical Stability
95(1)
3.5.2.3 Gripping Functions of Non-grip Parts
95(1)
3.5.3 Effect of Sweat
95(1)
3.5.4 Difference in Skin Structure Among Body Parts
96(1)
3.5.5 Stickiness
96(1)
3.5.6 Thermal Sensation
97(1)
3.5.7 Breathable Seat Materials and Structures
98(1)
3.5.8 Texture and Durability
98(1)
References
98(4)
4 Driver State 102(60)
4.1 Driving Fatigue, Workload, and Stress
102(7)
4.1.1 Stress and Strain
102(1)
4.1.2 Driver Fatigue
103(1)
4.1.3 Mental Workload and Tasks
104(1)
4.1.4 Mental Workload Described in ISO 10075
105(2)
4.1.5 Task Demand, Mental Resource and Fatigue
107(1)
4.1.6 Difference Between the Concept of Mental Workload and the Concept of Stress/Strain
107(1)
4.1.7 Driver's Stress
108(1)
4.2 Enjoyment Generated by Automobiles
109(6)
4.2.1 Utility of Automobile Use
109(1)
4.2.2 Automobiles as a Tool for Stimulating Emotions
110(1)
4.2.3 Flow Theory of Csikszentmihalyi
110(2)
4.2.4 Flow and Increase of Skills
112(1)
4.2.5 Flow and the Zone
113(1)
4.2.6 Effects of Feelings of Enjoyment
114(1)
4.2.7 Subjective Well-being and Automobiles
114(1)
4.3 Arousal Level
115(15)
4.3.1 Arousal Level and Sleepiness
115(2)
4.3.2 Sleepiness Measurement Methods
117(4)
4.3.2.1 Sleep Propensity
117(1)
4.3.2.2 Vigilance
118(2)
4.3.2.3 Subjective Sleepiness
120(1)
4.3.3 Arousal Level Measurement
121(5)
4.3.3.1 Driving Behavior
121(1)
4.3.3.2 EEG
121(1)
4.3.3.3 Rating Based on Facial Expressions
121(1)
4.3.3.4 Pupil Diameter
122(1)
4.3.3.5 Eye Movement
122(1)
4.3.3.5.1 Saccade
122(1)
4.3.3.5.2 Slow Eye Movement
123(1)
4.3.3.5.3 Vestibulo-ocular reflex (VOR)
123(1)
4.3.3.6 Eyelid Activity
123(3)
4.3.3.6.1 PERCLOS
123(1)
4.3.3.6.2 Integrated Indices of Eye-related Measures
124(2)
4.3.3.7 Heart Rate
126(1)
4.3.3.8 Summary
126(1)
4.3.4 Arousal-enhancing Technology
126(4)
4.3.4.1 Sleepiness and Arousal Level
126(2)
4.3.4.2 Counter Measures against Sleepiness, Napping
128(1)
4.3.4.3 Counter Measure against Sleepiness, Other than Napping
129(1)
4.3.4.4 Summary
130(1)
4.4 Techniques for Measuring/Analyzing Physical Conditions
130(25)
4.4.1 Significance of Introducing Biosignal Measurement
130(2)
4.4.1.1 Purpose of Biosignal Measurement
130(1)
4.4.1.2 Activities of an Organism and Biological Systems
131(1)
4.4.1.3 Advantages and Disadvantages of Biological Measurement
131(1)
4.4.1.4 Potential of Biosignal Measurement
132(1)
4.4.2 Indices of Central Nervous System Activity
132(7)
4.4.2.1 Electroencephalogram (EEG)
133(2)
4.4.2.2 Functional Magnetic Resonance Imaging (fMRI)
135(1)
4.4.2.3 Functional Near Infrared Spectroscopy (fNIRS)
135(4)
4.4.2.4 Critical Flicker Fusion Frequency (CFF)
139(1)
4.4.3 Indices Relating to the Visual System
139(5)
4.4.3.1 Eye Movement
140(2)
4.4.3.2 Visual Field
142(1)
4.4.3.3 Eye Blink
143(1)
4.4.3.4 Pupil
143(1)
4.4.4 Indices of Autonomic Nervous System Activity
144(4)
4.4.4.1 Heart Rate
144(1)
4.4.4.2 Heart Rate Variability (HRV) Indices
145(1)
4.4.4.3 Blood Pressure and Pulse Waves
146(1)
4.4.4.4 Respiration
146(1)
4.4.4.5 Electrodermal Activity
147(1)
4.4.4.6 Skin Temperature
148(1)
4.4.5 Facial Expression
148(4)
4.4.5.1 Anatomy of Mimetic Muscles
148(1)
4.4.5.2 Relationship Between Facial Expression and Emotion
149(2)
4.4.5.3 Techniques for Estimating Emotions Based on Facial Images
151(1)
4.4.5.4 Relationship Between Facial Expression and Driver States
152(1)
4.4.5.5 Application of Facial Expressions to Automobile and Future Challenges
152(1)
4.4.6 Biochemical Reactions
152(3)
References
155(7)
5 Driver and System Interaction 162(95)
5.1 Mental Workload while Using In-vehicle System
162(16)
5.1.1 Workload Measurement Using Questionnaires
162(6)
5.1.1.1 Cooper-Harper Rating Scale
162(1)
5.1.1.2 NA SA-TLX
162(2)
5.1.1.3 SWAT
164(2)
5.1.1.4 Workload Profile Method (WP)
166(1)
5.1.1.5 Rating Scale Mental Effort (RSME)
167(1)
5.1.2 Mental Workload Assessment Using the Subsidiary Task Method
168(4)
5.1.2.1 Two Types of Subsidiary Tasks
169(1)
5.1.2.2 Psychological Concepts Related to the Subsidiary Task Method
169(2)
5.1.2.3 Example of Application of Subsidiary Task Method
171(1)
5.1.3 Workload Measurement Based on Driving Performance
172(6)
5.1.3.1 Overview
172(1)
5.1.3.2 Steering Entropy (SE) Method
173(2)
5.1.3.3 Real-time Steering Entropy (RSE) Method
175(3)
5.1.3.4 Summary
178(1)
5.2 HMI of In-car Information Systems
178(16)
5.2.1 Interaction with a System
178(3)
5.2.1.1 Design of Interaction
179(1)
5.2.1.2 Tactile Feedback
179(1)
5.2.1.3 Audio Interface
179(1)
5.2.1.4 Integrated Controller
180(1)
5.2.1.5 Internet Connection of In-car Devices
180(1)
5.2.2 Route Navigation and Map Display
181(10)
5.2.2.1 Volume of Graphic Information
181(1)
5.2.2.2 Mental Map
181(2)
5.2.2.3 Expression of Maps
183(1)
5.2.2.4 Displaying Roads
184(1)
5.2.2.5 Displaying Background
184(1)
5.2.2.6 Presenting Text
185(1)
5.2.2.7 Presenting Landmarks
186(1)
5.2.2.8 Displaying Remaining Distance/Estimated Required Time
186(1)
5.2.2.9 Displaying Routes
187(3)
5.2.2.9.1 Turn by Turn Display
187(1)
5.2.2.9.2 Route Display
187(1)
5.2.2.9.3 Traffic Lane Display
188(1)
5.2.2.9.4 Crossing Macrograph
188(1)
5.2.2.9.5 Highway Map
188(1)
5.2.2.9.6 Manoeuver List
188(2)
5.2.2.9.7 Guide Information to Support Safe Driving
190(1)
5.2.2.10 Display of Traffic Information
190(1)
5.2.3 Design of Menus
191(3)
5.2.3.1 Menu-based Interaction
192(1)
5.2.3.1.1 Fundamental Principles
192(1)
5.2.3.1.2 Presentation and Selection of Menu Items
193(1)
5.2.3.1.3 Strengths and Weaknesses of Menu-based Interaction
193(1)
5.2.3.2 Design Guidelines
193(1)
5.2.3.3 Evaluation Methods for Menu Designs
194(1)
5.3 Assessment of Driver Distraction
194(21)
5.3.1 Definition of Distraction
194(3)
5.3.1.1 Characteristics of Attention and Related Definitions
195(1)
5.3.1.2 Distraction
196(1)
5.3.1.2.1 Suggested Definitions
196(1)
5.3.1.2.2 Relation to Inattention
196(1)
5.3.1.2.3 Relation to Arousal Level and Workload
196(1)
5.3.1.3 Conclusion
197(1)
5.3.2 Assumptions for Distraction Assessment
197(4)
5.3.2.1 Information Processing and Distraction
197(1)
5.3.2.2 Ideas and Types of Assessment Methods
198(3)
5.3.2.2.1 Requirements for Assessment Methods
198(1)
5.3.2.2.2 Types of Assessment Methods
199(1)
1 Primary task measurement and secondary (subsidiary) task measurement
199(1)
2 Assumptions and notes for the secondary task measurement
199(1)
3 Secondary task measurement and dual task measurement
199(1)
4 Primary task and subsidiary/additional task
200(1)
5.3.2.2.3 Conclusion
200(1)
5.3.3 Visual-Manual Distraction Assessment
201(5)
5.3.3.1 Direct Assessment
201(4)
5.3.3.1.1 Visual Behavior
201(2)
5.3.3.1.2 Driving Performance
203(2)
5.3.3.2 Occlusion Method
205(1)
5.3.4 Cognitive Distraction Assessment
206(4)
5.3.4.1 Lane Change Test (LCT Method)
206(2)
5.3.4.2 Detection Response Task (DRT Method)
208(1)
5.3.4.3 Physiological Index
209(1)
5.3.5 Reference Tasks in Distraction Assessment
210(3)
5.3.5.1 Item Recognition Task
210(1)
5.3.5.2 N-back Task
211(1)
5.3.5.3 Calibration Task
212(1)
5.3.5.4 Conclusion
213(1)
5.3.6 Use of Cellular Phone while Driving
213(2)
5.4 Interaction with Advanced Driver Assistance Systems
215(35)
5.4.1 Presentation and Management of Information
215(19)
5.4.1.1 Design of Warning Signal
215(6)
5.4.1.1.1 Warning
215(1)
5.4.1.1.2 Warning Compliance
215(1)
5.4.1.1.3 Expected Driver's Response
216(1)
5.4.1.1.4 Warning Level and Warning Design
217(1)
1 Criticality and urgency
217(1)
2 Warning level
217(1)
5.4.1.1.5 Basic Requirements for Warning Designs
218(1)
1 Visual presentation of warnings
218(1)
2 Impression given by the design of warning signals
219(2)
5.4.1.2 Influence of the Warning Signal on the Driver Behavior
221(4)
5.4.1.2.1 Assessment of Effectiveness of the Warning System on the Avoidance of Danger
221(1)
5.4.1.2.2 Hazard Avoidance Scenarios of Experiments
222(1)
1 Effectiveness of warning systems
222(1)
2 Assessment of the warning signal
222(1)
5.4.1.2.3 Assessment of the Compliance with Warning/alerting Systems
223(1)
1 Compliance
223(1)
2 Example of assessment of effectiveness of seat belts reminders
223(2)
5.4.1.3 Priority and Management of In-vehicle Information
225(4)
5.4.1.3.1 Need for Information Management
225(1)
5.4.1.3.2 Information Importance
226(1)
5.4.1.3.3 Message Management
227(1)
1 Selection and integration of the message to be presented (priority management)
227(1)
2 Design consistency between messages from different systems
229(1)
3 Display management
229(1)
4 Presentation style management
229(1)
5 Time management
229(1)
5.4.1.4 Estimation of the Driving Demand or Workload for Message Management
229(5)
5.4.1.4.1 Workload Manager in Information Management
229(1)
5.4.1.4.2 Estimation of the Driving Demand based on the Road Traffic Environment
230(1)
5.4.1.4.3 Estimation based on Automotive Sensor Signals of Driving Demand in Road Traffic Environment
231(2)
5.4.1.4.4 Estimation of the Driving Workload in Real-time based on Sensor Signals
233(1)
5.4.2 Systems and Drivers
234(23)
5.4.2.1 Levels of Automation of Systems and Drivers
234(2)
5.4.2.1.1 Automation of Systems
234(1)
5.4.2.1.2 Levels of Automation
234(1)
5.4.2.1.3 Examples of Level 1 to 3
234(1)
5.4.2.1.4 Examples of Level 4 to 6
235(1)
5.4.2.1.5 Examples of Level 6.5
235(1)
5.4.2.1.6 Examples of Level 7
236(1)
5.4.2.2 Over-trust and Overdependence
236(3)
5.4.2.3 Monitoring of the System Status by the Driver
239(3)
5.4.2.3.1 Supervisory Control
239(1)
5.4.2.3.2 HMI in Driving Supporting Systems Using V2X communication
239(1)
1 Verification of operating status
239(1)
2 Easy to understand
241(1)
3 Communication certainty
241(1)
4 Easy understanding of criticality
241(1)
5 Prevention of over-trust and distrust
241(1)
5.4.2.3.3 More General HMI in Driving Support/Automated Driving Systems
242(1)
5.4.2.4 Changes in Driver's Behavior Caused by Introduction of the System
242(2)
5.4.2.4.1 Driving Behavior Induced by the System
242(1)
5.4.2.4.2 Definition of Road/traffic Factors Influencing Driving Behavior
243(1)
5.4.2.4.3 Example of Analysis of Behavioral Changes Caused by the System
243(1)
5.4.2.5 Compatibility of the System with Drivers' Behavior
244(2)
5.4.2.5.1 Distance without the System and Distance with the ACC System
244(1)
5.4.2.5.2 Relation Between Drivers' Characteristics, Driving Behavior and the Distance Selected in the ACC
245(1)
5.4.2.6 Human Factors in Automated Driving Systems
246(11)
5.4.2.6.1 Intersection Between Automated Driving Systems and Humans
246(1)
5.4.2.6.2 Understanding of the System
247(1)
1 Understanding of system's functions
247(1)
2 Understanding of the system status
247(1)
3 Understanding of the system operation
248(1)
4 Understanding of the behavior of the system
248(1)
5.4.2.6.3 State of the Driver
248(1)
1 State of the driver when using automated driving systems
248(1)
2 Gap in the transition to the state where the driver is able to execute driving tasks
248(1)
5.4.2.6.4 Value of Automated Driving Systems for Humans
249(1)
5.4.2.6.5 Interaction Between the Car and other Traffic Participant
249(1)
1 Communication between traffic participants
249(1)
2 Communication functions that automated vehicles must have
250(1)
References
250(7)
6 Driver Behavior 257(68)
6.1 Human Characteristics Related to Driver Behavior
257(20)
6.1.1 Visual Cognitive Functions
257(11)
6.1.1.1 Visual Attention and Its Psychological Measurements
257(5)
6.1.1.1.1 Shift of Attention
257(1)
6.1.1.1.2 Selection of Visual Information at a Fixation Point
258(1)
6.1.1.1.3 Useful Field of View
259(3)
6.1.1.2 Physiological Measurement of Attention
262(3)
6.1.1.2.1 Attentional Resource Allocation and Event-related Potentials
262(1)
6.1.1.2.2 Evaluation of Visual Attentional Resource Allocation using Eye-fixation-related Potentials
263(1)
6.1.1.2.3 Evaluation of Attentional Resource Allocation Using Probe Methods
264(1)
6.1.1.3 Visual Attentional Models
265(3)
6.1.1.3.1 Saliency Model of Itti and Koch
266(1)
6.1.1.3.2 Models that take Account of Top-down Factors
267(1)
6.1.1.3.3 Application of Models to Moving Images
268(1)
6.1.2 Information Processing and Cognitive Models for Humans
268(9)
6.1.2.1 Driver Information Processing Models
268(7)
6.1.2.1.1 Basic Three-stage Information Processing Models for Humans
268(1)
6.1.2.1.2 Information-processing Model taking Account of Memory and Attention
269(1)
6.1.2.1.3 Norman's Seven-stage Action Model
270(1)
6.1.2.1.4 Situation Awareness Model
271(1)
6.1.2.1.5 Hierarchical Model of Driving Behavior
272(1)
6.1.2.1.6 Rasmussen's Skills-rules-knowledge (SRK) Model
273(1)
6.1.2.1.7 Relationship Among Different Human Information-processing Models
274(1)
6.1.2.1.8 Extended Contextual Control Model (E-COM)
274(1)
6.1.2.2 Task-capability Interface Model
275(2)
6.2 Driving Performance
277(16)
6.2.1 Driving Performance Measures
277(10)
6.2.1.1 Longitudinal Driving Performance
277(3)
6.2.1.1.1 Velocity, Acceleration, and Jerk
278(1)
6.2.1.1.2 Response Time
278(1)
6.2.1.1.3 Headway Distance and Time
279(1)
6.2.1.2 Lateral Driving Performance
280(3)
6.2.1.2.1 Steering Operation
281(1)
6.2.1.2.2 Steering Reversal
281(1)
6.2.1.2.3 Steering Entropy
281(1)
6.2.1.2.4 Lane Position of a Vehicle
282(1)
6.2.1.2.5 Standard Deviation of Lane Position (SDLP)
282(1)
6.2.1.2.6 Time to Line Crossing (TLC)
282(1)
6.2.1.3 Parking Maneuver
283(1)
6.2.1.3.1 Cognitive Function Necessary for Parking Maneuver
283(1)
6.2.1.3.2 Prediction of One's Capability for Park Maneuver based on the Psycho-motor Tests
283(1)
6.2.1.4 Situation Awareness Evaluation Methods
284(3)
6.2.1.4.1 Situation Awareness Global Assessment Technique (SAGAT)
285(1)
6.2.1.4.2 Real-time Probe Technique
285(1)
6.2.1.4.3 Subjective Rating (SART: Situation Awareness Rating Technique)
286(1)
6.2.2 Driving Ability Evaluation for Elderly Drivers
287(6)
6.2.2.1 Ability Evaluation of Driving Behavior
287(1)
6.2.2.2 Evaluation of Perceptual-Motor Coordination
288(1)
6.2.2.3 Evaluation of Cognitive Functions
289(2)
6.2.2.3.1 Neuro-psychological Tests and Driving Ability
289(2)
6.2.2.3.2 Screening Test for Elderly Drivers
291(1)
6.2.2.4 Models of Driving Ability for Elderly People
291(2)
6.2.2.4.1 Multifactorial Model for Enabling Driving Safety
291(1)
6.2.2.4.2 Adaptive Driving Behavior of Elderly People
292(1)
6.3 Driver's Behavior Models
293(32)
6.3.1 Driving Behavior Models
293(8)
6.3.1.1 Driver Steering Control Models
293(4)
6.3.1.1.1 Basics of Modeling
294(1)
6.3.1.1.2 Major Examples of Driver Steering Control Models
295(1)
1 Preview-predictive model
295(1)
2 Describing function model
296(1)
3 Pursuit control model
297(1)
4 Other models
297(1)
6.3.1.2 Model of Visual Recognition During Driving
297(4)
6.3.1.2.1 Perception of Direction of Travel
297(1)
6.3.1.2.2 Use of Tangent Points
298(1)
6.3.1.2.3 Use of Information on Near and Far Areas
299(2)
6.3.1.2.4 Effect of Gaze Direction
301(1)
6.3.2 Information-processing Models Related to Driver's Behavior
301(11)
6.3.2.1 Information-processing Models for Drivers Using Car Navigation System
301(6)
6.3.2.1.1 Information-processing Models for Drivers using a Digital Map System with Self-localization Function
302(2)
6.3.2.1.2 Information-processing Models for Drivers using a Turn-by-turn Navigation System
304(1)
6.3.2.1.3 Information-processing Models for Drivers using a Navigation System Capable of Displaying an Enlarged View of Intersection
305(2)
6.3.2.2 ACT-R (Adaptive Control of Thought-Rational) Model of Driving Behavior
307(5)
6.3.2.2.1 Driving Behavior and Integrated Driver Models with an ETA Framework Viewpoint
307(1)
6.3.2.2.2 Integrated Driver Model using the ACT-R Cognitive Architecture
308(1)
1 Control
308(1)
2 Monitoring
310(1)
3 Decision-making
310(1)
4 Component integration and multitasking
311(1)
5 Parameter values
311(1)
6.3.2.2.4 Validation and Application ACT-R Model of Driving Behavior
312(1)
6.3.3 Statistical Behavior Models
312(13)
6.3.3.1 Structural Equation Models for Driving Behavior
312(4)
6.3.3.1.1 Structural Equation Models (SEM)
313(2)
6.3.3.1.2 Structural Equation Model of Driving Behavior for Making a Turn
315(1)
6.3.3.1.3 Application of Structural Equation Model to Theory of Planed Behavior
316(1)
6.3.3.2 Bayesian Network Models for Driving Behavior
316(4)
6.3.3.2.1 Bayesian Network Model
316(1)
6.3.3.2.2 Dynamic Bayesian Network Model
317(3)
6.3.3.3 Modeling Driving Behavior Using Hidden Markov Models
320(5)
6.3.3.3.1 Theoretical Background of Modeling Driving Behavior Using HMM
320(1)
6.3.3.3.2 Example of Constructing a Driving Behavior Model Using Discrete HMM
321(1)
6.3.3.3.3 Estimation of Road Shape and Driving Behavior Using Continuous HMM
322(1)
1 Collection of driving signals and creation of corpus
322(1)
2 Estimation of driving behavior in relation to specific road shape
323(1)
6.3.3.3.4 Estimating Driving Behavior Using HMM and other Applications
323(1)
1 Prediction of driving behavior
323(1)
2 Estimating characteristics of individuals
324(1)
3 Future direction and issues
324(1)
References 325(8)
Index 333
Motoyuki Akamatsu is a distinguished senior researcher at the Automotive Human Factors Research Center (AHFRC), a part of National Institute of Advanced Industrial Science and Technology (AIST), Japan. He was formerly the director of Human Technology Research Institute of AIST. He received a doctorate in administration engineering from Keio University in 1983, and has worked on automotive human factors for 30 years, and also has experience in other ergonomics and human factors fields. He has conducted many collaborative researches with automobile manufactures and related companies. Dr. Akamatsu has also worked in international standards for 15 years. He is as an expert in ISO/TC22/SC39/WG8.
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