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EbookBell Team
4.7
36 reviews
ISBN 10: 1849966281
ISBN 13: 978-1849966283
Author: Carlo Cacciabue
In the automotive environment, the paradigm of the joint human machine system is called the "Driver-Vehicle-Environment" (DVE) model. Several studies have pointed out the uniqueness of this domain, which can refer to minimum standardisation and normalisation of behaviours, contexts and technology.
This book presents a general overview of various factors that contribute to modelling human behaviour in a DVE. In practice, it is rare that all of these aspects have to be considered in total by a designer or safety analyst. However, they all contribute to creating the overall picture of the DVE model, and show the scope and dimensions of the many different interaction process that may take place and demand modelling consideration.
This long-awaited volume written by experts in the field presents state-of-the-art research and case studies. It will be invaluable reading for graduate students, researchers and professional practitioners alike.
I International Projects and Actions on Driver Modelling
1 Modelling Driver Behaviour in European Union and International Projects
1.1 Introduction
1.2 Evaluation of Driver Behaviour Models
1.2.1 Michon's Hierarchical Control Model
1.2.2 The GADGET-Matrix: Integrating Hierarchical Control Models and Motivational Models of Driver B
1.2.3 DRIVABILITY Model
1.3 Driver Behaviour Adaptation Models and Their Relation to ADAS
1.3.1 Automaticity
1.3.2 Locus of Control
1.3.3 Risk Homeostasis
1.3.4 Risk Compensation
1.3.5 Threat Avoidance
1.3.6 Utility Maximisation
1.3.7 Behavioural Adaptation Formula
1.4 Use of Driver Behaviour Models in EU and International Projects
1.4.1 Driver Models Use for Driver Training and Assessment
1.4.2 Evaluation ofDriver Models' Use for Safety Aids
1.4.2.1 Use of Seat Belts
1.4.2.2 Use of Motorcycle Helmet
1.4.2.3 Studded Tyres
1.4.2.4 Antilock Braking Systems
1.4.3 Driver Models Use for ADAS Design and Impact Assessment
1.5 Conclusions
References
2 TRB Workshop on Driver Models: A Step Towards a Comprehensive Model of Driving?
2.1 Introduction
2.2 Workshop Presentation and Speakers' Contribution
2.2.1 Workshop Content
2.2.1.1 Driver Model Purpose and Application
2.2.1.2 Driver Model Architecture and Implementations
2.2.1.3 Calibration and Validation
2.2.2 Summaries ofthe Speakers' Contributions
2.2.2.1 In-Vehicle Information System - Jon Hankey
2.2.2.2 ACT-R Driver Model- Dario Salvucci
2.2.2.3 Optimal Control Model - Richard van der Horst
2.2.2.4 ACME
2.2.2.5 Fuzzy Logic Based Motorway Simulation
2.3 Synthesis of Presented Models
2.3.1 Understanding Models' Scope
2.3.2 Driver Model Toolbox
2.4 Towards a Comprehensive Model of Driving
2.5 Conclusions
References
3 Towards Monitoring and Modelling for Situation-Adaptive Driver Assist Systems
3.1 Introduction
3.2 Behaviour-Based Human Environment Creation Technology Project
3.2.1 Aims of the Project
3.2.2 Measurement of Driving Behaviour
3.2.3 Driving Behaviour Modelling
3.2.4 Detection of Non-Normative Behaviour
3.2.5 Estimation of Driver's State
3.2.5.1 Estimation of Driver 's Mental Tension
3.2.5.2 Estimation of Driver's Fatigue
3.3 Situation and Intention Recognition for Risk Finding and Avoidance Project
3.3.1 Aims of the Project
3.3.2 Adaptive Function Allocation Between Drivers and Automation
3.3.3 Decision Authority and the Levels of Automation
3.3.4 Model-Based Evaluation of Levels of Automation
3.3.4.1 Drivers' Psychological States and Their Transitions
3.3.4.2 Driver's Response to an Alert
3.3.4.3 Evaluation of Efficacy of Levels of Automation
3.4 Concluding Remarks
References
II Conceptual Framework and Modelling Architectures
4 A General Conceptual Framework for Modelling Behavioural Effects of Driver Support Functions
4.1 Introduction
4.2 Intended Application Areas and Requirements
4.2.1 Functional Characterisation of Driver Support Functions
4.2.2 Coherent Description ofExpected Behavioural Effects of Driver Support Functions
4.2.3 Conceptualising Relations Between Behavioural Effects and Road Safety
4.2.4 Specific Requirements
4.3 Existing Models of Driver Behaviour
4.3.1 Manual Control Models
4.3.2 Information Processing Models
4.3.3 Motivational Models
4.3.4 Safety Margins
4.3.5 Hierarchical Models
4.4 A Conceptual Framework
4.4.1 Driver Behaviour as Goal-Directed Activity
4.4.2 Dynamical Representation of Driver Behaviour
4.4.3 The Contextual Control Model (COCOM)
4.4.4 The Extended Control Model (ECOM)
4.5 Application
4.5.1 Characterising Driver Support Functions
4.5.1.1 Support for Tracking
4.5.1.2 Support for Regulating
4.5.1.3 Support for Monitoring
4.5.1.4 Support for Targeting
4.5.1.5 Non-Driving-Related Functions
4.5.1.6 Workload Management Functions
4.5.2 Characterising Behavioural Effects of Driver Support Functions
4.5.2.1 Behavioural Adaptation to Driving Support Functions
4.5.2.2 Effects of Multitasking While Driving
4.5.3 Driver Behaviour and Accident Risk
4.6 Discussion and Conclusions
References
5 Modelling the Driver in Control
5.1 Introduction
5.2 A Cognitive View of Driving
5.3 Human Abilities
5.4 Classifying Driver Behaviour Models
5.5 Hierarchical Control Models
5.6 Control Theory
5.7 Adaptive Control Models
5.8 Cognition in Control
5.9 Goals for Control
5.10 Time and Time Again
5.11 Multiple Layers of Control
5.12 Joystick Controlled Cars - An Example
5.13 Summary and Conclusion
References
6 From Driver Models to Modelling the Driver: What Do We Really Need to Know About the Driver?
6.1 Introduction
6.2 A Typology of Models
6.3 Descriptive Models
6.3.1 Task Models
6.3.2 Adaptive Control Models
6.3.3 Production Models
6.4 Motivational Models
6.5 Towards a Real-Time Model of the Driver
6.5.1 What Type of Model Is Required?
6.5.2 Grouping the Factors
6.5.3 A Proposed Structure
6.5.4 Verifying the Model
6.6 Developing an Online Model
6.7 Conclusions
References
III Learning and Behavioural Adaptation
7 Subject Testing for Evaluation of Driver Information Systems and Driver Assistance Systems - Learn
SUMMARY
7.1 Introduction
7.2 Methodological Issues
7.3 Experimental Examples
7.3.1 Evaluation of a Multimodal HMI
7.3.2 Destination Entry While Driving
7.3.3 Evaluation of Driver Assistance Systems
7.4 Solutions
7.5 Conclusions
References
8 Modelling Driver's Risk Taking Behaviour
8.1 Introduction
8.2 Expected Risk Reductions from New Technology on the Road
8.3 Behaviour When Driving with Supports
8.3.1 The Importance of Plain Old Ergonomics
8.3.2 The Loss of Potentially Useful Skills
8.3.3 Opportunities for New Errors
8.3.4 Problematic Transitions
8.3.5 Risk and Risk Perception: My Risk and Yours
8.4 Behavioural Adaptation
8.4.1 Direct Changes in Behaviour
8.4.2 A Word of Caution About Working with Risk Measures in Traffic Safety Studies
8.4.3 A Piece of Empirical Evidence from Seat Belt Accident Statistics
8.4.4 Higher-Order Forms ofAdaptation
8.5 The Link Between Behaviour and Risk
8.5.1 Average Speed, Speed Variability and Risk
8.5.2 Lane-Keeping Performance and Risk
8.5.3 Car-Following and Risk
8.6 Countermeasures Against Behavioural Adaptation
8.6.1 Should There Be Any?
8.6.2 Incentive Schemes and Their Expected Results
8.7 Conclusions
8.8 An Afterthought
References
9 Dealing with Behavioural Adaptations to Advanced Driver Support Systems
9.1 Introduction
9.2 'Behavioural Adaptation' in Road Safety Research
9.3 Behavioural Adaptation to Advanced Driver Support Systems
9.3.1 The Diversity of Behavioural Changes Studied and Observed
9.3.2 The Importance of the Situational Context and the Interactive Dimension of Driving
9.3.3 The Potential Differential Impact of Driver Support Systems
9.3.4 Learning to Drive with New Driver Support Systems
9.4 Behavioural Adaptation in the AIDE Project
References
IV Modelling Motivation and Psychological Mechanisms
10 Motivational Determinants of Control in the Driving Task
10.1 Introduction
10.2 Understanding Speed Choice
10.2.1 Behaviour Analysis
10.2.2 The Theory of Planned Behaviour
10.2.3 Risk Homeostasis Theory
10.2.4 The Task-Capability Interface Model
10.2.4.1 The Determination of Task-Difficulty Level: Task-Difficulty Homeostasis
10.2.4.2 The Representation of Task-Difficulty
10.2.5 The Somatic-Marker Hypothesis
10.2.5.1 Predictions and Speculations from the Somatic-Marker Hypothesis
10.3 Conclusions
References
11 Towards Understanding Motivational and Emotional Factors in Driver Behaviour: Comfort Through Sat
11.1 Introduction
11.2 Emotional Tension and 'Risk Monitor'
11.3 Safety Margins and Safety Zone
11.4 Available Time, Workload and Multilevel Task Control
11.5 Safety Margins, Affordances and Skills
11.6 Towards Unifying Emotional Conceptsin Routine Driving
11.6.1 Safety Margins - To Control and Survive
11.6.2 Vehicle/Road System - To Provide Smooth and Comfortable Travel
11.6.3 Rule Following - ToAvoid Sanctions
11.6.4 Good (or Expected) Progress of Trip -Mobility and Pace/Progress
11.7 Comfort Through Satisficing
11.8 'Go to the Road': Need of On-Road Research
References
12 Modelling Driver Behaviour on Basis of Emotions and Feelings: Intelligent Transport Systems and B
12.1 Introduction
12.2 Defining Motivation
12.3 Motivational Aspects in Driver Behaviour Models
12.4 Behavioural Adaptation and Risk Compensation
12.5 Wilde's Risk Homeostasis Theory (RHT)
12.5.1 Target Risk or Target Feeling?
12.6 Effects of ABS: An Illustrative Example of ITS
12.7 Issues Raised by the Example of ABS: The Relevance for ITS
12.8 Adaptation - Mismatch Between Technology and Human Capability
12.9 ITS Technology May Enhance As Well As Reduce the Window of Opportunities
12.10 Damasio and the Somatic Marker Hypothesis
12.11 The Monitor Model
12.12 The Monitor Model and Prediction of Effects of ITS
12.13 Summary and Conclusions
References
V Modelling Risk and Errors
13 Time-Related Measures for Modelling Risk in Driver Behaviour
13.1 Introduction
13.2 The Driving Task
13.3 Lateral Control
13.3.1 Time-to-Line Crossing (TLC)
13.3.2 Lateral Distance When Passing
13.4 Longitudinal Control
13.4.1 Time-to-Collision (ITC)
13.4.2 Time-to-Intersection (TTl)
13.4.3 Time-to-Stop-Line (ITS)
13.5 Conclusions
References
14 Situation Awareness and Driving: A Cognitive Model
14.1 Introduction
14.2 Situation Awareness
14.2.1 An Algorithmic Description of Situation Awareness
14.2.1.1 The Construction of the Situation Model: Comprehending the Situation
14.2.1.2 Selection of Actions and the Control of Behaviour
14.3 Errors and the Comprehension Based-Model of Situation Awareness
14.4 Situation Awareness and In-Vehicle Information System Tasks
14.4.1 A Measurement Procedure: Context-Dependent Choice Reaction Task
14.4.2 Evaluation of the Context-Dependent Choice Reaction Task
14.5 Conclusions
References
15 Driver Error and Crashes
15.1 Slips, Lapses and Mistakes
15.2 Errors and Violations
15.3 The Manchester Driver Behaviour Questionnaire
15.4 The DBQ and Road Traffic Accidents
15.5 Aggressive Violations
15.6 Anger-Provoking Situations
15.7 Conclusions
References
VI Control Theory Models of Driver Behaviour
16 Control Theory Models of the Driver
16.1 Introduction
16.2 Modelling Human Controlling Behaviour
16.2.1 The Tustin-Model: Linear Part + Remnant
16.2.2 Laboratory Research, Stochastic Input, Quasi-Linear Model
16.2.3 A Holistic Approach: The Crossover Model
16.2.4 Nonlinear Approaches: Improved Reproduction of Measured Behaviour
16.3 Driver Models for Vehicle Design
16.4 Summary and Future Prospects
References
17 Review of Control Theory Models for Directional and Speed Control
17.1 Introduction
17.2 Basic Crossover Model of the Human Operator
17.3 Model for Driver Steering Control
17.3.1 Equivalent Single-Loop System for Steering Control
17.4 Model for Speed Control with Accelerator Pedal
17.5 Experimental Data
17.5.1 Driving Simulator Measurements
17.5.1.1 Steering Control
17.5.1.2 Speed Control
17.5.2 Actual Vehicle Measurements
17.6 Example Directional Control Application
17.7 Discussion
References
VII Simulation of Driver Behaviour
18 Cognitive Modelling and Computational Simulation of Drivers Mental Activities
18.1 Introduction: A Brief Historical Overview on Driver Modelling
18.2 COSMODRIVE Model
18.2.1 Cognitive Architecture ofCOSMODRIVE
18.2.2 The Tactical Module
18.2.2.1 Driving Frames: A Framework for Modelling Mental Models
18.2.2 .2 Architecture of the Tactical Module
18.2.2.3 The Blackboards of the Tactical Module
18.2.2.4 The Knowledge Bases (KB) of the Tactical Module
18.2.2.5 The Cognitive Processes of the Tactical Module
18.2.2.5.1 Categorisation
18.2.2.5.2 The Place Recognition Process
18.2.2.5.3 The Tactical Representations Generator Process
18.2.2.5.4 The Anticipation Process
18.2.2.5.5 The Decision Process
18.3 Methodology to Study Driver's Situation Awareness
18.3.1 Main Hypothesis
18.3.2 Methodology
18.3.3 Main Results
18.3.4 Discussion and Conclusion Concerning Experimental Study of Drivers Situation Awareness
18.4 Some Experimental Results Simulation with Cosmodrive
18.5 Conclusion and Perspectives: From Behaviours to Mental Model
References
19 Simple Simulation of Driver Performance for Prediction and Design Analysis
19.1 Introduction
19.1.1 Modelling Human Behaviour in Modern Technology
19.1.2 Modelling Drivers in the Automotive Context
19.1.3 Use and Applications ofDriver Models
19.1.4 Content ofthe Paper
19.2 Simple Simulation of Driver Behaviour
19.2.1 Paradigm of Reference
19.2.2 Simulation Approach for Normative Behaviour
19.2.2.1 Task Analysis
19.2.2.2 Dynamic Logical Simulation of Tasks
19.2.3 Algorithms for Cognition, Behavioural Adaptation and Errors
19.2.3.1 Normative Driver Behaviour
19.2.3.2 Descriptive Driver Behaviour
19.2.3.3 Parameters and Measurable Variables
19.2.3.3.1 Task Demand
19.2.3.3.2 Driver State
19.2.3.3.3 Situation Awareness
19.2.3.4 Intentions, Decision Making and Human Error
19.2.3.4.1 Intentions and Decision Making
19.2.3.4.2 Error Generation
19.2.4 Simulation of Control Actions
19.2.4.1 Normal Driving
19.2.4.2 Error in Control Actions
19.3 Sample Cases of Predictive DVE Interactions
19.3.1 Case 1
19.3.2 Case 2
19.4 Conclusions
References
VIII Simulation of Traffic and Real Situations
20 Real-Time Traffic and Environment Risk Estimation for the Optimisation of Human-Machine Interacti
20.1 Introduction
20.2 The AWAKE Use Case - Adaptation of a Driver Hypovigilance Warning System
20.2.1 AWAKE System Overview
20.2.2 Traffic Risk Estimation in AWAKE System
20.2.3 The Scenario-Assessment Unit
20.2.4 The Warning Strategies Unit
20.2.5 The Risk-Level Assessment Unit
20.3 The AIDE Use Case - Optimisation of the In-Vehicle Human-Machine Interaction
20.3.1 Overview
20.3.2 Architecture
20.3.2.1 Relevance to the AIDE Use Cases
20.3.2.2 Description of Environment
20.3.3 Algorithm for Risk Assessment
20.3.3.1 Rule-Based System Employed for TERA Algorithms
20.3.3.2 Main Traffic Risk Condition Detection
20.3.3.2.1 Risk of Frontal/(Lateral) Collision
20.3.3.2.2 Criteria of Assigning the Level of Risk
20.3.3.2.3 Risk of Lane/Road Departure
20.3.3.2.4 Risk of Approaching a Dangerous Curve Too Fast
20.3.4 Algorithmfor Estimating the Intention of the Driver
20.3.5 TERA Implementation
20.4 Conclusions
References
21 Present and Future of Simulation Traffic Models
21.1 Introduction
21.2 Traffic Simulator
21.2.1 General Overview: A Survey of Road Traffic Simulations
21.2.2 Types of Simulator
21.2.3 Case Studies of Traffic Simulator
21.2.4 Vehicle Model Properties
21.2.4.1 Perception Topics
21.2.4.2 Cognition Topics
21.2.4.3 Actuation/Control Topics
21.2.4.4 Implementation of Vehicle Model
21.2.5 Two Examples of Applications with Traffic Simulator
21.2.5.1 The University of Michigan Microscopic Traffic Simulator
21.2.5.2 The MECTRON-HMI Group at University of Modena and Reggio Emilia Driving Simulator used in H
21.2.6 Integration of Driver, Vehicle and Environment in a Closed-Loop System: The AIDE Project
21.2.6.1 General DVE Architecture
21.2.6.2 Time Frame for DVE Model
21.3 Conclusions and Further Steps
21.3.1 Towards a Multi-Agent Approach
21.3.2 New Developments and Prospective
21.3.3 Open Points and Future Steps
References
Index
driver behaviour modelling
driver behavior analysis
driver behavior modeling
driver model
driver-based model example
Tags: Carlo Cacciabue, Modelling Driver, Automotive Environments
