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Human Modelling in Assisted Transportation: Models, Tools and Risk Methods

✍ Scribed by Erik Hollnagel (auth.), P. Carlo Cacciabue, Magnus Hjälmdahl, Andreas Luedtke, Costanza Riccioli (eds.)


Publisher
Springer-Verlag Mailand
Year
2011
Tongue
English
Leaves
401
Edition
1
Category
Library

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✦ Synopsis


In modern society, the human being is the central element of the design process of non-fully automated control and safety system, as well as the major source and contributor to accidents. Therefore, accounting for human modelling is necessary in design processes and in safety assessments, in order to ensure appropriate consideration of human factors. These issues are particularly true for the domain of transportation, where safety related aspects are of paramount importance for their impact on citizen well being, in consideration of the simple fact that almost everybody makes daily usage of public and private transportation systems.

Even though the behavioural and cognitive science has dealt with this problem for decades, the issue of modelling human behaviour remains central to the topic of design of human-machine systems. To tackle this issue, three Eu Co-funded projects, ISi-PADAS, ITERATE and HUMAN, will provide, in different domains, overall models of the joint cognitive systems, represented by the human in control, the governed machine and the working environment. These models, in addition to providing an improved understanding of the interactions between human and machines in a design perspective, enable the consideration of human error in risk-based approaches and the development of appropriate countermeasures.

The objective of this book, which is the result the Workshop “Human Modelling in Assisted Transportation” (HMAT), is to provide an overview of the state of the art of the problem of human behaviour modelling in transportation systems, and to confront models, methods and tools developed within these three projects with the ongoing research carried out worldwide.

✦ Table of Contents


Front Matter....Pages i-ix
Front Matter....Pages 1-1
The Human in Control: Modelling What Goes Right Versus Modelling What Goes Wrong....Pages 3-7
The Art to Make an Error: The Dilemma Between Prevention, Learning and Mitigation....Pages 9-13
Modeling Differences in Behavior Within and Between Drivers....Pages 15-22
Drivers’ Information Processing, Decision-Making and the Role of Emotions: Predictions of the Risk Monitor Model....Pages 23-32
To What Extent May Assistance Systems Correct and Prevent ‘Erroneous’ Behaviour of the Driver?....Pages 33-41
Man–machine Integration Design and Analysis System (MIDAS) v5: Augmentations, Motivations, and Directions for Aeronautics Applications....Pages 43-54
Operational Modeling and Data Integration for Management and Design....Pages 55-63
The ISi-PADAS Project—Human Modelling and Simulation to support Human Error Risk Analysis of Partially Autonomous Driver Assistance Systems....Pages 65-77
The HUMAN Project: Model-Based Analysis of Human Errors During Aircraft Cockpit System Design....Pages 79-95
The ITERATE Project—Overview, Theoretical Framework and Validation....Pages 97-106
Front Matter....Pages 107-107
From Theoretical Model to Experimental Data: A Structured Approach to Design Experiments to Seed a Model of Vehicle Operation with New Systems....Pages 109-117
Learning Optimal Control Strategies from Interactions with a PADAS....Pages 119-127
Selecting Human Error Types for Cognitive Modelling and Simulation....Pages 129-138
Modelling Driver Behaviour in the Case of Failures in a Steer-by-Wire System....Pages 139-146
Flexible Design and Implementation of Cognitive Models for Predicting Pilot Errors in Cockpit Design....Pages 147-154
Effective and Acceptable Forward Collision Warning Systems Based on Relationships Between Car-Following Behaviour and Reaction to Deceleration of Lead Vehicle....Pages 155-164
Modelling and Validating Pilots’ Visual Attention Allocation During the Interaction with an Advanced Flight Management System....Pages 165-172
Estimating Traffic System Wide Impacts of Driver Assistance Systems Using Traffic Simulation....Pages 173-180
Modelling Aspects of Longitudinal Control in an Integrated Driver Model....Pages 181-189
Towards Model-Based AHMI Automatic Evaluation....Pages 191-198
Front Matter....Pages 107-107
Darmstadt Risk Analysis Method (DRAM)....Pages 199-206
Modeling Pilot Situation Awareness....Pages 207-213
Review of Models of Driver Behaviour and Development of a Unified Driver Behaviour Model for Driving in Safety Critical Situations....Pages 215-223
Integrating Anticipatory Competence into a Bayesian Driver Model....Pages 225-232
JDVE: A Joint Driver-Vehicle-Environment Simulation Platform for the Development and Accelerated Testing of Automotive Assistance and Automation Systems....Pages 233-240
Effects of Distraction and Traffic Events Expectation on Drivers’ Performances in a Longitudinal Control Task....Pages 241-248
Front Matter....Pages 249-249
Human Driver Modelling and Simulation into a Virtual Road Environment....Pages 251-262
Driver Behaviour and User Acceptance of Cooperative Systems Based on Infrastructure-to-Vehicle Communication....Pages 263-274
Exploratory Investigation of Vibration Floor as Potential Collision Warning....Pages 275-281
The Influence of Predictability and Frequency of Events on the Gaze Behaviour While Driving....Pages 283-290
A Hierarchical Task Analysis of Merging onto a Freeway—Comparison of Driver’s and Driver Model’s Task Representation....Pages 291-298
Predicting the Effect of Driver Assistance via Simulation....Pages 299-306
Simulation Study for Driver Behaviour Analysis as a Basis for the Design of a Partially Autonomous Driver Assistance System....Pages 307-315
Application of Simulation Based Risk Assessment for Driver Assistance Systems Development....Pages 317-325
Human Factors Engineering in Train Cab Design—Prospects and Problems....Pages 327-333
Assessment of Transportation System Resilience....Pages 335-341
Effects of Situational Characteristics on Drivers’ Merging into Freeway Traffic....Pages 343-351
A Reinforcement Learning Approach for Designing and Optimizing Interaction Strategies for a Human–Machine Interface of a PADAS....Pages 353-361
The Multisensory Driver: Contributions from the Time-Window-of-Integration Model....Pages 363-371
Front Matter....Pages 373-373
Culture Implications on Future Work Design—New Technologies and Collaborations for Controllers and Pilots....Pages 375-382
Front Matter....Pages 373-373
Cultural Variation of Views on Effective Crew Resource Management Skills....Pages 383-390

✦ Subjects


Automotive Engineering; Simulation and Modeling; Psychology, general; Artificial Intelligence (incl. Robotics); Aerospace Technology and Astronautics


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