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Full Description
This book describes different methods that are relevant to the development and testing of control algorithms for advanced driver assistance systems (ADAS) and automated driving functions (ADF). These control algorithms need to respond safely, reliably and optimally in varying operating conditions. Also, vehicles have to comply with safety and emission legislation.
The text describes how such control algorithms can be developed, tested and verified for use in real-world driving situations. Owing to the complex interaction of vehicles with the environment and different traffic participants, an almost infinite number of possible scenarios and situations that need to be considered may exist. The book explains new methods to address this complexity, with reference to human interaction modelling, various theoretical approaches to the definition of real-world scenarios, and with practically-oriented examples and contributions, to ensure efficient development and testing of ADAS and ADF.
Control Strategies for Advanced Driver Assistance Systems and Autonomous Driving Functions is a collection of articles by international experts in the field representing theoretical and application-based points of view. As such, the methods and examples demonstrated in the book will be a valuable source of information for academic and industrial researchers, as well as for automotive companies and suppliers.
Contents
Chapter 1. Introduction - Control Strategies for Advanced Driver Assistance Systems and Autonomous Driving Functions: Development, Testing and Verification.- Chapter 2. Cooperation and the Role of Autonomy in Automated Driving.- Chapter 3. Robust, Real-world Emissions by Integrated ADF and Powertrain Control Development.- Chapter 4. Gaining Knowledge on Automated Driving's Safety - The risk-free VAAFO Tool.- Chapter 5. Statistical Model Checking for Scenario-based Verification of ADAS.- Chapter 6. Game Theory Based Traffic Modeling for Calibration of Automated Driving Algorithms.- Chapter 7. A Virtual Development and Evaluation Framework for ADAS - Case Study of a P-ACC in a Connected Environment.- Chapter 8. A Vehicle-in-the-Loop Emulation Platform for Demonstrating Intelligent Transportation Systems.- Chapter 9. Virtual Concept Development on the Example of a Motorway Chauffeur.- Chapter 10. Automation of Road Intersections Using Distributed Model Predictive Control.- Chapter 11. MPDM: Multi-policy Decision-making from Autonomous Driving to Social Robot Navigation.
