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Control Strategies for Advanced Driver Assistance Systems and Autonomous Driving Functions
(Englisch)
Development, Testing and Verification
Waschl, Harald & Kolmanovsky, Ilya & Willems, Frank

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Control Strategies for Advanced Driver Assistance Systems and Autonomous Driving Functions

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Produktbeschreibung

Provides a detailed treatment of control development, testing and verification of advanced driving functions and driver assistance systems

Describes formal approaches to verification of such systems and at the same time presents real-world applications and examples

Includes a diverse set of perspectives on this large, interdisciplinary area, covering the topic of partially automated driving and driver assistance functions


Harald Waschl is Assistant Professor at the Johannes Kepler University Linz, where he is with the Institute for Design and Control of Mechatronical systems. He is working there in the field of optimal and model based control for automotive applications and testing of advanced driving functions.  

Ilya Kolmanovsky is a Professor of Aerospace Engineering at the University of Michigan with research interests in control applications to automotive and aerospace systems.  Prior to joining the University of Michigan, he has close to 15 years of industrial research experience in powertrain control at Ford Research and Advanced Engineering.

Frank Willems is a  Professor at Eindhoven University of Technology in the Mechanical Engineering, Control Systems Technology department. He is further a senior research scientist at TNO Automotive in Helmond in the Powertrains department.  



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.
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Provides a detailed treatment of control development, testing and verification of advanced driving functions and driver assistance systems

Describes formal approaches to verification of such systems and at the same time presents real-world applications and examples

Includes a diverse set of perspectives on this large, interdisciplinary area, covering the topic of partially automated driving and driver assistance functions

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.


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.


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.
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.


Über den Autor

rn Harald Waschl is Assistant Professor at the Johannes Kepler University Linz, where he is with the Institute for Design and Control of Mechatronical systems. He is working there in the field of optimal and model based control for automotive applications and testing of advanced driving functions.  

rn

rn Ilya Kolmanovsky is a Professor of Aerospace Engineering at the University of Michigan with research interests in control applications to automotive and aerospace systems.  Prior to joining the University of Michigan, he has close to 15 years of industrial research experience in powertrain control at Ford Research and Advanced Engineering.

rn

rn Frank Willems is a  Professor at Eindhoven University of Technology in the Mechanical Engineering, Control Systems Technology department. He is further a senior research scientist at TNO Automotive in Helmond in the Powertrains department.  
rn

rn


Inhaltsverzeichnis

Chapter 1. Introduction - Control Strategies for Advanced Driver Assistance Systems and Autonomous Driving Functions: Development, Testing and Veri¿cation.- 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 Veri¿cation of ADAS.- Chapter 6. Game Theory Based Traf¿c 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.


Klappentext

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.
rn
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.
rn
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.


Provides a detailed treatment of control development, testing and verification of advanced driving functions and driver assistance systems

Describes formal approaches to verification of such systems and at the same time presents real-world applications and examples

Includes a diverse set of perspectives on this large, interdisciplinary area, covering the topic of partially automated driving and driver assistance functions



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