Overview
Discuss the emerging topic of automated driving from the viewpoint of academia and from industrial perspective
Provides a seamless coverage of all relevant systems for automated driving, their integration and their reliability assurance
Current state-of-the art will be extensively discussed and both progressive and conservative short-/mid-/long-term road maps will be considered
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Table of contents (34 chapters)
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Front Matter
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The Importance of Control for Automated Driving
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Front Matter
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Advances in Environment Sensing, Sensor Fusion, and Perception
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Front Matter
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In-Vehicle Architectures and Dependable Power Computing
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Front Matter
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Active and Functional Safety in Automated Driving
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Front Matter
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Keywords
About this book
The current state of the art of automated vehicle research, development and innovation is given. The book also addresses industry-driven roadmaps for major new technology advances as well as collaborative European initiatives supporting the evolvement of automated driving. Various examples highlight the state of development of automated driving as well as the way forward.
The book will be of interest to academics and researchers within engineering, graduate students, automotive engineers at OEMs and suppliers, ICT and software engineers, managers, and other decision-makers.
Editors and Affiliations
About the editors
Daniel Watzenig was born in Austria. He received his Master degree in electrical engineering and the doctoral degree in technical science from Graz University of Technology, Graz, Austria, in 2002 and 2006, respectively. He is currently divisional director of the automotive electronics and embedded software department of the Virtual Vehicle Research Center in Graz. Since 2009 he is an Associate Professor at the Institute of Electrical Measurement and Measurement Signal Processing, Graz University of Technology, Austria. He is author or co-author of over 120 peer-reviewed papers, book chapters, patents, and articles. His research interests focus on sensor fusion and signal processing, automotive control systems, uncertainty estimation, and robust optimization methods. In 2005 he was a visiting researcher at the University of Auckland, New Zealand, working on multi-sensor arrays and statistical signal processing. In 2011 he was visiting researcher and guest lecturer at the Federal University of Rio de Janeiro. He is IEEE Senior Member of the IEEE Control Systems, Signal Processing and Instrumentation & Measurement Societies. Furthermore, he is Vice President and member of the steering board of the EU ARTEMIS Industrial Association.
Martin Horn was born in Austria. He received his Master degree in electrical engineering and the doctoral degree in technical science from Graz University of Technology, Graz, Austria, in 1992 and 1998, respectively. From 2003 to 2008 he was is an Associate Professor at the Institute of Automation and Control at Graz University of Technology. From 2008 to 2014 he was full professor for Control and Mechatronic Systems at Klagenfurt University. Since 2014 he is full professor for Automation and Control at Graz University of Technology. He is author or co-author of around 100 peer-reviewed papers, book chapters, patents, and articles. His research interests focus on automotive control systems, robust control, variable structure systems and robust observer design.
Bibliographic Information
Book Title: Automated Driving
Book Subtitle: Safer and More Efficient Future Driving
Editors: Daniel Watzenig, Martin Horn
DOI: https://doi.org/10.1007/978-3-319-31895-0
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2017
Hardcover ISBN: 978-3-319-31893-6Published: 04 October 2016
Softcover ISBN: 978-3-319-81146-8Published: 14 June 2018
eBook ISBN: 978-3-319-31895-0Published: 23 September 2016
Edition Number: 1
Number of Pages: XVII, 620
Number of Illustrations: 84 b/w illustrations, 171 illustrations in colour
Topics: Automotive Engineering, Robotics and Automation, Transportation Technology and Traffic Engineering