Computing Systems for Autonomous Driving (PDF)
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This book on computing systems for autonomous driving takes a comprehensive look at the state-of-the-art computing technologies, including computing frameworks, algorithm deployment optimizations, systems runtime optimizations, dataset and benchmarking, simulators, hardware platforms, and smart infrastructures. The objectives of level 4 and level 5 autonomous driving require colossal improvement in the computing for this cyber-physical system. Beginning with a definition of computing systems for autonomous driving, this book introduces promising research topics and serves as a useful starting point for those interested in starting in the field. In addition to the current landscape, the authors examine the remaining open challenges to achieve L4/L5 autonomous driving.
Computing Systems for Autonomous Driving provides a good introduction for researchers and prospective practitioners in the field. The book can also serve as a useful reference foruniversity courses on autonomous vehicle technologies.
Liangkai Liu is a PhD candidate at Wayne State University. His research is on connected and autonomous vehicles and edge computing. He has published papers in top conference and journals including SEC, ICDCS, HotEdge, Proceedings of IEEE, IoTJ, etc. He is the reviewer for several journals in transportation and computer systems domain including IEEE Communications Magazine, TVT, IoTJ, IEEENetwork Magazine, etc. He is the instructor for Autonomous Vehicle Technologies online Course at Wayne State University.
- Autoren: Weisong Shi , Liangkai Liu
- 2021, 1st ed. 2021, 232 Seiten, Englisch
- Verlag: Springer International Publishing
- ISBN-10: 3030815641
- ISBN-13: 9783030815646
- Erscheinungsdatum: 15.11.2021
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Größe: 7.29 MB
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