Overview
- Reports on cutting-edge technologies for automated driving
- Describes advanced applications of machine learning, big data, AI and control
- Discusses aspects related to safety, energy efficiency, and human-machine interaction
Part of the book series: Lecture Notes in Intelligent Transportation and Infrastructure (LNITI)
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Table of contents (20 chapters)
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Front Matter
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Sensors and Perception
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Front Matter
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Automated Driving Decisions and Control
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Front Matter
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Advanced Driver Assistant Systems
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Front Matter
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Connected Autonomous Vehicles, Mobility, and Security
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Front Matter
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Keywords
- Automated Vehicle Control
- Autonomous Vehicle Perception
- V2V and V2X Communication
- Autonomous Driving
- Highly Automated Vehicles
- Self-learning decision
- Vehicle Safety Systems
- Driving simulators
- Electrified Mobility
- AI Safety Systems
- Autonomous Vehicle Security
- Sensor Fusion for Autonomous Driving
- Traffic Control
- Eco-Driving
About this book
This book reports on cutting-edge research and advances in the field of intelligent vehicle systems. It presents a broad range of AI-enabled technologies, with a focus on automated, autonomous and connected vehicle systems. It covers advanced machine learning technologies, including deep and reinforcement learning algorithms, transfer learning and learning from big data, as well as control theory applied to mobility and vehicle systems. Furthermore, it reports on cutting-edge technologies for environmental perception and vehicle-to-everything (V2X), discussing socioeconomic and environmental implications, and aspects related to human factors and energy-efficiency alike, of automated mobility. Gathering chapters written by renowned researchers and professionals, this book offers a good balance of theoretical and practical knowledge. It provides researchers, practitioners and policy makers with a comprehensive and timely guide on the field of autonomous driving technologies.
Editors and Affiliations
Bibliographic Information
Book Title: AI-enabled Technologies for Autonomous and Connected Vehicles
Editors: Yi Lu Murphey, Ilya Kolmanovsky, Paul Watta
Series Title: Lecture Notes in Intelligent Transportation and Infrastructure
DOI: https://doi.org/10.1007/978-3-031-06780-8
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Hardcover ISBN: 978-3-031-06779-2Published: 08 September 2022
Softcover ISBN: 978-3-031-06782-2Published: 09 September 2023
eBook ISBN: 978-3-031-06780-8Published: 07 September 2022
Series ISSN: 2523-3440
Series E-ISSN: 2523-3459
Edition Number: 1
Number of Pages: VIII, 567
Number of Illustrations: 13 b/w illustrations, 252 illustrations in colour
Topics: Automotive Engineering, Computational Intelligence, Transportation Technology and Traffic Engineering, Signal, Image and Speech Processing