AI-enabled Technologies for Autonomous and Connected Vehicles / edited by Yi Lu Murphey, Ilya Kolmanovsky, Paul Watta

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Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Lecture Notes in Intelligent Transportation and Infrastructure | Springer eBook CollectionPublisher: Cham : Springer International Publishing, 2023Publisher: Cham : Imprint: Springer, 2023Edition: 1st ed. 2023Description: 1 Online-Ressource(VIII, 567 p. 265 illus., 252 illus. in color.)ISBN:

9783031067808

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Additional physical formats: 9783031067792 | 9783031067815 | 9783031067822 | Erscheint auch als: 9783031067792 Druck-Ausgabe | Erscheint auch als: 9783031067815 Druck-Ausgabe | Erscheint auch als: 9783031067822 Druck-AusgabeDOI: DOI: 10.1007/978-3-031-06780-8Online resources:

Summary: Advances, Opportunities and Challenges in AI-enabled Technologies for Autonomous and Connected Vehicles -- Semi-autonomous Truck Platooning with a Lean Sensor Package -- Environmental Perception for Intelligent Vehicles -- 3D Object Detection for Autonomous Driving. .Summary: 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. .PPN: PPN: 1816516597Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-ENG | ZDB-2-SXE | BSZ-2-SN-Auswahl

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