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AI-enabled Technologies for Autonomous and Connected Vehicles: Lecture Notes in Intelligent Transportation and Infrastructure

Editat de Yi Lu Murphey, Ilya Kolmanovsky, Paul Watta
en Limba Engleză Hardback – 8 sep 2022
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. 

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Specificații

ISBN-13: 9783031067792
ISBN-10: 3031067797
Pagini: 567
Ilustrații: VIII, 567 p. 265 illus., 252 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 1.13 kg
Ediția:1st ed. 2023
Editura: Springer International Publishing
Colecția Springer
Seria Lecture Notes in Intelligent Transportation and Infrastructure

Locul publicării:Cham, Switzerland

Cuprins

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. 

Textul de pe ultima copertă

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. 



Caracteristici

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