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

Colaborador(es): Murphey, Yi Lu [editor.] | Kolmanovsky, Ilya [editor.] | Watta, Paul [editor.] | SpringerLink (Online service)Tipo de material: TextoTextoSeries Lecture Notes in Intelligent Transportation and InfrastructureEditor: Cham : Springer International Publishing : Imprint: Springer, 2023Edición: 1st ed. 2023Descripción: VIII, 567 p. 265 illus., 252 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783031067808Tema(s): Automotive engineering | Computational intelligence | Transportation engineering | Traffic engineering | Human-machine systems | Automotive Engineering | Computational Intelligence | Transportation Technology and Traffic Engineering | Human-Machine InterfacesFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 629.2 Clasificación LoC:TL1-483Recursos en línea: Libro electrónicoTexto
Contenidos:
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. .
En: Springer Nature eBookResumen: 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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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. .

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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