{"product_id":"construction-methods-for-an-autonomous-driving-map-in-an-intelligent-network-environment-9780443273162","title":"Construction Methods for an Autonomous Driving Map in an Intelligent Network Environment","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003eConstruction Methods for an Autonomous Driving Map in an Intelligent Network Environment is a book that discusses the use of advanced machine learning and artificial intelligence theories to develop an Autonomous Driving Map. It covers areas such as fusion target perception, cross-field of view object perception, vehicle motion recognition, and vehicle trajectory prediction, promoting the development of Intelligent \u0026amp; Connected Transportation and autonomous driving applications. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 196 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 09 April 2024\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Elsevier - Health Sciences Division\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eConstruction Methods for an Autonomous Driving Map in an Intelligent Network Environment play a pivotal role in advancing Intelligent \u0026amp; Connected Transportation, while also fostering the practical application of autonomous driving. This comprehensive book delves into various areas, including the fusion target perception method based on vehicle vision and millimeter wave radar, the cross-field of view object perception method, the vehicle motion recognition method utilizing vehicle road fusion information, and the vehicle trajectory prediction method leveraging improved hybrid neural networks. Additionally, it presents a novel approach for constructing driving maps driven by road perception fusion.\u003cbr\u003e\u003cbr\u003eBy leveraging advanced computer techniques, this book employs cutting-edge machine learning and artificial intelligence theories to guide readers through the intricate process of constructing an Autonomous Driving Map. It offers a comprehensive exploration of the fusion target perception, cross-field of view object perception, vehicle motion recognition, and vehicle trajectory prediction methods, providing valuable insights into the development of autonomous driving technologies.\u003cbr\u003e\u003cbr\u003eThe book's comprehensive coverage and in-depth analysis make it an invaluable resource for researchers, engineers, and practitioners in the field of intelligent transportation systems. Its practical applications and real-world examples further enhance its relevance and applicability, making it a must-read for anyone interested in advancing the future of transportation.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 328g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 152 x 230 x 12 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9780443273162\u003c\/p\u003e","brand":"ZhijunChen","offers":[{"title":"Paperback \/ softback","offer_id":45866747363578,"sku":"9780443273162","price":123.15,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/files\/1714167162490_book.jpg?v=1715113303","url":"https:\/\/shulphink.com\/products\/construction-methods-for-an-autonomous-driving-map-in-an-intelligent-network-environment-9780443273162","provider":"Shulph Ink","version":"1.0","type":"link"}