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Titlebook: Creating Autonomous Vehicle Systems, Second Edition; Shaoshan Liu,Liyun Li,Jean-Luc Gaudiot Book 2020Latest edition Springer Nature Switze

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發(fā)表于 2025-3-21 16:33:55 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Creating Autonomous Vehicle Systems, Second Edition
編輯Shaoshan Liu,Liyun Li,Jean-Luc Gaudiot
視頻videohttp://file.papertrans.cn/240/239344/239344.mp4
叢書名稱Synthesis Lectures on Computer Science
圖書封面Titlebook: Creating Autonomous Vehicle Systems, Second Edition;  Shaoshan Liu,Liyun Li,Jean-Luc Gaudiot Book 2020Latest edition Springer Nature Switze
描述This book is one of the first technical overviews of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences designing autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. The algorithm subsystem extracts meaningful information from sensor raw data to understand its environment and make decisions as to its future actions. The client subsystem integrates these algorithms to meet real-time and reliability requirements. The cloud platform provides offline computing and storage capabilities for autonomous vehicles. Using the cloud platform, new algorithms can be tested so as to update the HD map—in addition to training better recognition, tracking, and decision models..Since the first edition of this book was released, many universities have adopted it in their autonomous driving classes, and the aut
出版日期Book 2020Latest edition
版次2
doihttps://doi.org/10.1007/978-3-031-01805-3
isbn_softcover978-3-031-00677-7
isbn_ebook978-3-031-01805-3Series ISSN 1932-1228 Series E-ISSN 1932-1686
issn_series 1932-1228
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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Water Politics and Development Cooperationd on lane segmentation of the HD-maps. Routing simply informs the autonomous vehicle how to reach its destination by following a sequence of lanes on the HD-maps. Its output is also sent to the downstream planning and control modules.
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Perception in Autonomous Driving,trol depend on a correct perception output, its importance cannot be overstated. In this chapter, major functionalities of perception are covered, along with public datasets, problem definitions, and typical algorithms. Algorithms based on neural networks are discussed in the next chapter.
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Prediction and Routing,d on lane segmentation of the HD-maps. Routing simply informs the autonomous vehicle how to reach its destination by following a sequence of lanes on the HD-maps. Its output is also sent to the downstream planning and control modules.
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Book 2020Latest editionheir practical experiences designing autonomous vehicle systems. These systems are complex, consisting of three major subsystems: (1) algorithms for localization, perception, and planning and control; (2) client systems, such as the robotics operating system and hardware platform; and (3) the cloud
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https://doi.org/10.1007/978-3-540-76711-4 planning and control problems. We thus conclude that reinforcement learning-based planning and control will gradually become a viable solution to autonomous driving planning and control problems or at least become a necessary complement to current optimization approaches.
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