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007			cr nn 008mamaa
008			220601s2020 sz | s |||| 0|eng d
020			_a9783031018053
024	7		_a10.1007/978-3-031-01805-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTL152.8 _b2020 EB
100	1		_aLiu, Shaoshan _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686116
245	1	0	_aCreating Autonomous Vehicle Systems _cby Liu Shaoshan, Li Liyun, Tang Jie, Wu Shuang, Gaudiot Jean-Luc
250			_a2nd edition 2020
264		1	_aCham _bSpringer International Publishing _c2020
300			_a1 recurso en línea (XXIII, 221 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Computer Science _x1932-1686
505	0		_aPreface to the Second Edition -- Teaching and Learning from This Book -- Introduction to Autonomous Driving -- Autonomous Vehicle Localization -- Perception in Autonomous Driving -- Deep Learning in Autonomous Driving Perception -- Prediction and Routing -- Decision, Planning, and Control -- Reinforcement Learning-Based Planning and Control -- Client Systems for Autonomous Driving -- Cloud Platform for Autonomous Driving -- Autonomous Last-Mile Delivery Vehicles in Complex Traffic Environments -- PerceptIn's Autonomous Vehicles Lite -- Author Biographies.
520			_aThis 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 authors received many helpful comments and feedback from readers. Based on this, the second edition was improved by extending and rewriting multiple chapters and adding two commercial test case studies. In addition, a new section entitled "Teaching and Learning from this Book" was added to help instructors better utilize this book in their classes. The second edition captures the latest advances in autonomous driving and that it also presents usable real-world case studies to help readers better understand how to utilize their lessons in commercial autonomous driving projects. This book should be useful to students, researchers, and practitioners alike. Whether you are an undergraduate or a graduate student interested in autonomous driving, you will find herein a comprehensive overview of the whole autonomous vehicle technology stack. If you are an autonomous driving practitioner, the many practical techniques introduced in this book will be of interest to you. Researchers will also find extensive references for an effective, deeper exploration of the various technologies.
988			_aSynthesis Collection of Technology_2020
650		7	_2embne _9673285 _aAutomóviles _xControl automático
650		7	_2embne _9151458 _aVehículos eléctricos
650		7	_9687883 _aVehículos de motor _xConducción
700	1		_aLi, Liyun _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686946
700	1		_aTang, Jie _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686947
700	1		_aShuang, Wu _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686948
700	1		_aGaudiot, Jean-Luc _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686949
776	0	8	_iPrinted edition: _z9783031000737
776	0	8	_iPrinted edition: _z9783031006777
776	0	8	_iPrinted edition: _z9783031029332
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-01805-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2023 _dz _esc _zSI