Introduction To Self Driving Vehicle Technology
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Introduction To Self Driving Vehicle Technology
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Author : Hanky Sjafrie
language : en
Publisher: CRC Press
Release Date : 2019-11-27
Introduction To Self Driving Vehicle Technology written by Hanky Sjafrie and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-27 with Computers categories.
This book aims to teach the core concepts that make Self-driving vehicles (SDVs) possible. It is aimed at people who want to get their teeth into self-driving vehicle technology, by providing genuine technical insights where other books just skim the surface. The book tackles everything from sensors and perception to functional safety and cybersecurity. It also passes on some practical know-how and discusses concrete SDV applications, along with a discussion of where this technology is heading. It will serve as a good starting point for software developers or professional engineers who are eager to pursue a career in this exciting field and want to learn more about the basics of SDV algorithms. Likewise, academic researchers, technology enthusiasts, and journalists will also find the book useful. Key Features: Offers a comprehensive technological walk-through of what really matters in SDV development: from hardware, software, to functional safety and cybersecurity Written by an active practitioner with extensive experience in series development and research in the fields of Advanced Driver Assistance Systems (ADAS) and Autonomous Driving Covers theoretical fundamentals of state-of-the-art SLAM, multi-sensor data fusion, and other SDV algorithms. Includes practical information and hands-on material with Robot Operating System (ROS) and Open Source Car Control (OSCC). Provides an overview of the strategies, trends, and applications which companies are pursuing in this field at present as well as other technical insights from the industry.
Theories And Practices Of Self Driving Vehicles
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Author : Qingguo Zhou
language : en
Publisher: Elsevier
Release Date : 2022-07-03
Theories And Practices Of Self Driving Vehicles written by Qingguo Zhou and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-03 with Technology & Engineering categories.
Self-driving vehicles are a rapidly growing area of research and expertise. Theories and Practice of Self-Driving Vehicles presents a comprehensive introduction to the technology of self driving vehicles across the three domains of perception, planning and control. The title systematically introduces vehicle systems from principles to practice, including basic knowledge of ROS programming, machine and deep learning, as well as basic modules such as environmental perception and sensor fusion. The book introduces advanced control algorithms as well as important areas of new research. This title offers engineers, technicians and students an accessible handbook to the entire stack of technology in a self-driving vehicle. Theories and Practice of Self-Driving Vehicles presents an introduction to self-driving vehicle technology from principles to practice. Ten chapters cover the full stack of driverless technology for a self-driving vehicle. Written by two authors experienced in both industry and research, this book offers an accessible and systematic introduction to self-driving vehicle technology. Provides a comprehensive introduction to the technology stack of a self-driving vehicle Covers the three domains of perception, planning and control Offers foundational theory and best practices Introduces advanced control algorithms and high-potential areas of new research Gives engineers, technicians and students an accessible handbook to self-driving vehicle technology and applications
Introduction To Driverless Self Driving Cars
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Author : Lance Eliot
language : en
Publisher: Lbe Press Publishing
Release Date : 2018
Introduction To Driverless Self Driving Cars written by Lance Eliot and has been published by Lbe Press Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Based on his popular AI Insider column and reader feedback, this is Dr. Eliot's highly rated introductory coverage on the emergence and advent of autonomous driverless self-driving cars. Readable for everyone, discover the underlying technology that makes self-driving cars achievable. Furthermore, learn about the key business aspects, economics, and politics that will shape the future of self-driving cars. Essential elements of Artificial Intelligence (AI) and Machine Learning are covered, along with blockchain, bitcoins, genetic algorithms, neural networks, and more.
Autonomous Vehicles
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Author : George Dimitrakopoulos
language : en
Publisher: Elsevier
Release Date : 2021-04-15
Autonomous Vehicles written by George Dimitrakopoulos and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-15 with Transportation categories.
Autonomous Vehicles: Technologies, Regulations, and Societal Impacts explores both the autonomous driving concepts and the key hardware and software enablers, Artificial intelligence tools, needed infrastructure, communication protocols, and interaction with non-autonomous vehicles. It analyses the impacts of autonomous driving using a scenario-based approach to quantify the effects on the overall economy and affected sectors. The book assess from a qualitative and quantitative approach, the future of autonomous driving, and the main drivers, challenges, and barriers. The book investigates whether individuals are ready to use advanced automated driving vehicles technology, and to what extent we as a society are prepared to accept highly automated vehicles on the road. Building on the technologies, opportunities, strengths, threats, and weaknesses, Autonomous Vehicles: Technologies, Regulations, and Societal Impacts discusses the needed frameworks for automated vehicles to move inside and around cities. The book concludes with a discussion on what in applications comes next, outlining the future research needs. Broad, interdisciplinary and systematic coverage of the key issues in autonomous driving and vehicles Examines technological impact on society, governance, and the economy as a whole Includes foundational topical coverage, case studies, objectives, and glossary
Autonomous Driving
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Author : Markus Maurer
language : en
Publisher: Springer
Release Date : 2016-05-21
Autonomous Driving written by Markus Maurer and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-21 with Technology & Engineering categories.
This book takes a look at fully automated, autonomous vehicles and discusses many open questions: How can autonomous vehicles be integrated into the current transportation system with diverse users and human drivers? Where do automated vehicles fall under current legal frameworks? What risks are associated with automation and how will society respond to these risks? How will the marketplace react to automated vehicles and what changes may be necessary for companies? Experts from Germany and the United States define key societal, engineering, and mobility issues related to the automation of vehicles. They discuss the decisions programmers of automated vehicles must make to enable vehicles to perceive their environment, interact with other road users, and choose actions that may have ethical consequences. The authors further identify expectations and concerns that will form the basis for individual and societal acceptance of autonomous driving. While the safety benefits of such vehicles are tremendous, the authors demonstrate that these benefits will only be achieved if vehicles have an appropriate safety concept at the heart of their design. Realizing the potential of automated vehicles to reorganize traffic and transform mobility of people and goods requires similar care in the design of vehicles and networks. By covering all of these topics, the book aims to provide a current, comprehensive, and scientifically sound treatment of the emerging field of “autonomous driving".
Creating Autonomous Vehicle Systems
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Author : Liu Shaoshan
language : en
Publisher: Springer Nature
Release Date : 2017-10-25
Creating Autonomous Vehicle Systems written by Liu Shaoshan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-25 with Mathematics categories.
This book is the first technical overview of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences of creating 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 about its 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, we are able to test new algorithms and update the HD map—plus, train better recognition, tracking, and decision models. This book consists of nine chapters. Chapter 1 provides an overview of autonomous vehicle systems; Chapter 2 focuses on localization technologies; Chapter 3 discusses traditional techniques used for perception; Chapter 4 discusses deep learning based techniques for perception; Chapter 5 introduces the planning and control sub-system, especially prediction and routing technologies; Chapter 6 focuses on motion planning and feedback control of the planning and control subsystem; Chapter 7 introduces reinforcement learning-based planning and control; Chapter 8 delves into the details of client systems design; and Chapter 9 provides the details of cloud platforms for autonomous driving. 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 plenty of references for an effective, deeper exploration of the various technologies.
Autonomous Vehicle Technology
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Author : James M. Anderson
language : en
Publisher: Rand Corporation
Release Date : 2014-01-10
Autonomous Vehicle Technology written by James M. Anderson and has been published by Rand Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-10 with Transportation categories.
The automotive industry appears close to substantial change engendered by “self-driving” technologies. This technology offers the possibility of significant benefits to social welfare—saving lives; reducing crashes, congestion, fuel consumption, and pollution; increasing mobility for the disabled; and ultimately improving land use. This report is intended as a guide for state and federal policymakers on the many issues that this technology raises.
Creating Autonomous Vehicle Systems Second Edition
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Author : Liu Shaoshan
language : en
Publisher: Springer
Release Date : 2020-09-11
Creating Autonomous Vehicle Systems Second Edition written by Liu Shaoshan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-11 with Mathematics categories.
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 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.
Computing Systems For Autonomous Driving
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Author : Weisong Shi
language : en
Publisher: Springer Nature
Release Date : 2021-11-15
Computing Systems For Autonomous Driving written by Weisong Shi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-15 with Computers categories.
This book on computing systems for autonomous driving takes a comprehensive look at the state-of-the-art computing technologies, including computing frameworks, algorithm deployment optimizations, systems runtime optimizations, dataset and benchmarking, simulators, hardware platforms, and smart infrastructures. The objectives of level 4 and level 5 autonomous driving require colossal improvement in the computing for this cyber-physical system. Beginning with a definition of computing systems for autonomous driving, this book introduces promising research topics and serves as a useful starting point for those interested in starting in the field. In addition to the current landscape, the authors examine the remaining open challenges to achieve L4/L5 autonomous driving. Computing Systems for Autonomous Driving provides a good introduction for researchers and prospective practitioners in the field. The book can also serve as a useful reference for university courses on autonomous vehicle technologies.This book on computing systems for autonomous driving takes a comprehensive look at the state-of-the-art computing technologies, including computing frameworks, algorithm deployment optimizations, systems runtime optimizations, dataset and benchmarking, simulators, hardware platforms, and smart infrastructures. The objectives of level 4 and level 5 autonomous driving require colossal improvement in the computing for this cyber-physical system. Beginning with a definition of computing systems for autonomous driving, this book introduces promising research topics and serves as a useful starting point for those interested in starting in the field. In addition to the current landscape, the authors examine the remaining open challenges to achieve L4/L5 autonomous driving. Computing Systems for Autonomous Driving provides a good introduction for researchers and prospective practitioners in the field. The book can also serve as a useful reference for university courses on autonomous vehicle technologies.
Creating Autonomous Vehicle Systems
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Author : Shaoshan Liu
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2017-10-25
Creating Autonomous Vehicle Systems written by Shaoshan Liu and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-25 with Computers categories.
This book is the first technical overview of autonomous vehicles written for a general computing and engineering audience. The authors share their practical experiences of creating 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 about its 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, we are able to test new algorithms and update the HD map—plus, train better recognition, tracking, and decision models. This book consists of nine chapters. Chapter 1 provides an overview of autonomous vehicle systems; Chapter 2 focuses on localization technologies; Chapter 3 discusses traditional techniques used for perception; Chapter 4 discusses deep learning based techniques for perception; Chapter 5 introduces the planning and control sub-system, especially prediction and routing technologies; Chapter 6 focuses on motion planning and feedback control of the planning and control subsystem; Chapter 7 introduces reinforcement learning-based planning and control; Chapter 8 delves into the details of client systems design; and Chapter 9 provides the details of cloud platforms for autonomous driving. 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 plenty of references for an effective, deeper exploration of the various technologies.