Theories and Practices of Self-Driving Vehicles PDF Download
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Author: Qingguo Zhou
Publisher: Elsevier
ISBN: 0323994490
Category : Technology & Engineering
Languages : en
Pages : 346
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Book Description
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
Author: Qingguo Zhou
Publisher: Elsevier
ISBN: 0323994490
Category : Technology & Engineering
Languages : en
Pages : 346
Get Book Here
Book Description
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
Author: Markus Maurer
Publisher: Springer
ISBN: 3662488477
Category : Technology & Engineering
Languages : en
Pages : 698
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Book Description
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".
Author: James M. Anderson
Publisher: Rand Corporation
ISBN: 0833084372
Category : Transportation
Languages : en
Pages : 215
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Book Description
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.
Author: Peng Hang
Publisher: CRC Press
ISBN: 1000625028
Category : Mathematics
Languages : en
Pages : 237
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Book Description
This book details cutting-edge research into human-like driving technology, utilising game theory to better suit a human and machine hybrid driving environment. Covering feature identification and modelling of human driving behaviours, the book explains how to design an algorithm for decision making and control of autonomous vehicles in complex scenarios. Beginning with a review of current research in the field, the book uses this as a springboard from which to present a new theory of human-like driving framework for autonomous vehicles. Chapters cover system models of decision making and control, driving safety, riding comfort and travel efficiency. Throughout the book, game theory is applied to human-like decision making, enabling the autonomous vehicle and the human driver interaction to be modelled using noncooperative game theory approach. It also uses game theory to model collaborative decision making between connected autonomous vehicles. This framework enables human-like decision making and control of autonomous vehicles, which leads to safer and more efficient driving in complicated traffic scenarios. The book will be of interest to students and professionals alike, in the field of automotive engineering, computer engineering and control engineering.
Author: Amit Kumar Tyagi
Publisher: Springer Nature
ISBN: 9811976228
Category : Technology & Engineering
Languages : en
Pages : 407
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Book Description
This book provides fundamental principles of intelligent transport systems with comprehensive insight and state of the art of vehicles, vehicular technology, connecting vehicles, and intelligent vehicles/autonomous intelligent vehicles. The book discusses different approaches for multiple sensor-based multiple-objects tracking, in addition to blockchain-based solutions for building tamper-proof sensing devices. It introduces various algorithms for security, privacy, and trust for intelligent vehicles. This book countermeasures all the drawbacks and provides useful information to students, researchers, and scientific communities. It contains chapters from national and international experts and will be essential for researchers and advanced students from academia, and industry experts who are working on intelligent transportation systems.
Author: Hong Cheng
Publisher: Springer Science & Business Media
ISBN: 1447122801
Category : Computers
Languages : en
Pages : 151
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Book Description
This important text/reference presents state-of-the-art research on intelligent vehicles, covering not only topics of object/obstacle detection and recognition, but also aspects of vehicle motion control. With an emphasis on both high-level concepts, and practical detail, the text links theory, algorithms, and issues of hardware and software implementation in intelligent vehicle research. Topics and features: presents a thorough introduction to the development and latest progress in intelligent vehicle research, and proposes a basic framework; provides detection and tracking algorithms for structured and unstructured roads, as well as on-road vehicle detection and tracking algorithms using boosted Gabor features; discusses an approach for multiple sensor-based multiple-object tracking, in addition to an integrated DGPS/IMU positioning approach; examines a vehicle navigation approach using global views; introduces algorithms for lateral and longitudinal vehicle motion control.
Author: Andreas Herrmann
Publisher: Emerald Group Publishing
ISBN: 1787148335
Category : Business & Economics
Languages : en
Pages : 460
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Book Description
The technology and engineering behind autonomous driving is advancing at pace. This book presents the latest technical advances and the economic, environmental and social impact driverless cars will have on individuals and the automotive industry.
Author: Mustapha Mouloua
Publisher: CRC Press
ISBN: 0429857454
Category : Computers
Languages : en
Pages : 630
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Book Description
This two-volume set addresses a variety of human factors issues and engineering concerns across various real-world applications such as aviation and driving, cybersecurity, and healthcare systems. The contents of these books also present recent theories and methods related to human performance, workload and usability assessment in automated and autonomous systems. In this set, the authors discuss both current and developing topics of advanced automation technologies and present emerging practical challenges. Topics covered include unmanned aerial systems and self-driving cars, individual and team performance, human-robot interaction, and operator selection and training. Both practical and theoretical discussions of modern automated and autonomous systems are provided throughout each of the volumes. These books are suitable for those first approaching the issues to those well versed in these fast-moving areas, including students, teachers, researchers, engineers, and policy makers alike. Volume 1 - Human Performance in Automated and Autonomous Systems: Current Theory and Methods Volume 2 - Human Performance in Automated and Autonomous Systems: Emerging Issues and Practical Perspectives
Author: Andreas Riener
Publisher: Springer Nature
ISBN: 303077726X
Category : Technology & Engineering
Languages : en
Pages : 603
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Book Description
This book is dedicated to user experience design for automated driving to address humane aspects of automated driving, e.g., workload, safety, trust, ethics, and acceptance. Automated driving has experienced a major development boost in recent years. However, most of the research and implementation has been technology-driven, rather than human-centered. The levels of automated driving have been poorly defined and inconsistently used. A variety of application scenarios and restrictions has been ambiguous. Also, it deals with human factors, design practices and methods, as well as applications, such as multimodal infotainment, virtual reality, augmented reality, and interactions in and outside users. This book aims at 1) providing engineers, designers, and practitioners with a broad overview of the state-of-the-art user experience research in automated driving to speed-up the implementation of automated vehicles and 2) helping researchers and students benefit from various perspectives and approaches to generate new research ideas and conduct more integrated research.
Author: David Michael Stavens
Publisher: Stanford University
ISBN:
Category :
Languages : en
Pages : 104
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Book Description
Every year, 1.2 million people die in automobile accidents and up to 50 million are injured. Many of these deaths are due to driver error and other preventable causes. Autonomous or highly aware cars have the potential to positively impact tens of millions of people. Building an autonomous car is not easy. Although the absolute number of traffic fatalities is tragically large, the failure rate of human driving is actually very small. A human driver makes a fatal mistake once in about 88 million miles. As a co-founding member of the Stanford Racing Team, we have built several relevant prototypes of autonomous cars. These include Stanley, the winner of the 2005 DARPA Grand Challenge and Junior, the car that took second place in the 2007 Urban Challenge. These prototypes demonstrate that autonomous vehicles can be successful in challenging environments. Nevertheless, reliable, cost-effective perception under uncertainty is a major challenge to the deployment of robotic cars in practice. This dissertation presents selected perception technologies for autonomous driving in the context of Stanford's autonomous cars. We consider speed selection in response to terrain conditions, smooth road finding, improved visual feature optimization, and cost effective car detection. Our work does not rely on manual engineering or even supervised machine learning. Rather, the car learns on its own, training itself without human teaching or labeling. We show this "self-supervised" learning often meets or exceeds traditional methods. Furthermore, we feel self-supervised learning is the only approach with the potential to provide the very low failure rates necessary to improve on human driving performance.
