Autonomous Vehicle Technology


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.




Creating Autonomous Vehicle Systems


Book Description

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 Vehicles, Volume 1


Book Description

AUTONOMOUS VEHICLES Addressing the current challenges, approaches and applications relating to autonomous vehicles, this groundbreaking new volume presents the research and techniques in this growing area, using Internet of Things (IoT), Machine Learning (ML), Deep Learning, and Artificial Intelligence (AI). This book provides and addresses the current challenges, approaches, and applications relating to autonomous vehicles, using Internet of Things (IoT), machine learning, deep learning, and Artificial Intelligence (AI) techniques. Several self-driving or autonomous (“driverless”) cars, trucks, and drones incorporate a variety of IoT devices and sensing technologies such as sensors, gyroscopes, cloud computing, and fog layer, allowing the vehicles to sense, process, and maintain massive amounts of data on traffic, routes, suitable times to travel, potholes, sharp turns, and robots for pipe inspection in the construction and mining industries. Few books are available on the practical applications of unmanned aerial vehicles (UAVs) and autonomous vehicles from a multidisciplinary approach. Further, the available books only cover a few applications and designs in a very limited scope. This new, groundbreaking volume covers real-life applications, business modeling, issues, and solutions that the engineer or industry professional faces every day that can be transformed using intelligent systems design of autonomous systems. Whether for the student, veteran engineer, or another industry professional, this book, and its companion volume, are must-haves for any library.




Autonomous Vehicles


Book Description

Better public policies can make the road smoother for self-driving vehicles and the society that soon will depend on them. Whether you find the idea of autonomous vehicles to be exciting or frightening, the truth is that they will soon become a significant everyday presence on streets and highways—not just a novel experiment attracting attention or giggles and sparking fears of runaway self-driving cars. The emergence of these vehicles represents a watershed moment in the history of transportation. If properly encouraged, this innovation promises not only to vastly improve road travel and generate huge benefits to travelers and businesses, but to also benefit the entire economy by reducing congestion and virtually eliminating vehicle accidents. The impacts of autonomous vehicles on land use, employment, and public finance are likely to be mixed. But widely assumed negative effects are generally overstated because they ignore plausible adjustments by the public and policymakers that could ameliorate them. This book by two transportation experts argues that policy analysts can play an important and constructive role in identifying and analyzing important policy issues and necessary steps to ease the advent of autonomous vehicles. Among the actions that governments must take are creating a framework for vehicle testing, making appropriate investments in the technology of highway networks to facilitate communication involving autonomous vehicles, and reforming pricing and investment policies to enable operation of autonomous vehicles to be safe and efficient. The authors argue that policymakers at all levels of government must address these and other issues sooner rather than later. Prompt and effective actions outlined in this book are necessary to ensure that autonomous vehicles will be safe and efficient when the public begins to adopt them as replacements for current vehicles.




Autonomous and Connected Vehicles


Book Description

AUTONOMOUS AND CONNECTED VEHICLES Discover the latest developments in autonomous vehicles and what the future holds for this exciting technology In Autonomous and Connected Vehicles, networking experts Dominique Paret and Hassina Rebaine deliver a robust exploration of the major technological changes taking place in the field, and describe the different levels of autonomy possible with current technologies and the legal and regulatory contexts in which new autonomous vehicles will circulate. The book also includes discussions of the sensors, including infrared, ultrasound, cameras, lidar, and radar, used by modern autonomous vehicles. Readers will enjoy the intuitive descriptions of Advanced Driver Assistance Systems (ADAS), network architectures (CAN-FD, FlexRay, and Backbone Ethernet), and software that power current and future autonomous vehicles. The authors also discuss how ADAS can be fused with data flowing over newer and faster network architectures and artificial intelligence to create greater levels of autonomy. The book also includes: A thorough introduction to the buzz and hype surrounding autonomous and connected vehicles, including a brief history of the autonomous vehicle Comprehensive explorations of common issues affecting autonomous and connected vehicles, including regulatory guidelines, legislation, relevant norms and standards, and insurance issues Practical discussions of autonomous vehicle sensors, from DAS to ADAS and HADAS, and VA L3 to L5 In-depth examinations of networks and architecture, including discussions of data fusion, artificial intelligence, and hardware architecture in vehicles Perfect for graduate and undergraduate students in programs dealing with the intersection of wireless communication technologies and vehicles, Autonomous and Connected Vehicles is also a must-read reference for industry professionals and researchers seeking a one-stop reference for the latest developments in vehicle communications technology.




Explainable Artificial Intelligence for Autonomous Vehicles


Book Description

Explainable AI for Autonomous Vehicles: Concepts, Challenges, and Applications is a comprehensive guide to developing and applying explainable artificial intelligence (XAI) in the context of autonomous vehicles. It begins with an introduction to XAI and its importance in developing autonomous vehicles. It also provides an overview of the challenges and limitations of traditional black-box AI models and how XAI can help address these challenges by providing transparency and interpretability in the decision-making process of autonomous vehicles. The book then covers the state-of-the-art techniques and methods for XAI in autonomous vehicles, including model-agnostic approaches, post-hoc explanations, and local and global interpretability techniques. It also discusses the challenges and applications of XAI in autonomous vehicles, such as enhancing safety and reliability, improving user trust and acceptance, and enhancing overall system performance. Ethical and social considerations are also addressed in the book, such as the impact of XAI on user privacy and autonomy and the potential for bias and discrimination in XAI-based systems. Furthermore, the book provides insights into future directions and emerging trends in XAI for autonomous vehicles, such as integrating XAI with other advanced technologies like machine learning and blockchain and the potential for XAI to enable new applications and services in the autonomous vehicle industry. Overall, the book aims to provide a comprehensive understanding of XAI and its applications in autonomous vehicles to help readers develop effective XAI solutions that can enhance autonomous vehicle systems' safety, reliability, and performance while improving user trust and acceptance. This book: Discusses authentication mechanisms for camera access, encryption protocols for data protection, and access control measures for camera systems. Showcases challenges such as integration with existing systems, privacy, and security concerns while implementing explainable artificial intelligence in autonomous vehicles. Covers explainable artificial intelligence for resource management, optimization, adaptive control, and decision-making. Explains important topics such as vehicle-to-vehicle (V2V) communication, vehicle-to-infrastructure (V2I) communication, remote monitoring, and control. Emphasizes enhancing safety, reliability, overall system performance, and improving user trust in autonomous vehicles. The book is intended to provide researchers, engineers, and practitioners with a comprehensive understanding of XAI's key concepts, challenges, and applications in the context of autonomous vehicles. It is primarily written for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer science and engineering, information technology, and automotive engineering.




Connected and Autonomous Vehicles in Smart Cities


Book Description

This book presents a comprehensive coverage of the five fundamental yet intertwined pillars paving the road towards the future of connected autonomous electric vehicles and smart cities. The connectivity pillar covers all the latest advancements and various technologies on vehicle-to-everything (V2X) communications/networking and vehicular cloud computing, with special emphasis on their role towards vehicle autonomy and smart cities applications. On the other hand, the autonomy track focuses on the different efforts to improve vehicle spatiotemporal perception of its surroundings using multiple sensors and different perception technologies. Since most of CAVs are expected to run on electric power, studies on their electrification technologies, satisfaction of their charging demands, interactions with the grid, and the reliance of these components on their connectivity and autonomy, is the third pillar that this book covers. On the smart services side, the book highlights the game-changing roles CAV will play in future mobility services and intelligent transportation systems. The book also details the ground-breaking directions exploiting CAVs in broad spectrum of smart cities applications. Example of such revolutionary applications are autonomous mobility on-demand services with integration to public transit, smart homes, and buildings. The fifth and final pillar involves the illustration of security mechanisms, innovative business models, market opportunities, and societal/economic impacts resulting from the soon-to-be-deployed CAVs. This book contains an archival collection of top quality, cutting-edge and multidisciplinary research on connected autonomous electric vehicles and smart cities. The book is an authoritative reference for smart city decision makers, automotive manufacturers, utility operators, smart-mobility service providers, telecom operators, communications engineers, power engineers, vehicle charging providers, university professors, researchers, and students who would like to learn more about the advances in CAEVs connectivity, autonomy, electrification, security, and integration into smart cities and intelligent transportation systems.




Creating Autonomous Vehicle Systems, Second Edition


Book Description

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.




Autonomous Vehicles


Book Description

Elon Musk thought that his company Tesla will have fully autonomous cars ready by the end of 2020. "There are no fundamental challenges left," he said recently. "There are a number of minor issues. And then there's a struggle to solve all these little problems and bring the whole thing together." Although the technology to allow a car to complete a journey without human interference (what the industry calls "level 5 autonomy") can move quickly, the development of a vehicle that can do so safely and legally is another matter. The novelty of autonomous technology is intended to turn our legal and social ties into daily transport. Importantly, without a driver behind the wheel, autonomous vehicles raise concerns about the liability and responsibility for the conduct of the lane. Therefore, this book is structured to answer many questions about autonomous vehicles and make you not only understand all the aspects of this emerging technology, but master the discussions and debates about the following topics: Chapter One: The rise of autonomous vehicles Autonomous vehicles become reality History of Autonomous vehicles Road Items Weights Society of Automotive Engineers (SAE International) Chapter Two: Tesla Autopilot AutoPilot AI Advanced Sensor Coverage Wide, Main and Narrow Forward Cameras Wide Main Narrow Forward Looking Side Cameras Rearward Looking Side Cameras Rear View Camera Radar Ultrasonic Sensors Processing Power Increased 40x Tesla Vision Autopilot Navigate on Autopilot Autosteer+ Smart Summon Full Self-Driving Capability From Home To your Destination Chapter Three: A level-by-level explainer of autonomous vehicles Classification System For The Development Of Innovations The J3016 Guidelines Six SAE level Criticism of SAE classification Level 0: No automation Level 1: Driver assistance Level 2: Partial automation Level 3: Conditional automation Level 4: High automation Level 5: Full automation Chapter Four: Main Connectivity Specifications Of Autonomous Vehicles Vehicle-To-Everything Architectures must be both redundant and real-time. The demand for high-speed data would increase only Security and other applications Include external connectivity Autonomous driving efficiency and reliability are non-negotiable More and more electrified cars would need a new approach to safety Next generation Car Design Would Need Miniaturized Solutions Co-creation of the future of mobility Chapter Five: Building Passenger Trust Is Key Technology for self-driving cars is accelerating fast, but our driverless future isn't going anywhere if people don't trust it. rules of the road implicit laws are more challenging The math-based AV safety model What is Sensitive Protection Responsibility? RSS is compatible with other AV systems How are AVs safely sharing the road with human drivers? 01 Safe distance: Don't hit the car in front of you 02 Cutting in: Don't cut it in recklessly 03 Right of Way: Right of way is given, not taken 04 Limited Visibility: Be cautious in areas with limited visibility 05 Avoid Crashes: If you can avoid a crash without causing another one, you must Moving past the miles-driven Improving road safety with RSS today RSS to gain support Baidu Valeo China ITS Alliance RAND Corp. The Arizona Institute for Automated Mobility Joint Research Institutes Chapter Six: The reasons Autonomous vehicles still aren’t on our roads The Gap Between the Invention and The Application Sensors Machine Learning The Open Road Regulations Social Acceptability Chapter Seven: Legal frameworks and other national initiatives The United States European Union Membership United Arab Emirates Japan Australia Chapter Eight: Liability, ethics and human rights implications The novelty of autonomous vehicles The critical debate Autonomy Threats Chapter Nine: Leading opinions on an ethical rollout for autonomous vehicles The Three Laws of Robotics The Ethical Dilemmas of Autonomy The Worst-Case Scenario The Trolley Issue Chapter Ten: Social and economic implications Roads Safety Vehicles Ownership and Vehicles Insurance Jobs Chapter Eleven: Ongoing research and impediments to autonomous vehicle development Research and Development The Social Acceptance of Autonomous Vehicles Chapter Twelve: The Sensor Types Drive Autonomous Vehicles Multiple Redundant Sensor Systems Overview of the study SAE Levels Short DESCRIPTIONS No car manufacturer has reached level 3 or higher Which sensors are needed? Camera and LIDAR Systems Cameras Back and 360° cameras Front-Facing Camera Systems RADAR Sensor LiDAR Summary and insight