This book reports on cutting-edge research and advances in the field of intelligent vehicle systems. It presents a broad range of AI-enabled technologies, with a focus on automated, autonomous and connected vehicle systems. It covers advanced machine learning technologies, including deep and reinforcement learning algorithms, transfer learning and learning from big data, as well as control theory applied to mobility and vehicle systems. Furthermore, it reports on cutting-edge technologies for environmental perception and vehicle-to-everything (V2X), discussing socioeconomic and environmental implications, and aspects related to human factors and energy-efficiency alike, of automated mobility. Gathering chapters written by renowned researchers and professionals, this book offers a good balance of theoretical and practical knowledge. It provides researchers, practitioners and policy makers with a comprehensive and timely guide on the field of autonomous driving technologies.

The main topic of this book is the recent development of on-board advanced driver-assistance systems (ADAS), which we can already tell will eventually contribute to the autonomous and connected vehicles of tomorrow. With the development of automated mobility, it becomes necessary to design a series of modules which, from the data produced by on-board or remote information sources, will enable the construction of a completely automated driving system. These modules are perception, decision and action. State-of-the-art AI techniques and their potential applications in the field of autonomous vehicles are described. Perception systems, focusing on visual sensors, the decision module and the prototyping, testing and evaluation of ADAS systems are all presented for effective implementation on autonomous and connected vehicles. This book also addresses cooperative systems, such as pedestrian detection, as well as the legal issues in the use of autonomous vehicles in open environments.

With the advent of advanced technologies in AI, driverless vehicles have elevated curiosity among various sectors of society. The automotive industry is in a technological boom with autonomous vehicle concepts. Autonomous driving is one of the crucial application areas of Artificial Intelligence (AI). Autonomous vehicles are armed with sensors, radars, and cameras. This made driverless technology possible in many parts of the world. In short, our traditional vehicle driving may swing to driverless technology. Many researchers are trying to come out with novel AI algorithms that are capable of handling driverless technology. The current existing algorithms are not able to support and elevate the concept of autonomous vehicles. This addresses the necessity of novel methods and tools focused to design and develop frameworks for autonomous vehicles. There is a great demand for energy-efficient solutions for managing the data collected with the help of sensors. These operations are exclusively focused on non-traditional programming approaches and depend on machine learning techniques, which are part of AI. There are multiple issues that AI needs to resolve for us to achieve a reliable and safe driverless technology. The purpose of this book is to find effective solutions to make autonomous vehicles a reality, presenting their challenges and endeavors. The major contribution of this book is to provide a bundle of AI solutions for driverless technology that can offer a safe, clean, and more convenient riskless mode of transportation.

The main topic of this book is the recent development of on-board advanced driver-assistance systems (ADAS), which we can already tell will eventually contribute to the autonomous and connected vehicles of tomorrow. With the development of automated mobility, it becomes necessary to design a series of modules which, from the data produced by on-board or remote information sources, will enable the construction of a completely automated driving system. These modules are perception, decision and action. State-of-the-art AI techniques and their potential applications in the field of autonomous vehicles are described. Perception systems, focusing on visual sensors, the decision module and the prototyping, testing and evaluation of ADAS systems are all presented for effective implementation on autonomous and connected vehicles. This book also addresses cooperative systems, such as pedestrian detection, as well as the legal issues in the use of autonomous vehicles in open environments.

This book reports on cutting-edge research and advances in the field of intelligent vehicle systems. It presents a broad range of AI-enabled technologies, with a focus on automated, autonomous and connected vehicle systems. It covers advanced machine learning technologies, including deep and reinforcement learning algorithms, transfer learning and learning from big data, as well as control theory applied to mobility and vehicle systems. Furthermore, it reports on cutting-edge technologies for environmental perception and vehicle-to-everything (V2X), discussing socioeconomic and environmental implications, and aspects related to human factors and energy-efficiency alike, of automated mobility. Gathering chapters written by renowned researchers and professionals, this book offers a good balance of theoretical and practical knowledge. It provides researchers, practitioners and policy makers with a comprehensive and timely guide on the field of autonomous driving technologies.

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 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.