Intelligent Vehicles

The Handbook of Intelligent Vehicles provides a complete coverage of the fundamentals, new technologies, and sub-areas essential to the development of intelligent vehicles; it also includes advances made to date, challenges, and future trends. Significant strides in the field have been made to date; however, so far there has been no single book or volume which captures these advances in a comprehensive format, addressing all essential components and subspecialties of intelligent vehicles, as this book does. Since the intended users are engineering practitioners, as well as researchers and graduate students, the book chapters do not only cover fundamentals, methods, and algorithms but also include how software/hardware are implemented, and demonstrate the advances along with their present challenges. Research at both component and systems levels are required to advance the functionality of intelligent vehicles. This volume covers both of these aspects in addition to the fundamentals listed above.

Intelligent Road Vehicles examines specific aspects of intelligent vehicles such as enabling technologies, human factors and an analysis of social and economic impacts. The book is an invaluable resource for those pursuing deeper knowledge in the intelligent vehicles field, providing readers with an idea of current and future technologies, current projects and developments and the future of intelligent vehicles. Intelligent road vehicles are becoming a challenging area of research worldwide. Apart from the final applications and systems in vehicles, there are many enabling technologies that should be introduced. Communications and automation are two key areas for future automobiles. This book benefits from collaboration on the Thematic Network on Intelligent Vehicles led by Felipe Jimenez. Provides a general overview of different aspects related to intelligent road vehicles (sensors, applications, communications, automation, human factors, etc.) Addresses the different components and building blocks of intelligent vehicles in a single, comprehensive reference Explains how sensors are interpreted, including how different sensor readings are fused Addresses issues involved with avoiding collisions and other factors such as pot holes, unclear road lines or markings, and unexpected weather conditions

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.

This book presents the results of the successful Sensors Special Issue on Intelligent Vehicles that received submissions between March 2019 and May 2020. The Guest Editors of this Special Issue are Dr. David Fernández-Llorca, Dr. Ignacio Parra-Alonso, Dr. Iván García-Daza and Dr. Noelia Parra-Alonso, all from the Computer Engineering Department at the University of Alcalá (Madrid, Spain). A total of 32 manuscripts were finally accepted between 2019 and 2020, presented by top researchers from all over the world. The reader will find a well-representative set of current research and developments related to sensors and sensing for intelligent vehicles. The topics of the published manuscripts can be grouped into seven main categories: (1) assistance systems and automatic vehicle operation, (2) vehicle positioning and localization, (3) fault diagnosis and fail-x systems, (4) perception and scene understanding, (5) smart regenerative braking systems for electric vehicles, (6) driver behavior modeling and (7) intelligent sensing. We, the Guest Editors, hope that the readers will find this book to contain interesting papers for their research, papers that they will enjoy reading as much as we have enjoyed organizing this Special Issue

On-Road Intelligent Vehicles: Motion Planning for Intelligent Transportation Systems deals with the technology of autonomous vehicles, with a special focus on the navigation and planning aspects, presenting the information in three parts. Part One deals with the use of different sensors to perceive the environment, thereafter mapping the multi-domain senses to make a map of the operational scenario, including topics such as proximity sensors which give distances to obstacles, vision cameras, and computer vision techniques that may be used to pre-process the image, extract relevant features, and use classification techniques like neural networks and support vector machines for the identification of roads, lanes, vehicles, obstacles, traffic lights, signs, and pedestrians. With a detailed insight into the technology behind the vehicle, Part Two of the book focuses on the problem of motion planning. Numerous planning techniques are discussed and adapted to work for multi-vehicle traffic scenarios, including the use of sampling based approaches comprised of Genetic Algorithm and Rapidly-exploring Random Trees and Graph search based approaches, including a hierarchical decomposition of the algorithm and heuristic selection of nodes for limited exploration, Reactive Planning based approaches, including Fuzzy based planning, Potential Field based planning, and Elastic Strip and logic based planning. Part Three of the book covers the macroscopic concepts related to Intelligent Transportation Systems with a discussion of various topics and concepts related to transportation systems, including a description of traffic flow, the basic theory behind transportation systems, and generation of shock waves. Provides an overall coverage of autonomous vehicles and Intelligent Transportation Systems Presents a detailed overview, followed by the challenging problems of navigation and planning Teaches how to compare, contrast, and differentiate navigation algorithms

This book provides the latest information in intelligent vehicle control and intelligent transportation. Detailed discussions of vehicle dynamics and ground-vehicle interactions are provided for the modeling, simulation and control of vehicles. It includes an extensive review of past and current research achievements in the intelligent vehicle motion control and sensory field, and the book provides a careful assessment of future developments.

This book presents the most recent state-of-the-art algorithms on robust environmental perception and reliability control for intelligent vehicle systems. By integrating object detection, semantic segmentation, trajectory prediction, multi-object tracking, multi-sensor fusion, and reliability control in a systematic way, this book is aimed at guaranteeing that intelligent vehicles can run safely in complex road traffic scenes. Adopts the multi-sensor data fusion-based neural networks to environmental perception fault tolerance algorithms, solving the problem of perception reliability when some sensors fail by using data redundancy. Presents the camera-based monocular approach to implement the robust perception tasks, which introduces sequential feature association and depth hint augmentation, and introduces seven adaptive methods. Proposes efficient and robust semantic segmentation of traffic scenes through real-time deep dual-resolution networks and representation separation of vision transformers. Focuses on trajectory prediction and proposes phased and progressive trajectory prediction methods that is more consistent with human psychological characteristics, which is able to take both social interactions and personal intentions into account. Puts forward methods based on conditional random field and multi-task segmentation learning to solve the robust multi-object tracking problem for environment perception in autonomous vehicle scenarios. Presents the novel reliability control strategies of intelligent vehicles to optimize the dynamic tracking performance and investigates the completely unknown autonomous vehicle tracking issues with actuator faults.

This book highlights cyber-security overview, perspectives, and challenges that affect advanced Vehicular technology. It considers vehicular security issues and possible solutions, with the aim of providing secure vehicle-to-vehicle, vehicle-to-infrastructure and inside-of-vehicle communication. This book introduces vehicle cryptography mechanism including encryption and decryption approaches and cryptography algorithms such as symmetric and asymmetric cryptography, Hash functions and Digital Signature certificates for modern vehicles. It discusses cybersecurity structure and provides specific security challenges and possible solutions in Vehicular Communication such as vehicle to vehicle communication, vehicle to Infrastructure and in-vehicle communciation. It also presents key insights from security with regards to vehicles collaborative information technology. The more our vehicles become intelligent, the more we need to work on safety and security for vehicle technology. This book is of interest to automotive engineers and technical managers who want to learn about security technologies, and for those with a security background who want to learn about basic security issues in modern automotive applications.