On-Road Intelligent Vehicles : Motion Planning for Intelligent Transportation Systems by Rahul Kala read book PDF, FB2, DOC
9780128037560 English 0128037563 On-Road Intelligent Vehicles, On-Road Intelligent Vehicles deals with the technology of autonomous vehicles, with a special focus on the navigation and planning aspects. The book has been divided into 3 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. The proximity sensors give the distances to obstacles, while the vision cameras may be calibrated and computer vision techniques may be used to pre-process the image, extract relevant features and use classification techniques like neural networks, support vector machines, etc. for the identification of roads, lanes, vehicles, obstacles, traffic lights, signs and pedestrians. The location of the different vehicles on the road may be obtained by localization techniques including Kalman filtering, particle filtering and Bayesian methods. The vehicle is planned using a variety of planning algorithm and controlled using PID or Fuzzy based control techniques. With a detailed insight into the technology behind the vehicle, the second part 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 comprising of Genetic Algorithm and Rapidly-exploring Random Trees; 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 based planning; and Logic based planning. The third part of the book covers the macroscopic concepts related to Intelligent Transportation Systems with a discussion over various topics and concepts related to transportation systems. Describes the traffic flow, the basic theory behind transportation systems and generation of shock waves. Followed by a discussion of an emerging problem, which is diversity. Further, a solution for the problem of routing in a city like traffic is presented under non-recurrent conditions. Also a solution to the problem of reaching the destination on time by assuming recurrent traffic conditions and assuming cooperation from the transportation system is presented. The solutions use A* algorithm as the basic routing technique, while information about the traffic is mapped to the costs of the A* algorithm. Modelling of traffic lights, lane changes and mechanisms of road and lane reservations are presented. This book can be used for the researchers in the areas of Intelligent Vehicles, Intelligent Transportation Systems, Autonomous Vehicles and as a reference book for graduate courses such as Robot Motion Planning, Special Topics in Robotics, Cooperative Systems, Planning and Navigation. It will also be a great book for those who plan to migrate to this domain. Get an overall coverage of autonomous vehicles and Intelligent Transportation Systems Learn from a detailed overview, followed by the challenging problems of navigation and planning Learn how to compare, contrast, and differentiate navigation algorithms., 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
9780128037560 English 0128037563 On-Road Intelligent Vehicles, On-Road Intelligent Vehicles deals with the technology of autonomous vehicles, with a special focus on the navigation and planning aspects. The book has been divided into 3 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. The proximity sensors give the distances to obstacles, while the vision cameras may be calibrated and computer vision techniques may be used to pre-process the image, extract relevant features and use classification techniques like neural networks, support vector machines, etc. for the identification of roads, lanes, vehicles, obstacles, traffic lights, signs and pedestrians. The location of the different vehicles on the road may be obtained by localization techniques including Kalman filtering, particle filtering and Bayesian methods. The vehicle is planned using a variety of planning algorithm and controlled using PID or Fuzzy based control techniques. With a detailed insight into the technology behind the vehicle, the second part 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 comprising of Genetic Algorithm and Rapidly-exploring Random Trees; 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 based planning; and Logic based planning. The third part of the book covers the macroscopic concepts related to Intelligent Transportation Systems with a discussion over various topics and concepts related to transportation systems. Describes the traffic flow, the basic theory behind transportation systems and generation of shock waves. Followed by a discussion of an emerging problem, which is diversity. Further, a solution for the problem of routing in a city like traffic is presented under non-recurrent conditions. Also a solution to the problem of reaching the destination on time by assuming recurrent traffic conditions and assuming cooperation from the transportation system is presented. The solutions use A* algorithm as the basic routing technique, while information about the traffic is mapped to the costs of the A* algorithm. Modelling of traffic lights, lane changes and mechanisms of road and lane reservations are presented. This book can be used for the researchers in the areas of Intelligent Vehicles, Intelligent Transportation Systems, Autonomous Vehicles and as a reference book for graduate courses such as Robot Motion Planning, Special Topics in Robotics, Cooperative Systems, Planning and Navigation. It will also be a great book for those who plan to migrate to this domain. Get an overall coverage of autonomous vehicles and Intelligent Transportation Systems Learn from a detailed overview, followed by the challenging problems of navigation and planning Learn how to compare, contrast, and differentiate navigation algorithms., 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