On-road intelligent vehicles : motion planning for intelligent transportation systems
著者
書誌事項
On-road intelligent vehicles : motion planning for intelligent transportation systems
Butterworth-Heinemann, c2016
- : pbk
大学図書館所蔵 全2件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
"Butterworth-Heinemann is an imprint of Elsevier"--T.p. verso
Includes bibliographical references and index
内容説明・目次
内容説明
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.
目次
Part I: Autonomous Vehicles
1. Introduction
2. Basics of Autonomous Vehicles
3. Perception in Autonomous Vehicles
4. Advanced Driver Assistance Systems
Part II: Deliberative Motion Planning of Autonomous Vehicles
5. Introduction to Planning
6. Optimization Based Planning
7. Sampling Based Planning
8. Graph Search based Hierarchical Planning
9. Using Heuristics in Graph Search based Planning
Part III: (Near-)Reactive Motion Planning of Autonomous Vehicles
10. Fuzzy Based Planning
11. Potential Based Planning
12. Logic Based Planning
Part IV: Intelligent Transportation Systems
13. Basics of Intelligent Transportation System
14. Intelligent Transportation Systems with Diverse Vehicles
15. Reaching Destination before Deadline with Intelligent Transportation Systems
16. Conclusions
Appendix A: Resources from the Author
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