• DocumentCode
    181708
  • Title

    A Multiple Attribute-based Decision Making model for autonomous vehicle in urban environment

  • Author

    Chen, Jiajia ; Pan Zhao ; Huawei Liang ; Tao Mei

  • Author_Institution
    Univ. of Sci. & Technol. of China, Hefei, China
  • fYear
    2014
  • fDate
    8-11 June 2014
  • Firstpage
    480
  • Lastpage
    485
  • Abstract
    In this paper, a maneuver decision making method for autonomous vehicle in complex urban environment is studied. We decompose the decision making problem into three steps. The first step is for selecting the logical maneuvers, in the second step we remove the maneuvers which break the traffic rules. In the third step, Multiple Attribute Decision Making (MADM) methods such as Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are used in the process of selecting the optimum driving maneuver in the scenario considering safety and efficiency. AHP is used for obtaining the weights of attributes, TOPSIS is responsible for calculating the ratings and ranking the alternatives. Road test indicates that the proposed method helps the autonomous vehicle to make reasonable decisions in complex environment. In general, the experiment results show that this method is efficient and reliable.
  • Keywords
    TOPSIS; analytic hierarchy process; mobile robots; road safety; road vehicles; AHP; MADM methods; TOPSIS; analytic hierarchy process; autonomous vehicle; logical maneuvers; maneuver decision making method; multiple attribute-based decision making model; optimum driving maneuver; road safety; road test; technique for order preference by similarity to ideal solution; traffic rules; urban environment; Analytic hierarchy process; Mobile robots; Roads; Safety; Urban areas; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium Proceedings, 2014 IEEE
  • Conference_Location
    Dearborn, MI
  • Type

    conf

  • DOI
    10.1109/IVS.2014.6856470
  • Filename
    6856470