• DocumentCode
    1798044
  • Title

    An effective search and navigation model to an auto-recharging station of driverless vehicles

  • Author

    Chaomin Luo ; Yu-Ting Wu ; Krishnan, Mohan ; Paulik, Mark ; Jan, Gene Eu ; Jiyong Gao

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Detroit Mercy, Detroit, MI, USA
  • fYear
    2014
  • fDate
    9-12 Dec. 2014
  • Firstpage
    100
  • Lastpage
    107
  • Abstract
    An electric vehicle auto-recharging station is a component in an infrastructure supplying electric energy for the recharging of plug-in electric vehicles. An auto-recharging station is usually accessible to an autonomous driverless vehicle driven by intelligent algorithms. A driverless vehicle is assumed to be capable of autonomously searching and navigating it into a recharging station. In this paper, a novel hybrid intelligent system is developed to navigate an autonomous vehicle into a recharging station. The driverless vehicle driven by D*Lite path planning methodology in conjunction with a Vector Field Histogram (VFH) local navigator is developed for search and navigation purpose to reach an auto-recharging station with obstacle avoidance. Once it approaches vicinity of the recharging station, the driverless vehicle should be directed at the recharging station at a proper angle, which is accomplished by a Takagi-Sugeno fuzzy logic model. A novel error control of angle and distance heuristic approach is proposed to adjust the vehicle straight at the recharging station. Development of the driverless vehicle in terms of hardware and software design is described. Simulation studies on the Player/Stage platform demonstrate that the proposed model can successfully guide an autonomous driverless vehicle into the recharging station. Experimental effort shows its promising results that the driverless vehicle is able to autonomously navigate it to an auto-recharging station.
  • Keywords
    battery storage plants; collision avoidance; electric vehicles; fuzzy control; intelligent transportation systems; vectors; D*Lite path planning methodology; Player-Stage platform; Takagi-Sugeno fuzzy logic model; VFH local navigator; angle error control; autonomous driverless vehicle; distance heuristic approach; electric vehicle auto-recharging station; hybrid intelligent system; intelligent algorithms; obstacle avoidance; plug-in electric vehicles; vector field histogram local navigator; Artificial intelligence; Cameras; Chaos; Histograms; MATLAB; Navigation; Recharging station system; angle and distance heuristic approach; computational intelligence; fuzzy logic model; hybrid intelligent system; navigation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Vehicles and Transportation Systems (CIVTS), 2014 IEEE Symposium on
  • Conference_Location
    Orlando, FL
  • Type

    conf

  • DOI
    10.1109/CIVTS.2014.7009484
  • Filename
    7009484