Autonomous Vehicle Parking Using Hybrid Artificial Intelligent Approach

This paper describes a hybrid artificial intelligent control scheme that could be used by a car-like vehicle to perform the task of optimal, autonomous parking. The parallel parking control scheme addresses three issues: trajectory planner, decisional kernel, and trajectory tracking control. The authors discuss the techniques used in the design of the control scheme, including genetic algorithm, Petri net, and fuzzy logic control. The genetic algorithm is used to determine the feasible parking locations. The Petri net is used to replace the traditional decision flow chart and plan alternative parking routes. The parking routine can be re-performed if the initially assigned route is interfered with or when the targeted parking space has been occupied. The fuzzy logic controller is used to drive the vehicle along the optimal parking route. The authors report on how the scheme performs in several scenarios.

  • Availability:
  • Authors:
    • Lee, Chen-Kui
    • Lin, Chun-Liang
    • Shiu, Bing-Min
  • Publication Date: 2009-10


  • English

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  • Accession Number: 01150423
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Feb 16 2010 5:47AM