• DocumentCode
    181947
  • Title

    A new approach for autonomous vehicle navigation in urban scenarios based on roadway Magnets

  • Author

    Gang Zhu ; Ming Yang ; Bing Wang ; Chunxiang Wang

  • Author_Institution
    Dept. of Autom., Shanghai Jiao Tong Univ., Shanghai, China
  • fYear
    2014
  • fDate
    8-11 June 2014
  • Firstpage
    432
  • Lastpage
    437
  • Abstract
    Magnetic guidance is a commonly used vehicle navigation solution in real applications due to its reliability. The vehicle control of magnetic guidance, however, is difficult because of the look-down property of road detecting sensors. This paper proposes a curvature map based approach to realize look-ahead control for magnetic guidance used in urban scenarios. The basis of the approach is a magnet tracking algorithm, which makes it possible to calculate the curvature of the passed road. The tracking algorithm is used not only to localize the vehicle but also to build the curvature map of the reference trajectory. Once the magnetic ruler detects a magnet, a magnet tracker is initialized and tracks the magnet in the vehicle coordinate. Then these tracking results combined with the curvature map are used to predict the upcoming road´s curvature. The curvature map is obtained by running the tracking algorithm when the vehicle is driving along the magnetic trajectory by hand. Compared with existing methods, the algorithm predominates in implementation and robustness. Experiments on real application scenario have verified the effectiveness of the proposed idea.
  • Keywords
    magnets; remotely operated vehicles; road vehicles; tracking; autonomous vehicle navigation; curvature calculation; curvature map based approach; look-ahead control; look-down property; magnet detection; magnet tracker; magnet tracking algorithm; magnetic guidance; magnetic ruler; reference trajectory; road detecting sensors; roadway magnets; upcoming road curvature prediction; urban scenarios; vehicle control; vehicle localization; Equations; Mathematical model; Nails; Prediction algorithms; Roads; Trajectory; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium Proceedings, 2014 IEEE
  • Conference_Location
    Dearborn, MI
  • Type

    conf

  • DOI
    10.1109/IVS.2014.6856603
  • Filename
    6856603