• DocumentCode
    3463598
  • Title

    Nonlinear filter road vehicle model development

  • Author

    Wada, Massaki ; Yoon, Kangsup ; Hashimoto, Hideki

  • Author_Institution
    Inst. of Ind. Sci., Tokyo Univ., Japan
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    734
  • Lastpage
    739
  • Abstract
    This paper describes the first results of the investigation efforts performed in the development of the high-accuracy multisensor vehicle state estimation scheme. The use of UKF (Unscented Kalman Filter) in the state estimation scheme and vehicle model development framework is proposed. The first nonlinear vehicle model developed in this framework is also described. The model is able to cope with vehicle slip using multisensor data from inertial sensors, odometry, and the D-GPS. The simulation results indicated that the scheme is able to significantly reduce the errors in vehicle state estimates and is also able to perform real time internal sensors calibration
  • Keywords
    road vehicles; sensor fusion; state estimation; Kalman Filter; UKF; multisensor data; multisensor vehicle state estimation; sensors calibration; state estimation; unscented Kalman filter; vehicle model development; vehicle state estimates; Control systems; Global Positioning System; Nonlinear filters; Road vehicles; Robustness; Sensor phenomena and characterization; Sensor systems; State estimation; Vehicle driving; Vehicle safety;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Transportation Systems, 2001. Proceedings. 2001 IEEE
  • Conference_Location
    Oakland, CA
  • Print_ISBN
    0-7803-7194-1
  • Type

    conf

  • DOI
    10.1109/ITSC.2001.948751
  • Filename
    948751