• DocumentCode
    2963757
  • Title

    Dynamic estimation of freeway origin-destination demand and travel time using extended Kalman filtering algorithm

  • Author

    Hu, Shou-Ren ; Chen, Chi-Bang

  • Author_Institution
    Dept. of Transp. Manage., Tamkang Univ., Taipei, Taiwan
  • Volume
    2
  • fYear
    2004
  • fDate
    2004
  • Firstpage
    1329
  • Abstract
    In the present research, a nonlinear Kalman filtering approach, i.e., extended Kalman filter (EKF) was proposed to solve dynamic OD flows and travel times on a freeway segment. The non-linearity results from the facts that the coefficient matrices in the measurement equation of the Kalman filtering framework are unknown in advance and needed to be obtained/updated in light of the most recent observations. The numerical results demonstrated the capability of the proposed EKF model in the dynamic estimation of freeway OD demands and travel times. More significantly, one can design beneficial traffic control and management strategies in accordance with the estimation results.
  • Keywords
    Kalman filters; control system synthesis; filtering theory; matrix algebra; traffic control; Kalman filtering algorithm; coefficient matrices; dynamic estimation; freeway origin-destination demand; traffic control; travel times; Bayesian methods; Current measurement; Filtering algorithms; Kalman filters; Least squares approximation; Maximum likelihood estimation; Nonlinear equations; State estimation; Traffic control; Transportation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking, Sensing and Control, 2004 IEEE International Conference on
  • ISSN
    1810-7869
  • Print_ISBN
    0-7803-8193-9
  • Type

    conf

  • DOI
    10.1109/ICNSC.2004.1297140
  • Filename
    1297140