• DocumentCode
    1939876
  • Title

    A short-term freeway traffic flow prediction method based on road section traffic flow structure pattern

  • Author

    Zhang, Ping ; Xie, Kunqing ; Song, Guojie

  • Author_Institution
    Key Lab. of Machine Perception (Minister of Educ.), Peking Univ., Beijing, China
  • fYear
    2012
  • fDate
    16-19 Sept. 2012
  • Firstpage
    534
  • Lastpage
    539
  • Abstract
    Accurate short-term traffic flow prediction is the foundation of the efficient and proactive management of freeway networks, especially on the abnormal traffic states. The relationship between traffic flow on the current section and the upstream stations can be used for predicting short-term traffic flow. In this paper, we reveal this relationship by the traffic flow structure pattern. The structure pattern can be drawn from real freeway toll data and a few video detective cameras on the freeway segments. Based on the stability pattern, a new traffic flow prediction algorithm has been proposed. Experimental based on real data showed that the prediction method based on structure pattern is an effective approach for traffic flow prediction, especially on the abnormal traffic state.
  • Keywords
    prediction theory; road traffic; transportation; abnormal traffic states; freeway network management; freeway segments; real freeway toll data; road section traffic flow structure pattern; short-term freeway traffic flow prediction method; stability pattern; traffic flow structure pattern; video detective cameras; Accuracy; History; Prediction algorithms; Prediction methods; Roads; Stability analysis; Traffic control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on
  • Conference_Location
    Anchorage, AK
  • ISSN
    2153-0009
  • Print_ISBN
    978-1-4673-3064-0
  • Electronic_ISBN
    2153-0009
  • Type

    conf

  • DOI
    10.1109/ITSC.2012.6338674
  • Filename
    6338674