• DocumentCode
    400112
  • Title

    An applicable short-term traffic flow forecasting method based on chaotic theory

  • Author

    Hu, Jianming ; Zong, Chunguang ; Song, Jingyan ; Zhang, Zuo ; Ren, Jiangtao

  • Author_Institution
    Dept. of Autom., Tsinghua Univ., Beijing, China
  • Volume
    1
  • fYear
    2003
  • fDate
    12-15 Oct. 2003
  • Firstpage
    608
  • Abstract
    Short-term traffic flow forecasting plays a very important role in urban traffic management and control. In this paper, According to the chaotic property of urban traffic flow, we compute the parameters of phrase space reconstruction for traffic flow system. Meanwhile, a local-forecasting method is introduced to predict urban road short-term traffic flow based on the theory of phrase space reconstruction. Self-organizing Map (SOM) network is introduced to seek the near neighbor. Case study using real traffic flow data from UTC-SCOOT system proves the validity of the method. The research in this paper is a significant attempt to forecast traffic flow from the viewpoint of non-linear time series.
  • Keywords
    forecasting theory; road traffic; self-organising feature maps; time series; SOM; UTC-SCOOT system; chaotic theory; nonlinear time series; phrase space reconstruction; self organizing map network; short term traffic flow forecasting method; traffic flow data; urban traffic flow system; urban traffic management; Artificial neural networks; Chaos; Communication system traffic control; Intelligent transportation systems; Modems; Stochastic systems; Telecommunication traffic; Time series analysis; Traffic control; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Transportation Systems, 2003. Proceedings. 2003 IEEE
  • Print_ISBN
    0-7803-8125-4
  • Type

    conf

  • DOI
    10.1109/ITSC.2003.1252024
  • Filename
    1252024