• DocumentCode
    2840479
  • Title

    Short-time prediction method based on fractal theory for traffic flow

  • Author

    Ning, Chen ; Jian, Wu ; Yifeng, Wang ; Juanjun, Xu ; Hangzao, Dong

  • Author_Institution
    Sch. of Mech. & Automotive Eng., Zhejiang Univ. of Sci. & Technol., Hang Zhou, China
  • fYear
    2009
  • fDate
    17-19 June 2009
  • Firstpage
    458
  • Lastpage
    461
  • Abstract
    It´s very difficult to predict the nonlinear traffic flow message, especially short-time traffic flow. To solve the issue, the nonlinear fractal phenomenon of urban traffic is analyzed. Based on the fractal prediction technology applied in other fields, a dedicated improved fractal model is raised to predict short-time traffic flow parameter. A minimum fractal dimension is given according to the distinguished concrete traffic circumstance in the model. The weekly traffic similarity is also inducted to improve the accuracy of the model. Finally, the improved fractal model is employed to predict the traffic flow in Hangzhou city. The experiment result shows the improved fractal method proposed here possesses a high prediction precision.
  • Keywords
    forecasting theory; road traffic; Hangzhou city; fractal prediction technology; improved fractal model; minimum fractal dimension; nonlinear fractal phenomenon; nonlinear traffic flow message; short-time prediction method; short-time traffic flow; urban traffic; weekly traffic similarity; Automotive engineering; Cities and towns; Concrete; Electronic mail; Fractals; Mathematics; Mechanical engineering; Prediction methods; Predictive models; Traffic control; Fractal Theory; Mathematic Model for Prediction; Prediction Method; Urban Traffic Flow;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference, 2009. CCDC '09. Chinese
  • Conference_Location
    Guilin
  • Print_ISBN
    978-1-4244-2722-2
  • Electronic_ISBN
    978-1-4244-2723-9
  • Type

    conf

  • DOI
    10.1109/CCDC.2009.5195007
  • Filename
    5195007