• DocumentCode
    3463430
  • Title

    Non-linear analysis of traffic flow

  • Author

    Nair, Attoor Sanju ; Liu, Jyh-Cham ; Rilett, Laurence ; Gupta, Saurabh

  • fYear
    2001
  • fDate
    2001
  • Firstpage
    681
  • Lastpage
    685
  • Abstract
    Traffic flow prediction is an important application of the ITS technology. In this paper, we applied nonlinear time-series modeling techniques to analyze a traffic data. Our objective is to investigate the deterministic properties of traffic flow using a nonlinear time series analysis technique. The experiment is performed for inductance loop data collected from the San Antonio freeway system. Our study concludes that the traffic data exhibits chaotic properties and techniques based on phase space dynamics can be used to analyze and predict the traffic flow
  • Keywords
    automated highways; chaos; nonlinear systems; phase space methods; prediction theory; road traffic; time series; ITS technology; San Antonio freeway system; Texas; USA; chaotic properties; inductance loop data; nonlinear analysis; nonlinear time-series modeling; phase space dynamics; traffic flow prediction; Chaos; Data analysis; Inductance; Nonlinear dynamical systems; Predictive models; Scattering; Space exploration; Telecommunication traffic; Time series analysis; Traffic control;
  • 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.2001.948742
  • Filename
    948742