• DocumentCode
    536160
  • Title

    Identifying Traffic Jamming by the Spatiotemporal Correlation Function

  • Author

    Fan, Yaping ; Xue, Yu

  • Author_Institution
    Inst. of Phys. Sci. & Eng., Guangxi Univ., Nanning, China
  • Volume
    2
  • fYear
    2010
  • fDate
    23-24 Oct. 2010
  • Firstpage
    387
  • Lastpage
    391
  • Abstract
    In this paper, we identify the traffic jamming in SDNaSch and First-noise traffic model by the spatiotemporal correlation functions, respectively. The correlation in the first model shows the sharp change rather than a crossover type. It indicates the transition from freely moving to jammed traffic. The correlation function of the second model shows rather complicated oscillating behaviors without the sharply changing. It implies the transition from freely moving cross over to jammed traffic.
  • Keywords
    correlation methods; road traffic; SDNaSch; first-noise traffic model; spatiotemporal correlation function; traffic jamming identification; Automata; Biological system modeling; Correlation; Jamming; Numerical models; Physics; Spatiotemporal phenomena; cellular automaton; correlation function; traffic flow;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Computational Intelligence (AICI), 2010 International Conference on
  • Conference_Location
    Sanya
  • Print_ISBN
    978-1-4244-8432-4
  • Type

    conf

  • DOI
    10.1109/AICI.2010.202
  • Filename
    5657167