• DocumentCode
    109987
  • Title

    Modeling and Forecasting the Urban Volume Using Stochastic Differential Equations

  • Author

    Tahmasbi, Rasool ; Hashemi, S.M.

  • Author_Institution
    Intell. Transp. Syst. Res. Inst., Amirkabir Univ. of Technol., Tehran, Iran
  • Volume
    15
  • Issue
    1
  • fYear
    2014
  • fDate
    Feb. 2014
  • Firstpage
    250
  • Lastpage
    259
  • Abstract
    Traffic flow prediction can be used for the management of traffic control systems and can be applied toward improving traffic light split times at intersections. In this paper, we developed a methodology for the short-term prediction of traffic flow using the stochastic differential equation (SDE). Since the current volume depends on the previous short-term volume and time, we used the Hull-White model. With the proposed method, a flexible short-term prediction of volume is suggested. It is possible to simulate traffic conditions easily and also detect incidents precisely. This method is applied in Tehran´s highways, and the obtained results are compared with previous artworks. Our results offered a better fit to the traffic volume.
  • Keywords
    differential equations; forecasting theory; road traffic control; stochastic processes; Hull-White model; SDE; Tehran highways; flexible short-term prediction; incident detection; stochastic differential equations; traffic condition simulation; traffic control system management; traffic flow prediction; traffic light split time improvement; urban volume forecasting; urban volume modeling; Cameras; Cities and towns; Mathematical model; Polynomials; Predictive models; Solid modeling; Splines (mathematics); Hull–White model; Ito integral; stochastic differential equation (SDE); traffic flow;
  • fLanguage
    English
  • Journal_Title
    Intelligent Transportation Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1524-9050
  • Type

    jour

  • DOI
    10.1109/TITS.2013.2278614
  • Filename
    6588933