• DocumentCode
    2119668
  • Title

    Short-Term Traffic Flow Forecasting Using Macroscopic Urban Traffic Network Model

  • Author

    Lin, Shu ; Xi, Yugeng ; Yang, Yanfei

  • Author_Institution
    Dept. of Autom., Shanghai Jiao Tong Univ., Shanghai
  • fYear
    2008
  • fDate
    12-15 Oct. 2008
  • Firstpage
    134
  • Lastpage
    138
  • Abstract
    Traffic flow forecasting provides important information for both traffic control and traffic guidance. It should be both quick and accurate. A short-term traffic flow forecasting method is given based on the macroscopic urban traffic network model. The model is established to describe the substantial mechanism of traffic flow movement and the topology of the entire urban traffic network. It can simulate the traffic movement in the urban traffic network, and forecast the traffic flow states in the near future accurately. Also, the method has a good real-time feature due to the macroscopic model. In the simulation experiment, microscopic model CORSIM is used as the practical traffic system, and the proposed method is used to forecast the traffic flow of it. The simulation results show that the method has a good forecasting effectiveness.
  • Keywords
    forecasting theory; graph theory; network theory (graphs); road traffic; transportation; graph theory; macroscopic urban traffic network model; microscopic model; short-term traffic flow forecasting; topology; traffic control; traffic guidance; Communication system traffic control; Intelligent networks; Intelligent transportation systems; Microscopy; Network topology; Parameter estimation; Predictive models; Roads; Telecommunication traffic; Traffic control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Transportation Systems, 2008. ITSC 2008. 11th International IEEE Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-2111-4
  • Electronic_ISBN
    978-1-4244-2112-1
  • Type

    conf

  • DOI
    10.1109/ITSC.2008.4732567
  • Filename
    4732567