• DocumentCode
    620386
  • Title

    A stochastic traffic equilibrium model and algorithm with combined mode

  • Author

    Li Xian-jin ; Zhang Guo-ping ; Zhang Jie ; Lv Xuan ; Meng Meng

  • Author_Institution
    China Railway Express Co., Beijing, China
  • fYear
    2013
  • fDate
    25-27 May 2013
  • Firstpage
    3821
  • Lastpage
    3826
  • Abstract
    In order to investigate the stochastic traffic equilibrium assignment, the super-network theory is applied to describe the traffic network with combined mode. The mode and route choices are considered to be stochastic under elastic demand. Using the network equilibrium theory, an equivalent variational inequality model is proposed after analyzing the network equilibrium conditions. Moreover, the existence and uniqueness of an optimal solution are given. A solution algorithm for solving the model is proposed and validated by a numerical example. The influences of different parameters to OD demand and flow distribution are analyzed. These results show that this model can reflect the combined travel behavior more practically and has a certain generality.
  • Keywords
    network theory (graphs); optimisation; road traffic; stochastic processes; variational techniques; OD demand; combined travel behavior; combined travel mode; elastic demand; flow distribution; mode choices; network equilibrium conditions; network equilibrium theory; optimal solution; route choices; stochastic traffic equilibrium assignment; stochastic traffic equilibrium model; super-network theory; traffic network; variational inequality model; Companies; Electronic mail; Laboratories; Numerical models; Rail transportation; Stochastic processes; Combined Travel Mode; Super-network; Traffic Engineer; Traffic Equilibrium; Variational Inequality;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2013 25th Chinese
  • Conference_Location
    Guiyang
  • Print_ISBN
    978-1-4673-5533-9
  • Type

    conf

  • DOI
    10.1109/CCDC.2013.6561615
  • Filename
    6561615