• DocumentCode
    2820862
  • Title

    Modeling Correlation between Origin-Destination Traffic Demands in Stochastic Transportation Networks

  • Author

    Song, Xiaoqiu ; Shao, Hu ; Wang, Guodong

  • Author_Institution
    Sch. of Sci., China Univ. of Min. & Technol., Xuzhou, China
  • Volume
    2
  • fYear
    2009
  • fDate
    24-26 April 2009
  • Firstpage
    147
  • Lastpage
    149
  • Abstract
    This paper proposes an analytical method to investigate the correlation between origin-destination (OD) demands in stochastic transportation network with demand uncertainty. Different from the existing researches, the OD traffic demand is assumed to follow a multivariate probability distribution, which explicitly considers the correlation between OD demands. Under this assumption, the correlation between path flows and correlation between link flows are also deduced using the proposed analytical method. As a result, the multivariate distribution of link flows and path flows can be obtained, which are further applied in a reliability-based traffic assignment problem. The numerical examples indicate that the correlation between OD demands will influence not only the flow patterns but also the total network travel time. Moreover, the ignorance of correlations between OD demands can either underestimate or overestimate the network congestion.
  • Keywords
    correlation methods; road traffic; statistical distributions; stochastic processes; transportation; analytical method; correlation method; demand uncertainty; link flow; multivariate probability distribution; origin-destination traffic demand; path flow; stochastic transportation network; Analytical models; Computer networks; Large-scale systems; Probability distribution; Random variables; Stochastic processes; Telecommunication traffic; Traffic control; Transportation; Uncertainty; Correlation; Origin-Destination Traffic Demand; Stochastic Transportation Network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
  • Conference_Location
    Sanya, Hainan
  • Print_ISBN
    978-0-7695-3605-7
  • Type

    conf

  • DOI
    10.1109/CSO.2009.268
  • Filename
    5193918