Traffic flow on freeway is a complex stochastic nonlinear phenomenon, with many complex interactions between vehicles and random perturbations such as traffic jams, incident and delay phenomenon. The Cell Transmission Model (CTM) is one of the most widely used dynamic link models for simulating dynamic traffic network. Its popularity is due to its simple formulation and low computation requirement. In this paper we develop a stochastic cell transmission model (SCTM) to model the evolution of traffic flows on freeways taking into account various uncertainties. We model the transportation network as stochastic system with various supply uncertainties (random variables). The SCTM is formulated by using analytical probability theory and is formulated into a discrete time bilinear stochastic system. A set of probablistic switching conditions is proposed to evaluate the joint traffic density.


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    Title :

    Stochastic Cell Transmission Model: Traffic State Estimation under Uncertainties


    Contributors:

    Conference:

    Sixth International Conference of Traffic and Transportation Studies Congress (ICTTS) ; 2008 ; Nanning, China



    Publication date :

    2008-07-17




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English