Traditional route guidance systems usually model the transportation network as a static graph, however, this model is not close to reality. Due to time-varying and stochastic properties, we establish the mathematical model of a transportation network as a stochastic time-dependent network. Then we define the mathematical formulation of our knowledge about the network, which can be divided into two categories, prior information and real-time information. Under the framework developed by us, we propose two solutions to solve the problem of route guidance based on real-time information. The solutions are, respectively, a fastest path finding algorithm and two time-adaptive decision rules based on greedy strategy. At last, simulation results on an artificial stochastic time-dependent network with multidimensional normal distribution are given and the performance of our algorithms is evaluated and compared.


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    Titel :

    Route guidance systems based on real-time information


    Beteiligte:
    Wu, Chengjin (Autor:in) / Zhang, Xuedan (Autor:in) / Dong, Yuhan (Autor:in)


    Erscheinungsdatum :

    01.12.2013


    Format / Umfang :

    338030 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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