In order to provide a satisfying quality of service to passengers, companies operating suburban trains seek to implement timetables that perform well despite the occurrence of random disturbances. However, due to some specificities of Mass Transit, the standard approaches for robust train timetabling do not apply in that context. In this paper, we present a data-based stochastic simulation method for assessing the efficiency of train timetables for dense traffic areas. We describe models for the random variabilities that occur daily on such networks, and use them in a stochastic simulation algorithm. Results are presented on a saturated line of Paris suburban network.


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    Title :

    Assessing train timetable efficiency in a Mass Transit context using a data-based simulation method


    Contributors:


    Publication date :

    2020-09-20


    Size :

    392874 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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