Affected by unexpected events, the nominal operation of high-speed trains will become invalid. To maintain the efficiency of trains, train dispatchers need to reschedule the train timetable, which is a challenging task. On the one hand, the dispatchers need to take into account complex conflicts between trains on the track; on the other hand, the rescheduled timetable should be efficient to reduce operating costs. To address the above issues, this study proposes a traffic modeling method for high-speed trains based on a block section to describe in detail the operation conflicts between trains. A train rescheduling approach combining reinforcement learning and model predictive control is proposed to accomplish train rescheduling efficiently. The experiments show the effectiveness of the proposed method.


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    Title :

    Traffic Modeling and Rescheduling for High-speed Train Based on Block Sections


    Contributors:
    Yue, Peng (author) / Jin, Yaochu (author) / Dai, Xuewu (author) / Cui, Dongliang (author) / Shi, Qi (author)


    Publication date :

    2022-10-28


    Size :

    3314286 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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