Nowadays, high-speed railway has become an important mode of transportation. In real life, train operation is often disturbed by various factors, which may lead to unexpected delay in train running time. Therefore, train timetable should be designed with robustness to improve the ability to cope with disturbances. The research on optimal layout of slack time of high-speed railway timetable can provide important support and guarantee for the safety, reliability and efficiency of high-speed railway operation. Firstly, based on the research of many experts at home and abroad, the present situation of train slack time research is summarized, and the shortcomings of current research are put forward. In this paper, a light robustness model is established. Taking the operation performance of Beijing-Shanghai high-speed railway within one month as an example, trains in Tengzhou-Bengbu South section of Beijing-Shanghai high-speed Railway are selected, and the optimized slack time setting scheme and related train timetable are solved by using the Gurobi solver, which provides a new idea for the optimization and adjustment of train timetable. Finally, by setting the disturbance conditions, it is proved that the scheme of optimizing the slack time using the light robustness model can improve the flexibility of the train timetable.


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    Title :

    A Method for Optimizing Slack Time for High-Speed Railway Train Timetable


    Additional title:

    Lecture Notes in Civil Engineering


    Contributors:
    Meng, Lingyun (editor) / Qian, Yongsheng (editor) / Bai, Yun (editor) / Lv, Bin (editor) / Tang, Yuanjie (editor) / Liu, Fei (author) / Meng, Lingyun (author) / Miao, Jianrui (author) / Luan, Xiaojie (author) / Liao, Zhengwen (author)

    Conference:

    International Conference on Traffic and Transportation Studies ; 2024 ; Lanzhou, China August 23, 2024 - August 25, 2024



    Publication date :

    2024-11-21


    Size :

    9 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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