Abstract This paper presents a novel railway timetable diagnostic analysis framework based on train operation data. Firstly, we define the concept of train deviation and give a new definition of train delay. Secondly, we propose the delay high-incidence section, station and train identification methods On the basis of deviation-based visualization technology. Finally, we take Chengdu-Kunming railway line (from Puxiong-Xichangbei section) as an example to verify the proposed method. The results show that: (1) Our method can effectively identify stations and sections that are prone to delays; (2) Cargo trains are more likely to occur delay than passenger trains; (3) There is a strong linear correlation between arrival delay and departure delay.


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    Title :

    Railway Timetable Diagnostic Analysis Based on Train Operation Data


    Contributors:
    Xu, Changan (author) / Ni, Shaoquan (author) / Li, Shengdong (author) / Chen, Dingjun (author)


    Publication date :

    2018-12-01


    Size :

    8 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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