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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    Titel :

    Railway Timetable Diagnostic Analysis Based on Train Operation Data


    Beteiligte:
    Xu, Changan (Autor:in) / Ni, Shaoquan (Autor:in) / Li, Shengdong (Autor:in) / Chen, Dingjun (Autor:in)


    Erscheinungsdatum :

    2018-12-01


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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