Railway Timetable Diagnostic Analysis Based on Train Operation Data

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.