Research on Risk Factors Affecting High-Speed Railway Delays in China Based on Association Rules
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This study aimed to investigate the contributing factors to high-speed railway (HSR) delays and their interdependency in China. A total of 420 records of high-speed railway delays in China were collected, and 15 risk factors related to high-speed railway delays were extracted. Descriptive statistics were used to illustrate the causes of HSR delays in terms of device, personnel and environmental conditions. The association rule mining technique was further applied to explore contributing factors that cause HSR delays, revealing the underlying mechanisms of delay occurrence. The results show that HSR delays of more than 1 hour are most likely caused by foreign objects hanging on the catenary. Moreover, 65% of HSR delays are within the range of 9–30 minutes. Among delay events with durations of 9 to 30 minutes, about 9% of are caused by the fault of on-board train control equipment, mainly the Automatic Train Protection (ATP). Regarding short delays of HSR within 8 minutes, the most likely cause is platform screen door faults, followed by traveller’s misconduct and train door faults. This study offers transportation agencies insights into HSR delay causes and aids in developing policies and engineering measures to reduce delays.
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Chen S. Research on the method of propagation delays of high-speed railway trains based on maximum algebra and ensemble learning. PhD thesis. Beijing Jiao Tong University; 2021.
Wen C, et al. Statistical investigation on train primary delay based on real records: Evidence from Wuhan-Guangzhou HSR. International Journal of Rail Transportation. 2017;5(3):170-189. DOI: 10.1080/23248378.2017.1307144
Lessan J, et al. Stochastic model of train running time and arrival delay: A case study of Wuhan–Guangzhou high-speed rail. Transportation Research Record. 2018;863081277. DOI: 10.1177/0361198118780830
Huang P, Peng Q, Wen C, Yang Y. Random forest prediction model for Wuhan-Guangzhou HSR primary train delays recovery. Journal of China Railway Society. 2018;40(7):1–9. DOI: 10.3969/j.issn.1001-8360.2018.07.001
Steven H, Fabrizio C, Otto A. A closed form railway line delay propagation model. Transportation Research Part C: Emerging Technologies. 2019;102:189-209. DOI: 10.1016/j.trc.2019.02.022
Barbour W, Mori J, Kuppa S, Daniel B. Prediction of arrival times of freight traffic on US railroads using support vector regression. Transportation Research Part C: Emerging Technologies. 2018;93:211-227. DOI: 10.1016/j.trc.2018.05.019
Marković N, Milinković S, Tikhonov K, Schonfeld P. Analyzing passenger train arrival delays with support vector regression. Transportation Research Part C: Emerging Technologies. 2015;56:251-262. DOI: 10.1016/j.trc.2015.04.004
Corman F, Kecman P. Stochastic prediction of train delays in real-time using Bayesian networks. Transportation Research Part C: Emerging Technologies. 2015;95:599-615. DOI: 10.1016/j.trc.2018.08.003
Nair R, et al. An ensemble prediction model for train delays. Transportation Research Part C: Emerging Technologies. 2019;104:196-209. DOI: 10.1016/j.trc.2019.04.026
Huang P, et al. Modeling train operation as sequences: A study of delay prediction with operation and weather data. Transportation Research Part E: Logistics and Transportation Review. 2020;141(102022). DOI: 10.1016/j.tre.2020.102022
Ilalokhoin O, Pant R, Hall J. A model and methodology for resilience assessment of interdependent rail networks – Case study of Great Britain's rail network. Reliability Engineering and System Safety. 2023;229(108895). DOI: 10.1016/j.ress.2022.108895
Preston J, et al. Impact of delays on passenger train services: Evidence from Great Britain. Transportation Research Record. 2009;2117(1):14-23. DOI: 10.3141/2117-03
Zhuang H, et al. Cause based primary delay distribution models of high-speed trains on account of operation records. Journal of China Railway Society. 2017;39(9):25-31. DOI: 10.3969/j.issn.1001-8360.2017.09.004
Wang J, Peng Y, Lu J, Jiang Y. Analysis of risk factors affecting delay of high-speed railway in China based on Bayesian network modeling. Journal of Transportation Safety & Security. 2021;3:1-22. DOI: 10.1080/19439962.2021.1890290
Goverde R. A delay propagation algorithm for large-scale railway traffic networks. Transportation Research Part C: Emerging Technologies. 2010;18(3):269-287. DOI: 10.1016/j.trc.2010.01.002
Yang B. Study on countermeasures of increasing punctuality of high-speed trains. Railway Transport and Economy. 2012;34(12):53-57.
Nabian M, Alemazkoor N, Meidani H. Predicting near-term train schedule performance and delay using Bi-level random forests. Transportation Research Record. 2019;2673(5):564-573. DOI: 10.1177/0361198119840339
Mirabadi A, Sharifian S. Application of association rules in Iranian railways (RAI) accident data analysis. Safety Science. 2010;48:1427-1435. DOI: 10.1016/j.ssci.2010.06.006
Montella A. Identifying crash contributory factors at urban roundabouts and using association rules to explore their relationships to different crash types. Accident Analysis & Prevention. 2011;43:1451-1463. DOI: 10.1016/j.aap.2011.02.023
Cheng C, Lin C, Leu S. Use of association rules to explore cause-effect relationships in occupational accidents in the Taiwan construction Industry. Safety Science. 2010;48:436-444. DOI: 10.1016/j.ssci.2009.12.005
Verma A, Khan S, Maiti J, Krishna O. Identifying patterns of safety related incidents in a steel plant using association rule mining of incident investigation reports. Safety Science. 2014;70:89-98. DOI: 10.1016/j.ssci.2014.05.007
Han J, Kamber M, Pei J. Data mining: Concepts and techniques. Beijing, China: Machinery Industry Press; 2012.
Aggarwal C. Data mining: The textbook. Beijing, China: Machinery Industry Press; 2021.
Wang J, Wang Y, Peng Y, Lu J. Examining partial proportional odds model in analyzing severity of high-speed railway accident. Smart and Resilient Transportation. 2020;3(1):1-13. DOI: 10.1108/SRT-10-2020-0022
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