Temporal and Spatial Distributions of Primary Delays in a High-Speed Rail System

Improving the quality of service of a rail transportation system, and enhancing the operation safety require a quantitative understanding of the dynamic and stochastic characteristics of its train operations, especially those caused by unexpected disruptions. In this paper, based on historical train operation records, the characteristics of the primary delays (PDs) occurred on the Wuhan-Guangzhou (WH-GZ) high-speed railway (HSR) are investigated, with a specific focus on the underlying behavioral and physical factors. Alternative distribution models, including Log- normal, Weibull, and Gamma distributions, are calibrated and subsequently tested using hold-out data, to investigate the temporal and spatial distributions of PDs. The Kolmogorov- Smirnov (K-S) test results show that all the candidate models can fit the PD distribution curves, however, the Log-normal distributional form outperforms the other models. Subsequently, the model validation, carried out on the test dataset and the entire data, supported by the results obtained from the K-S two-sample test, indicate that the Log-normal model could satisfy the requirements with sufficient accuracy. Keywords–High-speed railway; Primary delay; Spatial and temporal distribution; Kolmogorov-Smirnov test; Train operation records

[1]  Liping Fu,et al.  Statistical investigation on train primary delay based on real records: evidence from Wuhan–Guangzhou HSR , 2017 .

[2]  Erhan Kozan,et al.  Modeling Train Delays in Urban Networks , 1998, Transp. Sci..

[3]  Rob M.P. Goverde,et al.  Evaluating Stochastic Train Process Time Distribution Models on the Basis of Empirical Detection Data , 2006 .

[4]  T Takimoto DEVELOPMENT OF EFFICIENT OPERATIONAL CONTROL USING OBJECT REPRESENTATION , 2000 .

[5]  Paul Schonfeld,et al.  Analyzing passenger train arrival delays with support vector regression , 2015 .

[6]  Jouni Wallander,et al.  Data mining in rail transport delay chain analysis , 2012 .

[7]  Wikimedia Commons,et al.  Automatic Train Control System Development and Simulation for High-Speed Railways , 2010 .

[8]  Norbert Pavlovic,et al.  A fuzzy Petri net model to estimate train delays , 2013, Simul. Model. Pract. Theory.

[9]  Lee Chapman,et al.  The impacts of the 28 June 2012 storms on UK road and rail transport , 2015 .

[10]  Meng Lingyun A method for constructing train delay propagation process by mining train record data , 2012 .

[11]  Yong Cui,et al.  Calibration of disturbance parameters in railway operational simulation based on reinforcement learning , 2016, J. Rail Transp. Plan. Manag..

[12]  Maddi Garmendia,et al.  High speed rail: implication for cities , 2012 .

[13]  R. Zamar,et al.  A multivariate Kolmogorov-Smirnov test of goodness of fit , 1997 .

[14]  Rob M.P. Goverde,et al.  Propagation of train delays in stations , 2002 .

[15]  Francesco Corman,et al.  Analyzing Railway Disruptions and Their Impact on Delayed Traffic in Chinese High-Speed Railway , 2016 .

[16]  Lei Zhang,et al.  Short-term forecasting of high-speed rail demand: A hybrid approach combining ensemble empirical mode decomposition and gray support vector machine with real-world applications in China , 2014 .

[17]  Chris Nash,et al.  Is high speed rail an appropriate solution to China’s rail capacity problems? , 2014 .