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

Abstract

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 Lognormal, 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.