Stochastic Model of Train Running Time and Arrival Delay: A Case Study of Wuhan–Guangzhou High-Speed Rail

Train operations are subject to stochastic variations, reducing service punctuality and thus the quality of service (QoS). Models of such variations are needed to evaluate and predict the potential impact of disturbances and to avoid service punctuality reduction in train service management and timetabling. In this paper, through a case study of the Wuhan–Guangzhou (WH–GZ) high-speed rail (HSR), we show how a wealth of train operation records can be used to model the stochastic nature of train operations at each level, section and station. Specifically, we examine different distribution models for running times of individual sections and show that the Log-logistic probability density function is the best distributional form to approximate the empirical distribution of running times on the specified line. Next, we show that the distribution of running times in each section can be used to accurately infer arrival delays. Consequently, we construct the underlying analytical model and derive the respective arrival delay distribution at the downstream stations. The results support the correctness of the model presented and show that the proposed model is suitable for constructing the distribution of arrival delays at every station of the specified line. We show that the integrated distribution models of running times and arrival delays, driven by empirical data, can also be used to evaluate the QoS at individual track sections.

Stone blowing as a remedial measure to mitigate differential movement problems at railroad bridge approaches

Railroad track transitions such as bridge approaches often experience recurrent track geometry problems due to differential settlement between the bridge and the adjacent track. The resulting “bump at the end of the bridge” leads to significant passenger discomfort and causes rapid deterioration of the track as well as vehicular components. In general, railroad managers address recurrent track geometry defects through track resurfacing methods, such as tamping that involve raising the track through mechanically induced vibration and rearrangement of particles within the ballast layer. Although widely used for track resurfacing, the tamping process tends to destabilize the ballast layer, and the track may rapidly return to its former deteriorated state based on the traffic flow. The method of “stone blowing,” on the other hand, which was developed as an alternative to tamping, relies on the principle of injecting fresh ballast particles into gaps underneath ties and raising the track level rather than disturbing the packing condition of the existing ballast. In a recently completed research study in the United States, stone blowing was successfully implemented as a remedial measure to mitigate the problem of differential movement at a problematic bridge approach along Amtrak’s Northeast Corridor. Advanced geotechnical instrumentation was used to monitor transient deformations within individual track substructure layers before and after stone blowing. Moreover, tie support conditions and track geometry data were also analyzed to quantify the effectiveness of stone blowing on the improvement of track performance.