Simulation Based Robustness Evaluation of Train Rescheduling Plan Under Uncertainties

Dezhao Zhao, Dongliang Cui, Pengxin Yang, Ruiguang Liu, Xuewu Dai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


When a train deviates from its planned operational schedule due to unexpected events causing delays, it becomes necessary to reschedule the train in order to obtain a revised operation plan and minimize the delays. However, evaluating the robustness of the actual train schedule under various uncertainties is a critical aspect of train rescheduling. This paper presents the development of a simulation system for high-speed railway operation scheduling and proposes a method to evaluate the robustness of train rescheduling plans considering uncertain disturbances in the simulation process. The simulation system incorporates a train operation model based on both mechanisms and data, as well as an uncertain interference model for train delays based on data. By introducing various disturbances generated by the uncertain interference model, the robustness of the train rescheduling plan can be simulated and evaluated. Using the Jinan West-Shanghai Hongqiao high-speed railway network as a case study, the rescheduling plans generated by two scheduling algorithms are simulated. The results validate the reliability of the developed simulation system for verifying and evaluating train rescheduling plans. Furthermore, it provides valuable data and technical support for intelligent scheduling of high-speed trains and performance verification of scheduling algorithms.
Original languageEnglish
Title of host publication2023 28th International Conference on Automation and Computing (ICAC)
Subtitle of host publicationDigitalisation for Smart Manufacturing and Systems: Aston University, Birmingham, UK 30th Aug – 1st Sep 2023
Place of PublicationPiscataway, NJ, USA
Number of pages6
ISBN (Electronic)9798350335859
ISBN (Print)9798350335866
Publication statusPublished - 30 Aug 2023

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