Transformer-Based Macroscopic Regulation for High-Speed Railway Timetable Rescheduling

Abstract

Unexpected delays in train operations can cause a cascade of negative consequences in a high-speed railway system. In such cases, train timetables need to be rescheduled. However, timely and efficient train timetable rescheduling is still a challenging problem due to its modeling difficulties and low optimization efficiency. This paper presents a Transformer-based macroscopic regulation approach which consists of two stages including Transformer-based modeling and policy-based decision-making. Firstly, the relationship between various train schedules and operations is described by creating a macroscopic model with the Transformer, providing the better understanding of overall operation in the high-speed railway system. Then, a policy-based approach is used to solve a continuous decision problem after macro-modeling for fast convergence. Extensive experiments on various delay scenarios are conducted. The results demonstrate the effectiveness of the proposed method in comparison to other popular methods.