Collaborative rescheduling of train timetables to relieve passenger congestions in an urban rail transit network: A rolling horizon approach

Abstract

At some urban rail transit (URT) stations, large activities, emergencies, or holidays usually lead to a significant surge in passenger flow demand quickly, known as Large Passenger Flow (LPF) events. The passenger congestion will spread quickly via transfer stations and affect other stations and lines in the URT network. This study develops a timetable rescheduling and coordinating method for the URT network under LPF events. Firstly, a collaborative adjustment model of train timetables with an implement backup vehicle strategy is formulated to simultaneously consider rescheduling and coordinating problems, to reduce the congestion influence for an URT network. Then, a rolling horizon approach is developed to divide the whole adjustment problem into several decision-making stages to ensure solution efficiency. In each decision-making stage, the influence of LPF propagation within the URT network is firstly evaluated. Based on the congestion evaluation results, the proposed method determines whether it’s necessary to adjust timetables of the LPF Line or other lines. The proposed method is applied to the Xi’an Metro network in China. Our results indicate that the proposed method can effectively evaluate and adjust the train timetables for large URT networks under the LPF events.