Simulation-based optimization of timetables coordination in an urban rail transit network

Abstract

Synchronous optimization of train timetables is to solve the problem of train service coordination among different lines in the urban rail transit network, which can reduce passenger waiting time and subsequently enhance passenger satisfaction. This paper develops an efficient simulation system to reproduce the train operation of an urban rail network. It takes into account the realistic characteristics of urban rail operations, including time-dependent demand, dynamic dwell time, and train capacity constraint. In the simulations, both the train trajectories and the passenger waiting time can be easily obtained. On this basis, a simulation-based algorithm (i.e., simultaneous perturbation stochastic approximation, SPSA) is designed to search an improved flexible-interval dispatch solution in the network. A case study of the Chengdu urban rail transit network is implemented to verify the effectiveness of the simulation system and the optimization algorithm. The simulation system is found to be time efficient since it takes less than 1 s to simulate the network with 4 h of operation and more than 200,000 passengers. The optimization algorithm is also effective as it can reduce the average passenger waiting time by 9.52 % compared to the equal-interval dispatch solution without increasing the train service frequency. It is also found that the reduction in waiting time is mainly due to the improved coordination of train services in the transfer station.