Discrete-event simulations for metro train operation under emergencies: A multi-agent based model with parallel computing

Abstract

Emergencies of metro systems have become more frequent in rush hours, which have significant consequences for metro planning, designing, operating, and even the passengers’ daily travel. The motivation of this paper is to establish a hybrid metro simulation method with high efficiency and sufficient precision. To this end, a discrete-event simulation method based on a multi-agent model with parallel computing is proposed to estimate the effects of emergencies efficiently. Firstly, the trains’ motion algorithms are developed to compute the train speed profile for normal operation and metro emergency operation, respectively. Moreover, three types of agents (passenger, station, and train agents) are classified for rescheduling calculation, and six types of events are defined to discretize the emergency simulation process. Furthermore, a parallel computing method is proposed to accelerate the simulation process. Finally, a case study of the Yizhuang Line in Beijing metro is conducted to verify the effectiveness of the proposed simulation methodology. The results have proved the effectiveness and practicality of the proposed simulation method and the influence of the positions where emergencies occur and the emergency durations upon delays of trains and passengers.