State-dependent Multi-agent Discrete Event Simulation for Urban Rail Transit Passenger Flow

Abstract

Urban Rail Transit Passenger Flow Modeling (URTPFM) is the foundation of urban rail transit (URT) planning, design, and operation. The motivation of this paper is to accurately and efficiently simulate passenger flow dynamics in URT systems. To this end, a State-dependent Multi-agent Discrete Event Simulation (SdMaDES) based on the O²DES.NET framework is proposed to quickly estimate passenger movement in the URT system. Specifically, we first establish a Multi-agent Discrete Event Simulation (MaDES), which includes four types of modules (passenger, train, station, and network modules) and three types of agents (passenger, train, and station agents). The logical connections and event triggering modes between the modules are analyzed and defined, and 30 types of events are designed. The state-dependence is then captured by an improved social force model (ISFM), which adds autonomous obstacle avoidance. The ISFM reproduces passenger movement behavior within bottleneck facilities of URT systems at the microscopic level. The state-dependent parameters fitted from the result of ISFM are applied to the proposed MaDES model, resulting in the SdMaDES, to increase the accuracy of the simulation. A real case from the Chengdu Metro network is used to verify the effectiveness of the proposed method. The results show that the SdMaDES model has higher accuracy than the MaDES model with similar efficiency.

Keywords: discrete event simulation, multi-agent simulation, state-dependence, urban railway transit, social force model