Parallel Urban Rail Transit Stations for Passenger Emergency Management

Abstract

Passenger emergency management of urban rail transit station (URTS) has become an indispensable issue with attaching importance to economic benefits and personal security. In this article, a parallel URTS system for passenger emergency management is presented based on artificial systems, computational experiments, and parallel execution (ACP) approach. The agent-based modeling technology is applied to build the artificial URTS system, which contains the models of personal, trains, facilities, events, environments, and center control and decision unit. The computational experiments are performed on the artificial system to analyze and evaluate emergency management strategies. The mechanism of parallel execution between the actual system and artificial system is presented to manage and optimize the emergency strategy, which is capable of guiding the actual URTS system through real-time online supervision and adjustment and providing an active rather than a traditionally passive optimization of passenger emergency management. The ACP-based parallel URTS system provides a novel approach to formulation, evaluation, and optimization of passenger emergency management strategies for URTS.