A Simulation-Based Model for Evacuation Demand Estimation under Unconventional Metro Emergencies

Abstract

When metro networks are shut down due to an unconventional emergency, numerous passengers will get stranded and wait to be evacuated. A clear understanding of the stranded passengers in the network is the basis for designing an efficient evacuation strategy. Previous studies focused more on disruption management and assumed a known evacuation demand. Few studies considered the distribution of stranded passengers, especially when the metro network is shut down due to unconventional emergencies. This motivates us to develop a discrete event-based simulation model to estimate the number and distribution of stranded passengers. The proposed model takes the numbers of stranded passengers at stations and trains as the state variables and develops the state evolution rule of the metro system. The numbers and destinations of stranded passengers at trains and on stations at each time step, including the transfer and non-transfer stations, are calculated to describe the state evolution of the metro system. Chongqing Rail Transit (CRT) network is taken as an example. The result shows that the stations with the most stranded passengers are located downtown. Origin-Destinations (ODs) with more stranded passengers have a relatively shorter travel distance, while ODs with fewer stranded passengers have a relatively long travel distance. The average directional disequilibrium factor of stranded passengers of ODs in the whole network is high, especially for those ODs with many stranded passengers. These findings reveal the distribution characteristics of stranded passengers and can provide significant assistance to an emergency manager who is designing an efficient emergency evacuation plan.