Experiment and path optimization on Large-Space Multi-Area crowd evacuation

Abstract

Abstract In large spaces where there are multiple evacuation zones, the flow patterns during evacuation are intricate, leading to congestion in emergency scenarios, and affecting evacuation efficiency. To address this, we proposed an optimization method for crowd evacuation paths in large-space multi-area environment settings under fire scenarios by utilizing multi-agent simulation. Using Pathfinder software, disorganized evacuation simulations are conducted within expansive multi-zonal settings to pinpoint areas with inadequate evacuation capabilities. Subsequent evacuation experiments are performed for verification, facilitating adjustments to agent-based model parameters for evacuees in fire scenarios, and carrying out organized evacuation simulations. Through meticulous simulation analysis, we aim to optimize the most efficient evacuation paths under organized responses in large-space multi-area settings. Results indicate that in emergency conditions due to fire, the evacuation speeds reach 1.8 m/s, and significant reductions in total evacuation time are achieved through simulation optimization, with the time required for the slowest individuals to evacuate decreasing from 240.32 s to 209.32 s. Furthermore, the flow rate per second at congested exits diminishes from 2.01 persons/s to 1.39 persons/s, highlighting the efficacy of the proposed path optimization method.