A Hybrid Model for Evacuation Simulation Under Extreme High-Density Crowds

Abstract

High-density commercial districts are vibrant hubs in modern cities, yet during peak periods, they face immense evacuation pressure that severely threatens sustainable urban governance. Under extreme crowd gathering, restricted egress pathways and spatial bottlenecks can rapidly escalate physical compression into stampede hazards, making timely evacuation exceptionally difficult. To alleviate these site-specific vulnerabilities and enhance urban disaster resilience, this study proposes an innovative hybrid simulation framework, designated as the Extreme Crowd Evacuation (ECE) model, which deeply couples multi-agent (MA) and cellular automata (CA) approaches. Crucially, its core innovation lies in a dynamic accumulation mechanism of localized stampede hazards. This mechanism quantitatively couples crowding pressure with progressive biomechanical trauma, converting physiological injury into a direct driver of speed degradation rather than a static output, thereby realistically capturing dynamic crowd vulnerability under extreme densities. Simulating a typical open commercial district in China with official operational data, the model yields critical safety bounds: when the initial population exceeds 3.75×104 persons, fatalities rise non-linearly; at a 30% tourist ratio, fatalities surge to around 2% of total evacuees. Driven by these safety thresholds, targeted crowd guidance and spatial management strategies are formulated. These outcomes confirm the model’s effectiveness in assessing extreme crowd congestion while providing actionable decision-support for sustainable emergency management in dense public spaces.