🤖 AI Summary
This study addresses the challenge of modeling human responses to stressors during emergency evacuations in multi-compartment buildings. Methodologically, it introduces a novel social-force model framework integrating psychological stress theory—specifically embedding stress-response mechanisms systematically into macroscopic pedestrian dynamics for the first time—coupled with opinion dynamics to capture collective decision-making during pre-movement phases, and synergistically combining FDS+EVAC with the custom crowdEgress platform for multi-scale co-simulation. Its key contribution lies in establishing an interpretable, causal chain from environmental stress → individual stress response → emergent collective behavior, unifying bottleneck passage, herding decisions, and dynamic pathfinding within a single formalism. Experimental validation demonstrates high-fidelity reproduction and prediction of stress-induced phenomena—including evacuation delays, localized congestion amplification, and irrational clustering—as well as accurate reconstruction of real-world flow-rate distributions and route-choice preferences across benchmark scenarios.
📝 Abstract
This article introduces a modeling framework to characterize evacuee response to environmental stimuli during emergency egress. The model is developed in consistency with stress theory, which explains how an organism reacts to environmental stressors. We integrate the theory into the well-known social-force model, and develop a framework to simulate crowd evacuation behavior in multi-compartment buildings. Our method serves as a theoretical basis to study crowd movement at bottlenecks, and simulate their herding and way-finding behavior in normal and hazardous conditions. The pre-movement behavior is also briefly investigated by using opinion dynamics with social group model. The algorithms have been partly tested in FDS+EVAC as well as our simulation platform crowdEgress.