Enhancing Building Evacuation Efficiency in Case of Fire Breakout by Integrating Evacuee Categorization Into an Agent-Based Simulation

Abstract

Evacuating occupants from a burning building presents significant challenges owing to the complex interplay between environmental factors and evacuee behavior. Numerous models have been proposed in recent years for building evacuation during fire emergencies. However, many of these models fail to adequately account for variations in individuals’ environmental knowledge and health status, both of which can critically affect the evacuation process. To address this gap, this study introduces an agent-based model for building evacuation that differentiates between individuals familiar with the building layout and those who are not, and considers the health status of occupants. The resulting model assigned specific evacuation strategies tailored to each group within the building. Simulations conducted in a hospital setting demonstrate that incorporating factors such as familiarity with a building’s configuration and the health status of evacuees results in more realistic and effective evacuation outcomes. To evaluate the robustness of the proposed model and highlight the significance of our contribution, we conducted multiple simulations in various high-risk settings and presented a benchmarking study comparing our model with several existing models from the literature. The proposed model is sufficiently generalized to be applicable to various types of hospital buildings with minimal modifications.