Highlights What are the main findings? The agent-based evacuation model accurately reflects the real-life reactions of individuals during evacuation scenarios by incorporating behavioral conditions such as accidents, hysteria, and disorientation. This allows the model to provide more realistic and applicable results compared to traditional models that do not account for these factors. The proposed model offers valuable insights into the evacuation process by simulating interactions between individuals, obstacles, and exits in diverse urban environments. Through comprehensive experiments and case studies, the model demonstrates its ability to provide a more precise assessment of evacuation behavior and effectiveness during emergency scenarios. What is the implication of the main finding? By accurately simulating the behaviors of individuals under stress, this model enables planners to better predict and prepare for real-world evacuation scenarios. This can improve the design of safety protocols, optimize evacuation routes, and help reduce the risks associated with emergency evacuations in both natural and human-made disasters. The model's accurate evaluation of evacuation patterns provides crucial knowledge that can guide the creation of more robust urban structures and regulations. By comprehending how people navigate around barriers, locate exits, and interact with one another during evacuations, we can enhance architectural designs, optimize exit locations, and implement specific measures to reduce crowding and improve the overall effectiveness of evacuation procedures.Highlights What are the main findings? The agent-based evacuation model accurately reflects the real-life reactions of individuals during evacuation scenarios by incorporating behavioral conditions such as accidents, hysteria, and disorientation. This allows the model to provide more realistic and applicable results compared to traditional models that do not account for these factors. The proposed model offers valuable insights into the evacuation process by simulating interactions between individuals, obstacles, and exits in diverse urban environments. Through comprehensive experiments and case studies, the model demonstrates its ability to provide a more precise assessment of evacuation behavior and effectiveness during emergency scenarios. What is the implication of the main finding? By accurately simulating the behaviors of individuals under stress, this model enables planners to better predict and prepare for real-world evacuation scenarios. This can improve the design of safety protocols, optimize evacuation routes, and help reduce the risks associated with emergency evacuations in both natural and human-made disasters. The model's accurate evaluation of evacuation patterns provides crucial knowledge that can guide the creation of more robust urban structures and regulations. By comprehending how people navigate around barriers, locate exits, and interact with one another during evacuations, we can enhance architectural designs, optimize exit locations, and implement specific measures to reduce crowding and improve the overall effectiveness of evacuation procedures.Abstract Buildings and their supporting infrastructure are vulnerable to both natural and human-made disasters, which pose significant risks to the safety of the occupants. Evacuation models are essential tools for assessing these risks and for ensuring the safety of individuals during emergencies. The primary objective of an evacuation model is to realistically simulate the process by which a large group of people can reach available exits efficiently. This paper introduces an agent-based evacuation model that represents the environment as a rectangular grid, where individuals, obstacles, and exits interact dynamically. The model employs only five rules to simulate evacuation dynamics while also accounting for complex factors such as movement and stagnation. Different from many evacuation models, this approach includes rules that account for common behaviors exhibited in stressful evacuation situations such as accidents, hysteria, and disorientation. By incorporating these behavioral conditions, the model more accurately reflects the real-life reactions of individuals during evacuation, leading to more realistic and applicable results. To validate the effectiveness of the proposed model, comprehensive experiments and case studies are conducted in diverse urban settings. The results of these experiments demonstrate that the model offers valuable insights into the evacuation process and provides a more precise assessment of its behavior in emergency scenarios.
