Evacuation Decision

Evacuation decision research focuses on understanding and optimizing human behavior during emergencies, aiming to improve safety and efficiency in evacuations from various environments. Current research employs diverse modeling approaches, including agent-based models (often incorporating game theory or reinforcement learning), cellular automata, and machine learning techniques like random forests and enhanced logistic regression, to simulate and predict evacuation dynamics, considering factors like environmental conditions, individual characteristics, and social interactions. These studies are crucial for informing the design of safer buildings, developing effective emergency response plans, and improving the accuracy of evacuation time predictions, ultimately leading to better preparedness and reduced casualties in real-world emergencies.