Modeling and simulating human behavior in large-scale emergency evacuations: A comprehensive review.

Disasters pose persistent threats to human life and infrastructure, making evacuation planning vital for disaster risk reduction. The effectiveness of such efforts depends on understanding and accurately modeling human behavior. This study reviews peer-reviewed articles on large-scale evacuation planning and management, classifying them along two dimensions: behavioral factors influencing key authority-issued decisions and modeling approaches incorporating these dynamics within optimization, simulation, and simulation--optimization frameworks. Findings reveal that while demographic and route-choice behaviors are extensively studied, mode selection and road-segment designation remain largely unexplored. Optimization models commonly assume full- or non-compliance, with limited research that considers partial-compliance, leading to more realistic solutions. On the other hand, simulation-based studies capture dynamic and uncertain conditions more effectively but are dominated by rule-based behavioral proxies, particularly for departure timing and route choice, and typically limit dynamic feedback to route choice alone. Simulation--optimization approaches, while increasingly adopted, remain largely reliant on parameter-based behavioral representations rather than empirically calibrated, behavior-oriented coupling. Emphasizing the importance of embedding behavioral heterogeneity in model structures, this review develops a taxonomy, highlights research gaps, and outlines future directions for behaviorally-realistic and adaptive evacuation models that enhance the effectiveness, fairness, and practicality of evacuation strategies in real-world crises.