Research on Game-Theoretic Behavior of Collective Emergency Evacuation in Wildfire Under the Drive of Individual Risk Perception

The increasing frequency of wildfires has made large-scale collective emergency evacuation increasingly critical. However, existing studies provide limited understanding of how information structures shape the interaction between individual risk perception and collective evacuation behavior. This study develops a collective evolutionary game-based evacuation framework under ambiguous and clear information conditions. Under ambiguous information, individual heterogeneity in risk sensitivity, mobility, and resource endowment is incorporated into social interaction payoffs. Under clear information, observable evacuation consequences, including travel time, risk exposure, and congestion effects derived from route-choice interactions, are incorporated into evacuation utility. Numerical simulations examine the evolutionary characteristics of collective evacuation behavior under different information conditions and population scales. The results show that social interactions play an important role in shaping evacuation decisions under ambiguous information, while congestion effects and route-choice interactions influence evacuation utility under large-scale demand. Sensitivity analyses further demonstrate that congestion representation affects evacuation utility across different population scales. These findings highlight the importance of considering information structure, individual heterogeneity, and collective interactions in evacuation modeling. Emergency management should therefore improve risk communication, evacuation capacity, and congestion mitigation strategies. This study provides theoretical insights into collective evacuation decision-making under heterogeneous information conditions.

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Publication Details

Journal
Fire
Published
2026-09-14
DOI
https://doi.org/10.3390/fire9090397
Primary Topic
Evacuation and Crowd Dynamics
Type
article
Field-Weighted Citation Impact
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article

Research on Game-Theoretic Behavior of Collective Emergency Evacuation in Wildfire Under the Drive of Individual Risk Perception

Mingyuan Li, Yueqiao Yang, Yuanhong Bi, Zewen Song et al.
Fire
Evacuation and Crowd Dynamics
article

Research on Game-Theoretic Behavior of Collective Emergency Evacuation in Wildfire Under the Drive of Individual Risk Perception

Mingyuan Li, Yueqiao Yang, Yuanhong Bi, Zewen Song, Zhixiang Yuan, Liang Zhao, Gege Gai
article en

Abstract

The increasing frequency of wildfires has made large-scale collective emergency evacuation increasingly critical. However, existing studies provide limited understanding of how information structures shape the interaction between individual risk perception and collective evacuation behavior. This study develops a collective evolutionary game-based evacuation framework under ambiguous and clear information conditions. Under ambiguous information, individual heterogeneity in risk sensitivity, mobility, and resource endowment is incorporated into social interaction payoffs. Under clear information, observable evacuation consequences, including travel time, risk exposure, and congestion effects derived from route-choice interactions, are incorporated into evacuation utility. Numerical simulations examine the evolutionary characteristics of collective evacuation behavior under different information conditions and population scales. The results show that social interactions play an important role in shaping evacuation decisions under ambiguous information, while congestion effects and route-choice interactions influence evacuation utility under large-scale demand. Sensitivity analyses further demonstrate that congestion representation affects evacuation utility across different population scales. These findings highlight the importance of considering information structure, individual heterogeneity, and collective interactions in evacuation modeling. Emergency management should therefore improve risk communication, evacuation capacity, and congestion mitigation strategies. This study provides theoretical insights into collective evacuation decision-making under heterogeneous information conditions.

FireVol. 9(9)
University of Management and Technology (US), Gansu Academy of Sciences (CN), Beijing University of Civil Engineering and Architecture (CN), China Earthquake Administration (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 15%
Evacuation and Crowd Dynamics
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