Conversation Simulation and Behavioral Change Design for Evacuation Decision-Making

This study introduces multi-agent conversation models that utilize generative AI to overcome the challenges posed by traditional rule-based multi-agent simulations. It proposes an effective method for issuing appropriate evacuation instructions method through simulations considering psychological factors and information transmission during disasters. Using an earthquake as the disaster scenario, the correlation between agent conversations and evacuation behaviors was evaluated, and the effectiveness of various evacuation instructions were compared. Additionally, the evacuation instruction methods were analyzed, and the improvements in prediction accuracy were verified. This research enhances the understanding of evacuation behavior during disasters and contributes to the development of realistic disaster response simulations, offering insights for improving actual evacuation instruction methods.