Phase Transitions in Pedestrian Evacuation: A Dynamic Modeling With Small-World Networks

In today’s high-density urban environments, understanding pedestrian behavior in emergency evacuations is increasingly crucial. This study develops a sophisticated model integrating small-world network dynamics with emotional contagion to dissect pedestrian behaviors in such situations. Utilizing agent-based and complex network analyses, it delves into phase transitions in pedestrian order under various risk scenarios. The findings demonstrate significant behavioral variations in medium-risk environments, which are especially susceptible to transitions from orderly to disorderly states. This model emphasizes the important roles of emotional contagion in shaping crowd dynamics and the psychological factors alongside physical ones in evacuation strategies. Notably, this research illuminates the impacts of crowd size and speed on disorder evolution, which offers valuable insights for urban planning, architectural design, intelligent transportation systems, and emergency management. Overall, our study enriches the understanding of pedestrian dynamics in emergencies and provides a foundation for developing more effective public safety measures.