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Due to the universal existence of human subgroups in reality, an increasing number of studies have incorporated them into the modeling process of crowd evacuation. However, such models seldom explain subgroup behaviors from the aspect of what individuals see and how they respond to visual input. Here, we propose a vision-driven model based on cognitive heuristics, in which the mechanisms of avoidance with the environment and attraction to other members within the field of view are explicitly clarified. Numerical simulations demonstrate that various spatial characteristics of subgroup members can be effectively represented by this model, and both the intensity and heterogeneity of spatial cohesion have significant impacts on subgroup evacuation. By comparing with an empirical study, the reproducibility of our model has been validated in terms of the temporal and spatial dimensions. This model produces more natural and realistic subgroup behaviors in multiple interaction contexts than existing models, and also quantitatively exhibits the superiority in reproduction effects. Overall, this work provides an interpretable mathematical framework for modeling subgroups from the perspective of visual perception.

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.