Social behavior in crowds, such as herding or increased interpersonal spacing, is driven by the psychological states of pedestrians. Current macroscopic crowd models assume that these are static, limiting the ability of models to capture the complex interplay between evolving psychology and collective crowd dynamics that defines a “social crowd”. This paper introduces a novel approach by explicitly incorporating an “activity” variable into the modeling framework, which represents the evolving psychological states of pedestrians and is linked to crowd dynamics. To demonstrate the role of activity, we model pedestrian egress when this variable captures stress and awareness of contagion. In addition, to highlight the importance of dynamic changes in activity, we examine a scenario in which an unexpected incident necessitates alternative exits. These case studies demonstrate that activity plays a pivotal role in shaping crowd behavior. The proposed modeling approach thus opens avenues for more realistic macroscopic crowd descriptions with practical implications for crowd management.

人群中的社会行为，例如羊群行为或增加人际间距，是由行人的心理状态驱动的。当前的宏观人群模型假设这些是静态的，限制了模型捕捉不断变化的心理和定义“社会人群”的集体人群动态之间复杂相互作用的能力。本文引入了一种新颖的方法，将“活动”变量明确地纳入建模框架中，该变量代表行人不断变化的心理状态，并与人群动态相关。为了证明活动的作用，当该变量捕获压力和传染意识时，我们对行人外出进行建模。此外，为了强调活动动态变化的重要性，我们研究了意外事件需要替代退出的场景。这些案例研究表明，活动在塑造人群行为方面发挥着关键作用。因此，所提出的建模方法为更现实的宏观人群描述开辟了道路，对人群管理具有实际意义。