A Coupled SFM-ASCRIBE Model To Investigate the Influence of Emotions and Collective Behavior in Homogeneous and Heterogeneous Crowds

Yassine Lamrhary, Aissam Jebrane, Pierre Argoul, A. Boukamel, A. Hamdaoui
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Abstract

The understanding of crowd behavior dynamics holds immense significance in ensuring public safety across a range of situations, including emergency evacuations and large-scale events. Our research focuses on two primary objectives: investigating the impact of emotions on crowd movement and gaining valuable insights into collective behavior within crowds. To achieve this, we present a coupled model, incorporating an enhanced ASCRIBE model with an agent displacement model. We introduce heterogeneity into our model by incorporating specific mobility laws for different categories of panicked crowds, considering the influence of emotions on both speed and direction. Through numerical simulations, we analyze the model's parameters, observe the behavior of uniform crowds, and explore the collective dynamics within diverse crowds. By conducting comprehensive simulations and analyses, the findings from this study can contribute to the development of more effective crowd management strategies and emergency evacuation protocols.
研究同质和异质人群中情绪和集体行为影响的 SFM-ASCRIBE 耦合模型
了解人群行为动态对确保紧急疏散和大型活动等各种情况下的公共安全具有重要意义。我们的研究侧重于两个主要目标:研究情绪对人群移动的影响,以及获得对人群中集体行为的宝贵见解。为此,我们提出了一个耦合模型,将增强型 ASCRIBE 模型与代理位移模型相结合。考虑到情绪对速度和方向的影响,我们为不同类别的恐慌人群引入了特定的移动规律,从而在模型中引入了异质性。通过数值模拟,我们分析了模型的参数,观察了均匀人群的行为,并探索了不同人群的集体动态。通过进行全面的模拟和分析,本研究的结果将有助于制定更有效的人群管理策略和紧急疏散协议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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