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Modeling the collective behavior of pedestrians with the spontaneous loose leader–follower structure in public spaces
Computer-Aided Civil and Infrastructure Engineering ( IF 8.5 ) Pub Date : 2025-01-27 , DOI: 10.1111/mice.13429
Jie Xu, Dengyu Xu, Jing Wu, Xiaowei Shi

Gaining insights into pedestrian flow patterns in public spaces can greatly benefit decision‐making processes related to infrastructure planning. Interestingly, even pedestrians are unfamiliar with one another, they often follow others, drawing on positive information and engaging in a spontaneous collective behavior of pedestrians. To model this collective behavior, this paper proposed a social force‐based technique characterized by a loosely defined leader–follower structure. First, a complex field‐based phase transfer entropy (PTE) method was applied to measure the difference in information flow between pedestrians. Setting the detecting threshold with the 3 sigma principle, the radial basis function (RBF) was utilized to identify the leader in the collective. Integrating the PTE, RBF, and social force model (SFM), a comprehensive model (PTE‐RBF‐SFM) was developed to simulate collective behavior. Some bidirectional pedestrian flow data, collected from Fairground Düsseldorf, were used to validate the model in a real‐world setting. The results showed that the proposed model provided more realistic trajectories than benchmark models, and the spontaneous leader–follower structure was found to change over time and stable with time interval prolonging.

中文翻译:


在公共空间中,用自发的松散领导者-追随者结构对行人的集体行为进行建模



深入了解公共场所的行人流模式可以极大地有利于与基础设施规划相关的决策过程。有趣的是,即使是行人彼此不熟悉,他们也经常关注他人,获取积极信息并参与行人的自发集体行为。为了模拟这种集体行为,本文提出了一种基于社会力量的技术,其特征是定义松散的领导者-追随者结构。首先,应用基于复杂场的相转移熵 (PTE) 方法来测量行人之间信息流的差异。使用 3 西格玛原理设置检测阈值,利用径向基函数 (RBF) 来识别集合中的领导者。集成 PTE、RBF 和社会力量模型 (SFM),开发了一个综合模型 (PTE-RBF-SFM) 来模拟集体行为。从杜塞尔多夫展览中心收集的一些双向人流数据用于在真实环境中验证模型。结果表明,所提出的模型提供了比基准模型更真实的轨迹,并且发现自发的领导者-跟随者结构随时间变化并随着时间间隔的延长而稳定。
更新日期:2025-01-27
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