预测(人工智能)
动力学(音乐)
运动(物理)
行人
计算机科学
社会力量模型
运动(音乐)
瓶颈
模拟
人机交互
认知心理学
心理学
人工智能
物理
工程类
运输工程
嵌入式系统
声学
教育学
作者
Xiangmin Hu,Tao Chen,Yushan Song
出处
期刊:Chaos
[American Institute of Physics]
日期:2023-07-01
卷期号:33 (7)
被引量:3
摘要
Humans have excellent predictive capabilities, and this anticipation would reflect in the interactions between people. In this work, we utilize the elliptical specification of the social force model (SFM) for pedestrian movements to study how anticipation affects motion dynamics. An elliptical potential determines the interaction between pedestrians not in contact. Anticipation is introduced by shaping the ellipse according to the relative velocity. By adjusting the time to extrapolate, we can control the strength of anticipation. Simulations are conducted in four typical scenarios, i.e., circular motion, crowd gathering, escape through a bottleneck, and free wander. In each case, the qualitative observations from visual animations are followed by quantitative analyses involving different indicators. Simulation results demonstrate that anticipation plays an important role in pedestrian dynamics in several aspects. Briefly, it helps stabilize the movement by reducing perturbations, facilitates a more ordered crowd configuration, and promotes spontaneous collective motion. The findings may set avenues for further research in anticipation dynamics.
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