期刊
PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
卷 289, 期 1970, 页码 -出版社
ROYAL SOC
DOI: 10.1098/rspb.2021.2089
关键词
collective behaviour; crowd dynamics; pedestrian dynamics; vision-based model; agent-based model
Patterns of collective motion in bird flocks, fish schools, and human crowds emerge from local interactions between individuals, which are influenced by visual coupling. This visual model outperforms previous models and explains basic properties of interaction, showing that local interactions underlying human flocking are a natural consequence of the laws of optics.
Patterns of collective motion in bird flocks, fish schools and human crowds are believed to emerge from local interactions between individuals. Most 'flocking' models attribute these local interactions to hypothetical rules or metaphorical forces and assume an omniscient third-person view of the positions and velocities of all individuals in space. We develop a visual model of collective motion in human crowds based on the visual coupling that governs pedestrian interactions from a first-person embedded viewpoint. Specifically, humans control their walking speed and direction by cancelling the average angular velocity and optical expansion/contraction of their neighbours, weighted by visibility (1 - occlusion). We test the model by simulating data from experiments with virtual crowds and real human 'swarms'. The visual model outperforms our previous omniscient model and explains basic properties of interaction: 'repulsion' forces reduce to cancelling optical expansion, 'attraction' forces to cancelling optical contraction and 'alignment' to cancelling the combination of expansion/contraction and angular velocity. Moreover, the neighbourhood of interaction follows from Euclid's Law of perspective and the geometry of occlusion. We conclude that the local interactions underlying human flocking are a natural consequence of the laws of optics. Similar perceptual principles may apply to collective motion in other species.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据