Development of a socially aware crowd flow model and control of crowd flow based on reinforcement learning

分析了社会关系和社会互动对行人运动模式的影响。特别是研究了生态环境中行人二人组与行人个体之间的避碰动力学。我们的研究结果表明，随着社会联系和互动强度的增加，避免碰撞变得更加明显。此外，我们观察到，随着社会联系强度和互动强度的增加，入侵的可能性降低。此外，为了了解视觉刺激如何影响行人运动（转向等），我们设计了一项初步研究，以评估在观察自然运动和人工运动时跟踪性能的差异。

Analyses of the impact of social relations and social interactions on pedestrian motion patterns have been pursued. In particular, the dynamics of collision avoidance between pedestrian two-person groups and individual pedestrians in an ecological environment have been studied. Our findings revealed that, as social bonding and interaction intensity increase, collision avoidance becomes more pronounced. Additionally, we observed that the likelihood of intrusion decreases as the strength of social bonding and interaction intensity increases.Furthermore, to understand how visual stimuli could be used to influence pedestrian motion (steering, etc.), a preliminary study to evaluate differences in tracking performances when viewing natural motion against artificial motion has been designed.