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Data Collection for Modeling and Simulation: Case Study at the University of Milan-Bicocca

机译:建模和仿真的数据收集:米兰比可卡大学的案例研究

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The investigation of crowd dynamics is a complex field of study that involves different types of knowledge and skills, and, also from the socio-psychological perspective, the definition of crowd is still controversial. We propose to investigate analytically this phenomenon focusing on pedestrian dynamics in medium-high density situations, and, in particular, on proxemic behavior of walking groups. In this work we will present several results collected during the observation of the incoming pedestrian flows to an admission test at the University of Milano-Bicocca. In particular, we collected empirical data about: levels of density and of service, group spatial arrangement (degree of alignment and cohesion), group size and composition (gender), walking speed and lane formation. The statistical analysis of video footages of the event showed that a large majority of the incoming flow was composed of groups and that groups size significantly affects walking speed. Collected data will be used for an investigative modeling work aimed at simulating the observed crowd and pedestrian dynamics.
机译:人群动力学的研究是一个复杂的研究领域,涉及不同类型的知识和技能,而且从社会心理学角度来看,人群的定义仍存在争议。我们建议对这种现象进行分析研究,重点关注中高密度情况下的行人动态,尤其是步行人群的近距离行为。在这项工作中,我们将介绍在米兰比可卡大学的入学考试中观察到的行人流量过程中收集到的一些结果。特别是,我们收集了以下经验数据:密度和服务水平,群体空间安排(对齐和凝聚度),群体规模和组成(性别),步行速度和车道形成。对事件录像的统计分析表明,大部分传入流量是由组组成的,并且组的大小会显着影响步行速度。收集的数据将用于调查建模工作,旨在模拟观察到的人群和行人动态。

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