ABSTRACT

In the COVID-19 pandemic, keeping a two-metre physical distance (called social distancing) from others is a critical action to limit the amount of social contact among individuals. Thus, regulating the number of persons in a space is one means to limit social contact and ensure physical distancing among people. In addition to the privacy concerns of individuals’ locations, the lack of elevation information can result in false positive cases for people who are horizontally close but vertically apart beyond the social distance. Therefore, we develop a normative model of the statistical distribution of physical distances to estimate the number of persons not social distancing in a three-dimensional complex built space from the current number of persons in the space (i.e. population density) present on an hourly basis. We conduct an empirical case study in the districts around the central stations of 13 of Japan’s prefectures. To determine the number of people not social distancing in these districts, the proposed model uses open data such as the number of persons before the national emergency declaration, the ratio of the number of persons after the declaration to that before, and the floor area ratio specified by land use regulations in these districts.

摘要

在 COVID-19 大流行中，保持两米的物理距离（称为社交距离）) 来自他人是限制个人之间社交接触量的关键措施。因此，调节空间中的人数是限制社会接触和确保人与人之间保持身体距离的一种手段。除了个人位置的隐私问题之外，缺乏海拔信息可能会导致水平靠近但垂直远离社交距离的人出现误报。因此，我们开发了一个物理距离统计分布的规范模型，以根据每小时存在的空间中当前人数（即人口密度）来估计三维复杂建筑空间中未保持社交距离的人数. 我们在日本 13 个都道府县的中央车站周边地区进行了实证案例研究。