The ambient population, i.e. the demographics and volume of people in a particular location throughout the day, has been studied less than the night-time residential population. Although the spatio-temporal behaviour of some groups, such as commuters, are captured in sources such as population censuses, much less is known about groups such as retired people who have less documented behaviour patterns. This paper uses agent-based modelling to disaggregate some ambient population data to estimate the size and demographics of the constituent populations during the day. This is accomplished by first building a model of commuters to model typical 9–5 workday patterns. The differences between the model outputs and real footfall data (the error) can be an indication of the contributions that other groups make to the overall footfall. The research then iteratively simulates a wider range of demographic groups, maximising the correspondence between the model and data at each stage. An application of this methodology to the town centre of Otley, West Yorkshire, UK, is presented. Ultimately this approach could lead to a better understanding about how town- and city-centres are used by residents and visitors, contributing useful information in a situation where raw data on the populations do not exist.

中文翻译：

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使用每小时人口流量数据和基于代理的每日流动性模型量化环境人口

研究的环境人口，即一天中特定位置的人口统计信息和人口数量，少于夜间居住人口的数量。尽管通勤者等某些群体的时空行为是在人口普查等来源中捕获的，但对于诸如退休人群等行为模式文献较少的群体却知之甚少。本文使用基于主体的模型来分解一些环境人口数据，以估计白天组成人口的规模和人口统计。这是通过首先建立通勤者模型来模拟9–5个典型工作日模式来实现的。模型输出与实际人流量数据之间的差异（误差）可以表明其他群体对总体客流量的贡献。然后，该研究迭代地模拟了更大范围的人口统计群体，从而最大化了模型与数据在每个阶段之间的对应关系。介绍了该方法在英国西约克郡奥特利市中心的应用。最终，这种方法可以使人们更好地了解居民和游客如何使用城镇中心，在不存在有关人口原始数据的情况下提供有用的信息。