Crowded transport within networked representations of complex geometries
Crowded transport within networked representations of complex geometries
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DOI：
10.1038/s42005-021-00732-y
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发表时间：
2020-06
影响因子：
5.5
通讯作者：
D. Wilson;Francis G. Woodhouse;M. Simpson;R. Baker
中科院分区：
文献类型：
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作者：
D. Wilson;Francis G. Woodhouse;M. Simpson;R. Baker
在拥挤、复杂的环境中，运输跨越许多空间尺度。几何限制可能阻碍个人的行动，再加上拥挤，可能对全球迁移现象产生严重影响。然而，在一般情况下，拥挤和几何形状之间的相互作用在复杂的现实生活中的环境是知之甚少。现有的分析方法并不总是容易扩展到异构环境，在这些情况下，拥挤的交通行为的预测依赖于计算密集型网格为基础的方法。在这里，我们采取了不同的方法，基于复杂环境的网络表示，以提供一个有效的框架来探索环境的几何形状和拥挤之间的相互作用。我们演示了如何使用这个框架来提取详细的信息，无论是在个人的水平，以及整个人口，识别环境的拓扑特征，使运输现象的准确预测，并提供见解的最佳环境的设计。
Transport in crowded, complex environments occurs across many spatial scales. Geometric restrictions can hinder the motion of individuals and, combined with crowding, can have drastic effects on global transport phenomena. However, in general, the interplay between crowding and geometry in complex real-life environments is poorly understood. Existing analytical methodologies are not always readily extendable to heterogeneous environments and, in these situations, predictions of crowded transport behaviour rely on computationally intensive mesh-based approaches. Here, we take a different approach based on networked representations of complex environments in order to provide an efficient framework to explore the interactions between environments’ geometry and crowding. We demonstrate how this framework can be used to extract detailed information both at the level of the individual as well as of the whole population, identify the environments’ topological features that enable accurate prediction of transport phenomena, and provide insights into the design of optimal environments.