描述行人接触互动轨迹,了解人群中的扩散风险

IF 3.1 3区 计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Jaeyoung Kwak , Michael H. Lees , Wentong Cai
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引用次数: 0

摘要

在社会和生物系统中,当特定信息、物质或疾病随着时间的推移在人群中传播时,就可以观察到传播过程。人们普遍认为,个体间的接触互动在传播过程中起着至关重要的作用。虽然接触互动通常会受到几何条件的影响,但人们很少关注这些条件的影响,尤其是对行人之间接触持续时间的影响。为了研究行人流设置如何影响接触持续时间分布,我们分析了单向、双向和多向设置的行人流实验中收集到的行人接触互动轨迹。根据转角熵和效率,我们对接触互动中观察到的运动类型进行了分类。我们发现,在单向流动设置中,大多数接触互动可归类为封闭运动,这暗示了接触持续时间较长的可能性。然而,在其他流动条件下,弹道运动更为常见,从而产生频繁而短暂的接触相互作用。我们的研究结果表明,无论行人流设置如何,观察到更多的封闭运动可能与平行接触相互作用的增加有关。这项研究强调,受限的运动往往会产生较长的接触时间,这表明即使传播率较低,传染病的传播风险也会相当大。这些结果对人群管理中的传播风险最小化具有重要意义。这项工作是 Kwak 等人(2023 年)在 2023 年国际计算科学大会(ICCS)上发表的论文的扩展版本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Characterizing pedestrian contact interaction trajectories to understand spreading risk in human crowds

A spreading process can be observed when particular information, substances, or diseases spread through a population over time in social and biological systems. It is widely believed that contact interactions among individual entities play an essential role in the spreading process. Although contact interactions are often influenced by geometrical conditions, little attention has been paid to understand their effects, especially on contact duration among pedestrians. To examine how the pedestrian flow setups affect contact duration distribution, we have analyzed trajectories of pedestrians in contact interactions collected from pedestrian flow experiments of uni-, bi- and multi-directional setups. Based on turning angle entropy and efficiency, we have classified the type of motion observed in the contact interactions. We have found that the majority of contact interactions in the unidirectional flow setup can be categorized as confined motion, hinting at the possibility of long-lived contact duration. However, ballistic motion is more frequently observed in the other flow conditions, yielding frequent, brief contact interactions. Our results demonstrate that observing more confined motions is likely associated with the increase of parallel contact interactions regardless of pedestrian flow setups. This study highlights that the confined motions tend to yield longer contact duration, suggesting that the infectious disease transmission risk would be considerable even for low transmissibility. These results have important implications for crowd management in the context of minimizing spreading risk.

This work is an extended version of Kwak et al. (2023) presented at the 2023 International Conference on Computational Science (ICCS).

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来源期刊
Journal of Computational Science
Journal of Computational Science COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
5.50
自引率
3.00%
发文量
227
审稿时长
41 days
期刊介绍: Computational Science is a rapidly growing multi- and interdisciplinary field that uses advanced computing and data analysis to understand and solve complex problems. It has reached a level of predictive capability that now firmly complements the traditional pillars of experimentation and theory. The recent advances in experimental techniques such as detectors, on-line sensor networks and high-resolution imaging techniques, have opened up new windows into physical and biological processes at many levels of detail. The resulting data explosion allows for detailed data driven modeling and simulation. This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods. Computational science typically unifies three distinct elements: • Modeling, Algorithms and Simulations (e.g. numerical and non-numerical, discrete and continuous); • Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems; • Computer and information science that develops and optimizes the advanced system hardware, software, networking, and data management components (e.g. problem solving environments).
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