Characterizing pedestrian contact interaction trajectories to understand spreading risk in human crowds
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arXiv
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866917712588963840 |
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| author | Kwak, Jaeyoung Lees, Michael H. Cai, Wentong |
| author_facet | Kwak, Jaeyoung Lees, Michael H. Cai, Wentong |
| contents | 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). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_02121 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Characterizing pedestrian contact interaction trajectories to understand spreading risk in human crowds Kwak, Jaeyoung Lees, Michael H. Cai, Wentong Physics and Society 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). |
| title | Characterizing pedestrian contact interaction trajectories to understand spreading risk in human crowds |
| topic | Physics and Society |
| url | https://arxiv.org/abs/2401.02121 |