校园通勤行人流时空伴随分析与疫情防控策略

doi:10.16265/j.cnki.issn1003-3033.2022.09.2737

中国安全科学学报 ›› 2022, Vol. 32 ›› Issue (9): 86-93.doi: 10.16265/j.cnki.issn1003-3033.2022.09.2737

校园通勤行人流时空伴随分析与疫情防控策略

马剑¹(), 李慧文¹, 宋丹丹¹, 陈娟²^,^**()

1 西南交通大学交通运输与物流学院,四川成都 610031
2 西南交通大学地球科学与环境工程学院,四川成都 610031

收稿日期:2022-03-12 修回日期:2022-07-11 出版日期:2022-10-19 发布日期:2023-03-28
通讯作者: 陈娟
作者简介:
马剑 (1983—),男,江苏徐州人,博士,教授,主要从事行人流与人员疏散动力学等方面的研究。E-mail: majian@swjtu.edu.cn。
陈娟讲师
基金资助:
国家自然科学基金资助(71871189); 国家自然科学基金资助(72104205); 四川省重点研发计划项目(2020YFS0291)

Spatiotemporal concomitant analysis and epidemic control strategies for commuter pedestrian flow in campus

MA Jian¹(), LI Huiwen¹, SONG Dandan¹, CHEN Juan²^,^**()

1 School of Transportation and Logistics, Southwest Jiaotong University, Chengdu Sichuan 610031,China
2 Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu Sichuan 610031,China

Received:2022-03-12 Revised:2022-07-11 Online:2022-10-19 Published:2023-03-28
Contact: CHEN Juan

摘要/Abstract

摘要：

为严防新冠肺炎(COVID-19)疫情在人员密集的高校蔓延,选取高校校园内学生流动的典型场景,构建校园内上下课行人流模型,引入时空伴随的概念,量化行人间接触导致疫情传播的风险。基于时空伴随指标,针对西南交大犀浦校区设计开放宿舍园区内的所有通道、增设不同区域间的新道路以及分批次上下课等3种校园疫情防控策略开展模拟计算。结果表明:3种方案的空间伴随指标降幅分别为12.12%、6.08%、74.02%,时间伴随指标的降幅分别为30.49%、0.16%、60.78%。同时施行3种防控方案时,空间伴随指标和时间伴随指标降幅分别为82.37%和76.63%。

关键词: 校园, 行人流, 时空伴随, AnyLogic, 新冠肺炎(COVID-19), 疫情防控

Abstract:

In order to prevent the spread of the epidemic due to the frequent movement of students, densely populated colleges and universities are under pressure during the normalization stage of epidemic prevention and control. A typical scene of student flow in college campuses was selected, and a pedestrian flow model on campus was built in this paper. By introducing the concept of spatiotemporal concomitant, the risk of epidemic transmission caused by pedestrian-to-pedestrian contact was quantified. Based on the spatiotemporal concomitant indicators, simulation calculations were carried out for three campus epidemic prevention and control strategies in Xipu Campus of Southwest Jiaotong University, including opening all passageways in the dormitory park, designing a new road between different areas, and classes in batches. Comparing and analyzing the simulation results, it can be found that the declines of the spatial concomitant indicators of the three strategies are: 12.12%, 6.08%, and 74.02%, and the declines of the temporal concomitant indicators are 30.49%, 0.16%, and 60.78%, respectively. When the three strategies are implemented at the same time, the declines of the spatial concomitant indicators and temporal concomitant indicators are 82.37% and 76.63% respectively.

Key words: campus, pedestrian flow, spatiotemporal concomitant, AnyLogic, corona virus disease 2019 (COVID-19), epidemic prevention

马剑, 李慧文, 宋丹丹, 陈娟. 校园通勤行人流时空伴随分析与疫情防控策略[J]. 中国安全科学学报, 2022, 32(9): 86-93.

MA Jian, LI Huiwen, SONG Dandan, CHEN Juan. Spatiotemporal concomitant analysis and epidemic control strategies for commuter pedestrian flow in campus[J]. China Safety Science Journal, 2022, 32(9): 86-93.

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宿舍楼号	1	2	3	4	5	6	7	8	9	10	11
平均上课人次	892	689	892	689	388	320	262	456	369	388	369
比例/%	7.61	5.88	7.61	5.88	3.31	2.73	2.24	3.89	3.15	3.31	3.15
宿舍楼号	12	13	14	15	16	17	18	19	20	21	22
平均上课人次	417	417	310	921	465	921	465	921	465	233	465
比例/%	3.56	3.56	2.65	7.86	3.97	7.86	3.97	7.86	3.97	1.99	3.97

教学楼号	1	2	3	4	5	6	7	8	9
平均上课人次	654	5 171	673	1 384	265	475	504	1 027	1 561
比例/%	5.58	44.14	5.75	11.81	2.26	4.05	4.30	8.77	13.33

区域	北区宿舍区	南区宿舍区	北区教学区	南区教学区	道路区	总计
空间伴随点数量/个	109 480	24 159	9 416	58 156	27 4115	475 326
比例/%	23.03	5.08	1.98	12.23	57.67	100

区域	北区宿舍区	南区宿舍区	北区教学区	南区教学区	道路区	总计
总伴随时间/s	10 200	1 714	395	3 394	21 430	37 133
比例/%	27.47	4.62	1.06	9.14	57.71	100

校园通勤行人流时空伴随分析与疫情防控策略

Spatiotemporal concomitant analysis and epidemic control strategies for commuter pedestrian flow in campus

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