[1]胡明伟,等.基于系统动力学的地铁客流防疫调控仿真分析[J].深圳大学学报理工版,2021,38(2):111-120.[doi:10.3724/SP.J.1249.2021.02111]
 HU Mingwei,,et al.Simulation analysis of epidemic prevention and regulation for metro passenger flow based on system dynamics[J].Journal of Shenzhen University Science and Engineering,2021,38(2):111-120.[doi:10.3724/SP.J.1249.2021.02111]
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基于系统动力学的地铁客流防疫调控仿真分析()
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《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第38卷
期数:
2021年第2期
页码:
111-120
栏目:
交通物流
出版日期:
2021-03-12

文章信息/Info

Title:
Simulation analysis of epidemic prevention and regulation for metro passenger flow based on system dynamics
文章编号:
202102001
作者:
胡明伟1 2 3李微微1陈湘生1 2 3
1) 深圳大学土木与交通工程学院,广东深圳 518060
2)深圳大学滨海城市韧性基础设施教育部重点实验室,广东深圳 518060
3)深圳大学未来地下城市研究院,广东深圳 518060
Author(s):
HU Mingwei1 2 3 LI Weiwei1 and CHEN Xiangsheng1 2 3
1) College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, Guangdong Province, P.R.China
2) Key Laboratory of Coastal Urban Resilient Infrastructures of Ministry of Education, Shenzhen University , Shenzhen 518060, Guangdong Province, P.R.China
3) Underground Polis Academy, Shenzhen University, Shenzhen 518060, Guangdong Province, P.R.China
关键词:
交通运输工程新型冠状病毒肺炎地铁站系统动力学客流调控交通出行易感度
Keywords:
transportation engineering corona virus disease 2019 (COVID-19) metro station system dynamics (SD) passenger flow regulation traffic-infected susceptibility
分类号:
U239.5
DOI:
10.3724/SP.J.1249.2021.02111
文献标志码:
A
摘要:
新型冠状病毒主要通过飞沫和空气传播,地铁是大运量公共交通方式,站内客流密度高,存在一定的感染风险,需采取有效客流组织和调控措施降低站内感染风险概率.借助系统动力学模型仿真地铁车站客流组织和分布;提出改进的交通出行易感度计算模型,并预测感染概率;运用仿真手段评价限制进站客流量、控制服务设施数量、延长站厅走行流线及增加地铁发车频次4种客流调控方案,并定量分析其对易感度的影响.研究结果表明,限制进站客流量对降低非付费区易感度较为有效;增加地铁发车频次对降低付费区易感度较为有效;延长站厅区域走行流线对降低站台层易感度较为有效. 系统动力学建模为客流防控措施的预案制定和比较评价提供有效手段,仿真分析结果可为地铁站运营管理方采取科学防疫措施提供参考.
Abstract:
According to the spreading mechanism of corona virus disease 2019 (COVID-19), the passengers in the metro system have a certain risk of being infected because the metro is a large capacity public transport mode with high passenger density in the stations. Relevant operational agencies need to organize passenger flow and take measures effectively to reduce infection risk in stations. In this paper, we establish a system dynamics model to simulate the passenger flow organization and distribution in metro stations. Then, we build an improved calculation model for the traffic-infected susceptibility and use it to predict the probability of infection. Four passenger flow control schemes are evaluated and their impacts on susceptibility are quantitatively analyzed. The four passenger flow control schemes include limiting the inbound passenger flow, controlling the number of service facilities, extending the streamline length of the station hall, and increasing the frequency of metro trains. The simulation results show that limiting the passenger flow is more effective in reducing the susceptibility of the unpaid area, increasing the frequency of metro trains is more effective in reducing the susceptibility of the paid area, and extending the streamline length of the station hall is more effective in reducing the susceptibility of the platform. We find that system dynamics modeling is an effective means to formulate and assess passenger flow organization schemes and control measures. The simulation results can provide a reference for metro station operational departments to take scientific epidemic prevention measures.

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备注/Memo

备注/Memo:
Received:2020-07-26;Accepted:2020-10-18
Foundation:National Key Research and Development Project of China (2018YFB2100901); National Natural Science Foundation of China (52090084, L1924061)
Corresponding author:Professor CHEN Xiangsheng.E-mail: xschen@szu.edu.cn
Citation:HU Mingwei, LI Weiwei, CHEN Xiangsheng.Simulation analysis of epidemic prevention and regulation for metro passenger flow based on system dynamics[J]. Journal of Shenzhen University Science and Engineering, 2021, 38(2): 111-120.(in Chinese)
基金项目:国家重点研发计划资助项目(2018YFB2100901);国家自然科学基金资助项目(52090084,L1924061)
作者简介:胡明伟(1972—),深圳大学教授、博士生导师.研究方向:交通仿真及智能交通等.
E-mail:humw@szu.edu.cn
引文:胡明伟,李微微,陈湘生.基于系统动力学的地铁客流防疫调控仿真分析[J]. 深圳大学学报理工版,2021,38(2):111-120.
更新日期/Last Update: 2021-03-30