[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]
点击复制

基于系统动力学的地铁客流防疫调控仿真分析()
分享到：

《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.

参考文献/References:

［1］ 广东省人民政府新闻办公室. 广东省政府新闻办疫情防控第五十场新闻发布会［EB/OL］.(2020-04-02)［2020-05-02］. http://gdio.southcn.com/g/2020-04/02/content_190688522.htm.
Information Office of The People’s Government of Guangdong Province.The 50th press conference of the Information Office of the People’s Government of Guangdong Province［EB/OL］.(2020-04-02)［2020-05-02］. http://gdio.southcn.com/g/2020-04/02/content_190688522.htm.(in Chinese)
［2］ 胡明伟, 黄文柯. 行人交通仿真方法与技术［M］. 北京：清华大学出版社, 2017.
HU Mingwei, HUANG Wenke. Methods and techniques of pedestrian traffic simulation［M］. Beijing: Tsinghua University Press, 2017.(in Chinese)
［3］ HU Mingwei. A high-fidelity 3D simulation method for evaluating passenger flow organization and facility layout at metro stations［J］. Simulation: Transactions of the Society for Modeling and Simulation International, 2017, 93(10): 841-851.
［4］ JI Xiangfeng, ZHANG Jian, HU Yongkai, et al. Pedestrian movement analysis in transfer station corridor: velocity-based and acceleration-based［J］. Physica A: Statistical Mechanics and its Applications, 2016, 450: 416-434.
［5］ JI Xiangfeng, ZHOU Xuemei, RAN Bin. A cell-based study on pedestrian acceleration and overtaking in a transfer station corridor［J］. North-Holland, 2013, 392(8): 1828-1839.
［6］ TRIVEDI A, PANDEY M. Agent based modelling and simulation to estimate movement time of pilgrims from one place to another at Allahabad Jn. Railway Station during Kumbh Mela-2019［J］. Autonomous Agents and Multi-Agent Systems, 2020, 34(1): 1-37.
［7］ 陈春安, 荣建, 李伴儒, 等. 基于系统动力学的枢纽换乘系统运能匹配研究［J］. 城市交通, 2017, 15(2): 48-55, 66.
CHEN Chun’an, RONG Jian, LI Banru, et al. Capacity matching of transfer system within public transit terminals based on system dynamics［J］. Urban Transport of China, 2017, 15(2): 48-55, 66.(in Chinese)
［8］ 吴开信, 陈鉴声, 刘蔼珺. 基于系统动力学的地铁车站客流演变规律研究［J］. 科技风, 2019(18): 204-206.
WU Kaixin, CHEN Jiansheng, LIU Aijun. Research on the evolution rules of passenger flow in subway station based on system dynamics［J］. Technology Wind, 2019(18): 204-206.(in Chinese)
［9］ 郑雪梅, 蒋熙. 基于系统动力学的地铁客村站客流控制研究［J］. 铁道科学与工程学报, 2016, 13(11): 2284-2289.
ZHENG Xuemei, JIANG Xi. The study of passenger flow control at kecun station of urban rail transit based on system dynamics［J］. Journal of Railway Science and Engineering, 2016, 13(11): 2284-2289.(in Chinese)
［10］ 石俊刚, 杨静, 杨立兴. 以安全为导向的地铁高峰时段多车站客流协同控制模型［J］. 交通运输系统工程与信息, 2019, 19(1): 125-131.
SHI Jungang, YANG Jing, YANG Lixing. Safety-oriented cooperative passenger flow control model in peak hours for a metro line［J］. Journal of Transportation Systems Engineering and Information Technology, 2019, 19(1): 125-131.(in Chinese)
［11］ 曾璐. 突发事件下城市轨道交通客流控制方法研究［D］. 北京：北京交通大学, 2018.
ZENG Lu. Research on passenger flow control method for urban mass transit under emergency［D］.Beijing: Beijing Jiaotong University, 2018.(in Chinese)
［12］ 马骁. 基于系统动力学的城市轨道交通车站客流仿真与控制研究［D］. 北京：北京交通大学, 2019.
MA Xiao. Research on passenger flow simulation and control of urban rail transit station based on system dynamics［D］. Beijing: Beijing Jiaotong University, 2019.(in Chinese)
［13］ 中国疾病预防控制局. 中国-世界卫生组织新型冠状病毒肺炎（COVID-19）联合考察报告［EB/OL］.(2020-02-29)［2020-02-29］. http://www.nhc.gov.cn/jkj/s3578/202002/87fd92510d094e4b9bad597608f5cc2c.shtml.
Chinese Bureau for Disease Control and Prevention. China-World Health Organization novel coronavirus pneumonia (COVID-19) joint survey report ［EB/OL］.(2020-02-29)［2020-02-29］. http://www.nhc.gov.cn/jkj/s3578/202002/87fd92510d094e4b9bad597608f5cc2c.shtml.(in Chinese)
［14］ 钱华, 章重洋, 郑晓红. 呼吸道传染病气溶胶传染致病机理及预测方法［J］. 科学通报, 2018, 63(10): 931-939.
QIAN Hua, ZHANG Chongyang, ZHENG Xiaohong. The function of aerosols in transmitting and infecting of respiratory infectious diseases and its risk prediction［J］. Chinese Science Bulletin, 2018, 63(10): 931-939.(in Chinese)
［15］ 钱华, 郑晓红, 张学军. 呼吸道传染病空气传播的感染概率的预测模型［J］. 东南大学学报自然科学版, 2012, 42(3): 468-472.
QIAN Hua, ZHENG Xiaohong, ZHANG Xuejun. Prediction of risk of airborne transmitted diseases［J］. Journal of Southeast University Natural Science Edition, 2012, 42(3): 468-472.(in Chinese)
［16］ 张毅, 王雪成, 毕清华. 基于新型冠状病毒传播机理的交通出行易感度研究［J］. 交通运输研究, 2020, 6(1): 73-80.
ZHANG Yi, WANG Xuecheng, BI Qinghua. Travel-infected susceptibility based on transmission mechanism of COVID-19［J］. Transport Research, 2020, 6(1): 73-80.(in Chinese)
［17］ WELLS W F. Airborne contagion and air hygiene: an ecological study of droplet infections［M］. Cambridge, USA: Harvard University Press, 1955.
［18］ RILEY E, MURPHY G, RILEY R. Airborne spread of measles in a suburban elementary school［J］. American Journal of Epidemiology, 1978, 107(5): 421-432.
［19］ FENNELLY K P, NARDELL E A. The relative efficacy of respirators and room ventilation in preventing occupational tuberculosis［J］. Infection Control Hospital Epidemiology, 1998, 19(10): 754-759.
［20］ GB 50157—2013地铁设计规范［S］. 2013.
GB 50157—2013 Code for design of metro［S］.(in Chinese)
［21］ 刘兆. 地铁屏蔽门系统岛式站台新风量控制指标研究［D］. 北京：华北电力大学, 2019.
LIU Zhao. Research on new air volume control index of island platform in subway screen door system［D］.Beijing: North China Electric Power University, 2019.(in Chinese)
［22］ 杨鑫泽. 广州地区地铁车站隧道活塞风的应用研究［D］. 广州：广州大学, 2019.
YANG Xinze. Application of piston wind in tunnel of guangzhou metro station［D］. Guangzhou: Guangzhou University, 2019.(in Chinese)
［23］ 杨静, 代盛旭, 周浪雅, 等. 城市轨道交通相邻多车站动态协同限流研究［J］. 铁道运输与经济, 2020, 42(3): 112-118.
YANG Jing, DAI Shengxu, ZHOU Langya. A study on passenger flow control with multi-station dynamic coordination in urban transit system［J］. Railway Transport and Economy, 2020, 42(3): 112-118.(in Chinese)
［24］ 董瀚萱. 城市轨道交通车站承载能力计算及客流控制分析［D］. 西安：长安大学, 2018.
DONG Hanxuan. Calculation of urban rail transit station carrying capacity and analysis of passenger flow control［D］. Xi’an: Chang’an University, 2018.(in Chinese)
［25］ GB 50736—2012民用建筑供暖通风与空气调节设计规范 (附条文说明)［S］.
GB 50736—2012 Design specification for heating ventilation and air conditioning in civil buildings［S］.(in Chinese)
［26］ GAO Xiaolei, WEI Jianjian, COWLING B J, et al. Potential impact of a ventilation intervention for influenza in the context of a dense indoor contact network in Hong Kong［J］. Science of the Total Environment, 2016, 569: 373-381.

相似文献/References:

[1]李伟,罗钦.基于逐步优化的轨道交通网络行车计划衔接[J].深圳大学学报理工版,2018,35(6):629.[doi:10.3724/SP.J.1249.2018.06629]
　LI Wei and LUO Qin.Rail transit network planning based on gradual optimization[J].Journal of Shenzhen University Science and Engineering,2018,35(2):629.[doi:10.3724/SP.J.1249.2018.06629]
[2]于泉,刘洋,郭骁伟.基于路口相关性的交通流量修复研究[J].深圳大学学报理工版,2019,36(3):304.[doi:10.3724/SP.J.1249.2019.03304]
　YU Quan,LIU Yang,and GUO Xiaowei.Restoration of traffic flow data based on intersection correlation[J].Journal of Shenzhen University Science and Engineering,2019,36(2):304.[doi:10.3724/SP.J.1249.2019.03304]
[3]李德昌,张明霞,林大川,等.新型冠状病毒ELISA试剂盒灵敏度和特异度评价[J].深圳大学学报理工版,2020,37(3):224.[doi:10.3724/SP.J.1249.2020.03224]
　LI Dechang,ZHANG Mingxia,et al.Evaluation of the sensitivity and specificity of ELISA kits for the SARS-CoV-2 diagnosis[J].Journal of Shenzhen University Science and Engineering,2020,37(2):224.[doi:10.3724/SP.J.1249.2020.03224]
[4]贺云鹏,李建国.平面移动式立体车库客流状态聚类研究[J].深圳大学学报理工版,2020,37(3):314.[doi:10.3724/SP.J.1249.2020.03314]
　HE Yunpeng and LI Jianguo.Passenger flow state clustering in flat mobile automated garage[J].Journal of Shenzhen University Science and Engineering,2020,37(2):314.[doi:10.3724/SP.J.1249.2020.03314]
[5]周菁楠,李伟,罗钦.城轨车站大客流条件下列车运行调整[J].深圳大学学报理工版,2020,37(6):617.[doi:10.3724/SP.J.1249.2020.06617]
　ZHOU Jingnan,LI Wei,and LUO Qin.Adjustment for train operation under the condition of mass passenger flow in urban rail transit[J].Journal of Shenzhen University Science and Engineering,2020,37(2):617.[doi:10.3724/SP.J.1249.2020.06617]
[6]李军,郑培庆.城市公交过剩通勤分析与评价——以广州市为例[J].深圳大学学报理工版,2020,37(6):623.[doi:10.3724/SP.J.1249.2020.06623]
　LI Jun and ZHENG Peiqing.Analyzing and evaluating of the urban transit excess commuting: a case study of Guangzhou City[J].Journal of Shenzhen University Science and Engineering,2020,37(2):623.[doi:10.3724/SP.J.1249.2020.06623]
[7]杨波,李建国,康耀军.立体车库顾客到达的非齐次泊松过程模拟仿真[J].深圳大学学报理工版,2021,38(2):121.[doi:10.3724/SP.J.1249.2021.02121]
　YANG Bo,LI Jianguo,and KANG Yaojun.Simulation of non-homogeneous Poisson process of customer arrival in stereo garage[J].Journal of Shenzhen University Science and Engineering,2021,38(2):121.[doi:10.3724/SP.J.1249.2021.02121]
[8]刘鹏,胡明伟,等.深圳市非道路移动机械排放清单研究[J].深圳大学学报理工版,2021,38(4):331.[doi:10.3724/SP.J.1249.2021.04331]
　LIU Peng,HU Mingwei,,et al.Emission inventory of non-road mobile machinery in Shenzhen[J].Journal of Shenzhen University Science and Engineering,2021,38(2):331.[doi:10.3724/SP.J.1249.2021.04331]
[9]胡明伟,等.地铁车站水侵应急疏散仿真研究[J].深圳大学学报理工版,2022,39(2):159.[doi:10.3724/SP.J.1249.2022.02159]
　HU Mingwei,TANG Jingyan,and HE Guoqing.Simulation study on emergency evacuation due to water invasion in subway stations[J].Journal of Shenzhen University Science and Engineering,2022,39(2):159.[doi:10.3724/SP.J.1249.2022.02159]
[10]胡迪,靳文舟.基于站点优化的需求响应公交调度研究[J].深圳大学学报理工版,2022,39(2):209.[doi:10.3724/SP.J.1249.2022.02209]
　HU Di and JIN Wenzhou.Flex-route demand response transit scheduling based on station optimization[J].Journal of Shenzhen University Science and Engineering,2022,39(2):209.[doi:10.3724/SP.J.1249.2022.02209]

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