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新冠肺炎交通防控政策对长沙市人口流动的影响
引用本文:闫常鑫,王彬,陈理,向往,王云,闫学东. 新冠肺炎交通防控政策对长沙市人口流动的影响[J]. 交通运输系统工程与信息, 2021, 21(5): 190-197. DOI: 10.16097/j.cnki.1009-6744.2021.05.019
作者姓名:闫常鑫  王彬  陈理  向往  王云  闫学东
作者单位:1. 长沙市规划勘测设计研究院,长沙 410007;2. 长沙理工大学,交通运输工程学院,长沙 410114; 3. 北京交通大学,交通运输学院,北京 100044
基金项目:国家自然科学基金;湖南省自然科学基金
摘    要:为探究新冠肺炎疫情下交通防控政策对长沙市人口流动的影响,本文根据长沙市在新冠肺炎疫情期间颁布的交通防控政策和疫情实时防控情况划分防控阶段,基于百度迁徙大数据,利用双重差分模型,识别长沙市不同阶段的交通防控政策以及量化防控效果,分析交通防控政策对长沙市人口流动的影响。结果显示,长沙市在交通管制阶段,平均人口迁出强度、平均人口迁入强度及城市内部出行强度分别下降了83.68%、69.24%及59.74%,有效地控制了人口流动,降低了疫情扩散危险。在交通恢复阶段,长沙市人口流动强度逐渐反弹,城市内部出行强度基本恢复到2019年同期水平。本文研究结果显示了交通管制对疫情扩散限制的有效性,为常态化疫情防控下精准防控政策和复工复产政策制定提供参考。

关 键 词:城市交通  交通防控政策  双重差分模型  人口流动  百度迁徙大数据  
收稿时间:2021-04-20

Impacts of COVID-19 Traffic Control Policy on Population Flows in Changsha
YAN Chang-xin,WANG Bin,CHEN Li,XIANG Wang,WANG Yun,YAN Xue-dong. Impacts of COVID-19 Traffic Control Policy on Population Flows in Changsha[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(5): 190-197. DOI: 10.16097/j.cnki.1009-6744.2021.05.019
Authors:YAN Chang-xin  WANG Bin  CHEN Li  XIANG Wang  WANG Yun  YAN Xue-dong
Affiliation:1. Changsha Planning & Design Survey Research Institute, Changsha 410007, China; 2. School of Traffic & TransportationEngineering, Changsha University of Science & Technology, Changsha 410114, China; 3. School of Traffic andTransportation, Beijing Jiaotong University, Beijing 100044, China
Abstract:To investigate the impact of COVID-19 traffic control policies on population flow in Changsha, this paperdivided the prevention and traffic control policies into different stages corresponding to the real-time epidemic situationin Changsha. Based on Baidu migration big data, the difference- in- difference model was used to identify differentstages of traffic prevention and control policies and quantify the effect of prevention. With the traffic control policyimplemented during COVID- 19, the average inflow intensity of Changsha City decreased by 83.68% , the averageoutflow intensity decreased by 69.24% and the internal travel intensity respectively, decreased by 59.74%. After theend of the traffic control policies, the population flow intensity of Changsha City gradually rebounded, and the urbaninternal travel intensity basically recovered to the same level as in 2019. The results indicated the effectiveness of thetraffic control policies on the limitation of population flow and epidemic spread. The results also provide reference formaking effective prevention and control policies for the normalized COVID-19 epidemic situations.
Keywords:urban traffic   traffic control policy   difference-in- difference model   population flow   baidu migration bigdata  
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