Policies, population and impacts in metro ridership response to COVID-19 in Changsha

IF 2.4 3区 工程技术 Q3 TRANSPORTATION
Wang Xiang, Li Chen, Bin Wang, Qingwan Xue, Wei Hao, Xuemei Liu
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引用次数: 4

Abstract

Abstract To secure the city against the transmission of COVID-19, metro ridership control is an important task of the metro corporation on the premise of meeting the basic travel demand as far as possible. First off, this paper describes the influence mechanism of COVID-19 on metro ridership in Changsha, including an analysis into the correlation among policies, population, and metro ridership. Secondly, this paper verifies the influence of governmental macro-policy on population mobility and metro train working diagram, and thereby on metro ridership, based on the actual data during Jan 12th to May 6th, 2020 and year-ago data (2019). And then the Difference-in-Difference (DID) model is used to verify the effect of policies on metro ridership in Changsha. Results also show the effectiveness of policy chain on the limit of metro ridership, which bears a strong correlation to the number of confirmed COVID-19 cases. A linear regression prediction model is built to predict metro ridership based on cumulative net inflow of population index, metro carrying capacity and confirmed COVID-19 cases. This paper is expected to provide reference for Metro Corporation to control ridership on the premise of meeting the basic travel demand amid the explosive outbreak of the epidemics.
长沙应对COVID-19地铁客流量的政策、人口和影响
在尽可能满足基本出行需求的前提下,控制地铁客流量是保障城市免受新冠肺炎疫情传播的重要任务。首先,本文阐述了新冠肺炎疫情对长沙市地铁客流量的影响机制,分析了政策、人口、地铁客流量三者之间的相关性。其次,本文根据2020年1月12日至5月6日的实际数据和一年前(2019年)的数据,验证政府宏观政策对人口流动和地铁列车运行图的影响,从而对地铁客流量的影响。然后运用差分差分(DID)模型验证了政策对长沙市地铁客流量的影响。结果还显示了政策链对地铁客流量限制的有效性,这与新冠肺炎确诊病例数有很强的相关性。基于人口累计净流入指数、地铁运载能力和新冠肺炎确诊病例,建立线性回归预测模型预测地铁客流量。希望本文能为在疫情爆发的情况下,地铁公司在满足基本出行需求的前提下控制客流量提供参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.00
自引率
15.40%
发文量
38
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