Yang Chao, Wan Zhiyang, Yuan Quan, Zhou Yang, Sun Maopeng
Urban Mobility Institute, the Key Laboratory of Road and Traffic Engineering, Ministry of Education at Tongji University, College of Transportation Engineering, Tongji University, 4800 Caoan Road, Shanghai 201804, PR China.
College of Transportation Engineering, Chang'an University, Xi'an 710064, China.
J Transp Geogr. 2023 Jun;110:103640. doi: 10.1016/j.jtrangeo.2023.103640. Epub 2023 Jun 23.
The COVID-19 pandemic has a significant impact on daily life, leading to quarantines and essential travel restrictions worldwide in an effort to curb the virus's spread. Despite the potential importance of essential travel, research on changes in travel patterns during the pandemic has been limited, and the concept of essential travel has not been fully explored. This paper aims to address this gap by using GPS data from taxis in Xi'an City between January and April 2020 to investigate differences in travel patterns across three periods pre, during, and post the pandemic. Spatial statistical models are used to examine the major supply and demand-oriented factors that affect spatial travel patterns in different periods, and essential and nonessential socioeconomic resources are defined based on types of services. Results indicate that the spatial distribution of travel demand was highly correlated with the location of socioeconomic resources and opportunities, regardless of the period. During the "Emergency Response" period, essential travel was found to be highly associated with facilities and businesses providing essential resources and opportunities, such as essential food provider, general hospital and daily grocery supplies. The findings suggest that local authorities may better identify essential travel destinations by referencing the empirical results, strengthening public transit connections to these locations, and ultimately promoting traffic fairness in the post-pandemic era.
新冠疫情对日常生活产生了重大影响,导致全球范围内实施隔离措施并限制必要出行,以遏制病毒传播。尽管必要出行可能具有重要意义,但关于疫情期间出行模式变化的研究有限,且必要出行的概念尚未得到充分探讨。本文旨在填补这一空白,利用2020年1月至4月西安市出租车的GPS数据,调查疫情前、疫情期间和疫情后三个时期出行模式的差异。采用空间统计模型来研究影响不同时期空间出行模式的主要供需导向因素,并根据服务类型定义必要和非必要的社会经济资源。结果表明,无论在哪个时期,出行需求的空间分布都与社会经济资源和机会的位置高度相关。在“应急响应”期间,发现必要出行与提供必要资源和机会的设施及企业高度相关,如主要食品供应商、综合医院和日常杂货店。研究结果表明,地方当局可以通过参考实证结果更好地确定必要出行目的地,加强公共交通与这些地点的连接,并最终在疫情后时代促进交通公平。