Measuring travel behavior in Houston, Texas with mobility data during the 2020 COVID-19 outbreak

被引：20

作者：

Jiao, Junfeng ^{[1
]}

Bhat, Mira ^{[1
]}

Azimian, Amin ^{[1
]}

机构：

[1] Univ Texas Austin, Urban Informat Lab, Austin, TX 78712 USA

来源：

TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH | 2021年 / 13卷 / 5-6期

关键词：

COVID-19; Economy; mobility; foot traffic; autoregressive models; Houston;

D O I：

10.1080/19427867.2021.1901838

中图分类号：

U [交通运输];

学科分类号：

08 ; 0823 ;

摘要：

COVID-19, a respiratory virus violently spread worldwide, has deeply affected people's daily life and travel behaviors. We adopted an autoregressive distributed lag model to analyze changes in travel patterns in Houston, Texas during COVID-19. The results indicated that visit patterns and changes in COVID-19 cases a week prior heavily influence the following week's behaviors. Additionally, unemployment claims, median minimum dwell time, and workplace visit activity played a major role in predicting total foot traffic. Notably, transit systems have seen an overall decrease in usage but were not significant in estimating total foot traffic. This model showcased a unique method of quantifying and analyzing travel behaviors in Houston in response to COVID-19.

引用

页码：461 / 472

页数：12

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