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

Publication Type

Journal Article

Publication Date

5-2021

Abstract

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.

Keywords

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

Discipline

Transportation | Urban Studies

Research Areas

Integrative Research Areas

Publication

Transportation Letters

Volume

13

Issue

5-6

First Page

461

Last Page

472

ISSN

1942-7867

Identifier

10.1080/19427867.2021.1901838

Publisher

Taylor and Francis Group

Additional URL

https://doi.org/10.1080/19427867.2021.1901838

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