TY  - JOUR
PY  - 2021//
TI  - Measuring travel behavior in Houston, Texas with mobility data during the 2020 COVID-19 outbreak
JO  - Transportation letters
A1  - Jiao, Junfeng
A1  - Bhat, Mira
A1  - Azimian, Amin
SP  - 461
EP  - 472
VL  - 13
IS  - 5-6
N2  - 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.<p />  <p>Language: en</p>
LA  - en
SN  - 1942-7867
UR  - http://dx.doi.org/10.1080/19427867.2021.1901838
ID  - ref1
ER  -