Exploring the association between travel demand changes and the built environment during the COVID-19 pandemic

Abstract

AbstractThis study compared the extent to which COVID-19 impacted travel demand of bike-sharing and taxi in New York City, and further explored how the changes in travel demand were associated with the built environment through four typical regression models, namely, least squares (OLS) regression, geographically weighted regression (GWR), temporally weighted regression (TWR), and geographically and temporally weighted regression (GTWR) models. In particular, this study looked at two phases: the lockdown phase (during which travel demand decreased dramatically) and initial recovery phase (during which travel demand started to increase). The results suggested that 1) GTWR performed better than the other three model types; 2) shared bike ridership rebounded much more significantly during the recovery phase than taxi ridership; 3) Commercial Point of Interest (POI) was positively associated with the change of ridership in both lockdown and recovery phases.