Using Geographically Weighted Models to Explore Temporal and Spatial Varying Impacts on Commute Trip Change Resulting from COVID-19

COVID-19 deeply affected people's daily life and travel behaviors. Comprehending changes in travel behavior holds significant importance, making it imperative to investigate the influential factors of sociodemographics and socioeconomics on such behavior. This study used large-scale mobile device location data at the U.S. county level in the Washington, D.C., Maryland, and Virginia (DMV) area, U.S., to reveal the impacts of demographic and socioeconomic variables on commute trip change. The study investigated the impact of these variables on commuter trips over time and space. It reflected the short- and long-term impact of COVID-19 on travel behavior via linear regression and geographically weighted regression (GWR) models. The findings indicated that counties with a higher percentage of people using walking and biking (active mode) for commuting during the initial phase of COVID-19 experienced a greater reduction in their commute trips compared with others. Conversely, for the long-term effect of COVID-19 in November 2020, we can see the impact of using active mode on trip change is not significant any more and, instead, results showed people who were using bus and rail (public mode) for commuting decreased their trips more than others. Additionally, a positive correlation was observed between median income levels and the reduction in commute trips. On the other hand, sectors that necessitated ongoing outdoor operations during the pandemic, such as manufacturing, wholesale trade, and food services, showed a substantial negative correlation with trip change. Moreover, in the DMV area, counties with a higher proportion of Democrat voters experienced less trip reduction than others. Notably, by applying the GWR and multiscale GWR models, the local spatial relationships of variables and commuting behaviors were captured. The results showed the emergence of local correlations as the pandemic evolved, suggesting a geographical impact pattern. At the onset of COVID-19, the pandemic's impact on commuting behaviors was global. However, as time passed, travel behavior became more influenced by spatial factors and started to show localized effects.