Changes in inter-city car travel behavior over the course of a year during the COVID-19 pandemic: A decision tree approach

Abstract

This study examined how inter-city car travel behavior changed due to the COVID-19 pandemic over the three pandemic waves in South Korea. We used daily freeway traffic volume data from 2019 and 2020 to represent inter-city car travel behavior and compiled a dataset that includes information on the COVID-19 pandemic, weather conditions, holidays, and socio-economic factors. A conditional inference tree model was employed to classify and understand changes in inter-city car travel during the pandemic. The modeling result demonstrates that inter-city travel-related responses to the pandemic varied over time but had few variations across regions. The main findings can be summarized as follows: i) inter-city car travelers responded more sensitively to the number of national confirmed cases than the number of regional confirmed cases; ii) the threshold of travelers' sensitivity to the number of confirmed cases rose as the pandemic continued; iii) inter-city travel behavior exhibited a more resilient recovery as the pandemic prolonged; and iv) travelers tend to resume their inter-city car travels before social distancing rules were actually eased. The findings in this study provide useful insights to suggest a transportation-related policy strategy for effectively managing possible future pandemics at the national level.