Analysis of Changes in Intercity Highway Traffic Travel Patterns under the Impact of COVID-19

Abstract

The unprecedented COVID-19 pandemic impacts negatively on the security and development of human society. Comparison and analysis of intercity highway travel patterns before and during the COVID-19 pandemic can bring vital insights for the prevention and control of the pandemic. Empirical studies are conducted using cellular network-based datasets associated with two groups of city pairs in China heavily affected by COVID-19. Spatial matching, full-sample extrapolation, and trajectory feature analysis are adopted to attain travel volumes of intercity highways during four different periods. The reliability of origin-destination (OD) matrices calculated based on the cellular network-based dataset is demonstrated by comparing with the fluctuation trend of traffic count data. The empirical studies show that the OD flows associated with passenger cars on intercity highways in China decreased significantly during COVID-19. With the effective implementation of the pandemic prevention control policy and the orderly promotion of the recovery to work and production, the volumes of intercity highway OD flows returned to the pre-pandemic level in mid-April 2020. Besides, the peak of passenger car trips decreases and the time span for truck trips gets longer owing to implemented control measures in dealing with COVID-19. The results can be applied to the calculation of OD flows between most adjacent cities and analyze the intercity highway traffic travel patterns changes, which provide insightful implications for making intercity travel safety prevention and control policies under epidemic conditions.