A Staying Time Analysis in Regional City Centers by COVID-19 using Smart Card Data

Abstract

This study focused on time spent in the city center. We proposed a simple method of determining this using smart card data. We then performed clustering analysis using a Gaussian mixture model to analyze the impact of the outbreak of the COVID-19. The case study was Takamatsu City, Kagawa Prefecture. After the outbreak, long stays decreased and medium-term stays increased on weekdays. It is suggested that the stay pattern is becoming more uniform. In contrast, weekend and holiday, the short-stay and medium-stay groups demonstrated a reversion to their pre-pandemic levels. However, there were indications of a decrease in trips and length of stay for the long-stay group.