Change in Travel Demand under the COVID-19 Pandemic using Route-Search History Data

Abstract

Route-search history data accumulated in a public transportation route-search system provide potential travel demands for public transportation. This study uses route-search history data to understand the changes in travel demand for public transportation before and after the COVID-19 pandemic. Specifically, we employ a piecewise linear approximation model for changes in the number of bus route searches performed using a route search system in Tottori Prefecture, Japan. By clarifying the date and time of changes in the number of route searches and trends, we identify the characteristics of the changes in the route search numbers. According to the analytical results, the potential travel demands shown by the route-search history data confirmed the bus routes that recovered from the impact of the COVID-19 pandemic and those that did not. Furthermore, the data confirmed the routes for which the travel demands changed, unrelated to the COVID-19 pandemic.