Presentation Information
[D2-03]Evaluating Industry-Specific Changes in freight vehicle travel with COVID-19: A Comprehensive Study Utilizing ETC2.0 data and POI Data
*Guocheng TANG1, Yoshiki Ogawa1, Chenbo Zhao1, Yoshihide Sekimoto1 (1. CSIS, Tokyo Univ.)
Keywords:
probe vehicle data,spatial pattern changes,point of interest data,Geographical Weighted Regression,industry sectors.
This study aims to analyze the mobility impacts of various industry sectors and the origin-destination (OD) distances of freight vehicles at a national scale in Japan by utilizing ETC2.0 data and point of interest (POI) data. The research focuses on changes in the number and distance of OD data for freight vehicles daily over the years 2021 and 2022 to identify industries experiencing significant traffic flow variations. First, a PostgreSQL database is used to organize the ETC2.0 data and extract the OD data. The spatial pattern changes of vehicle stay points are then analyzed using hotspot analysis. Then, Geographical Weighted Regression (GWR) is applied to examine the relationship between changes in probe vehicle data and the POI data from the Telepoint Pack DB of August 2021 for each sector. This approach aims to elucidate the relationship between the variations in vehicle OD data and different industries. The findings are expected to provide insights into how the levels and distribution of freight vehicles across various industries have changed due to the pandemic, ultimately informing future policy recommendations on urban transport and commerce.