Vehicle Detection Using YOLO and Mobility Tracking During COVID-19 Pandemic Lockdowns

Authors

Marion Ivan L. Tan, Ateneo de Manila UniversityFollow
Clyde J. Calgo, Ateneo de Manila UniversityFollow
Sheanne Eric P. Cabantac, Ateneo de Manila University
Jaime Luis E. Honrado, Ateneo de Manila UniversityFollow
Nathaniel Joseph C. Libatique, Ateneo de Manila UniversityFollow
Gregory L. Tangonan, Ateneo de Manila UniversityFollow

Document Type

Conference Proceeding

Publication Date

10-2021

Abstract

Data-driven approaches to traffic monitoring have important applications in tracking vehicle mobility in the COVID-19 pandemic lockdowns. We report preliminary results of a pipeline that uses the You Only Look Once (YOLOv3) and the Simple Online and Realtime Tracking (SORT) algorithms to count and classify vehicles in traffic videos. We correlate vehicle counts in Katipunan Avenue, Metro Manila and Google COVID-19 Community Mobility Reports from May to August 2020 and we show that vehicle detection data may be considered for monitoring community response to changes in COVID-19 lockdown stringency levels.

Recommended Citation

Tan, M. I. L., Calgo, C. J., Cabantac, S. E. P., Honrado, J. L. E., Libatique, N. J. C., & Tangonan, G. L. (2021). Vehicle detection using YOLO and mobility tracking during COVID-19 pandemic lockdowns. 2021 IEEE Global Humanitarian Technology Conference (GHTC), 1–7. https://doi.org/10.1109/GHTC53159.2021.9612481