Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.
Called the Pandemic Oil Demand Analysis, or PODA, this model compared mobility patterns before and during the COVID-19 pandemic, analyzing historical weekly motor travel trends and projecting future usage.
“We developed this machine learning-based model by studying trip activities and corresponding fuel usage,” ORNL’s Shiqi (Shawn) Ou said. “The PODA analysis can serve as a useful tool to understand the impact of travel quarantine on fuel demand.”
In a Nature Energy study sponsored by Aramco Research Center, researchers focusing on mid-May until August determined that average fuel demand is not likely to reach pre-pandemic levels before October 2020. However, while a continued quarantine would have a negative impact on fuel demand temporarily, demand would likely recover to normal levels quicker.
PODA data could help inform economic and energy planning.
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