Evaluating the Impact of COVID-19 on Transportation Infrastructure Funding

TL;DR

This study assesses how COVID-19 reduced fuel consumption and consequently impacted transportation infrastructure funding in the US, using machine learning models to project future revenue declines.

Contribution

It introduces machine learning models that integrate COVID-19 scenarios, fuel consumption, and demographic data to evaluate and project transportation funding impacts.

Findings

Fuel consumption dropped significantly during the pandemic.

Some states may experience 10-15% lower gas tax revenues for 1-2 years.

The models achieved over 95% R2-score in capturing fuel consumption fluctuations.

Abstract

The coronavirus disease 2019 (COVID-19) pandemic has caused a reduction in business and routine activity and resulted in less motor fuel consumption. Thus, the gas tax revenue is reduced which is the major funding resource supporting the rehabilitation and maintenance of transportation infrastructure systems. The focus of this study is to evaluate the impact of the COVID-19 pandemic on transportation infrastructure funds in the United States through analyzing the motor fuel consumption data. Machine learning models were developed by integrating COVID-19 scenarios, fuel consumptions, and demographic data. The best model achieves an R2-score of more than 95% and captures the fluctuations of fuel consumption during the pandemic. Using the developed model, we project future motor gas consumption for each state. For some states, the gas tax revenues are going to be 10%-15% lower than the pre-pandemic level for at least one or two years.