Date of Award

Fall 12-15-2023

Level of Access Assigned by Author

Open-Access Thesis

Degree Name

Master of Science in Civil Engineering (MSCE)

Department

Civil Engineering

Advisor

Ali Shirazi

Second Committee Member

Eric Landis

Third Committee Member

Per Garder

Abstract

Following the onset of the COVID-19 pandemic there was an observed decrease in traffic safety in the United Sates. New England was no exception to this, with traffic fatality rates increasing in Maine and Connecticut. This increase was attributed to the possibility that drivers had more opportunities to speed following the implementation of COVID-19 stay-at-home orders on roads with drastically reduced volume and decreased speed enforcement. To determine the state of research into the pandemic's effect on traffic safety around the world, an extensive critical review was conducted. The reviewed studies showed that roadways did indeed become less safe with increased crash rates, increased crash severities, and increased rates of drivers engaging in dangerous behavior such as aggressive driving, drunk driving, distracted driving, and speeding. The review also went further to examine the effects on bicycle and pedestrian safety as well as transit. These represent alternative modes to roadway safety, or in the case of bikes and pedestrians, interact with cars and roadways regularly. Examining how the other modes were affected by the pandemic can be important to finding out where gaps exist in the current level of research. Next, this thesis evaluates how speeding changed during and after the stay-at-home orders in the states of Maine and Connecticut. Emerging probe data were used along with mixed effect logistic regression models to find out how the odds of speeding were affected. The findings revealed that there was a significant increase in the odds of speeding by more than 10, 15, and 20 mph in both Maine and Connecticut, with a more pronounced effect in Connecticut. Operational data were combined with geometric characteristics of the roadway so we could also model how traffic densities, and the geometric characteristics of the roadways affect speeding. It was found that lower traffic densities, such as Level of Service (LOS) of A and B are associated with more speeding than greater traffic densities (LOS D or E). This shows a potential conflict between transportation agencies goals of improving roadway performance and safety as roadways that are less susceptible to jamming could be more susceptible to speeding. Lastly, this thesis evaluates the effect of the COVID-19 pandemic on crash occurrence. Random effect logit models are developed with all crashes (KABCO) and fatal-injury crashes (KABC). Speed data was included in the models in the forms of average hourly speed and the Coefficient of Variation (CV) of speed to capture speed variability. It was found that while average speed was not significant in most cases, the variability of speed was associated with increases in the odds of crashes. Furthermore, the models included dummy variables for 2021 and 2022, the post-pandemic periods. The dummies indicated that there were increases in the odds of crash occurrence post-covid for certain crash types and road types, as well as identifying a shift in crashes on urban roadways from morning onto off-peak and evening peak hours.

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