Data-Driven Assessment of Traffic Calming: A Case Study of University Campus Using Vehicle Telematics Data

This study presents a data-driven assessment of the effectiveness of a road diet, a traffic calming infrastructure, on McCormick Road at the University of Virginia using telematics data from the university’s facilities management fleet. With this data, we evaluated the impact of the road diet on driving behavior and overall traffic safety. Telematics data captured a variety of infraction metrics, including speeding, harsh braking, jackrabbit starts, and harsh cornering on thousands of trips before and after the implementation of the road diet. Our findings revealed a $\mathbf{7 5. 5 \%}$ reduction in total infractions, despite a $16.8 \%$ increase in trip volume within the study area. That, along with geospatial analysis of the McCormick Road zone and additional insights drawn from visualizations of hourly infraction patterns, demonstrated the success of the road diet and highlighted the power of vehicle telematics as a tool to monitor and evaluate traffic safety interventions in real-time. In addition, the study contributes to the growing body of evidence supporting data-informed urban planning, suggesting that even modest infrastructure changes, when designed with pedestrian safety in mind, can yield significant safety benefits. Future work is proposed to improve temporal resolution in data collection and develop personalized driver training programs for persistent outliers, further leveraging telematics for long-term traffic safety improvements.