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Towards Enhancing Road Safety in South Carolina Using Insights from Traffic and Driver-Education Data (Student Abstract)
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Analyzes South Carolina DOT traffic collision data and Alive@25 driver-education participation data via geospatial, economic, and temporal analysis plus interactive dashboards to generate road-safety recommendations.
Problem
Understanding collision patterns in South Carolina and assessing coverage gaps of a school-level student driver-education program (Alive@25) to inform road-safety interventions.
Approach
Combines geospatial, economic-impact, and temporal trend analysis of cleaned traffic and driver-education data with interactive visualizations, using AI techniques for data cleaning, to produce stakeholder-facing infrastructure and education recommendations.
Key results
- Higher collision rates observed in urban counties such as Greenville, Charleston, and Richland from 2017 to 2022.
- Mostly rural counties had higher average costs per incident despite lower overall collision numbers.
- Alive@25 participation declined in mostly rural counties while collision rates there increased.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Higher collision rates in urban counties (Greenville, Charleston, Richland) versus other counties | SC county-level collision data · SC traffic collisions 2017-2022 | collision rate | No clear effect |
| Mostly rural counties show higher average cost per incident despite lower collision counts | SC county-level collision data · SC traffic collisions 2017-2022 | average cost per incident | Mixed |
Surprising findings
- Mostly rural counties had higher average cost per incident despite lower overall collision counts.
- Collision rates rising in mostly rural areas where Alive@25 participation is declining.
Limitations
- Substantial data quality issues, with about 26.8% of 2021 traffic data and 18.3% of Alive@25 data missing.
- Recommendations are not prioritized with advanced statistical or simulation methods.
- Long-term effect of Alive@25 on driving behavior and crash rates is not evaluated.
Experimental setup
Datasets: South Carolina DOT traffic collision data (2017-2022) Alive@25 driver-education participation data US Census 2015 county data National Safety Council injury cost data
Metrics: collision rate average cost per incident participation trend
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