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Reducing impaired driving through the identification of Repeat Target Vehicles: A case study
1Saint John Police Force, 15 Market Square, Saint John, NB, Canada. james.stewart@saintjohn.ca
Journal of Safety Research
|March 6, 2012
Summary
Repeat impaired drivers are a persistent problem, often unaffected by traditional deterrents. This study introduces a new method to identify repeat target vehicles (RTVs) using vehicle data and driver characteristics for targeted interventions.
Area of Science:
- Criminology
- Traffic Safety
- Data Science
Background:
- Repeat impaired drivers constitute a significant challenge, disproportionately contributing to impaired driving incidents.
- Traditional interventions like social pressure and legal consequences are often ineffective against this group.
- Novel strategies are essential to identify and manage repeat impaired drivers.
Purpose of the Study:
- To develop a predictive method for identifying repeat impaired drivers.
- To leverage vehicle data and driver characteristics for enhanced law enforcement strategies.
Main Methods:
- Analysis of impaired driving calls for service data.
- Identification of repeat vehicles, calculating average time to repeat incidents.
- Incorporation of repeat impaired driver personality characteristics.
Main Results:
- Discovery that approximately 10% of impaired driving calls involve repeat vehicles.
- Development of a comprehensive and predictive description of Repeat Target Vehicles (RTVs).
Conclusions:
- The proposed method enables the creation of targeted crime reduction strategies.
- This approach offers innovative solutions for addressing repeat impaired driving.
- New avenues for intervention and prevention are opened by this predictive model.
