Feasibility of Collecting Traffic Safety Data from Law Enforcement Agencies
C H Wiliszowski, James C. Fell, Dereece Smither, M E Vegega, Amy Auld‐Owens, E Namuswe, Bedford Research, Pacific Institute For Research and Evaluation
Abstract
C H Wiliszowski, James C. Fell, Dereece Smither, M E Vegega, Amy Auld‐Owens, E Namuswe, Bedford Research, Pacific Institute For Research and Evaluation
Abstract
The resources expended and the specific activities used by law enforcement agencies (LEAs) to enforce traffic safety laws are generally unknown, at least in the aggregate. It would be beneficial to law enforcement and traffic safety experts to follow increases and decreases in traffic law enforcement over the years in order to understand better the activity levels necessary to reach traffic safety goals. It is important to understand the relationships of these measures with the frequency, rate, and severity of traffic crashes within a community, a State, and the Nation. Currently, no data collection systems capture nationally representative information of traffic safety law enforcement activities and resources. The focus of this project was to learn from law enforcement representatives what information is currently collected; document the resources, strategies, frequency, and intensity of activities dedicated to traffic-safety-related enforcement; and learn how LEAs use these resources. It was concluded that collecting traffic safety enforcement data from LEAs for a new data system is feasible, but initially it will be a difficult and complex task. According to LEA representatives from around the United States who participated in this project, it is feasible to collect at least minimum monthly data on traffic law enforcement activities at the police agency level (e.g., staffing, equipment, strategies employed, traffic stops/contacts with drivers, violations issued, calls for service, and crashes reported). Various methods for sampling LEAs are described. Recommendations include clearly defining the data elements to be collected, conducting a pilot study, and collecting appropriate information to make accurate cost estimates of developing and running such a system.
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The resources expended and the specific activities used by law enforcement agencies (LEAs) to enforce traffic safety laws are generally unknown, at least in the aggregate. It would be beneficial to law enforcement and traffic safety experts to follow increases and decreases in traffic law enforcement over the years in order to understand better the activity levels necessary to reach traffic safety goals. It is important to understand the relationships of these measures with the frequency, rate, and severity of traffic crashes within a community, a State, and the Nation. Currently, no data collection systems capture nationally representative information of traffic safety law enforcement activities and resources. The focus of this project was to learn from law enforcement representatives what information is currently collected; document the resources, strategies, frequency, and intensity of activities dedicated to traffic-safety-related enforcement; and learn how LEAs use these resources. It was concluded that collecting traffic safety enforcement data from LEAs for a new data system is feasible, but initially it will be a difficult and complex task. According to LEA representatives from around the United States who participated in this project, it is feasible to collect at least minimum monthly data on traffic law enforcement activities at the police agency level (e.g., staffing, equipment, strategies employed, traffic stops/contacts with drivers, violations issued, calls for service, and crashes reported). Various methods for sampling LEAs are described. Recommendations include clearly defining the data elements to be collected, conducting a pilot study, and collecting appropriate information to make accurate cost estimates of developing and running such a system.
Key concepts: Law enforcement, Staffing, Enforcement, Business, Agency (philosophy), Transport engineering, Computer security, Data collection