Institute for Transportation

About the research

High-visibility enforcement (HVE) promotes voluntary compliance with traffic safety laws through a combined approach using enforcement strategies (e.g., enhanced patrols), visibility elements (e.g., specially marked squad cars, electronic message boards), and public outreach. While HVE campaigns, which may target one or multiple traffic safety issues, have proven to be effective in general, it can be difficult to determine the impact of a campaign on a particular behavior. As a result, additional information is needed to assist agencies in evaluating the effectiveness of HVE campaigns. This includes methods that agencies can use despite resource and technical expertise constraints.

The goal of this project was to develop evaluation frameworks and methodologies to assist agencies in evaluating the effectiveness of HVE campaigns. The focus was to determine methods that can be used for combined HVE campaigns, but the tools developed can be used for single-theme HVE campaigns as well.

As part of the project, four frameworks were developed for two distinct audiences. Two frameworks were developed for law enforcement, or other interested agencies, that may have little background in statistics and few additional resources. This includes frameworks for data visualization and simple before-and-after statistics. Two frameworks were developed for use by agencies that have the necessary in-house skills—or the resources to use outside consultants—to develop more robust analyses capable of identifying the factors that contribute to campaign effectiveness. This included one framework outlining classical statistical methods and another that described the use of spatial/temporal models.

About the research

This project discusses the development of and presents five conceptual Safety Frameworks for evaluating the relationships between roadway or roadside features and crashes involving infrastructure-related distraction (IRD). Studies assessing the safety impact of outside-the-vehicle distraction and specific infrastructure elements were reviewed to identify common measures of and surrogates for distraction. Potentially useful data sources for investigating IRD were then identified and evaluated for their advantages and disadvantages, and the five Safety Frameworks were developed for the identified data sources. Each framework demonstrates the use of a particular data source—crash narratives, geospatial crash data, traffic simulator data, or naturalistic driving study data—to quantify the distraction potential of an infrastructure element. To this end, each framework identifies research questions that can be addressed using the data source, the variables and surrogates for indicating distraction, the analytical methods for quantifying distraction, and the efficacy of the approach, including the feasibility of the data source and methods. The Safety Frameworks are intended as templates to guide agencies in using a particular data source to assess the distraction potential of a specific infrastructure element.