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FHWA Home / OIPD / Accelerating Innovation / Every Day Counts / EDC-4: Data-Driven Safety Analysis

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Data-Driven Safety Analysis (DDSA)

Using tools to analyze crash and roadway data to predict the safety impacts of highway projects allows agencies to target investments with more confidence and reduce severe crashes on the roadways.

Traditional crash and roadway analysis methods mostly rely on subjective or limited quantitative measures of safety performance. This makes it difficult to calculate safety impacts alongside other criteria when planning projects. Data-driven safety analysis (DDSA) employs newer, evidence-based models that provide state and local agencies with the means to quantify safety impacts similar to the way they do other impacts such as environmental effects, traffic operations and pavement life.

The analyses provide scientifically sound, data-driven approaches to identifying high-risk roadway features and executing the most beneficial projects with limited resources to achieve fewer fatal and serious injury crashes. Through round four of Every Day Counts (EDC-4), this effort focuses on both predictive and systemic analyses—two types of data-driven approaches that state and local agencies can implement individually or in combination.

Predictive analysis helps identify roadway sites with the greatest potential for improvement and quantify the expected safety performance of different project alternatives. Predictive approaches combine crash, roadway inventory, and traffic volume data to provide more reliable estimates of an existing or proposed roadway’s expected safety performance. The results inform roadway safety management and project development decision-making. The data not only help agencies make better decisions, but also inform the public as to what safety benefits they can expect from their investment.

Systemic analysis uses crash and roadway data in combination to identify high-risk roadway features that correlate with particular crash types. Agencies have traditionally relied on crash history data to identify “hot spots,” or sites with high crash frequency. However, severe crashes are widely dispersed over road networks, and their location and frequency fluctuate over time. Systemic analysis identifies locations that are at risk for severe crashes, even if there is not a high crash frequency. Practitioners can then apply low-cost countermeasures to those locations. The benefit is wider, but more targeted, safety investment.

Benefits

  • Informed Decision-Making. Predictive and systemic analyses improve on traditional decision-making approaches that rely on subjective and limited quantitative measures of safety performance.
  • Targeted Investment. Agencies use the analyses to optimize funding by selecting the most appropriate roadway features and project sites.
  • Improved Safety. DDSA offers a scientifically sound, data-driven approach to allocating resources that results in fewer fatal and serious injury crashes on the Nation’s roadways.

State of the Practice

To date, 75 percent of states are applying DDSA in one or more of their project development processes. This effort is a result of collaborative work by AASHTO, FHWA, the Transportation Research Board and industry over the past two decades. DDSA was originally promoted under the third round of EDC (EDC-3), and it continues under the fourth round (EDC-4) with an additional focus on broadening use among local agencies.

Page last modified on November 15, 2016
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