Development of Arizona-Specific Safety Performance Functions

The Traffic Safety unit within ADOT’s Transportation Systems Management and Operations Division (TSMO) predicts the estimated number and severity of crashes that can be expected per year for selected roadways using traffic crash data with several other factors such as traffic volume, speed, and road geometry. The practice of estimating crash frequency is essential in managing safety improvements and mitigating transportation safety challenges. ADOT currently uses an automated tool, AASHTOWare Safety Analyst, which was developed by the American Association of State Highway and Transportation Officials (AASHTO), to perform predictive analysis. The safety performance functions (SPFs) that predict crash frequencies in Safety Analyst were developed using national data from the early 2000s. Therefore, Safety Analyst is not customized to Arizona roadway characteristics and conditions, which limits the accuracy of the predictive modelling. In addition, AASHTO will sunset this software in 2022, which means that the software will no longer be enhanced or supported. A 2016 ADOT Research Center study, ADOT State-Specific Crash Prediction Models: An Arizona Needs Study, recommended that ADOT develop and maintain a comprehensive dataset of roadway characteristics, crash data, and traffic volume linked through a common linear referencing system before it can proceed to develop state-specific SPFs. Since 2016, ADOT has implemented this recommendation. The Traffic Safety unit is proposing a research study to evaluate the quality and usefulness of the collected data and develop Arizona-specific SPFs for predictive modelling of crashes. The SPFs will reflect different roadway classes and types, including freeway segments, highways, arterials, interchanges, signalized, roundabout and unsignalized intersections, and crossroad ramp terminals. The study’s objectives are to develop SPFs that reflect Arizona roadway characteristics and conditions,and inform ADOT on the current state of its data collection effort to further enhance its future crash prediction capacity.