Identifying High-Crash-Risk Intersections

Abstract

Identifying high-crash-risk locations, called hot spots, is an important step in improving roadway safety. Use of the empirical Bayes (EB) method coupled with the use of safety performance functions (SPFs) is considered the state of the practice in identifying such locations. However, application of the EB-SPF method requires considerable resources in preparing data, as well as statistical expertise. As a consequence, many highway agencies still rely on traditional methods that use crash frequency and crash rate to identify locations for potential safety improvements without knowing the accuracy of such methods. This study examined four traditional methods commonly used in identifying potential locations for safety improvements and compared them with the EB-SPF method. The four methods evaluated were crash frequency, crash rate, rate–quality control, and equivalent property damage only. The study was limited to four-leg intersections with either a traffic signal or two-way stop control; 2004 to 2008 data were collected for 1,670 such intersections. The study found that the crash frequency method performed the best of the four in correctly identifying the top 1% of unsafe intersections. However, the method tended to flag top hot spots incorrectly. The rate–quality control method performed the best in identifying the top 5% and 10% of unsafe intersections. The findings are expected to help highway agencies that continue to use the traditional methods choose the most appropriate method so that scarce resources available for safety improvement can be invested effectively.