Empirical Bayes Identification of High Hazard Locations for Older Drivers

Abstract

As part of an emphasis on improving road safety, the Minnesota Department of Transportation seeks to identify the locations where older drivers were over-represented in accident records. This research project reports on the use of three methods to help improve the accuracy of identifying locations where older drivers were at increased risk: a basic statistical model, the Empirical Bayes statistical method and a clustering method. Overall, the basic statistical model preformed the best. The clustering method and the Empirical Bayes method could both be usefully applied to the traditional task of high-hazard identification--that of automatically screening a large number of accident sites to identify potential candidates for improvement. This information can point the way to areas that may require a more detailed engineering analysis.