Road safety management using Bayesian and cluster analysis

The paper reports the results of an application of the Bayesian approach-based cluster analysis applied to a problem of road safety. 1000 accidents were recorded (from 1 January 2003 to December 31, 2006) on a stretch of about 100 km. The incidents belonging to the years 2003-2004-2005 were used to construct the Bayesian model (EB) and accidents belonging to the year 2006, were used to check for the reliability of the EB model. The Bayesian model was constructed with the help of cluster analysis. In particular, Cluster Analysis was used to identify the entity on which the Empirical Bayesian was subsequently applied. From the model, obtained by combining the two techniques, the accident waiting in the different entities for the year 2006 was estimated. The reliability of this model was very good. In fact, by comparing accident rates estimated by the EB model(for the year 2006) with the observed accident, a very low error was found. With the help of this procedure (EB technique combined with Cluster Analysis) it was also possible to identify the more dangerous "Black Spot"; so as to have the necessary support to plan infrastructure projects designed to reduce danger.