Accident Prediction Models for Road Networks

Abstract

This paper illustrates road safety statistical models to predict injury accidents. Since 2003 the Department of Transportation Engineering at the University of Naples has been conducting a large – scale research program based on the accident data collection in Southern Italy. The Italian analyzed roadways in the Salerno Province are composed of multilane roadways for 242 kilometers and Major and Minor two-lane rural roads for 3,101 kilometers. Two accident prediction models were calibrated: one is associated with two-lane rural roads and the other with multilane roadways. Explanatory variables were used including traffic flow, lane width, vertical slope, curvature change rate, roadway segments length. Several procedures exist in the scientific literature to predict the number of accidents per kilometer per year, and a lot of relationships between accidents and explanatory variables exist basing on the multiple-variable non linear regression analyses. The accident data, presented in this manuscript, were analyzed using this procedure based on least squares method. The predicted values obtained by calibration procedure were then compared to several models presented in the scientific literature to analyze the residuals by using the t-test.