Increasing traffic flows on road infrastructures and the associated comfort and safety problems have led
to an increased risk of accidents for road users. To take the proper corrective actions, it is fundamental to
analyze the accident phenomenon in all its aspects. The purpose of the current paper was the development
of an accident prediction model for rural road segments of Friuli-Venezia Giulia (FVG) Region. The model
predicts the accident frequency as a function of Annual Average Daily Traffic (AADT), segment length,
and both geometrical and environmental features related to the targeted road segment. The procedure is
based on the Empirical Bayes (EB) method. The statistical model used to express the road segments’ safety
was the multivariate regression structure of the Safety Performance Functions. Results of a CURE plots
analysis verified that the model is highly reliable in predicting the accident dataset for AADT up to 12500
vehicles per day.
