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The present study investigates the adoption of predictive methods for road safety in the Italian context. The main goal of predictive methods is to describe safety performances of a road infrastructure according to the real number of occurred crashes and the actual infrastructure characteristics. Currently, the most reliable and widely used model is reported in the Highway Safety Manual (HSM), initially developed for the United States. In order to adapt the HSM existing model to the Italian context a calibration procedure is required. The main purpose of this study is to conduct the sensitivity analysis of the calibration factor, to evaluate the influence of various road characteristics (expressed in terms of Crash Modification Factors – CMFs) on the reliability of the model. Results show that the most influential factors are represented by planimetric curve radius, followed by shoulder type and width and Roadside Hazard Rating (RHR). In addition, the Italian roads taken into account for the present case study, which are single carriageway rural roads located in Emilia Romagna region, have generally exhibited more critical conditions compared to American roads. As a consequence, CMFs expressing the aforementioned infrastructure characteristics are typically greater than 1. Furthermore, road features and driving habits vary significantly with the orographic context (mountain, hill, or valley) and geographical area, factors that cannot be neglected when calibrating predictive models. As a result, a layered calibration would bring to the most reliable solution and, in specific situations, alternative predictive models to HSM could be developed. |
