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    Transferability and seasonality in extreme value theory applications to road safety: A case study in an Italian motorway

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    The application of extreme value theory (EVT) to road safety can produce quick and reliable safety evaluations. In view of a future widespread practical application, this paper investigates for the first time the issues of model transferability and seasonality in EVT. A case study dealing with motorway rear-end collision risk is presented. Vehicle-by-vehicle traffic data were collected in 14 motorway sections with similar characteristics for a year, and Time-To-Collision (TTC) was computed for each couple of consecutive vehicles. Two sets of Generalized Pareto distributions were fitted with the Peak-Over-Threshold approach: in Set#l TTC values were aggregated across all sections, for each month; in Set#2 for each section and each month, only TTC collected in all the other sections in the same month were considered. Model performance was evaluated comparing predicted and observed rear-end collisions. According to the findings of this work, it is possible to aggregate data from several road sections, provided that they share similar geometric, traffic and weather characteristics, to estimate EVT models; moreover, such models are transferable with very good results to other similar road sections. In addition to this, results show that it is important to take into account seasonality effect, as predictions made considering data collected for only a short continuous observation period may be largely overestimated or underestimated

    Safety analysis of unsignalized intersections: a bivariate extreme value approach

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    Application of extreme value theory (EVT) to road safety analysis is gaining interest, thanks to its ability to produce quick and reliable safety evaluations without the use of crash data. Traditionally applied to single collision types and single extreme variables (i.e. surrogate measures of safety), EVT can be further exploited to simultaneously model multiple collision types, with the use of multiple extreme variables. In this paper two bivariate EVT approaches are applied for the safety evaluation of a three-leg unsignalized intersection, considering: (i) two conflict points and a single surrogate measure of safety; (ii) two surrogate measures of safety collected in a single conflict point. Each bivariate analysis was applied with two EVT methods: Component-wise Maxima (CM) and Excesses Over a Threshold (EOT). Bivariate models produced good results, especially with the EOT method, and were able to significantly improve the univariate benchmark results when the two estimation datasets were correlated
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