Método Probabilístico para Identificação de Zonas de Acumulação de Acidentes

Abstract

This paper presents a new methodology to define and to identify hot spot based on a binary regression model. Considering the geometric and functional site characteristics, the model estimates the probability of a site being a hot spot. This method was applied to intersections using a simulation-based approach to data generated considering the characteristics of the Porto city data base. Using simulation, it is possible to establish sites that are a priori "true" hot spot. The performance of the new method was evaluated using the errors of the classification outcomes of the sites and compared with two commonly implemented methods that are the simple ranking of sites and the empirical Bayesian technique. This analysis has set that the proposed binary model performed better.