Abstract

Even though pedestrians represented 40% of all urban displacements in Brazil in 2017, they are still highly vulnerable to traffic accidents, with a mortality rate of 2.89 per 100 thousand inhabitants in 2018. The literature suggests a relationship between the occurrence of traffic accidents and demographic, socioeconomic, and urban structure variables. In this study, this relationship was investigated through a data-driven statistical model (logistic regression) combined with GIS spatial analysis, applied to estimate the pedestrian susceptibility to traffic accidents in the City of Curitiba, in Southern Brazil. By adopting broadly available spatial information, the proposed methods were robust in estimating the events, presenting an area under the ROC curve of 0.82 in the cross-validation. Additionally, the results highlighted a strong and statistically significant correlation between the pedestrian crashes and the analyzed variables of road system hierarchy, presence of BRT routes, land-use, population density and per capita income.

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