Predictive Modeling of Crash Frequency on Mountainous Highways: A Mixed-Effects Approach Applied to a Brazilian Road

This study investigates the influence of roadway geometry and environmental conditions on traffic crash frequency along a 57 km mountainous segment of the BR-116/SP (Régis Bittencourt Highway), one of Brazil’s most critical freight and passenger corridors. A Generalized Linear Mixed Model (GLMM) with a Negative Binomial distribution was developed using monthly data aggregated by highway segment. Explanatory variables included traffic exposure, geometric design characteristics, and meteorological factors. The results revealed that horizontal curvature and longitudinal grade are key determinants of crash occurrence and that the interaction between these factors substantially amplifies crash risk. Specifically, segments with combined tight curvature (radius < 500 m) and moderate-to-steep grades showed up to a 4.3-fold increase in expected crash frequency compared with straight or flat sections. The model achieved satisfactory fit (RMSE = 1.273) and provided a robust framework for identifying high-risk locations. The findings highlight the importance of geometric consistency and integrated safety management strategies, contributing to sustainable transport management and offering methodological and practical contributions to data-driven road safety policies in Brazil.