Author:
Bel-lahcen Marwane,Abdellaoui Alaoui El Arbi,Tékouabou Koumétio Stéphane Cédric,Naggar Othmane Naggar
Abstract
This paper uses machine learning to predict road accidents in Morocco, a country marked by high annual accident rates. Our model employs data such as weather, time of day, and road conditions, derived from historical accidents and environmental records. Findings suggest that such predictive modeling can enable traffic authorities to anticipate high-risk situations and enact pre-emptive safety measures, contributing to significant reductions in road accidents. This study provides a data-driven approach towards policy implementation for road safety, with insights applicable to global road safety initiatives.