Predicting car accident severity in Northwest Ethiopia: a machine learning approach leveraging driver, environmental, and road conditions

Predicting car accident severity in Northwest Ethiopia: a machine learning approach leveraging driver, environmental, and road conditions

Abstract Road traffic accidents (RTAs) in Northwest Ethiopia, a region with a fatality rate of 32.2 per 100,000 residents, pose a critical public health challenge exacerbated by infrastructural deficits and environmental hazards. This study leverages machine learning (ML) to predict accident severit...

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Bibliographic Details
Main Authors: Abraham Keffale Mengistu, Andualem Enyew Gedefaw, Nebebe Demis Baykemagn, Agmasie Damtew Walle, Tirualem Zeleke Yehuala, Meron Asmamaw Alemayehu, Mengistu Abebe Messelu, Bayou Tilahun Assaye
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Car accident severity
Machine learning
Ethiopia
Road safety
SHAP
SMOTE
Online Access:https://doi.org/10.1038/s41598-025-08005-2
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https://doi.org/10.1038/s41598-025-08005-2

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