2024
DOI: 10.1371/journal.pone.0302171
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Comparing fatal crash risk factors by age and crash type by using machine learning techniques

Abdulaziz H. Alshehri,
Fayez Alanazi,
Ahmed. M. Yosri
et al.

Abstract: This study aims to use machine learning methods to examine the causative factors of significant crashes, focusing on accident type and driver’s age. In this study, a wide-ranging data set from Jeddah city is employed to look into various factors, such as whether the driver was male or female, where the vehicle was situated, the prevailing weather conditions, and the efficiency of four machine learning algorithms, specifically XGBoost, Catboost, LightGBM and RandomForest. The results show that the XGBoost Model… Show more

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