Guardians of the road: machine learning solutions for safer commutes

作者：Qiao Peng, Honghao He, Ying Gao, Tangzhu Zhang · 年份：2024 · DOI：10.1117/12.3030614 · 研究领域：Traffic and Road Safety、Traffic Prediction and Management Techniques、Urban Transport and Accessibility

Road Traffic Accidents (RTAs) are a serious safety issue, especially in fast-growing cities, and have become one of the leading causes of death worldwide. This study takes Addis Ababa, Ethiopia, as a case study for the period from 2017 to 2020 and uses advanced interpretable machine learning techniques to analyse the key features that influence road safety. The results highlight the superior performance of the Random Forest model. Interestingly, findings indicate that a large number of accidents occurred under normal road and weather conditions, highlighting the significant influence of driver characteristics. This study provides relevant authorities with effective strategies to significantly reduce mortality in persistent RTAs.