Accident severity prediction modeling for road safety using random forest algorithm: an analysis of Indian highways.

ABSTRACT: Background: Road accidents claim around 1.35 million lives annually, with countries like India facing a significant impact. In 2019, India reported 449,002 road accidents, causing 151,113 deaths and 451,361 injuries. Accident severity modeling helps understand contributing factors and develop preventive strategies. AI models, such as random forest, offer adaptability and higher predictive accuracy compared to traditional statistical models. This study aims to develop a predictive model for traffic accident severity on Indian highways using the random forest algorithm. Methods: A multi-step methodology was employed, involving data collection and preparation, feature selection, training a random forest model, tuning parameters, and evaluating the model using accuracy and F1 sco

SUBMITTER: Khanum H 

PROVIDER: S-EPMC10787871 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature