Data Visualization and Machine Learning Approach for Analyzing Severity of Road Accidents

Abstract

Road accidents are a major critical problem in recent days, which cause death, severe injuries, disabilities to human lives, and substantial economic losses worldwide. A detailed analysis of the factors responsible for the accidents is required to reduce the accident rate. In this study, a descriptive analysis has been performed in-depth to identify the significant factors influencing accident severity. Machine learning techniques have been applied to predict the severity of accidents considering location, time, infrastructure, and environmental conditions-related factors that may cause road accidents. Here the findings of this study emphasize that the mediate severity of accidents have a high frequency of occurring rather than severities of very low and high risk. Moreover, the factors like infrastructure, day of the week, and weather conditions influence the severity of accidents differently. The Random Forest algorithm took the best performance with 97.2% high accuracy in predicting the severity of road traffic accidents. These results can guide relevant parties to identify dangerous situations and take the necessary actions to improve road safety by reducing accidents.