Enhancing Road Safety in India: A Predictive Analysis Using Machine Learning Algorithm for Accident Severity Modeling

Abstract

This chapter presents a comprehensive study aimed at enhancing road safety in India through the development and application of a machine-learning predictive model for traffic accident severity on Indian highways. With road accidents being a leading cause of death and injury, claiming approximately 1.35 million lives globally each year, India faces a particularly acute challenge, reporting nearly 449,002 road accidents in 2019 alone. This work leverages the adaptability and superior predictive accuracy of machine-learning algorithms to model accident severity, thereby providing a basis for understanding contributing factors and formulating effective preventive strategies. Employing a meticulous multistep methodology, this study involves the collection and preparation of data from authorized organizations for data availability, feature selection, model training, parameter tuning, and model evaluation based on statistical accuracy matrixes. The chapter concludes by highlighting the significant potential of integrating machine-learning techniques with enhanced data recording systems to improve road safety modeling, decision-making, and accident prevention, ultimately contributing to the reduction of road traffic accidents and their associated human and economic costs.