An Analytical Study of Road Accidents on Indian Highways: Causes, Trends, and Prevention Strategies

Abstract

Highway accidents remain one of the leading causes of fatalities in India, with over speeding, poor road conditions, and limited medical response contributing to rising death rates. This study analyses 8,116 accident records from selected Indian highways to identify accident prone locations, contributing factors, and severity patterns. Using descriptive statistics and visualization in Tableau, accident trends were explored across time, location, and causes. Advanced analytics were applied through Python, including Weighted Severity Index (WSI) for hotspot detection and machine learning models for severity prediction. The results highlight specific black spots, high risk conditions, and the critical influence of driver behavior and road features on accident outcomes. By simulating possible interventions, such as reducing over speeding and improving road safety infrastructure, the study demonstrates the potential to significantly lower severe accident rates. The findings provide actionable insights for policymakers, highway authorities, and enforcement agencies to design targeted strategies for reducing fatalities and improving highway safety.