Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{173919,
        author = {B N S V A SANKAR and B.NEERAJA and G.HIMA SRI GAYATHRI and D.ROHIT SIVA MANI KUMAR and CH.VEERA VENKATA RAHUL and B. SURYA CHANDRA RAO},
        title = {PATH TO SAFETY},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {2115-2120},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=173919},
        abstract = {Road traffic accidents remain a significant public safety concern worldwide, leading to numerous fatalities and injuries each year. This project focuses on the comprehensive analysis of road accidents to identify underlying patterns, contributing factors, and potential preventive measures. By leveraging statistical methods and machine learning techniques, the project aims to analyse a dataset comprising various features, including accident location, time, weather conditions, vehicle types, and human factors. The analysis will utilize data visualization tools to highlight trends and correlations, facilitating a deeper understanding of accident dynamics. Additionally, machine learning algorithms such as decision trees, random forests, and clustering techniques will be employed to classify accident types and predict high-risk scenarios. The findings are intended to inform policymakers and traffic management authorities, ultimately enhancing road safety initiatives and reducing the incidence of accidents.},
        keywords = {Road safety, Accident analysis, Machine Learning, Accident prevention.},
        month = {March},
        }