International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Development of a Predictive Model for Predicting the Risk of Road Accidents Using Machine Learning |
|---|---|
| ABSTRACT | Road accidents have become a major concern across the globe. Predicting the severity of accidents can help in proactive emergency response and improved road safety planning. This project leverages machine learning algorithms to classify accident severity levels using historical road accident data. Since the dataset is highly imbalanced, SMOTE (Synthetic Minority Oversampling Technique) is applied to balance the classes. The model aims to assist traffic departments in minimizing fatalities and optimizing resource allocation. By integrating complex environmental features such as localized weather conditions, visibility, and road geometry the system isolates hidden risk patterns. Advanced tree-based ensemble models are deployed to ensure robust classification across low, medium, and high-severity tiers. Five machine learning algorithms — Random Forest, XGBoost, Decision Tree, Support Vector Machine, and Logistic Regression — are evaluated. The results are deployed as a web-based predictor (AcciSense) enabling real-time severity prediction from GPS coordinates. Random Forest achieved the highest accuracy of 92.4%. |
| AUTHOR | PRIYA D, B. KEERTHI, A. SUDHAKAR PG Student, Department of Computer Science and Engineering, Bharathidasan Engineering College, Nattrampalli, Tamil Nadu, India Assistant Professor, Department of Computer Science and Engineering, Bharathidasan Engineering College, Nattrampalli, Tamil Nadu, India HOD, Department of Computer Science and Engineering, Bharathidasan Engineering College, Nattrampalli, Tamil Nadu, India |
| VOLUME | 185 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1406047 |
| pdf/47_Development of a Predictive Model for Predicting the Risk of Road Accidents Using Machine Learning.pdf | |
| KEYWORDS | |
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