Improving Road Safety Through Machine Learning Based Severity Prediction

Authors

  • Akil Chakravarthi A, Kamalesh M, Kanishka Devi S, Dr.S. Kayalvizhi Author

DOI:

https://doi.org/10.48047/z5whax39

Keywords:

Traffic Accident Severity, Machine Learning, XGBoost, Predictive Modeling, Road Safety, Accident Prediction.

Abstract

An efficient predictive system that can precisely categorize accident severity and allow for targeted interventions is necessary given the increased frequency of traffic accidents. This study divides traffic accidents into two groups: ”Serious Injury” and ”Slight Injury”. It uses advanced machine learning methods to do this..

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References

References K. K. Ahirwar, O. Mishra and G. Ramadurai, ”Determining Road Crash Severity from Police First Informa- tion Reports,” 2022 14th International Conference on Com- munication Systems NETworkS (COMSNETS), Bangalore, India, 2022, pp. 10.1109/COMSNETS53615.2022.9668585.

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Published

2025-02-20

Issue

Vol. 54 No. 4 (2025): Year 2025, Volume 54, Issue 4

Section

Articles

License

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How to Cite

Improving Road Safety Through Machine Learning Based Severity Prediction (Akil Chakravarthi A, Kamalesh M, Kanishka Devi S, Dr.S. Kayalvizhi , Trans.). (2025). Cuestiones De Fisioterapia, 54(4), 890-902. https://doi.org/10.48047/z5whax39