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March 30, 2026Scientific ReportsOpen Access

Improving road safety in smart cities using machine learning techniques

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Authors

MAMuhammad Shujaat AbidVirtual University of PakistanMHMushtaq HussainVirtual University of PakistanSNSaid NabiVirtual University of Pakistan

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Implication

Analysis reveals Machine Learning improves road safety factors in urban environments, suggesting effective predictive solutions.

Key Points

  • This research focuses on enhancing road safety in smart cities using Machine Learning techniques to analyze traffic accidents.
  • Traffic accident data were collected from Toronto and Rawalpindi, Pakistan.
  • Data preprocessing was performed using Python.
  • Machine Learning and Deep Learning models were trained and tested on the cleaned data.
  • Association Rule Mining was employed to identify factors leading to severe injuries.
  • XGBoost and Random Forest achieved 74% accuracy on the KSI dataset without hyperparameter tuning.
  • Random Forest reached 99% accuracy after applying Grid Search and undersampling techniques.
  • The analysis identified speeding and inattentiveness as key factors contributing to serious collisions.

Cite This Study

Abid et al. (2026) studied this question.

synapsesocial.com/papers/69c9c51bf8fdd13afe0bd195https://doi.org/10.1038/s41598-026-36795-6
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