Road Accident Prediction Model Using Machine Learning: A Review

Authors

  • N P Shah
  • Prajakta Masal
  • Samina mulani
  • Shraddha Khandomalke
  • Mahadevi Mukadm

Keywords:

Machine Learning, RFCNN Model, Decision Tree, SVM.

Abstract

The number of daily accidents due to road conditions, vehicle speed, weather conditions, etc.is a very crucial part today. Mainly accidents involving due to some weather, environmental conditions and due to traffic also. The relation between occurrence of traffic accidents and some factors and identifying main factors that contributing accident severity. Using advanced predictive capabilities of technology accurately assessing accidents and finding main reason or factors those contributing accidents. A series of machine learning and deep learning models are presented by integrating random forests and convolutional neural networks (RFCNN) to predict traffic accident severity. The model optimized further in future and help us to better monitor accident prone areas and provide emergency services.

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Published

2022-12-27

How to Cite

N P Shah, Prajakta Masal, Samina mulani, Shraddha Khandomalke, & Mahadevi Mukadm. (2022). Road Accident Prediction Model Using Machine Learning: A Review. International Journal of Progressive Research in Science and Engineering, 3(12), 162–165. Retrieved from https://journal.ijprse.com/index.php/ijprse/article/view/760

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Section

Articles