Road Accident Prediction and Analysis Using Machine Learning


Authors : Preshita Bhortake; Vivek Barhate

Volume/Issue : Volume 8 - 2023, Issue 1 - January

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3WT21OR

DOI : https://doi.org/10.5281/zenodo.7599119

Abstract : India has a substantial population, which contributes to a significant daily automobile commuter population. This leads to several accidents occurring every day. These mishaps frequently result in severe financial hardship for families as well as the possibility of fatalities. The goal of this article is to identify accidentprone areas and alert regular commuters to the incidents that are occurring there. Accidents can occur at any time and without warning, but as users of this interface, we can be more cautious in locations where accidents occur frequently. The user interface will alert a user to the high-medium accident risk areas.

Keywords : Random Forest Algorithm,GaussianNaïve Bayes algorithm, Logistic regression, Machine Learning.

India has a substantial population, which contributes to a significant daily automobile commuter population. This leads to several accidents occurring every day. These mishaps frequently result in severe financial hardship for families as well as the possibility of fatalities. The goal of this article is to identify accidentprone areas and alert regular commuters to the incidents that are occurring there. Accidents can occur at any time and without warning, but as users of this interface, we can be more cautious in locations where accidents occur frequently. The user interface will alert a user to the high-medium accident risk areas.

Keywords : Random Forest Algorithm,GaussianNaïve Bayes algorithm, Logistic regression, Machine Learning.

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