Indian Road Accident Analysis with Machine Learning

EasyChair Preprint no. 9960

Abstract

Road accidents are a major threat to both developed and underdeveloped countries. Traffic accidents and their safety is a major problem of the world and everyone has been trying to deal with it for years. Road traffic and reckless driving occur in all parts of the world. For this reason, many pedestrians are also affected. They become victims through no fault of their own. Many road accidents occur due to many factors such as atmospheric changes, sharp turns and human errors. Injuries caused by traffic accidents are large, but sometimes imperceptible, which later affects your health. This study aims to analyze traffic accidents in one of the popular metropolitan cities i.e. Bengaluru using k-means algorithm and machine learning by investigating the accident prone areas or hotspots and their root causes.

Keyphrases: atmospheric, hotspots, Imperceptible, K-means algorithm, Metropolitan, Pedestrians, reckless, underdeveloped, Victims

@Booklet{EasyChair:9960,
  author = {Chaturvedi Venugopal and Ajay Shanker Singh and Shruti Suman},
  title = {Indian Road Accident Analysis with Machine Learning},
  howpublished = {EasyChair Preprint no. 9960},

  year = {EasyChair, 2023}}