ROAD ACCIDENT ANALYSIS

Today, one of the top concerns for governments is road safety. Although there are various safety precautions in place to prevent auto accidents, they cannot be completely avoided. To lessen the harm caused by traffic accidents, the primary goal now is to determine what causes them. In this study, we use machine learning techniques to identify the causes of traffic accidents. By creating precise prediction models that can automatically separate distinct unintentional instances, patterns involved in diverse situations can be identified. The development of safety measures and the application of these classification approaches will help avoid accidents. Although there are numerous inventories in the automotive sector to create and construct safety features for cars, road accidents are inevitable. Both urban and rural regions see a high rate of accidents. By creating precise prediction models that can automatically separate distinct unintentional instances, patterns involved in diverse situations can be identified. These clusters will help create safety precautions and prevent mishaps. We think we can use some ML techniques to reduce accidents as much as possible while using limited resources.