Road Accident Prediction and Classification using Machine Learning

The safety of roads has long been a key concern for the entire world, and everyone has been working to address it. Due to a constant increase in the number of vehicles, traffic has evolved into a challenging structure to manage. Due to this condition, the issue of road accidents has been identified, and studies on potential solutions have been conducted all over the world. In this paper, we have discussed about one such model where we make use of machine learning and data mining concepts to predict and analyze such accidents all over the country. We are using regression and clustering types of Machine Learning algorithms to predict and analyze the accident rate for the year 2022 for all the States and UTs. We are using Linear Regression algorithm for the prediction of the accident rate for the year 2022. Furthermore, we classify all the states and UTs into two clusters where one cluster consists of states with High accident rate and another cluster consists of states with Low accident rate. We are using K-Means clustering algorithm for the classification of the states and UTs into clusters. We are considering many external factors such as Alcohol, Weather, Location, Junction and Vehicle Defect as the main parameters for the prediction and classification. It is high time for the government as well as the citizens of this country to take precautionary measures to avoid such fatal incidents and enhance the road safety and the information obtained from this model will be used to enhance the safety of the travellers.