Road accident analysis using random forest algorithm

Road accidents are one of the major causes of deadly injuries and deaths. It is possible to predict the possibility of accidents by studying past data. The occurrence of road accidents is associated with multiple factors such as speed, traffic condition, day, time, weather conditions, road construction, etc. Machine learning Algorithms are used to achieve the goal. The key steps involved are data pre-processing, Training the model with supervised learning concepts and creation of the interactive Dashboard. The supervised learning algorithms like Random Forest and Logistic regression are tried and assessed on the basis of accuracy and performance for the training of the model, along with the DBSCAN algorithm for the clustering of the data. The outcome of this project will benefit the public in providing a visualization tool that will evaluate the probability of an accident. In addition, it will help the traffic department in implementing strategies to reduce road accidents.