Traffic Accident Injury and Severity Prediction Using Machine Learning Algorithms

Abstract

Traffic crashes are the severe issues confronting the world as they are the root reason for numerous deaths, wounds, and fatalities just as financial misfortunes consistently. Effective model to deduce the severity of an accident is very helpful for both traffic department and general public. This examination sets up models to choose a lot of compelling variables and to develop a model for arranging the severity of wounds. These models are planned by different machine learning methods. Both supervised and unsupervised learning methods are actualized on accident data. The major aim of this is to find the relationship between various sorts of the accidents with the kind of the injuries that might have occurred. The discoveries of this investigation demonstrate that unsupervised learning methods can be a promising instrument for anticipating the damage severity of Traffic crashes.