Road Safety Modeling: Safe Road for All

In the last few years, road accidents have been emerged as a very big problem worldwide in develop and underdeveloped countries due to enormous increase in number of vehicles. Large number of deaths due to road accidents has been recorded which has become a big challenge for developing nations like India. Due to the increase in number of vehicles, traffic on roads has increased at a rapid rate; due to this, peoples traveling without vehicles are also becoming victims of road accidents. Various road accident occur because of many diverse factors like driving fast, drink and drive, and devastation to drivers, crossing red lights, and bypassing safety features like airbag, driving in wrong lane, and passing other vehicles in false. Road accident can lead to severe injuries but sometimes it can lead to death. Using state-of-the-art machine learning techniques like decision trees, K-nearest neighbors (KNN), Naive Bayes, and AdaBoost, this study aims to showcase the various efforts of its contributors in the area of traffic accident analysis. Various researchers have used these machine learning methods to predict the cluster of areas that are prone to accident or trouble spot areas and various factors that cause the road accident in that areas.