Review of the Machine Learning Techniques in Road Crashes

Abstract

Road crashes and resulting fatalities and injuries have evolved as a major issue across the globe. According to the Global Status Report on Road Safety 2018 [1] published by World Health Organization, the burden of road traffic injuries and deaths is borne by vulnerable road users living in low-and middle-income countries where deaths are increasing due to abrupt growth in number of motorized transport. It is estimated that road crashes alone are responsible for 3 to 4 percent of GDP loss in India. Considering the severity of the issue it is important to identify underlying factors of road crashes to reduce the damage caused to human lives and national asset. By applying various Machine Learning algorithms on road crash data, workable models can be built which can predict outcome based on past trends of road crashes.