Model-based clustering (MBC) for road data via multivariate mixture of normal distributions and factor analysis (FA)

In road traffic, there are many influential parameters that need to be analysed. For a long time, the statistical methods have been used for analysing, planning and preventing accidents in advanced countries. In this study, multivariate normal distribution was applied to a finite mixture model for clustering roads. In order to solve the problems of road traffic safety and road accidents, a new FA (Factor analysis)-MBC (Model based clustering) method was introduced based on the math theory of FA-MBC. First, the FA method was used to reduce the dimensions of the features, and then our proposed method (MBC) was applied to cluster the road data gathered for Tehran Province, Iran. The results show that our model has a good performance in dealing with data that may have high-dimensional features.