Background
Road and traffic accidents are uncertain and unpredictable incidents and their analysis
requires the knowledge of the factors affecting them. Road and traffic accidents are
defined by a set of variables which are mostly of discrete nature. The major problem in
the analysis of accident data is its heterogeneous nature [1]. Thus heterogeneity must be
considered during analysis of the data otherwise, some relationship between the data
may remain hidden. Although, researchers used segmentation of the data to reduce this
heterogeneity using some measures such as expert knowledge, but there is no guarantee
that this will lead to an optimal segmentation which consists of homogeneous groups
of road accidents [2]. Therefore, cluster analysis can assist the segmentation of road
accidents.