Road accident analysis particularly the spatial patterns of road
accidents requires further attention. This study aims to highlight
some of the gaps in the research with particular attention to
spatial clustering of road accidents. This is one of a handful of
research papers which addresses the nature of supplementary
data to examine the road accident hotspots. Traditionally research
has relied on raw statistics alone without examining the potential
indicators found in complimentary datasets such as those referring
to the environment, land use, accident victims and road furniture
for statistical clustering. This paper adds significant value to the
research on the delineation of road accident hotspots and the
complex nature of how we measure road accident hotspots
to investigate in further studies. This study represents a large
scale model for road accident clustering. Further study needs to be
conducted in a number of areas. Firstly, there needs to be development
of amethod for testing for statistical significance of the kernel
density output. Secondly, there needs to be investigation into the
changing dynamics of the clusters over different temporal and spatial
scales. Thirdly, a policy led investigation needs to be conducted
into the suggestions made from the cluster outcomes.