The aim of the present study is the representation of
a method to identify and prioritize accident-prone sections
(APSs) based upon efficiency concept to emphasize accidents
with regard to traffic, geometric and environmental
circumstances of road which can consider the interaction
of accidents as well as their casual factors. This study incorporates
the segmentation procedure into data envelopment
analysis (DEA) technique which has no requirement
of distribution function and special assumptions, unlike the
regression models. A case study has been done on 144.4km
length of Iran roads to describe the approach. Eleven accident-prone
sections were identified among 154 sections
obtained from the segmentation process and their prioritization
was made based on the inefficiency values coming
from DEA method. The comparisons demonstrated that the
frequency and severity of accidents would not be only considered
as the main factors for black-spots identification but
proper rating can be possible by obtaining inefficiency values
from this method for the road sections. This approach
could applicably offer decision-making units for identifying
accident-prone sections and their prioritizations. Also, it can
be used to prioritize intersections, roundabouts or the total
roads of the safety organization domain.