Citation

Shad R, Rahimi S. Int. J. Traffic Transp. Eng. (Belgrade) 2017; 7(3): 368-380.

Copyright

(Copyright © 2017, City Net Scientific Research Center, Faculty of Transport and Traffic Engineering, University of Belgrade)

DOI

10.7708/ijtte.2017.7(3).07

PMID

unavailable

Abstract

It is a crucial task to reduce road crashes by performing analyses and taking appropriate countermeasures to save lives. It has been a major issue for many people and government to reduce the amount of road collisions especially in Iran, since it could be a great threat to this country. Identification of crash black-sites is one of the most important fields in road safety studies. Many highway agencies have been using Geographical Information System (GIS) for analyzing crash data. The GIS based application integrates the information collection capabilities with the visualization. In this paper, Incident features like location, date, type of vehicle involved, and number of persons injured or died are imported in the GIS database. Then, Kernel density is to apply on the prepared data. The main objective is to specify road crash black-spots considering all types of traffic crashes based on their severity using Kernel Density through GIS environment. The results show that more severe crashes take place further from the cities than accidents with only property damages. Also, overlaying all crash types using the suggested SI (severity index) method will generate crash black-sites map which policy makers can use to determine accident-prone zones and take appropriate interventions.

Language: en