Issue |
MATEC Web Conf.
Volume 258, 2019
International Conference on Sustainable Civil Engineering Structures and Construction Materials (SCESCM 2018)
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Article Number | 03008 | |
Number of page(s) | 10 | |
Section | Forensic Engineering, Structural Health Monitoring System, Assessment and Retrofitting, Disaster Mitigation and Restoration | |
DOI | https://doi.org/10.1051/matecconf/201925803008 | |
Published online | 25 January 2019 |
Evaluation of various GIS-based methods for the analysis of road traffic accident hotspot
1 Centre for Transport Research, Universiti Teknologi Brunei, Brunei Darussalam
2 Civil Engineering Programme Area, Faculty of Engineering, Universiti Teknologi Brunei, Brunei Darussalam
* Corresponding author: elsaid.zahran@utb.edu.bn
In order to establish objective criteria for road traffic accident (RTA) hotspots, this paper examines the application of three different hotspot analysis methods to both identify and rank the RTA hotspots. The three methods selected are the network Kernel Density Estimation (KDE+) method, the Getis-Ord GI* method, and a recently proposed risk-based method that accounts for RTA frequency, severity and socioeconomic costs - STAA method. The study road, Jalan Tutong, is a major dual-carriageway connecting major residential and commercial areas from the west of Brunei-Muara district and beyond to the capital, Bandar Seri Begawan. The RTA data consists of cases reported to the police during a 5-year period from 2012 to 2016. The RTA data were digitised and prepared, before being imported into ESRI ArcGIS 10.2 software for analysis using each of these methods. The outcomes, particularly the location, extent and priority of the RTA hotspots, are subsequently compared to results from road safety audits, in order to determine the relative merits and drawbacks of each method. The findings from the comparative study would be useful to recommend the most suitable method to identify and rank the RTA hotspots for the study road.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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