Author ORCID Identifier

0000-0001-9178-5517

Document Type

Conference Paper

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Publication Details

Paper was presented at the ITRN 2017 conference 28th and 29th August 2017 University College Dublin

Abstract

This study aims to analyse traffic collisions in the Greater Dublin Region between the period 2006-2012, using GIS to identify hotspots and examine the relationship between collisions and a range of contributory factors including vehicular speeds, traffic volume, road curvature, road category and distance from intersection that could enable prediction of traffic collisions. To this end, Road Safety Authority (RSA) collision data for Dublin Region geocoded as point events, road profiles, traffic flow characteristics on which these occur are spatially merged using ArcGIS and FME software to establish if a significant relationship exists between collision frequencies on road links and the specific link characteristics and traffic flow characteristics. The road network has been divided into uniform segments and the collision frequencies on each of these noted. Traffic collisions are rare and random events and often a major proportion of segments would have no instance of collisions, thus following a Negative Binomial distribution. The outputs from GIS exercise are tested through SPSS software using Negative Binomial distribution for modelling the relationship between different variables. This paper comes at a significant time where efforts are being made to improve the safety of roads within the European Union [1]. Every year, road collisions cause human fatalities together with huge financial loss which can be significantly reduced by improving road safety through the enforcement of traffic laws and road user compliance. By identifying the cause effect relationship and the spatial locations most prone to collisions, prioritized regulatory and safety interventions can be put in place to reduce the collisions on the roads.

DOI

https://doi.org/10.21427/km7e-w124

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