A Framework for Spatial Road Safety Assessment: Case Study of Northern Ireland


Autoria(s): Farrell, Aimee; Moutari, Salissou
Data(s)

01/09/2016

Resumo

Road traffic injuries are a major health issue worldwide. There are many factors that can<br/>affect the levels of road traffic collisions which in turn increase the levels of people killed or<br/>seriously injured. When road traffic collisions occur, observed facts are recorded in relation<br/>to the incident. These facts are recorded as variable observations, and for this study,<br/>variables and indicators are defined almost equivalently. There can be hundreds of different<br/>indicators for the various collisions, as different countries face different road situations. This<br/>makes it difficult to perform a road safety assessment, which can be applied globally. The<br/>goal of this study is to select the most appropriate indicators and create a composite<br/>indicator as a function of these indicators, which can be used as summary values, allowing<br/>ease of comparisons between the countries/regions that have undergone a road safety<br/>assessment. The composite indicator will then be used to assess the current situation in<br/>Northern Ireland and provide scores for ranking policing in terms of overall road safety on<br/>their road networks.

Formato

application/pdf

Identificador

http://pure.qub.ac.uk/portal/en/publications/a-framework-for-spatial-road-safety-assessment-case-study-of-northern-ireland(02567716-26eb-447e-8bd6-c636db20fae0).html

http://pure.qub.ac.uk/ws/files/119717881/A_Framework_for_Spatial_Road_Safety_Assessment.pdf

Idioma(s)

eng

Publicador

Irish Transport Research Network

Direitos

info:eu-repo/semantics/openAccess

Fonte

Farrell , A & Moutari , S 2016 , A Framework for Spatial Road Safety Assessment: Case Study of Northern Ireland . in Proceedings of the Irish Transport Research Network Conference - 2016 . Irish Transport Research Network , Irish Transport Research Network , Dublin , Ireland , 1-1 September .

Tipo

contributionToPeriodical