Probabilistic model data of spatial-dependent crashes for ranking risk of road segments

This article presents the databases analyzed and used to evaluate the risk of segment-based roads resulting from traffic crashes for three main motorways in UK from 2010 to 2014. The raw database is collection to many partial data for variables related to compute the crashes rates for each segment....

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Detalles Bibliográficos
Autores principales: Kadhem, Safaa K., Hewson, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Mathematics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6926288/
https://www.ncbi.nlm.nih.gov/pubmed/31890806
http://dx.doi.org/10.1016/j.dib.2019.104966
Descripción
Sumario:This article presents the databases analyzed and used to evaluate the risk of segment-based roads resulting from traffic crashes for three main motorways in UK from 2010 to 2014. The raw database is collection to many partial data for variables related to compute the crashes rates for each segment. These data were used to develop and select the best Bayesian probabilistic model presented in our research article (Kadhem et al., 2018) [1]. The data provided in this article would be an important source for studies that require evaluating statistical models and also to improve and develop the plans of traffic safety.

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