A skid resistance prediction model for an entire road network

This article predicts the available minimum skid resistance in the road network of Biscay (Spain) with data collected in the summer season when friction values are at a minimum. Firstly, it was observed that pavement structure does not influence skid resistance. Therefore, roadway segments with avai...

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Detalles Bibliográficos
Autores: Pérez Acebo, Heriberto, Gonzalo Orden, Hernán, Findley, Daniel J., Rojí, Eduardo
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2020
País:España
Institución:Universidad de Burgos (UBU)
Repositorio:Repositorio Institucional de la Universidad de Burgos (RIUBU)
OAI Identifier:oai:riubu.ubu.es:10259/8936
Acceso en línea:http://hdl.handle.net/10259/8936
Access Level:acceso abierto
Palabra clave:Skid resistance
Friction
Pavement performance model
Pavement deterioration
Pavement management system
Deterministic model
Surface layer
Pavement management
Ingeniería civil
Resistencia de materiales
Materiales de construcción
Civil engineering
Strength of materials
Building materials
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repository_id_str
spelling A skid resistance prediction model for an entire road networkPérez Acebo, HeribertoGonzalo Orden, HernánFindley, Daniel J.Rojí, EduardoSkid resistanceFrictionPavement performance modelPavement deteriorationPavement management systemDeterministic modelSurface layerPavement managementIngeniería civilResistencia de materialesMateriales de construcciónCivil engineeringStrength of materialsBuilding materialsThis article predicts the available minimum skid resistance in the road network of Biscay (Spain) with data collected in the summer season when friction values are at a minimum. Firstly, it was observed that pavement structure does not influence skid resistance. Therefore, roadway segments with available data about the surface layer of single or double carriageway roads were analyzed. Two models were developed: 1) short model with only the surface material, average annual daily traffic, and number of lanes (no pavement history required) and 2) a long model which adds the required Polished Stone Value to improve the prediction. These models can help road agencies to identify the roads where lower skid resistance values are more probable to be obtained to focus their attention and efforts.This work was supported by the Diputación Foral de Bizkaia. Departamento de Obras Públicas y Transportes [Agreement on 25/06/2014]; Erasmus+ KA107 – 2017 project for mobilities from UPV/EHU (Spain) to universities in United States, Morocco, Russian Federation and Kazakhstan; and Erasmus+ KA107 – 2015 project for mobility from universities in the USA, Canada, South Korea and Russia to the UPV/EHU (Spain).Elsevier202420242020info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttp://hdl.handle.net/10259/8936reponame:Repositorio Institucional de la Universidad de Burgos (RIUBU)instname:Universidad de Burgos (UBU)InglésConstruction and Building Materials. 2020, V. 262, 120041https://doi.org/10.1016/j.conbuildmat.2020.120041Attribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:riubu.ubu.es:10259/89362026-05-28T07:56:11Z
dc.title.none.fl_str_mv A skid resistance prediction model for an entire road network
title A skid resistance prediction model for an entire road network
spellingShingle A skid resistance prediction model for an entire road network
Pérez Acebo, Heriberto
Skid resistance
Friction
Pavement performance model
Pavement deterioration
Pavement management system
Deterministic model
Surface layer
Pavement management
Ingeniería civil
Resistencia de materiales
Materiales de construcción
Civil engineering
Strength of materials
Building materials
title_short A skid resistance prediction model for an entire road network
title_full A skid resistance prediction model for an entire road network
title_fullStr A skid resistance prediction model for an entire road network
title_full_unstemmed A skid resistance prediction model for an entire road network
title_sort A skid resistance prediction model for an entire road network
dc.creator.none.fl_str_mv Pérez Acebo, Heriberto
Gonzalo Orden, Hernán
Findley, Daniel J.
Rojí, Eduardo
author Pérez Acebo, Heriberto
author_facet Pérez Acebo, Heriberto
Gonzalo Orden, Hernán
Findley, Daniel J.
Rojí, Eduardo
author_role author
author2 Gonzalo Orden, Hernán
Findley, Daniel J.
Rojí, Eduardo
author2_role author
author
author
dc.subject.none.fl_str_mv Skid resistance
Friction
Pavement performance model
Pavement deterioration
Pavement management system
Deterministic model
Surface layer
Pavement management
Ingeniería civil
Resistencia de materiales
Materiales de construcción
Civil engineering
Strength of materials
Building materials
topic Skid resistance
Friction
Pavement performance model
Pavement deterioration
Pavement management system
Deterministic model
Surface layer
Pavement management
Ingeniería civil
Resistencia de materiales
Materiales de construcción
Civil engineering
Strength of materials
Building materials
description This article predicts the available minimum skid resistance in the road network of Biscay (Spain) with data collected in the summer season when friction values are at a minimum. Firstly, it was observed that pavement structure does not influence skid resistance. Therefore, roadway segments with available data about the surface layer of single or double carriageway roads were analyzed. Two models were developed: 1) short model with only the surface material, average annual daily traffic, and number of lanes (no pavement history required) and 2) a long model which adds the required Polished Stone Value to improve the prediction. These models can help road agencies to identify the roads where lower skid resistance values are more probable to be obtained to focus their attention and efforts.
publishDate 2020
dc.date.none.fl_str_mv 2020
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10259/8936
url http://hdl.handle.net/10259/8936
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Construction and Building Materials. 2020, V. 262, 120041
https://doi.org/10.1016/j.conbuildmat.2020.120041
dc.rights.none.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositorio Institucional de la Universidad de Burgos (RIUBU)
instname:Universidad de Burgos (UBU)
instname_str Universidad de Burgos (UBU)
reponame_str Repositorio Institucional de la Universidad de Burgos (RIUBU)
collection Repositorio Institucional de la Universidad de Burgos (RIUBU)
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300724

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