A Skid Resistance Predicting Model for Single Carriageways

Skid resistance, or friction, on a road surface is a critical parameter in functional highway assessments, given its direct relationships with safety and accident frequency. Therefore, road administrations must collect friction data across their road networks to ensure safe roads for users. In addit...

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Detalles Bibliográficos
Autores: Isasa, Miren, Alonso-Solórzano, Ángela, Gurrutxaga, Itziar, Pérez-Acebo, Heriberto
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universidad Francisco de Vitoria
Repositorio:DDFV. Repositorio Institucional de la Universidad Francisco de Vitoria
Idioma:inglés
OAI Identifier:oai:ddfv.ufv.es:10641/6772
Acceso en línea:https://hdl.handle.net/10641/6772
Access Level:acceso abierto
Palabra clave:SCRIM coefficient
pavement friction
pavement management system
road safety
skid resistance
Mechanical Engineering
Surfaces, Coatings and Films
Yes
yes
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spelling A Skid Resistance Predicting Model for Single CarriagewaysIsasa, MirenAlonso-Solórzano, ÁngelaGurrutxaga, ItziarPérez-Acebo, HeribertoSCRIM coefficientpavement frictionpavement management systemroad safetyskid resistanceMechanical EngineeringSurfaces, Coatings and FilmsYesyesSkid resistance, or friction, on a road surface is a critical parameter in functional highway assessments, given its direct relationships with safety and accident frequency. Therefore, road administrations must collect friction data across their road networks to ensure safe roads for users. In addition, having a predictive model of skid resistance for each road section is essential for an efficient pavement management system (PMS). Traditionally, road authorities disregard rural roads, since they are more focused on freeways and traffic-intense roads. This study develops a model for predicting minimum-available skid resistance, which occurs in summer, measured using the Sideway-force Coefficient Routine Investigation Machine (SCRIM), on bituminous pavements in the single-carriageway road network of the Province of Gipuzkoa, Spain. To this end, traffic volume data available in the PMS of the Provincial Council of Gipuzkoa, such as the annual average daily traffic (AADT) and the AADT of heavy vehicles (AADT.HV), were uniquely used to forecast skid-resistance values collected in summer. Additionally, a methodology for eliminating outliers is proposed. Despite the simplicity of the model, which does not include information about the materials at the surface layer, a coefficient of determination (R2) of 0.439 was achieved. This model can help road authorities identify the roads for which lower skid-resistance values are most likely to occur, allowing them to focus their attention and efforts on these roads, which are key infrastructure in rural areas.Escuela Politécnica Superior20252025-08-0120252025-08-01journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10641/6772reponame:DDFV. Repositorio Institucional de la Universidad Francisco de Vitoriainstname:Universidad Francisco de VitoriaInglésengopen accesshttp://purl.org/coar/access_right/c_abf2http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:ddfv.ufv.es:10641/67722026-06-11T12:44:57Z
dc.title.none.fl_str_mv A Skid Resistance Predicting Model for Single Carriageways
title A Skid Resistance Predicting Model for Single Carriageways
spellingShingle A Skid Resistance Predicting Model for Single Carriageways
Isasa, Miren
SCRIM coefficient
pavement friction
pavement management system
road safety
skid resistance
Mechanical Engineering
Surfaces, Coatings and Films
Yes
yes
title_short A Skid Resistance Predicting Model for Single Carriageways
title_full A Skid Resistance Predicting Model for Single Carriageways
title_fullStr A Skid Resistance Predicting Model for Single Carriageways
title_full_unstemmed A Skid Resistance Predicting Model for Single Carriageways
title_sort A Skid Resistance Predicting Model for Single Carriageways
dc.creator.none.fl_str_mv Isasa, Miren
Alonso-Solórzano, Ángela
Gurrutxaga, Itziar
Pérez-Acebo, Heriberto
author Isasa, Miren
author_facet Isasa, Miren
Alonso-Solórzano, Ángela
Gurrutxaga, Itziar
Pérez-Acebo, Heriberto
author_role author
author2 Alonso-Solórzano, Ángela
Gurrutxaga, Itziar
Pérez-Acebo, Heriberto
author2_role author
author
author
dc.contributor.none.fl_str_mv Escuela Politécnica Superior
dc.subject.none.fl_str_mv SCRIM coefficient
pavement friction
pavement management system
road safety
skid resistance
Mechanical Engineering
Surfaces, Coatings and Films
Yes
yes
topic SCRIM coefficient
pavement friction
pavement management system
road safety
skid resistance
Mechanical Engineering
Surfaces, Coatings and Films
Yes
yes
description Skid resistance, or friction, on a road surface is a critical parameter in functional highway assessments, given its direct relationships with safety and accident frequency. Therefore, road administrations must collect friction data across their road networks to ensure safe roads for users. In addition, having a predictive model of skid resistance for each road section is essential for an efficient pavement management system (PMS). Traditionally, road authorities disregard rural roads, since they are more focused on freeways and traffic-intense roads. This study develops a model for predicting minimum-available skid resistance, which occurs in summer, measured using the Sideway-force Coefficient Routine Investigation Machine (SCRIM), on bituminous pavements in the single-carriageway road network of the Province of Gipuzkoa, Spain. To this end, traffic volume data available in the PMS of the Provincial Council of Gipuzkoa, such as the annual average daily traffic (AADT) and the AADT of heavy vehicles (AADT.HV), were uniquely used to forecast skid-resistance values collected in summer. Additionally, a methodology for eliminating outliers is proposed. Despite the simplicity of the model, which does not include information about the materials at the surface layer, a coefficient of determination (R2) of 0.439 was achieved. This model can help road authorities identify the roads for which lower skid-resistance values are most likely to occur, allowing them to focus their attention and efforts on these roads, which are key infrastructure in rural areas.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025-08-01
2025
2025-08-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/10641/6772
url https://hdl.handle.net/10641/6772
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2

http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2

http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:DDFV. Repositorio Institucional de la Universidad Francisco de Vitoria
instname:Universidad Francisco de Vitoria
instname_str Universidad Francisco de Vitoria
reponame_str DDFV. Repositorio Institucional de la Universidad Francisco de Vitoria
collection DDFV. Repositorio Institucional de la Universidad Francisco de Vitoria
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.81155

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