2026-04-29T02:53:53Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/89362024-04-16T00:05:20Zcom_10259_8929com_10259_5086com_10259_2604com_10259_4204col_10259_8930col_10259_5373

A skid resistance prediction model for an entire road network Pérez Acebo, Heriberto Gonzalo Orden, Hernán Findley, Daniel J. Rojí, Eduardo 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 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. 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). 2024-04-15T08:15:18Z 2024-04-15T08:15:18Z 2020-11 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion 0950-0618 http://hdl.handle.net/10259/8936 10.1016/j.conbuildmat.2020.120041 eng Construction and Building Materials. 2020, V. 262, 120041 https://doi.org/10.1016/j.conbuildmat.2020.120041 Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess application/pdf Elsevier