Prediction of Friction Degradation in Highways with Linear Mixed Models

The development of a linear mixed model to describe the degradation of friction on flexible road pavements to be included in pavement management systems is the aim of this study. It also aims at showing that, at the network level, factors such as temperature, rainfall, hypsometry, type of layer, and...

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Main Authors: Adriana Santos, Elisabete F. Freitas, Susana Faria, Joel R. M. Oliveira, Ana Maria A. C. Rocha
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Coatings
Subjects:
Online Access:https://www.mdpi.com/2079-6412/11/2/187
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spelling doaj-c9bfb55e1ba04e57aa835280696eef722021-02-06T00:02:21ZengMDPI AGCoatings2079-64122021-02-011118718710.3390/coatings11020187Prediction of Friction Degradation in Highways with Linear Mixed ModelsAdriana Santos0Elisabete F. Freitas1Susana Faria2Joel R. M. Oliveira3Ana Maria A. C. Rocha4CTAC, Doctoral Program in Civil Engineering, Department of Civil Engineering, University of Minho, 4800-058 Guimarães, PortugalISISE, Department of Civil Engineering, University of Minho, 4800-058 Guimarães, PortugalCBMA, Department of Mathematics, University of Minho, 4800-058 Guimarães, PortugalISISE, Department of Civil Engineering, University of Minho, 4800-058 Guimarães, PortugalALGORITMI, Department of Production and Systems Engineering, University of Minho, 4800-058 Guimarães, PortugalThe development of a linear mixed model to describe the degradation of friction on flexible road pavements to be included in pavement management systems is the aim of this study. It also aims at showing that, at the network level, factors such as temperature, rainfall, hypsometry, type of layer, and geometric alignment features may influence the degradation of friction throughout time. A dataset from six districts of Portugal with 7204 sections was made available by the Ascendi Concession highway network. Linear mixed models with random effects in the intercept were developed for the two-level and three-level datasets involving time, section and district. While the three-level models are region-specific, the two-level models offer the possibility to be adopted to other areas. For both levels, two approaches were made: One integrating into the model only the variables inherent to traffic and climate conditions and the other including also the factors intrinsic to the highway characteristics. The prediction accuracy of the model was improved when the variables hypsometry, geometrical features, and type of layer were considered. Therefore, accurate predictions for friction evolution throughout time are available to assist the network manager to optimize the overall level of road safety.https://www.mdpi.com/2079-6412/11/2/187frictionskid resistancepavementperformancedegradationlinear mixed models (LMMs)
collection DOAJ
language English
format Article
sources DOAJ
author Adriana Santos
Elisabete F. Freitas
Susana Faria
Joel R. M. Oliveira
Ana Maria A. C. Rocha
spellingShingle Adriana Santos
Elisabete F. Freitas
Susana Faria
Joel R. M. Oliveira
Ana Maria A. C. Rocha
Prediction of Friction Degradation in Highways with Linear Mixed Models
Coatings
friction
skid resistance
pavement
performance
degradation
linear mixed models (LMMs)
author_facet Adriana Santos
Elisabete F. Freitas
Susana Faria
Joel R. M. Oliveira
Ana Maria A. C. Rocha
author_sort Adriana Santos
title Prediction of Friction Degradation in Highways with Linear Mixed Models
title_short Prediction of Friction Degradation in Highways with Linear Mixed Models
title_full Prediction of Friction Degradation in Highways with Linear Mixed Models
title_fullStr Prediction of Friction Degradation in Highways with Linear Mixed Models
title_full_unstemmed Prediction of Friction Degradation in Highways with Linear Mixed Models
title_sort prediction of friction degradation in highways with linear mixed models
publisher MDPI AG
series Coatings
issn 2079-6412
publishDate 2021-02-01
description The development of a linear mixed model to describe the degradation of friction on flexible road pavements to be included in pavement management systems is the aim of this study. It also aims at showing that, at the network level, factors such as temperature, rainfall, hypsometry, type of layer, and geometric alignment features may influence the degradation of friction throughout time. A dataset from six districts of Portugal with 7204 sections was made available by the Ascendi Concession highway network. Linear mixed models with random effects in the intercept were developed for the two-level and three-level datasets involving time, section and district. While the three-level models are region-specific, the two-level models offer the possibility to be adopted to other areas. For both levels, two approaches were made: One integrating into the model only the variables inherent to traffic and climate conditions and the other including also the factors intrinsic to the highway characteristics. The prediction accuracy of the model was improved when the variables hypsometry, geometrical features, and type of layer were considered. Therefore, accurate predictions for friction evolution throughout time are available to assist the network manager to optimize the overall level of road safety.
topic friction
skid resistance
pavement
performance
degradation
linear mixed models (LMMs)
url https://www.mdpi.com/2079-6412/11/2/187
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