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Degradation Prediction Model for Friction in Highways

  • Adriana Santos
  • Elisabete Freitas
  • Susana Faria
  • Joel R. M. Oliveira
  • Ana Maria A. C. Rocha
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8581)

Abstract

The purpose of this paper is to develop a multiple linear regression model that describes the pavement’s friction behaviour using a degradation evolution law that also considers the effects of weather, vertical alignment and traffic factors.

This study is based on real data obtained from two different highways with an approximate total length of 43 km. These sections present different alignment features (plan/profile), different Annual Average Daily Traffic and are subjected to different weather conditions. Nevertheless, both comprise the same type of upper layer.

The efficiency of the linear regression model in approaching and explaining data was demonstrated. The most relevant factors involved in the degradation process of pavements’ friction were identified.

Keywords

Prediction regression model friction highways 

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References

  1. 1.
    Abaza, K., Ashur, S.: Optimum decision policy for management of pavement maintenancae and rehabilitation. Transp. Res. Record. 1655, 8–15 (1999)CrossRefGoogle Scholar
  2. 2.
    Agardh, S.: Rut Depth Prediction on Flexible Pavements, Calibration and Validation of Incremental-Recursive Models. PhD Thesis, Lunds University, Sweden (2005)Google Scholar
  3. 3.
    COST Action 324: Long Term Performance of Road Pavements, Final Report of the Action. European Commission (1997)Google Scholar
  4. 4.
    Efron, B.: Estimating the Error Rate of a Prediction Rule: Improvement on Crossvalidation. J. Am. Stat. Assoc. 78, 316–331 (1983)CrossRefMathSciNetzbMATHGoogle Scholar
  5. 5.
    Faber, K., Kowalski, B.R.: Propagation of measurement errors for the validation of prediction obtained by principal component regression and partial least squares. J. Chemometr. 11, 181–238 (1997)CrossRefGoogle Scholar
  6. 6.
    Freitas, E.: Contribuição para o desenvolvimento de modelos de comportamentos dos pavimentos rodoviários flexíveis – fendilhamento com origem na superfície. PhD Thesis, Universidade do Minho, Portugal (2004) (in Portuguese)Google Scholar
  7. 7.
    Falcão, D.: Conjuntos, Lógica e Sistemas Fuzzy, Technicalreport, Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia, COPPE/UFRJ, Brazil (2002) (in Portuguese)Google Scholar
  8. 8.
    Huamaní, I.: Sistemas Neurais Fuzzy Aplicados em Identificação e Controle de Sistemas, MScThesis, Faculdade de Engenharia Elétrica e de Computação, Universidade Estadual de Campinas (2003) (in Portuguese)Google Scholar
  9. 9.
    Miller, A.J.: Selection of subsets of regression variables (with discussion). J. R. Stat. Soc. 147(A), 389–425 (1984)zbMATHGoogle Scholar
  10. 10.
    Lorino, T., Lepert, P., Marion, J., Khraibani, H.: Modeling the road degradation processs: non-linear mixed effects models for correlation and heteroscedasticity of pavement longitunal data. Procedia Soc. Behav. Sci. 48, 21–29 (2012)CrossRefGoogle Scholar
  11. 11.
    Pereira, P., Picado-Santos, L.: Pavimentos rodoviários, Barbosa & Xavier, Braga, Portugal (2002) (in Portuguese)Google Scholar
  12. 12.
    R Development Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2014)Google Scholar
  13. 13.
    Sinhal, R.: The Implementation of a Skid Policy to Provide the Required Friction Demand on the Main Road Network in the United Kingdom. Highways Agency, UK (2004)Google Scholar
  14. 14.
    Yuan, X., Pandey, M.: A nonlinear mixed-effects model for degradation data obtained from in-service inspections. Reliab. Eng. Syst. Safe. 94, 509–519 (2009)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Adriana Santos
    • 1
  • Elisabete Freitas
    • 1
  • Susana Faria
    • 2
  • Joel R. M. Oliveira
    • 1
  • Ana Maria A. C. Rocha
    • 3
  1. 1.Department of Civil Engineering, C-TAC – Territory, Environment and Construction CentreUniversity of MinhoPortugal
  2. 2.Department of Mathematics and Applications, CMAT-Centre of MathematicsUniversity of MinhoGuimarãesPortugal
  3. 3.Department of Production and Systems, Algoritmi Research CentreUniversity of MinhoPortugal

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