Roads and Bridges - Drogi i Mosty
19, 3, 2020, 225-242

Prediction of the road pavement condition index using stochastic models

Angelika G. Batrakova Mail
Kharkiv National Automobile and Highway University, Road-Construction Faculty, Department of Highway Design, Geodesy and Land Management, 25 Yaroslava Mudroho St., Kharkiv, Ukraine, 61002
Vladimir V. Troyanovsky Mail
Kharkiv National Automobile and Highway University, Road-Construction Faculty, Department of Highway Design, Geodesy and Land Management, 25 Yaroslava Mudroho St., Kharkiv, Ukraine, 61002
Dmitry O. Batrakov Mail
V. Karazin National University, Radiophysics Biomedical Electronics and Computer Systems Faculty, Department of Theoretical Radiophysics, 4 Svobody Sq., Kharkiv, Ukraine, 61022
Maryna O. Pilicheva Mail
O.M. Beketov National University of Urban Economy in Kharkiv, Department of Land Administration and Geoinformation Systems, 17 Marshal Bazhanov St., Kharkiv, Ukraine, 61002
Nataliia S. Skrypnyk Mail
Kharkiv National Automobile and Highway University, Department of Foreign Languages, 25 Yaroslava Mudroho St., Kharkiv, Ukraine, 61002
Published: 2020-09-30

Abstract

Mathematical models for prediction of road network condition based on the so-called Markov chains are presented in this article. The data for calculation of elements of the transition matrix from one condition to another are taken from visual evaluation as well as from instrumental reading. It is recommended to prepare data sets in the form of pavement management system data tables based on a representative sample of measuring sections. Discrete time intervals – of one year – are used when constructing the model of transition matrices. The procedure of forming Markov transition matrix with partially complete data sets is proposed also in paper. The basis of this procedure is information on the previous condition of the structure and the results of the instrumental evaluation, which enables correction of the predicted values. The final matrix takes into account not only the probability, but also the speed of transition from one condition to another. It is also possible to work with the initial data using appropriate databases or other software.

Keywords


Markov chains, pavement condition index, stochastic models.

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References


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Prediction of the road pavement condition index using stochastic models

  
Batrakova, Angelika G. et al. Prediction of the road pavement condition index using stochastic models. Roads and Bridges - Drogi i Mosty, [S.l.], v. 19, n. 3, p. 225-242, sep. 2020. ISSN 2449-769X. Available at: <>. Date accessed: 22 Oct. 2020. doi:http://dx.doi.org/10.7409/rabdim.020.015.