Roads and Bridges - Drogi i Mosty
17, 1, 2018, 55-71

Pavement deterioration model based on GPR datasets

Angelika G. Batrakova Mail
Kharkiv National Automobile and Highway University, Road Construction Faculty, Chair of road survey and design, 25 Yaroslav Mudriy Str., Kharkiv, Ukraine, 61002
Dmitry O. Batrakov Mail
V.N. Karazin Kharkiv National University, Radiophysics Biomedical Electronics and Computer Systems Faculty, Chair of Theoretical Radiophysics, 4 Svobody Sq., Kharkiv, Ukraine, 61022
Mariya S. Antyufeyeva Mail
V.N. Karazin Kharkiv National University, Radiophysics Biomedical Electronics and Computer Systems Faculty, Chair of Theoretical Radiophysics, 4 Svobody Sq., Kharkiv, Ukraine, 61022
Published: 2018-03-30

Abstract

The paper deals with monitoring the current condition of flexible road pavement involving GPR technology. The methodology of using GPR is formed on remote measurements of thickness and permeability of pavement structural layers. After primary processing of GPR data they are interpreted by means of the developed algorithms and software. Then these data are used to build models of road section deterioration. Dynamic adaptive models are proposed in order to solve the problem of predicting the condition of individual local pavement segments. The mathematical apparatus of dynamic adaptive model of pavement deterioration was based not only on accounting the values of the explanatory variables at fixed times, but also on the rate and character of change of these variables. A comparative analysis carried out and the performance of the proposed models on the example of road sections of the Kharkiv region of Ukraine is shown.

Keywords


dynamic adaptive model, flexible road pavements, GPR pavement testing method, pavement condition index

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References


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Pavement deterioration model based on GPR datasets

  
Batrakova, Angelika G.; Batrakov, Dmitry O.; Antyufeyeva, Mariya S.. Pavement deterioration model based on GPR datasets. Roads and Bridges - Drogi i Mosty, [S.l.], v. 17, n. 1, p. 55-71, mar. 2018. ISSN 2449-769X. Available at: <>. Date accessed: 18 Aug. 2018. doi:http://dx.doi.org/10.7409/rabdim.018.004.