The article provides a comparative analysis of the approaches to forecasting rutting used in Russia and the USA. Mechanistic–Empirical Pavement Design Guide (MEPDG) and domestic regulatory documents are reviewed, and their key differences in forecast accuracy, applicability, and calculation complexity are identified.

Keywords: rutting, forecasting of road structures, MEPDG, monitoring of road conditions, regulatory methodologies

The application of a mechanical-empirical method of designing road pavement for predicting track formation on the surface of road structures is discussed in the article . The occurrence of ruts is one of the most common types of defects in road surfaces, significantly reducing safety and comfort of movement. MEPDG calculation models were used in this work for assessing the stability of a road structure to the accumulation of plastic deformations. Models takes into account factors such as the intensity and axial load of transport, climatic conditions, and the physic and mechanical properties of coating materials. An example of predicting the depth of a track using the considered method is given.

Keywords: rutting, mechanical and empirical method, road pavement, forecasting, MEPDG, traffic loads, climatic conditions

The stage of operation of a highway is one of the most important stages of its life cycle. The decisions made at this stage have a direct impact on the durability of the road, the safety and transport costs of its users. Optimization of the decisions made is an urgent task that requires a comprehensive consideration of both the technical and economic components. Within the framework of this work, using the algorithms of artificial neural networks (ANN), a mathematical model of the ANN was developed to determine the integral level of pavement safety, based on a complex of structural and operational factors, including the modulus of elasticity of pavement layers, longitudinal evenness, rutting, and the presence of fatigue failures. On the basis of the integral level of pavement safety, its operational condition is predicted, a scale is assigned for the selection of control actions to ensure its required durability.

Keywords: artificial neural networks, integral safety level, falling weight deflectometer, road maintenance, road life cycle management

The possibility of using artificial neural networks to assess the current characteristics of pavements and their potential application in the development of road maintenance strategies is considered. The results of the models showed the convergence between the estimated values ​​of the pavement condition and the actual values ​​at all stages of training. The results show that public road authorities can use the developed models to determine the optimal approach to road maintenance and determine the most effective measures to restore their capacity and operational condition.

Keywords: artificial neural networks, backpropagation algorithm, falling weight deflectometer, pavement maintenance, pavement management system

In the current socio-economic reality, the main task of design, road organizations is the high-quality reproduction of road structures, the development of the road network, and also to maintain the transport-operational condition of the highway. In this paper, examples and models are provided that allow an estimation of the probability of destruction of individual sections of a road structure, as well as the dependence of the reliability of a road structure on the actual coefficient.

Keywords: road wear, service life, defect, crack, analysis, actual condition, deflection, coefficient of strength, deformation

The paper deals with the use of Markov chains apparatus in problems of forecasting the operational status of non-rigid pavements maintained roads in the network layer. An example of predicting the deterioration of structural indicators for the non-rigid pavement of the existing road section.

Keywords: roads, pavement, forecasting, Markov chain