MATHEMATICAL MODELS AND ALGORITHMS FOR ROAD ASSESSMENT

Abstract. The purpose of the article is to determine the main methods of assessing the condition of roads and to substantiate their effectiveness in ensuring traffic safety and durability of road infrastructure. The condition of roads is a key indicator of the quality of transport infrastructure, which affects road safety, economic efficiency of transportation and comfort of road users. The work considers methods of assessing roads aimed at detecting coating defects, determining the strength of road surfaces, assessing adhesion qualities, evenness of the surface and lighting characteristics. Attention is paid to the analysis of visual inspections, video diagnostics and automated systems that ensure the efficiency and accuracy of data acquisition. The use of static and dynamic methods of assessing the strength of road surfaces allows you to model real operating conditions and predict the durability of the surface. The assessment of the adhesion qualities of the surface is carried out using specialized vehicles and portable devices, which allows you to ensure road safety even under adverse conditions. Analysis of road surface evenness using a three-meter rail, levels and push gauges allows you to obtain data that affects the comfort of drivers and passengers, as well as reduces vehicle wear. The International Road Evenness Index (IRI) is used as a unified indicator for comparing roads in different countries. The lighting characteristics of road infrastructure, such as the light reflection coefficient and brightness of road signs and markings, are crucial for ensuring visibility in poor lighting conditions. Their compliance with modern standards is critically important for reducing accidents.

Authors

Publication Details

Journal
Automobile Roads and Road Construction
Published
2025-01-01
DOI
https://doi.org/10.33744/0365-8171-2025-117.1-094-099
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
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article

MATHEMATICAL MODELS AND ALGORITHMS FOR ROAD ASSESSMENT

Natalia Sokolova, Pavlo Koncha
Automobile Roads and Road Construction
Traffic Prediction and Management Techniques
article

MATHEMATICAL MODELS AND ALGORITHMS FOR ROAD ASSESSMENT

Natalia Sokolova, Pavlo Koncha
article en

Abstract

Abstract. The purpose of the article is to determine the main methods of assessing the condition of roads and to substantiate their effectiveness in ensuring traffic safety and durability of road infrastructure. The condition of roads is a key indicator of the quality of transport infrastructure, which affects road safety, economic efficiency of transportation and comfort of road users. The work considers methods of assessing roads aimed at detecting coating defects, determining the strength of road surfaces, assessing adhesion qualities, evenness of the surface and lighting characteristics. Attention is paid to the analysis of visual inspections, video diagnostics and automated systems that ensure the efficiency and accuracy of data acquisition. The use of static and dynamic methods of assessing the strength of road surfaces allows you to model real operating conditions and predict the durability of the surface. The assessment of the adhesion qualities of the surface is carried out using specialized vehicles and portable devices, which allows you to ensure road safety even under adverse conditions. Analysis of road surface evenness using a three-meter rail, levels and push gauges allows you to obtain data that affects the comfort of drivers and passengers, as well as reduces vehicle wear. The International Road Evenness Index (IRI) is used as a unified indicator for comparing roads in different countries. The lighting characteristics of road infrastructure, such as the light reflection coefficient and brightness of road signs and markings, are crucial for ensuring visibility in poor lighting conditions. Their compliance with modern standards is critically important for reducing accidents.

Automobile Roads and Road Construction(117.1)
Openalex Percentile: Top 84%
Traffic Prediction and Management Techniques
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