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Received 01.10.2024

Revised 28.02.2025

Accepted 29.03.2025

Retrieved from Iss. 117, P. 1, 2025

Pages 94 -99

  • 195 Views

Suggested citation

Sokolova, N., & Koncha, P. (2025). MATHEMATICAL MODELS AND ALGORITHMS FOR ROAD ASSESSMENT. Automobile Roads and Road Construction, (117.1), 94-99. https://doi.org/10.33744/0365-8171-2025-117.1-094-099

MATHEMATICAL MODELS AND ALGORITHMS FOR ROAD ASSESSMENT

Natalia Sokolova Pavlo Koncha

Abstract

The purpose of this article is to identify the main methods for assessing road conditions and justify their effectiveness in ensuring traffic safety and the durability of road infrastructure. Road conditions are a key indicator of the quality of transport infrastructure, affecting road safety, the economic efficiency of transport and the comfort of road users. The paper considers methods for assessing roads aimed at identifying pavement defects, determining the strength of the road surface, assessing skid resistance, pavement evenness and lighting characteristics. Attention is paid to the analysis of visual inspections, video diagnostics and automated systems that ensure the speed and accuracy of data collection. The use of static and dynamic methods for assessing the strength of the road surface allows for the simulation of real operating conditions and the prediction of pavement durability. The assessment of the grip properties of the pavement is carried out using specialised vehicles and portable devices, which ensures road safety even under adverse conditions. Analysis of road surface evenness using a three-metre straightedge, levellers and shock meters provides data that affects the comfort of drivers and passengers and reduces vehicle wear. The International Roughness Index (IRI) is used as a unified indicator for comparing roads in different countries. Lighting characteristics of road infrastructure, such as light return and brightness coefficients. Analysis of road surface evenness using a three-metre straightedge, levellers and shock meters provides data that affects driver and passenger comfort and reduces vehicle wear and tear. The International Roughness Index (IRI) is used as a standardised indicator for comparing roads in different countries. The lighting characteristics of road infrastructure, such as the light return coefficient and brightness of road signs and markings, are crucial for ensuring visibility in poor lighting conditions. Their compliance with modern standards is critical for reducing accidents. The results of the study highlight the need to integrate innovative technologies into the road condition monitoring process. In particular, automated video diagnostic systems and the use of international standards can improve the efficiency of road network management. The article focuses on the importance of systematic monitoring and prioritisation of repair work based on comprehensive analysis. Prospects for further research are related to the improvement of road surface assessment technologies, in particular, in the direction of developing mobile monitoring systems and analysing the relationships between road condition parameters and traffic characteristics

Keywords:

assessment of roads, pavement defects, road surface strength, grip properties, road evenness, lighting characteristics

References

  1. Smolyanyuk, R.V., & Smolyanyuk, N.V. (2023). Automation of the road marking detection process. SWorldJournal, 18, 155-162.
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  3. Rybytskyi, L., & Pavliuk, D. (2021). Improvement of methods and means for assessing the grip qualities of road surfaces in Ukraine. European Journal of Intelligent Transportation Systems, 1, 1-7.
  4. Law of Ukraine No. 1314-VII "On metrology and metrological activity". (2014). Retrieved from https://zakon.rada.gov.ua/laws/show/1314-18.
  5. Sarkisyan, G.S., Tymoshevskyi, V.V., & Urdzyk, S.M. (2021). Metrological support of geodetic works in determining road pavement evenness. Municipal Economy of Cities, 166, 130-133.
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https://doi.org/10.33744/0365-8171-2025-117.1-094-099

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