Comprehensive assessment of road pavement performance using modern diagnostic technologies: insights from Uzbekistan’s evolving infrastructure

Authors

  • Inomjon Ganiev
  • Rustam Yuzboev
  • Zulfiya Ganieva

Keywords:

Pavement performance, road diagnostics, structural integrity, International Roughness Index (IRI), Pavement Condition Index (PCI), Falling Weight ISSN 2181-0842 / Impact Factor 4.526 71These interventions aim to improve load distribution and prevent recurrence of deep-seated failures. The combination of advanced diagnostics and context-sensitive rehabilitation planning enables a shift from reactive maintenance to a predictive, performance-based approach, ultimately contributing to cost-effective asset management and improved road user experience. 4. Conclusion This study highlights the critical value of employing modern, data-driven diagnostic technologies in assessing the technical condition and operational quality of highway pavements. By integrating surface condition metrics such as the International Roughness Index (IRI), visual distress evaluation through the Pavement Condition Index (PCI), and structural analysis using the Falling Weight Deflectometer (FWD), the research demonstrates a comprehensive approach to pavement performance assessment. The findings confirm that these tools not only enhance the accuracy and objectivity of condition evaluations but also provide essential input for prioritized, cost-effective maintenance and rehabilitation planning. For countries like Uzbekistan, where diverse climatic conditions and increasing traffic volumes exert significant pressure on road infrastructure, the adoption of such advanced assessment methodologies is both timely and necessary. Institutionalizing these practices within national and regional road management agencies will contribute to enhanced road safety, improved user comfort, prolonged service life, and more sustainable use of public resources. Looking ahead, future research and policy development should focus on the integration of diagnostic data with Geographic Information System (GIS)-based asset management platforms, enabling spatial visualization and long-term tracking of pavement performance. Additionally, leveraging artificial intelligence (AI) and machine learning algorithms for predictive maintenance modeling can further optimize resource allocation and improve the resilience of the national road network in the face of environmental and economic challenges.

Abstract

Ensuring the long-term durability and operational efficiency of highway pavements remains a fundamental challenge for developing nations such as Uzbekistan, where diverse climatic conditions, combined with intensifying vehicular traffic and inadequate historical maintenance practices, significantly accelerate the rate of pavement degradation. This research presents a comprehensive and systematic methodology for assessing the technical condition and service performance of road pavements through the application of advanced diagnostic tools and internationally recognized performance evaluation standards. Central to the study is the integration of key performance indicators, including the International Roughness Index (IRI), the Pavement Condition Index (PCI), and structural capacity assessments conducted using the Falling Weight Deflectometer (FWD). These indicators provide a quantitative framework for evaluating surface roughness, visual distress, and structural integrity, respectively. The study encompasses both field data collection and analytical evaluation across representative pavement sections in Uzbekistan, capturing the effects of environmental stresses, traffic loads, and construction quality. Through the synthesis of diagnostic data, the research identifies the most critical factors contributing to pavement deterioration, such as thermal cracking, rutting, moisture infiltration, and subgrade instability. Based on these findings, the study proposes a set of optimized, context-specific maintenance and rehabilitation strategies aimed at extending pavement life, reducing lifecycle costs, and improving road safety and user comfort. The results of this investigation contribute valuable insights for transportation agencies, infrastructure planners, and policy-makers, offering a data-driven foundation for prioritizing investments and enhancing the resilience and sustainability of national road infrastructure. Moreover, the study advocates for the widespread adoption of modern pavement evaluation technologies and performance-based maintenance planning as essential components of a forward-looking, cost-effective asset management system in Uzbekistan and similar emerging economies.

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Published

2025-07-25

How to Cite

Inomjon Ganiev, Rustam Yuzboev, & Zulfiya Ganieva. (2025). Comprehensive assessment of road pavement performance using modern diagnostic technologies: insights from Uzbekistan’s evolving infrastructure . Science and Education, 6(7), 71–77. Retrieved from https://openscience.uz/index.php/sciedu/article/view/7906

Issue

Section

Technical Sciences