Assessment of the Condition of the Flexible Pavement of Brack Alshatti Airport Road Using the Paver System

Abstract

This study aims to facilitate the decision-making process for managing a section of the road network in Brack. Recent advances in Web GIS technologies have enabled road authorities to adopt cost-effective solutions for efficient road network management. This study aims to evaluate the flexible pavement condition of a selected road network using the PAVER pavement management system based on the Pavement Condition Index (PCI). The goal is to provide an accurate database to support preventive and structural maintenance decisions. PAVER is one of the most widely used systems for pavement evaluation, offering a standardized methodology based on ASTM D6433 for identifying pavement defects, determining the severity and extent of each defect, and then calculating the PCI value for each section. In this study, the road network was divided into homogeneous evaluation sections. A visual field survey was then conducted to identify the most common surface defects, such as block cracking, longitudinal and transverse cracks, patching, potholes, and raveling. The data was then entered into the PAVER software to determine the PCI value for each section. The results showed that the AT-A section index was 53, the AT-B section index was 84, the AT-C section index was 93, the BA-A section index was 54, and the BA-B section index was 59. The analysis revealed a clear relationship between the road's operational lifespan and the deterioration of the PCI value, in addition to the impact of excessive axle loads and insufficient periodic maintenance. The study also proposed an optimal Maintenance and Repair Plan (M&R Plan) based on treatment priorities and maintenance costs, including: preventive maintenance for good sections, intermediate repairs for deteriorated sections, and rehabilitation for sections classified as "very poor." The study confirms that using the PAVER system provides a precise scientific method for pavement management and identifying actual maintenance needs, contributing to reduced maintenance costs and improved road service levels. The study recommends the periodic updating of network data and the implementation of automated surveying techniques to enhance future assessment accuracy.