<![CDATA[Effective expressway maintenance is crucial for enhancing safety and optimizing resource utilization. The interplay of safety risks, pavement deterioration, and constrained budgets underscores the necessity for a robust decision-making framework. This study introduces an integrated approach combining a data-driven scoring method, an Analytic Hierarchy Process (AHP), and a rule-based strategy to prioritize maintenance activities systematically. The scoring method evaluates critical factors, including Pavement Condition Rating (PCR), Accident Density (AD), Weighted Accident Severity Index (WASI), critical horizontal curves, projected traffic volumes, village access points, and annual rainfall. A rule-based strategy identifies high-priority segments using cumulative ratings derived from the Pavement Condition Index (PCI), International Roughness Index (IRI), Present Serviceability Index (PSI), and Present Serviceability Rating (PSR). AHP further refines prioritization by assigning weights to pavement distress types based on regression analyses. When applied to eight expressway sections, the framework identified Yangon-Phyu and Phyu-Naypyitaw as critical due to elevated safety risks and significant pavement deterioration. The most deteriorated units received top priority among the 130 pavement sample units analyzed. This research underscores the importance of data-driven maintenance strategies to prolong pavement lifespan, reduce accident rates, and enhance operational efficiency, providing actionable insights for engineers and policymakers engaged in sustainable expressway infrastructure management.]]>
