Abstract
Effective road maintenance is critical for ensuring safety, efficiency, and convenience in transportation networks. However, conventional assessment methods, often relying on isolated metrics or visual inspections, fail to capture the complex interplay of pavement condition factors, leading to potential misallocation of maintenance efforts. This study proposes a two-stage framework to enhance road condition assessment and maintenance prioritization by integrating individual performance indices with a unified pavement assessment metric (UPAM) developed through the fuzzy analytic hierarchy process. In the first stage, road segments are pre-screened based on individual indices—the structural condition index, international roughness index, international friction index, and pavement condition index—to identify localized deficiencies. Segments are classified as high or low priority based on threshold performance. In the second stage, segments are systematically ranked within each group using UPAM scores. While individual indices offer detailed diagnostic insights, they lack consistency for ranking; conversely, the UPAM provides standardized prioritization but may obscure critical localized issues. The combined approach improves transparency, reliability, and decision-making effectiveness, offering a comprehensive tool for optimizing pavement maintenance strategies.
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