Presentation Date: Feb 14, 2026
AGSA Abstract
Microsurfacing is a widely used pavement preservation treatment known for its cost-effectiveness and ability to restore surface condition and extend pavement life. However, current trigger values used to determine optimal microsurfacing timing in Louisiana are largely experience-based and lack systematic validation. This study conducted a comprehensive, PMS (Pavement Management System) data-driven evaluation and adjustment of microsurfacing trigger conditions for flexible pavements in Louisiana regarding Alligator Cracking, Random Cracking, Rutting, and Roughness. Post-treatment pavement performance was modeled using quadratic deterioration curves, and treatment effectiveness was assessed using treatment life, survival probability, and benefit–cost ratio (BCR) analyses. The results revealed significant variability in post-treatment performance among pavement sections, even within a single project, highlighting the role of site-specific factors. While treatment life and survival probability increased with better pre-treatment conditions, these metrics alone were insufficient for determining optimal treatment timing. Instead, BCR analysis proved more effective, identifying optimal trigger ranges for the four indices. Sensitivity analysis confirmed that assumed pre-treatment curves could be reliably used in the absence of historical data when focusing on relative BCR trends. Recommended trigger ranges were then developed by integrating BCR findings with engineering judgment, resulting in revised lower thresholds while retaining upper limits consistent with current practice. This study provides a replicable framework for data-driven optimization of microsurfacing strategies, offering a more efficient basis for treatment selection and preservation fund allocation.
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