2025 Volume 6 Issue 3 Pages 32-46
Pavement structural condition assessment is crucial for effective maintenance management, including quality control and maintenance planning. To support consistent evaluation, road agencies require reliable threshold criteria. Unlike traditional methods that primarily rely on numerical analysis and distress severity correlations, this study defines threshold values for structural indices derived from the Falling Weight Deflectometer (FWD) data using a deterioration modeling approach. A stochastic framework based on the Markov hazard model is employed to predict surface roughness deterioration by incorporating structural indices. This approach accounts for uncertainty and variability in pavement performance, accommodating diverse pavement characteristics and influencing factors. The key structural indices include maximum deflection, effective structural number, subgrade resilient modulus, and deflection bowl parameters (base layer index, middle layer index, and lower layer index). The analysis uses two sets of roughness inspection data from flexible pavements, specifically asphalt concrete (AC) and double bituminous surface treatment (DBST) pavements, linked to structural indices obtained from FWD measurements. Structural thresholds are determined at set failure probabilities, based on estimated deterioration rates and pavement lifespans. The benchmark criteria are categorized into three levels: Sound (0-50% failure probability), Warning (50-75%), and Severe (75-100%) for each pavement type. The findings indicate that AC pavements require more stringent thresholds than DBST pavements due to their higher structural standards and longer design life. By adopting uniform standards for interpreting FWD data, road agencies can more effectively evaluate pavement structural conditions, identify structural deficiencies, and optimize maintenance strategies to ensure compliance with performance standards without relying on mathematical models that require advanced technical knowledge.
