ABSTRACT
Assessing pavement structural conditions is crucial for effective maintenance management. Road agencies require consistent and reliable threshold criteria to evaluate these conditions. This study aims to define threshold values for structural indices derived from the Falling Weight Deflectometer (FWD) data. A stochastic approach, using the Bayesian Markov hazard (BMH) model, is employed to predict surface roughness deterioration by incorporating structural indices. The structural indices of interest include maximum deflection, effective structural number, subgrade resilient modulus, and deflection bowl parameters. The analysis is based on two sets of roughness inspection data from flexible pavements, specifically asphalt concrete (AC) and double bituminous surface treatment (DBST) pavements. Critical thresholds for structural indices are determined, and the threshold criteria can be benchmarked based on the probability of failure. By adopting uniform standards for interpreting FWD data, road agencies can effectively evaluate pavement structural conditions, identify pavement structure problems, and better manage maintenance activities.
