a practice-based approach to diagnose pavement roughness problems

Pavement engineers are constantly trying to develop correlations between functional and structural indicators to develop best practices for pavement evaluation and make more informative maintenance and repair (m&r) decisions. this study aims to thoroughly investigate the interaction between the international roughness index (iri), a standard index used to quantify the functional properties of a pavement, and various deflection-based parameters (dbps) used to detect changes in the structural integrity of pavement. to achieve this goal, long-term pavement performance (ltpp) data from two different pavements a and b are analyzed. the focus is to diagnose roughness problems detected on pavement surfaces by analyzing the predictability of dbps based on iri and pavement layer thickness. it is observed that two iri values are at least needed to properly reflect the pavement profile condition; a median level and an upper level corresponding to the 90th percentile of a subsection’s iri level. for pavement a, the median iri is considered a good predictor, with an r2 value of 0.71, of the surface curvature index that reflects the condition of the asphalt layers, whereas for pavement b, the upper iri is considered a good predictor, with a lower r2 value of 0.65, of the deflection index that reflects the pavement’s substructure condition (i.e., the condition at higher depths). from a practical perspective, the interaction between roughness and individual dbps can help engineers and practitioners better identify the potential origin depth of roughness problems and optimize pavement condition assessment strategy. © the author(s), under exclusive licence to the iran university of science and technology 2023.