Description

This research document focuses on the field calibration of HDM-4 bituminous pavement deterioration models tailored to Indian climatic and traffic conditions. Default HDM-4 deterioration relationships often fail to accurately capture pavement behavior in tropical, high-humidity, and heavy axle load environments typical of Indian highways. The study utilized long-term pavement performance (LTPP) data gathered from designated monitoring sections across different agro-climatic zones over multiple years. The researchers systematically calibrated the calibration coefficients (K-factors) for key distress modes: initiation and progression of structural cracking (Kcia, Kcpa), rutting development (Krid, Krip), raveling (Krav), and roughness progression (Kgm). Field observations revealed that high pavement temperatures combined with widespread overloaded commercial vehicles accelerate rutting progression and cracking initiation compared to standard European or North American baseline defaults. The recalibrated K-factors significantly improved the correlation between predicted deterioration curves and actual field measurements. The paper demonstrates how implementing these locally calibrated parameters in HDM-4 economic analyses prevents premature rehabilitation failures, optimizes life-cycle maintenance strategies, and yields more accurate net present value (NPV) estimates for highway investment decisions.