Description

This technical study presents a comprehensive sensitivity analysis of the HDM-4 (Highway Development and Management) pavement deterioration models applied to the state road network of Slovenia. HDM-4 utilizes complex mathematical relationships to predict structural and functional pavement degradation over time, including cracking progression, raveling, rutting, potholing, and roughness progression. However, the accuracy of these predictions depends heavily on input parameters describing pavement structure, subgrade strength, climate, maintenance history, and traffic loading. The authors conducted a systematic sensitivity analysis by varying key calibration parameters—such as the structural number (SNP), adjusted structural number, climate moisture index, traffic growth rates, and material strength factors—across typical Slovenian flexible and semi-rigid pavement structures. Using long-term field condition data from Slovenia's Pavement Management System, the study identifies which input parameters exert the strongest influence on long-term pavement life predictions and lifecycle costing results. Findings indicate that initial pavement roughness (IRI0), subgrade strength, and environmental moisture factors have the highest sensitivity, while cracking initiation factors show moderate sensitivity depending on surface dressing types. The paper provides calibration guidelines and recommended sensitivity thresholds, enabling road asset managers to prioritize field data collection efforts on high-impact parameters to maximize the reliability of network-level investment planning.