Model for the Evaluation of Road Economic Costs in Long-Term Program Considering Traffic and Pavement Performance Parameters Using HDM-4

This study presents a methodological approach for evaluating long-term road economic costs by integrating the Highway Development and Management Model (HDM-4) with the statistical technique of Design of Experiments (DOE). A 25-year road program was simulated through pavement life cycles, where traffic and pavement states were parameterized into experimental cells. The DOE Composite Central Design (CCD) was applied to generate response variables representing annual economic costs borne by the state (RAC) and users (RUC). Multiple linear regression models and sensitivity analysis were employed to approximate and validate the simulation results. The findings reveal that traffic volume (AADT) and the International Roughness Index (IRI) are the most influential performance parameters affecting cost variations. Polynomial models with linear, quadratic, and interaction effects were obtained, enabling the quantification of relationships between pavement deterioration and economic costs. Results demonstrate that preventive maintenance strategies significantly reduce user costs while increasing state expenditures, highlighting the trade-off between RAC and RUC. The proposed framework provides a robust tool for strategic highway planning and rational decision-making in infrastructure management under resource constraints.