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

This study proposes a methodological framework to evaluate long-term road economic costs by integrating the Highway Development and Management Model (HDM-4) with Design of Experiments (DOE). A 25-year road program is simulated through pavement life cycles, where traffic and pavement condition variables are organized into experimental cells. A Central Composite Design (CCD) is used to generate response variables for annual economic costs borne by the state (RAC) and by road users (RUC). Multiple linear regression and sensitivity analyses are applied to approximate, interpret, and validate the HDM-4 simulation outputs. The results show that traffic volume (AADT) and the International Roughness Index (IRI) are the most influential parameters affecting economic cost variability. Polynomial models with linear, quadratic, and interaction terms quantify the relationships between pavement deterioration and both state and user costs. The analyses indicate that preventive maintenance strategies significantly reduce user costs while increasing state expenditures, revealing a trade-off between RAC and RUC. The proposed approach offers a robust decision-support tool for strategic highway planning and infrastructure management under budget constraints.