Sensitivity of Design Parameters on Optimal Pavement Maintenance Decisions at the Project Level

Abstract

Sensitivity analyses are important parts of both studying complex systems and measuring the variation in input parameters on the response. They are useful to decision makers for understanding the robustness of the optimal solution that they are to adapt to variations of the parameters of the problem. The sensitivity of the optimal solution of a project-level pavement management problem is analyzed, and the robustness of the optimal solution to the interventions and the timing, cost, and benefit are investigated. The input parameters, which affect the optimal maintenance solution, are identified as the structural and functional condition parameters (defined in terms of deflection and roughness, respectively, at the beginning of the analysis period), traffic volume, growth rate, and discount rate. The problem of computing the optimal treatment and timing for a given budget level is modeled as a mixed integer nonlinear optimization problem and solved by using a computationally efficient network-optimization technique. The benefits are evaluated by considering the pavement performance and are quantified as the area between the performance curve and the threshold values. The optimal budget required for pavements in different structural and functional conditions as well as traffic levels is presented. The effect of initial pavement condition on the optimal maintenance actions as well as their timings is studied. The result of the sensitivity analysis showed that the cumulative standard axle loads and traffic growth rate have a significant effect on the selection and timing of rehabilitation and preventive maintenance actions. The effect of the discount rate on the maintenance management decisions is also presented.

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