Economic Risk Evaluation in Road Pavement Management

Abstract

Pavement maintenance is essential to prevent the deterioration of asset value and satisfy all stakeholders’ expectations. However, the budgets are often insufficient to keep the road pavement at optimum levels. Therefore, a decision-making process ought to be used to prioritize different maintenance activities to optimize the fulfillment of the pre-defined goals. At the same time, there is a growing need to integrate risk management into asset management, and therefore into the Pavement Management System. It is the best way to understand risk in decision-making at the program and organizational levels. This paper examines how risk-based pavement management practices can be implemented. The idea is to identify the best combination of maintenance actions given budget constraints, also considering budget risk reduction within a multiobjective optimization process. As far as economic risk assessment is concerned, probabilistic LCCA with Monte Carlo Simulation was used to investigate the risk of budget exceeding in Pavement Management Systems as a secondary criterion for choosing the optimal maintenance strategy on a road network. The method allows assessing epistemic uncertainties regarding discount rate and materials, man-power, transportation, and equipment rental costs. Outputs were able to show the possible variability of maintenance strategies costs. Moreover, probability density functions provide for establishing the most economically advantageous solutions (lower mean value) and for the riskiest ones (greater standard deviation). The optimal strategy might be selected by minimizing the probability of budget exceeding. The innovation of this research is in the introduction of the quantitative economic risk analyses into pavement management, with the aim to integrate epistemic and aleatory uncertainties in the process.