Enhancing life cycle cost analysis with a novel cost classification framework for pavement rehabilitation projects

Abstract

Life cycle cost analysis (LCCA) procedures have been used over the past decades to justify the choice of one pavement design alternative over the others. However, many ambiguities associated with the life cycle cost input values, such as the discount rate and future cost estimates have questioned the credibility of the analysis results. Another unrecognized source of errors in pavement LCCA is the misunderstanding of pavement treatment costs when historical costs are typically used for estimating those costs. The historical costs of pavement rehabilitation projects typically include a significant amount of non-pavement-related costs, which may result in a wrong LCCA if not treated appropriately. This paper addresses this specific point of error and proposes a solution to eliminating this error by using a novel cost classification framework that successfully differentiates mainline roadway costs from non-pavement cost items. A case study using Monte Carlo simulation is conducted to evaluate the probabilistic LCCA results. The results of the case study indicate that the conventional approach of using total rehabilitation project costs in LCCA may even lead to a wrong investment decision. The findings of this study will help practitioners and researchers better understand the nature of pavement rehabilitation project cost distributions.

Keywords:

• Asset management
• highway infrastructure
• Monte Carlo simulation
• pavement maintenance and rehabilitation
• stochastic life cycle cost analysis

Acknowledgements

The authors would like to gratefully appreciate the funding support from IHRB.