Incorporating cost uncertainty and path dependence into treatment selection for pavement networks

Abstract

This paper proposes a new probabilistic treatment path dependence (PTPD) model for budget allocation within pavement network management problems. During the evaluation of treatment alternatives for a segment in a pavement network, the model considers benefits of both the evaluated treatment and its following actions. It also incorporates the influence of treatment cost and deterioration uncertainties. Treatments are selected for each segment in the pavement network using a risk-based optimization model. Three case studies are presented to illustrate the application and benefits of this new model. Results of the first two cases show that the risk-aversion coefficient in the model influences segment-level treatment selections and pavement network performance. The third case shows that the PTPD model performs better than a benefit-cost ratio model due to the incorporation of uncertainties and treatment path dependence. To obtain a similar performance level, the conventional model requires a 10.4% higher annual budget for the given case study. The results presented here suggest that elements of this model – notably consideration of uncertainty in deterioration and cost, treatment path dependency, and explicit risk trade-offs – could be incorporated into asset management tools to improve the cost-effectiveness of pavement network planning.