Roads Performance Modeling and Management System from Two Condition Data Points: Case Study of Costa Rica

Abstract

Initial implementation of a road management system will typically face the challenge of a lack of time-series data for performance modeling. This paper presents one approach for developing initial performance prediction models that are required to support trade-off and optimization analyses in a road management system. The paper demonstrates that starting performance models can be formulated based on as little as 2 years' network-level data on condition and traffic. The paper builds a locally calibrated pavement condition index and subsequently uses it for network-level strategic planning and programming of works. The paper demonstrates a method of extracting initial estimates of treatments' effectiveness from the condition data. The case study is based on the Costa Rican national road network. The model uses commercial software to allocate resources and optimize decisions. Several investment strategies were tested to investigate the sustainability of the road network value over time. The results demonstrate that optimization improves road conditions in a sustainable manner, which in the long run releases funds for other necessities.