ABSTRACT
Condition prediction and LCC-models are utilized in every AM or PMS allowing a comparison and optimization of treatments and investment strategies. Based on described in previous papers innovative deterministic and stochastic condition prediction and LCC-models, the focus of this paper is on the methodical aspects and on the application for selection and optimization of treatment alternatives for road pavements. Starting with data from the initial short survey sections the presented deterministic LCC-model allows a distress-specific optimization of treatment alternatives, determination of timing of treatments and length of work zones. Furthermore, this model can be extended to a full stochastic approach for any complex system incorporating risks of failure, user costs and external costs alike. Based on a practical example for multiple types of distress and treatment options we address the flaws of the common practices and demonstrate why the typical cost-benefit approach based on total condition indices fall short compared to our method regarding life cycle costs.
