ABSTRACT
In every advanced PMS condition prediction and life cycle cost models are utilized allowing a comparison of different maintenance options and an optimization of investment strategies. The focus of this paper is on methodical aspects in condition prediction and life cycle costing models. For this purpose, common deterministic and stochastic approaches are compared with an innovative stochastic continuous time and continuous state space process on road section and network level. The results prove that this new approach provides a framework to achieve higher reliability in condition assessment, rating and accuracy of condition prediction leading to lower risks for road users and higher efficiency of invested funds compared to any common approach.
