Optimal Condition-Based Resurfacing Decisions for Roads
Résumé
We develop a condition-based maintenance optimization approach for the road cracking problem in order to derive an optimal action-planning policy from a Markov decision process that minimizes the expected cost. Our model deals with multiple imperfect actions that consist of different resurfacing thicknesses and that have varying effects on the future deterioration law. We model the deterioration after maintenance to be dependent upon both the state of the road before maintenance and the type of maintenance performed. Another new aspect of our model is the possibility for a maintenance action to render the road to a state better than as-good-as-new. The application of new road layers is, however, constrained by a maximum total road thickness. Some maintenance actions may then become infeasible due to the thickness of the road relative to the constraint. As the road is constrained by a maximum total thickness, the maintenance decision is made complex by the determination of not only how thick of a layer to apply, but also how much old road to remove. We model the road state by two deterioration variables: the longitudinal cracking percentage and its associated growth rate. Our degradation model will take into account the changing road composition which is a function of the successive application of new and removal of old layers.