Development of an integrated project-level pavement management model using risk analysis.

摘要

Historically, federal highway funding focused on the construction of new pavements and the upgrading of existing pavements. Today, much of the infrastructure is in place. Therefore, the focus of federal funding is shifting toward pavement maintenance and preservation. With this is mind, highway agencies are directing attention toward pavement preservation strategies that yield the greatest value from existing pavements.; Life cycle cost analysis (LCCA) is a decision-making tool that highway agencies may use in selecting an optimal pavement preservation strategy. Traditionally, LCCA models for pavement management use discrete input values that represent a conservative “best guess” of each parameter. Thus, inherent uncertainty associated with each input parameter is not considered. There are situations, however, when this uncertainty may significantly influence the decision-making process.; The model developed for this research is a probabilistic model that derives flexible pavement designs, generates preservation strategies, and evaluates the life-cycle costs of each alternative. Risk analysis is incorporated into the LCCA model so that the inherent uncertainty of each input parameter is considered. Other features of the model include the incorporation of functional aspects (structural capacity and pavement condition) and safety (skid resistance) into the design, the inclusion of rehabilitation and preventive maintenance as preservation strategy alternatives, and the consideration of both agency and user cost in the present worth cost analysis.; The LCCA model output consists of probability distributions that describe the total present worth cost, the agency present worth cost, and the user present worth cost for each preservation strategy over a specified analysis period. The probabilistic nature of this LCCA model exposes areas of uncertainty that may be hidden in a deterministic LCCA model, and allows the decision-maker to assess the risk associated with each preservation strategy based on the probability of various costs that may be incurred.; Finally, a sensitivity analysis was performed to assess the effects of various input parameters on model output. The highway agency can enhance the model output by focusing more detailed data collection and parameter estimation on the model components that were identified as having a statistically significant effect on the model results.