Integration of Pavement Cracking Prediction Model with Asset Management and Vehicle-Infrastructure Interaction Models.

摘要

Not long after the construction of a pavement or a new pavement surface, various forms of deterioration begin to accumulate due to the harsh effects of traffic loading combined with weathering action. In a recent NEXTRANS project, a pavement cracking prediction tool is developed, which can predict fundamental material fracture response and is capable of performing thermal cracking simulations. This deteriorated pavement condition, which is the sum effect of a number of distinct deterioration modes or ‘distresses,’ increases not only agency costs but also user costs. It is required to consider both users and agency investments while making decision for pavement maintenance and rehabilitation for better financial management. The material selection process can be optimized by incorporating user costs via pavement life-cycle analysis and maintaining pavement distress levels using the pavement cracking prediction tool. Pavement condition has significant impacts on user costs. There are many indices that represent pavement condition. International Roughness Index (IRI) is widely used to quantify pavement smoothness. From the driving comfort viewpoint, smoothness is considered as the most important aspect of pavement condition, and it is especially important for pavements with elevated speed limits. Highway agencies generally have their own specifications of IRI level for different classes of roadways. Roughness increases user costs including fuel, repair and maintenance, depreciation, and tire costs. User costs across a vehicle fleet resulting from increased roughness is undoubtedly significant, but has not been well quantified in light of newly available prediction tools.