Feasibility Study for Gray Theory Based Pavement Smoothness Prediction Models

In the proposed Mechanistic-Empirical Pavement Design Guide (MEPDG), the functional performance indicator is pavement smoothness as measured by the International Roughness Index (IRI). The MEPDG IRI prediction models were developed based on the general hypothesis that changes in smoothness result from various distress types that can be predicted by the MEPDG program. Using pavement distress data from the Long Term Pavement Performance (LTPP) database, traditional regression analysis was used to statistically establish the MEPDG prediction equations. This paper attempts to use a new technique for pavement smoothness prediction. The gray system theory was devised in the 1980s for modeling uncertain systems with the characteristics of partially known information. A pavement performance prediction system can fit the domain of the gray system. The gray theory based prediction method is used in this paper to develop IRI prediction equations. With the data exported from the LTPP database, it is found that certain specific types of distresses significantly affect the accuracy of the predictions. After trial and error calculations. Gray Model based smoothness predictions are established using influencing factors similar to the ones used in MEPDG. Based on the comparisons of results from the two prediction methods with LTPP field data, it is shown that the Gray Model based method provides promising results and may be useful for modeling pavement performance.