Ameliorating congestion by income redistribution

Properly specified pavement deterioration models are an important input for the efficient management of pavements, the allocation of cost responsibilities to various vehicle classes for their use of the highway system, and the design of pavement structures. However, most empirical deterioration progression models developed to date have had limited success. This paper is concerned with the development of an empirical rutting progression model using experimental data. The data used in this paper comprise an unbalanced panel data set with more than 14,000 observations taken from the AASHO Road Test. The salient features of the model specification are (1) the model eschews conventional (predefined) axle load equivalencies and structural numbers in favor of relationships determined entirely by the data itself; (2) a thawing index variable has been incorporated to capture the effects of the environmental factors in the AASHO Road Test; and (3) the model predicts incremental changes in rut depth, which is particularly advantageous in a pavement management context. The specified model is nonlinear in the variables and the parameters and is estimated using both fixed-effects and random-effects specifications to account for unobserved heterogeneity. The estimation results show that the model replicates the pavement behavior well, that the inclusion of an environmental variable is important to avoid biases in other parameters, and that the size of the unobserved heterogeneity is significant. It is also found that interactions between some parameters in the nonlinear specification leads to significant differences between parameter estimates among the two wheel paths rutting models.