Abstract
This paper presents the development of a pavement rutting model by combining experimental and field data. The experimental data came from the AASHO road test, while the field data was obtained from the Mn Roads Test site. Using joint estimation in this context allows us to improve the efficiency of the statistical estimates, quantify the values of the bias parameters in the experimental data, and identify some parameters that cannot be identified by using field data alone. The results of our research show that the pooling of experimental and field data yields better models than can be achieved by using a single data source.
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