The Mechanistic-Empirical Pavement Design Guide (M-E PDG) is becoming the state-of-the-practice in both newly constructed and rehabilitated pavement designs. A number of different material inputs are required by the M-E PDG, and accurate measurement of these inputs is crucial for the accuracy of the distress predictions. The main objective of the research study presented in this thesis was to investigate linear viscoelastic characteristics of asphalt mixtures and binders commonly used in Michigan. This is important for implementation of the M-E PDG in Michigan and for accurate prediction of flexible pavement distresses. The second objective was to develop analytical models in efforts to provide improved |E*| predictions of asphalt mixtures used in the State of Michigan. For this, the Modified Witczak model was locally calibrated. In addition, an Artificial Neural Network (ANN) model was developed and trained for Michigan asphalt mixtures. Another objective of this study was to investigate the Representative Volume Element (RVE) requirement for complex (dynamic) modulus (|E*|) of asphalt mixtures. Small thin mixture beam (TBM) specimens (0.5"x0.25"x4.5") were tested using the Bending Beam Rheometer (BBR) testing machine to obtain the Creep Compliance (D(t)). This study showed that there is a trend in D(t) values obtained from the BBR, but on the other hand; the factor between |E*|-based and TBM-based D(t) values was not consistent and ranged between 1.5 and 4 factors.
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