Asphalt mixtures are complex composites that comprise aggregate, asphalt binder, and air. Several research studies have shown that the mechanical behavior of the asphalt mixture is strongly influenced by the matrix, i.e. the asphalt binder. Therefore, accurate constitutive models for the asphalt binders are critical to ensure accurate performance predictions at a material and structural level. However, researchers who use computational methods to model the micromechanics of asphalt mixtures typically assume that (i) asphalt binders behave linearly in shear, and (ii) either bulk modulus or Poisson’s ratio of asphalt binders is not time dependent. This research develops an approach to measure and model the shear and bulk behavior of asphalt binders at intermediate temperatures. First, this research presents the findings from a systematic investigation into the nature of the linear and nonlinear response of asphalt binders subjected to shear using a Dynamic Shear Rheometer (DSR). The DSR test results showed that under certain conditions a compressive normal force was generated in an axially constrained specimen subjected to cyclic torque histories. This normal force could not be solely attributed to the Poynting effect and was also related to the tendency of the asphalt binder to dilate when subjected to shear loads. The generated normal force changed the state of stress and interacted with the shear behavior of asphalt binder. This effect was considered to be an “interaction nonlinearity” or “three dimensional effect”. A constitutive model was identified to accommodate this effect. The model was successfully validated for several different loading histories. Finally, this study investigated the time-dependence of the bulk modulus of asphalt binders. To this end, poker-chip geometries with high aspect ratios were used. The boundary value problem for the poker-chip geometry under step displacement loading was solved to determine the bulk modulus and Poisson’s ratio of asphalt binders as a function of time. The findings from this research not only improve the understanding of asphaltic materials behavior, but also provide tools required to accurately predict pavement performance. / text