This study evaluated 18 pavement sections located in high-traffic highways in Virginia to find a premium pavement design with a life span of 40 years or more using current and past field experience. The selected pavement sections were thought to perform well. Eight flexible pavements, six composite pavements, two continuously reinforced concrete pavements, and two jointed plain concrete pavements were investigated. Field testing consisted of (1) falling weight deflectometer (FWD) testing to assess the structural capacity of the different pavements and to backcalculate the pavement layer materials' moduli, (2) ground-penetrating radar (GPR) scanning to determine layer thicknesses and to locate any abnormalities inside the pavements, (3) digital imaging to determine condition indices, (4) longitudinal profile measurements to calculate International Roughness Index, and (5) coring and boring to perform material characterization of pavement layers. Hot mix asphalt tests included resilient modulus and creep compliance. Concrete was tested for compressive strength. The analysis of the collected data suggests that premium pavement designs can be obtained. The field investigations suggest that all the tested sites are performing satisfactorily and show very low structural distress. Limited material-related problems were found at some sites, which induced non-load related distresses. It was also confirmed that FWD, GPR, and digital imaging are very useful tools to assess the condition of existing pavements. Since the three categories of pavements (flexible, composite, and rigid) were found to perform well, the study recommends that evaluation of other pavement sections, which are thought to perform in a less than optimal state, be conducted to define the causes of the less than desired performance. The selection of the most appropriate premium pavement design should be based on a detailed life-cycle cost analysis; hence, such analysis should be performed. Mechanistic empirical modeling of the best performing section within each category would allow the prediction of future pavement performance for use in the life-cycle cost analysis.