Pavement instrumentation has recently become an important tool to monitor in-situ pavement material performance and quantitatively measure pavement system response to loading and environment. Parameters that need to be measured in the field include strains, stresses, deflections, moisture, and temperature. In-situ measurements of these parameters allow for the development of accurate performance models and the calibration of mechanistic pavement design approaches. In 1998, the Virginia Department of Transportation began the construction of a new test road, the Virginia Smart Road , to be an adaptable facility for transportation research and evaluation, to serve the transportation needs for the Montgomery region, and to act as a tool for regional economic development. The main objectives of the pavement research at the Virginia Smart Road are the performance evaluation of different SuperPave TM mixes, the calibration of pavement response to Falling Weight Deflectometer (FWD) testing, the evaluation of the feasibility of using Ground Penetrating Radar (GPR) as a pavement assessment tool, and to predict the pavement response under different environmental and loading conditions. The flexible-pavement part of the Virginia Smart Road test facility includes 12 (heavily instrumented) different test sections. Each section's length varies between 76 and 117 meters. More than 500 instruments were embedded in the Virginia Smart Road during construction to quantitatively measure pavement response to vehicular and environmental loading. Strains and stresses were carefully monitored throughout the depth of the pavement. Climatic parameters, including temperature, base and subbase moisture, and frost depth, were also monitored throughout the depth of the pavement. All instruments were embedded in the pavement sections during construction. A database of the measured stresses and strains at different layers of the 12 sections at the Virginia Smart Road as obtained from different truck loading tests was developed. The effects of truck speed, tire inflation pressure, axle load, and axle configuration (single versus dual) were quantified. Theoretical modeling including the use of existing software packages and the use of finite element method was evaluated to compare measure responses to theoretical ones.