Augmented reality AR is a promising paradigm that can provide users with real-time, high-quality visualization of a wide variety of information. In AR, virtual objects are added to the real-world view in a real time. Using the AR technology can offer a very realistic environment for driving enhancement as well as driving performance testing under different scenarios. This can be achieved by adding virtual objects (people, vehicles, hazards, and other objects) to the normal view while driving in a safe controlled environment. In this dissertation, the feasibility of adapting the AR technology into traffic engineering was investigated. Two AR systems; AR Vehicle ARV system and Offline AR Simulator OARSim system were built. The systems\u27 outcomes as well as the on-the-road driving under the AR were evaluated. In evaluating systems\u27 outcomes, systems were successfully able to duplicate real scenes and generate new scenes without any visual inconsistency. In evaluating on-the-road driving under the AR, drivers\u27 distance judgment, speed judgment, and level of comfort while driving were evaluated. In addition, our systems were used to conduct two traffic engineering studies; left-turn maneuver at un-signalized intersection, and horizontal visibility blockage when following a light truck vehicle. The results from this work supported the validity of our AR systems to be used as a surrogate to the field-testing for transportation research
