Intelligent transportation systems (ITS) are being designed to provide real-time control and route guidance to motorists to optimize traffic network performance. Current research and development efforts consist of a dynamic traffic assignment capability that can predict future traffic conditions and a real-time traffic adaptive control system (RT-TRACS) for generation of signal control strategies. Although these models are intimately connected, so far they have developed independently of one another. A framework is presented here for integrating the two models into a combined system with a practical approach for realizing it. First the static case involving the interaction between travelers (demand) and transportation facilities (supply) under recurrent conditions is discussed. This model is applicable in the design and planning of transportation systems management actions. The framework is then extended to the quasi-dynamic and the dynamic cases, which involve incorporation of advanced ITS technologies in the form of advanced traffic management systems and advanced traveler information systems. An innovative application of this framework to advanced traffic-adaptive signal control is presented using the hierarchic structure of RT-TRACS.
Unmanned ground vehicles: adaptive control system for real-time rollover prevention
