Development of dynamic network models for intelligent transportation systems applications

Dynamic network models can support development of network-wide traffic management strategies, and assist travelers' decision making by providing dynamic travel time information, within the framework of Intelligent Transportation Systems. Generating appropriate information necessary to implement these technologies is the heart of dynamic network models.; Dynamic network models proposed in the literature are generally formulated as a continuous time model and approximated as a discrete variable problem by dividing the analysis period into smaller intervals. Unfortunately, some mathematical properties could be lost during the discretization process. Also, the flow dynamics are too simplified, which makes the dynamic models less useful for practical applications.; This research aims to develop a set of dynamic network models that are based on discrete flow variables using the variational inequality approach. Those dynamic models are targeted to support Advanced Traveler Information Systems (ATIS) and Advanced Traffic Management Systems (ATMS) for major freeway corridors in urban areas. Solution algorithms are developed to allow the proposed models to be used in practical applications.; This research consists of three subjects. First, a dynamic flow model, the aim of which is to provide a mathematical approximation of the dynamics of traffic flows, is developed using discrete flow variables.; The second part of this research deals with dynamic route choice problems, also known as the dynamic traffic assignment problems, using both deterministic and stochastic approaches.; The last part of the research considers extensions or applications of the route choice models. A combined route/departure time choice model is developed for the analysis of peak-period travel patterns. A travel time prediction model that considers motorists' route diversion behavior is presented as another extension of the dynamic route choice models.