| This dissertation focuses on the incorporation of buses into both system-optimal and user equilibrium DTA models. Specifically, a cell transmission-based, single destination, system optimal integer linear programming model of intermodal trips on a network of cars and buses is presented, and the model is solved on a test network using standard mathematical programming methods. Also, the inter-nodal user equilibrium problem is formulated as a variational inequality, and an inner approximation solution algorithm that minimizes an equilibrium gap function is presented. Algorithm convergence is proven for cases with continuous, monotonic cost functions, and heuristic variations are proposed for problems where these assumptions do not hold. While the inner approximation assignment algorithm may be applied with any traffic propagation model for calculation of link costs, the approach implemented in the dissertation is a cell transmission-based simulation model. Further, for path generation, a label-correcting intermodal least cost path algorithm, which accounts for both time-varying and fixed travel and transfer costs, is presented with proofs of convergence and correctness.;Computational results are presented for the inner approximation DTA model first on a single-mode automobile network test network, as well as on a large-scale multimodal network of cars and buses. This multimodal automobile assignment-based approach is used in a real-world evaluation of the regional impacts of transit signal priority (TSP). Key findings relate not only to the impacts of TSP, but also to the practical aspects of realistic regional simulation, such as challenges in data acquisition and model validation. In addition, computational results are presented to explore the behavior of the inner assignment algorithm for the intermodal problem. |
