This thesis will develop advanced control methods that improve the performance of the traffic network. In particular, controllers for mixed urban/freeway networks, controllers that anticipate on route choice, and route choice control methods are developed. The developed control methods are based on model predictive control (MPC). MPC is a control method that uses a prediction model to determine the expected evolution of the traffic flows. Furthermore, within MPC an objective function is defined that describes the goals of the controller. Then an optimization algorithm is used to determine the optimal settings for the traffic control measures based on the model predictions and the objective function. If necessary, the method can also handle constraints on the variables and states in the network. Finally, the computed settings for the first control time step are applied by the control measures, and the next control time step the whole procedure is repeated. In this thesis, them objective function of most of the developed control methods is based on the total time the vehicles spend in the network. (Author/publisher)
Abstract