Model predictive control for freeway traffic using discrete speed limit signals

A model predictive control (MPC) approach for freeway traffic control using discrete signals for the activation of variable speed limit panels is proposed. The discrete characteristics of the panels and some necessary constraints for their real operation are usually underestimated in the literature, so first we propose a way to include them using the macroscopic traffic model METANET within an MPC framework. For obtaining practical discrete signals, the MPC controller has to solve a highly non-linear optimization problem, including mixed-integer variables. Since solving such a problem is complex and difficult to execute in real-time, we propose some methods to obtain reasonable control actions in a limited computation time. The methods consist of first relaxing the discrete constraints for the inputs; and then, based on this continuous solution and together with different search methods, to find discrete speed limit signals that provide the best performance, keeping the number of simulations reduced. The proposed methods are tested by simulation, showing not only a good performance but also keeping the computational time reduced.