travel time ∗

In this paper we use a model-based traffic control approach to determine dynamic speed limits with the aim of reducing fuel consumption and emissions, while still guaranteeing small travel times. The approach we propose is based on model predictive control (MPC). MPC is a modelbased control design method that combines prediction and on-line optimization of a performance criterion over a given time horizon to determine appropriate control inputs. MPC allows the inclusion of constraints on inputs and outputs, and it can handle changes in the system parameters by using a moving horizon approach, in which the model and the control strategy are updated regularly. We consider reduction of the total fuel consumption, total CO emissions, and total time spent in the traffic network. For the MPC controller we use a microscopic car-following traffic flow model and a microscopic emission and fuel consumption model. Based on simulations we demonstrate that a traffic control strategy (such as MPC) addressing total fuel consumption, total emissions, and total time spent can result in a balanced reduction of all the performance measures, by considering their weighted combinations as the overall performance criterion.