Traffic control via fleets of coordinates vehicles

In this thesis I investigated the impact of a few Connected and Automated Vehicles (CAVs) on the traffic flow. The study relies on a macroscopic approach, coupling a Partial Differential Equation describing the overall traffic flow and Ordinary Differential Equations accounting for CAV trajectories, which act as moving bottlenecks on the surrounding flux. The Controlled vehicles are able to merge, if they move on the same lane, or to overtake, in the case they move on different lanes. The effect of the CAVs on the traffic is the reduction of its density and thus a dependent cost function. More precisely, a Model Predictive Control is used to reduce fuel consumption in congested situations. Specifically, it is observed how the CAV number impacts the result, showing that low penetration rates are sufficient to significantly improve the selected performance indexes. Moreover, different strategies of control have been compared.