Stabilization of city-scale road traffic networks via macroscopic fundamental diagram-based model predictive perimeter control

Traffic control for large-scale urban road networks remains a challenging problem. Aggregated dynamical models of city-scale traffic, based on the macroscopic fundamental diagram (MFD), enable development model-based perimeter methods. Involving actuation over aggregated traffic flows, specifies an effective and practicable congestion solution. In this paper, we propose nonlinear model predictive schemes, regulation economic optimization objectives, with closed-loop stability by construction. Macroscopic microscopic simulations demonstrate performance domain attraction properties proposed formulations. Results indicate potential methods efficient reliable traffic. • control. Feedback stabilization is required to recover city from near-gridlock conditions. Stabilizing achieves recovery. Domain lost due uncertainty can be recovered via state estimation. Simulations suggest stabilizing practice.