Constrained Model Free Adaptive Predictive Perimeter Control and Route Guidance for Multi-Region Urban Traffic Systems

Perimeter control (PC) and route guidance (RG) have become two powerful traffic control methods to address the urban traffic congestion, especially for multi-region urban traffic systems (MRUTS). Accurate traffic system model is necessary in majority of the existing PC and RG methods. If the traffic model is inaccurate or unavailable, the aforementioned PC and RG strategies may not work well or cannot be applied. In this paper, a novel data driven scheme called constrained model free adaptive predictive control (cMFAPC) is provided for PC and RG of MRUTS. Two outstanding advantages of this method are that it can only use the input and output (I/O) data of the controlled MRUTS to design the PC and RG strategies, instead of utilizing the traffic dynamics model, and the merits of model free adaptive control (MFAC) method and model predictive control (MPC) approach are combined in the proposed cMFAPC strategy. The effectiveness of cMFAPC strategy and its superiority over other commonly used PC and RG methods are verified via simulation.