MPC Algorithm Design Based on Improved Macroscopic Traffic Flow Model

doi:10.16182/j.issn1004731x.joss.20-0315

Abstract

Abstract: In order to obtain stable and orderly traffic flow, a model predictive control method based on improved macroscopic traffic flow model is proposed for highway system. Considering the uncertainty caused by the inflow and outflow of ramp, the method takes the traffic density and velocity of each section as the control target. Based on the traditional macroscopic traffic flow model, a macroscopic traffic flow state space model is improved. Aiming at the problem of multiple variables and control constraints, a traffic flow density and velocity controller based on model predictive control is designed to ensure better control effect. The simulation results show that the density and velocity of traffic flow eventually converge to the expected value, and the method can effectively avoid traffic congestion.

Key words: highway system, model predictive control, traffic flow density and velocity control, macroscopic traffic model

CLC Number:

TP391.9

Pan Hongguang, Gao Lei, Mi Wenyu. MPC Algorithm Design Based on Improved Macroscopic Traffic Flow Model[J]. Journal of System Simulation, 2021, 33(8): 1875-1881.

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