Application of Ant Colony Optimization Algorithm to Ramp Metering

On-ramp control is the most effective and extensive way to improve freeway capacity. A proportional-integral (PI) control method based on ant colony optimization (ACO) is proposed to regulate the number of vehicles entering a freeway entrance point. First, a macroscopic traffic flow model is established. Then the basic principles of ant colony algorithm are formulated and the steps of ACO algorithm in optimizing the PI parameters are given. In conjunction with nonlinear feedback theory, on-ramp PI controller optimized by ant colony algorithm is designed. Finally, the controller is simulated in MATLAB software. The results show that the ACO-based ramp metering controller has fast response speed, high computation efficiency, and good dynamic and steady-state performance.