Coordinated Ramp Control Based on Genetic Algorithm

The coordinated ramp control depending on the traffic conditions in the whole freeway system rather than the local conditions around independent on-ramps has gained the most respect to ameliorate the freeway traffic situation. In this paper a hierarchy control strategy and genetic algorithm optimization for the coordinated ramp control are proposed. The macroscopic model to describe the evolution of freeway traffic flow is firstly built. Then the coordinated ramp control system is designed. There are two control layers in this coordinated control system: the coordination control layer to select traffic models, to adjust the model parameters, and to determine the desired traffic density in each freeway section according to the current traffic state; and the direct control layer to keep the actual values of state variables in the vicinity of the desired state points via PI controllers. Genetic algorithm is used to find the optimal PI parameters of the direct control layer. The detailed simulation for the control system is implemented to illustrate the efficiency and feasibility of the proposed control method. This method can effectively eliminate traffic jams, and make vehicles travel more efficiently and safely.