Integrated Control and Management Model for Mixed Networks Based on Stackelberg Games

Abstract:

Aimed at the phenomenon that local congestion is easy to evolve into large-scale congestion due to the decentralized coordinated control of the mixed network composed of the expressways and the surface streets， as well as the unbalanced distribution of traffic flow pressure in the road network during peak hours， a centralized cooperative optimization model LC-MPC（level change - model predictive control） of mixed network with changeable game roles between authority and users is constructed based on Stackelberg Games. User compliance rate is taken as the equilibrium index to represent the pressure distribution of road traffic flow， while role-change function is designed to fulfill the transformation of the relationship between leader and follower under different traffic states. The central controller of model predictive control（MPC） realizes the synchronous optimization solution of CAC （combined traffic assignment - signal control problem） of the mixed network. Finally， the effectiveness of the designed model is verified by comparing with different control models. The results show that the LC-MPC model with the highest degree of centralization has a better effect on reducing road network travel cost than other control models. Meanwhile， the model can maintain the user compliance rate within a certain range， which is conducive to the balanced distribution of traffic flow and the overall stability of the road network.

Key words:traffic operation;integrated control and management for mixed network;Stackelberg Games;users’ compliance rate;changeable game roles