Modeling and control of signaling split in urban traffic network based on hybrid systems

The operation of urban traffic network remains a challenge in Intelligent Transportation Systems (ITS) due to the intrinsic complexity of traffic systems. In this paper, for the sake of improving the network efficiency, we present a Model Predictive Control (MPC) framework for urban traffic network based on hybrid systems, which formulates split control as an MPC problem. Theoretical results ensure convergence of iterations to a globally optimal solution. The framework is applied to the signaling split control of traffic network. To validate the effectiveness of the proposed framework, a comparative study on the ZhongGuanCun west region, Beijing was conducted using traffic simulation software. Findings indicate that the proposed control strategy is more efficient to reduce delay time and relieve traffic congestion of the whole traffic network when compared to the conventional fixed time control.