An efficient model-based method for coordinated control of urban traffic networks

Traffic control is an effective and also efficient approach to reduce traffic jams. To alleviate the traffic congestion in an urban traffic network, a traffic control strategy that can coordinate the whole traffic network from a global point of view, is required. In this paper, an advanced control strategy, i.e. Model Predictive Control (MPC), is applied to control and coordinate urban traffic networks. However, the on-line computational complexity becomes a big challenge when the scale of the traffic network gets larger. To overcome this problem, the MPC control strategy is reformulated and solved efficiently on-line by a Mixed-Integer Linear Programming (MILP) solver. An MPC controller based on MILP is established and studied for the urban traffic network in different traffic scenarios. The simulation results show that the MILP-based MPC controller is a promising approach to reduce the on-line computational complexity of MPC controllers for urban traffic networks.