LAUSR

Many efforts have been focused on the network-wide traffic signal optimization to deal with the congestion problem in big cities. Nevertheless, research evidence illustrates that both improper traffic network managements and excessive traffic demands are the key factors leading to the oversaturated traffic conditions. Current studies encounter the bottleneck in addressing the multi-objective optimization problem. This point calls for designing the hierarchical control framework. In this paper, we concern a two-level hierarchical model-based predictive control scheme to improve mobility in heterogeneous large-scale urban traffic networks, so as to mitigate traffic jams. On the basis of a network partition, a regional demand management approach regulating the input traffic flow from adjacent regions is proposed for multi-subnetworks management taking the advantage of the concept of a macroscopic fundamental diagram of urban traffic networks. This can be viewed as a higher level control layer and can be integrated with other strategies. The lower level control layer utilizes the traffic signals coordination within the subnetworks based on a detailed link-level traffic model to optimize the allocation of vehicles in each subnetwork as homogeneous as possible. The simulation results show that integrating regional demand management with a local traffic responsive control into a hierarchical framework can significantly improve the whole network performance under different traffic scenarios in comparison with other available control strategies.