Research On Traffic Signal Coordination Control Theories And Methods In Urban Road Networks

As the rapid increase in traffic demand in urban road networks, the temporal and spacial in-terrelations between adjacent intersections in the network get stronger. For instance, the changes of traffic state at one intersection will cause changes in its neighbors’ traffic conditions. In other words, the traffic signal plan of one intersection follows changes to its neighbors. It is generally recognized that, to improve the performance of traffic signal control system, we need to take a subnetwork (or the whole network) as the control object and coordinate the intersections simulta-neously to maximize the total benefits of the whole network. To deal with the defects in existing traffic signal coordination methods, this dissertation researched and discussed in the following ar-eas, including two-way arterial traffic signal coordination, traffic signal coordination with model predictive control technology in large-scale urban road networks.The main contents and results in this dissertation are summarized as follows:1. Based on arterial signal coordination and network decomposition, we proposed a method to optimize and coordinate the traffic signal in urban road networks. To construct a two-way progression band, we proposed an arterial signal coordination model which optimized the green start time of coordinated phases. Furthermore, to achieve arterial signal coordination, a regulation scheme was designed to revise the phase sequences and the green start time of coordinated phases. To reduce the computational complexity in large-scale road networks, an network decomposition strategy was proposed in which a novel priority level index was employed to quantify the priority level of each arterial. The problem of coordinating a large-scale road network has been solved by coordinating the principal arterial and several isolated intersections on the boundary of the area.2. We proposed a two-way arterial signal coordination method with queueing process consid-ered. To accurately model the actual traffic conditions of an arterial road, the queueing process at the approach was analyzed and discussed. Then, to get the queue clearance time, we developed a model to estimate the queue length before the green light starts. To construct a two-way progres-sion band, the constraints of the green start time of coordinated phases were defined. In addition, to ensure the coordination strategy is feasible and maximize the bandwidth, we analyzed the pos-sible phase sequences combination and proposed several optimal strategies. Then, the two-way arterial signal coordination problem was formulated as a mixed-inter programming model. Finally, experiment results by means of simulation on an arterial road that includes eight intersections were presented, which illustrated the performance of the proposed approach.3. We proposed a hierarchical MPC approach for traffic signal coordination in large-scale urban road networks. Based on an improved linear traffic model, the MPC-based traffic signal con-trol model for the large-scale urban road network was presented, in which the interactions between neighboring subnetworks were described with interconnecting constraints. Since centralized MPC can not be applied in large-scale urban road networks due to the high computational complexi-ty and poor practicability, by developing a decomposition strategy, the original MPC optimization problem had been decomposed into several subnetwork optimization problems. An interaction pre-diction approach had been employed to coordinate the subnetworks. At the lower level, based on the predicted interactions from neighboring subnetworks, the optimization problem corresponding to each subnetwork was solved independently and the results were upload to the upper level. At the upper level, the coordination vectors which were used to guide the subnetwork controllers to agree on a global solution were optimized.4, We proposed a distributed MPC method for traffic signal coordination in large-scale ur-ban road networks. Aiming to model the traffic dynamics, an improved nonlinear traffic model was proposed, whereby the disturbing flow rate of each link was considered. Using the nonlinear traf-fic model for the prediction, the MPC-based traffic signal control model for the large-scale urban road network was proposed. Since the cycle time (or sampling time) of one intersection maybe different from those of its neighbors, to achieve signal coordination among adjacent intersections, we proposed an method to synchronize the sampling time. In addition, to reduce the computa-tional complexity and improve the applicable of the proposed coordination and control model, based on dual optimization theory and a designed decomposition strategy, the original MPC opti-mization problem was decomposed into several subnetwork optimization problems. A distributed coordination method was proposed to coordinate the resulted subnetworks. Finally, experiment results by means of simulation on a benchmark traffic network were presented, which illustrated the efficiency of the proposed method.