Research And Design Of Arterial Coordination Control

Traffic jams and over-saturation has been one of the major factors of restricting the urbanization process. It is unpractical to solve the existing traffic problems by large-scale construction of road infrastructure. Using advanced traffic signal control techniques to optimize the signal timing is an effective way to improve the existing road network capacity. Arterial coordination control is one of the important research areas in intelligent traffic, aiming at the present research of arterial coordination; arterial coordination control technique is studied on the basis of the research and development of urban traffic signal control system. The main work of this dissertation includes:1. The design of arterial coordination control schemeThe theory and method of arterial coordination control are further studied. Taking as the research background the arterial coordination control of Huangshan Road, Hefei City, the drawbacks of present control scheme are analyzed, on the basis of traffic flow investigation and its characteristics analysis, a grouping multi-time arterial coordination control scheme is developed by integrating the characteristics of different control ways such as single point of timing control, sensor control and green wave control.2. Study of two-direction trunk coordination based on particle swarm optimizationThe arterial delay models in different situations are studied. Based on the delay model, particle swarm optimization algorithm is utilized to coordinate and optimize the important parameters including cycle, phase and split of the arterial coordination control. This algorithm considers the effects of conflict turning vehicles and effectively overcomes the disadvantage of traditional arterial coordination control..3. Research of one-way dynamic green wave flexible controlThe traditional timing green wave control can not fit dynamic traffic flows. A one-way green wave flexible control algorithm is proposed. According to real-time traffic flows and the flow-velocity model, the algorithm can take a dynamic flexible regulation for the control scheme in term of the real-time traffic flow and the emotional characteristics of drivers. The simulation experimental results show that the algorithm ensures the green wave effect and makes the changes of control scheme fit the psychological and physiological characteristics of drivers. It embodies the humanization characteristics and improves traffic safety.In final, the work of this dissertation is summarized, and the further study is indicated.