Study On The Optimization Of Signal Coordination Control For Oversaturated Intersections

Under the influence of economic development and the rapid expansion of the city scale,the proportion of motorized travel has rapidly increased,and the road network of urban centers has experienced increasingly severe oversaturation at peak times.As the number of vehicles continues to increase,the over-saturated state will expand from a single intersection to the surrounding area,forming a group of over-saturated intersections,leading to regional congestion.The urban road intersection group has the characteristics of strong traffic correlation and has a great influence on the operating status of the entire road network.In the event of oversaturated traffic congestion,by signal coordination and optimization control,the operating efficiency of road network can be effectively improved.In this paper,the coordination and optimization control are carried out for the critical paths and critical sections in the control area,which can greatly improve the efficiency of signal optimization and effectively improve the overall traffic condition of the control area.The method proposed in this thesis is not only applicable to different road conditions and traffic status in the over-saturated traffic control area,but also have certain optimization effect when the status of control area that is un-saturation or near-saturation.Firstly,the correlation degree model of adjacent intersections is established according to some influencing factors of correlation degree between intersections in certain amount of area.It determines the rough boundary of control range,and through the average correlation weight to control the boundary intersection selection,which lays a foundation for the subsequent identification and control optimization of the critical paths and critical sections.Then,Breadth-First Search(BFS)algorithm is adopted to identify the logical connection paths based on the topological structure of road network in the control area.The model of path importance degree is established based on the path discreteness index and retardation index to determine the critical paths for coordination control optimization.And the critical sections which are connected with the critical paths are also identified for coordination control optimization.Finally,the traffic flow direction of the critical paths is taken as the main research object.This thesis sets up an optimization model aiming at the highest offset coordination rate of the critical paths and an optimization model aiming at the highest traffic efficiency of critical sections.The two aspects are combined into a two-objective optimization model to carry out signal coordination and optimization at critical path intersections.Through the Particle Swarm Optimization based on Genetic Algorithm(GA-PSO),the optimal phase difference combination is obtained,and the coordination and optimization control of key points in the control area are realized.The feasibility and effectiveness of method are verified though case studies and VISSIM simulation analysis,and indicators such as average delay and stop times of most intersections of the critical paths and the whole road network are significantly reduced.