Study On Urban Intersection Group Based On Multi-objective Optimization

With the development of economy and the rapid increase of vehicles,urban traffic congestion is becoming more and more serious.The road infrastructure of big cities can hardly meet the increasing traffic demand.Signal control of Urban Road intersection is still an important measure to solve urban congestion.The development of single-point signal control or regional signal coordination control system can not adapt to the sophisticated traffic jam as a result of more and more crowded vehicles.Through the study and analysis of the geometric state and traffic flow characteristics of short-distance intersection group,measures and optimization of signal timing schemes can reduce the parking delay at intersections and enable vehicles to pass through intersections quickly.Thus,the traffic efficiency of the whole intersection group can be improved.As the smallest unit of coordinated control,by far,intersection group is not perfect in signal control technology.In view of this,this paper focuses on the analysis of traffic flow characteristics of intersection group.Meanwhile,based on the theoretical research and practical application results of traffic signal control at home and abroad,some key technologies of traffic coordination control of intersection group under saturated conditions are studied in depth.Firstly,this paper defines the mathematical definition and related theory of intersection group based on the current research.Then this paper calculates path correlation of adjacent intersections.According to results,this paper establishes a critical path partition model based hierarchical clustering analysis.The key intersections are selected as the main control objects in the intersection group area,and then the phase optimization and green light time optimization of the key intersections are carried out.A control strategy suitable for saturated intersections is proposed.Additionally,based on the traffic characteristics and control strategies of intersections under saturated conditions,this paper established a model with multiple optimization objectives and multiple model constraints.This multi-objective optimization model includes maximum number of vehicles passing through the critical path of this intersection group and minimum average queuing proportion.In this paper,non-dominated sorting genetic algorithm(NSGA-?)is introduced to solve the model,and the process of solving the model is given in detail.Then,the simulation software Synchro is used to simulate the results,and the optimization results are compared with the traditional signal timing results.The comparison results show that when the intersection group is saturated,the proposed control strategy and method can effectively control the traffic volume of the intersection group,distribute traffic pressure equally,reduce critical traffic flow delay,and improve traffic congestion to a certain extent.