Research On Adaptive Coordinated Control Method Of Urban Road Intersection Signals

With the continuous development of cities,the demand for transportation for people is increasing.Especially during the morning and evening rush hours,the sharp increase in traffic volume has brought a great burden to the operation of the transportation system,resulting in increased vehicle delays and inconvenient travel.This paper analyzes the problem of coordinated signal control based on three basic urban traffic models of single intersections,arterial roads,and regional intersections.The optimized signal control scheme designed in this paper makes it possible to perform adaptive control to reduce traffic congestion under the condition that the traffic volume increases and the conditions of each road section are different.The specific work of this article is as follows:For the problem of signal control for the single intersection,this paper designs a type 2 fuzzy controller to perform signal timing.First,a traffic flow model of a four-phase single intersection is established,and the calculation expressions of vehicle queue length and vehicle delay are given.In order to solve the highly dynamic non-linear characteristics of the traffic system and uncontrollable factors such as the geometric conditions of various intersections and driver behavior in practice,a type 2 fuzzy adaptive controller is designed for the single intersection model.The secondary fuzzy information more accurately describes the uncertain behavior in the system.Finally,the adaptive genetic algorithm is used to optimize the selection of membership function parameters and fuzzy rule base parameters in the type 2 fuzzy controller.The simulation results show that the proposed method has better control effect on vehicle delay index.For the problem of signal control on arterial roads,this paper proposes a partial form dynamic linearization model free adaptive controller scheme design.Considering the inconsistencies in the distances and cycles between different arterial intersections in cities and the complexity of modelling,this paper uses a model-free adaptive control method that relies only on input and output data and does not rely on model parameter to solve the problem.We introduce a fixed-length time window to solve the situation that the average density of the roads at the current moment may be related to the total state change over a period of time.For different traffic flows on the arterial roads,we control the average density of arterial roads by controlling the flows of traffic left at the intersection and entering the arterial roads.The simulations show that the controller can control the average density of the roads to reach the desired average density and maintain stability.For the signal control problem of the intersection groups,this paper proposes a method for coordinated traffic induction control that considers the traffic conditions in both within the sub-region and between the sub-region.For the problem of calculating the intersection degree of intersection groups,a sub-region division method of the association degree matrix considering the impedance of the road section is proposed.For the problem that traffic guidance needs dynamic information of traffic flow,a short-term prediction method of traffic flow based on singular spectrum analysis is proposed.At the same time,the survival model method is introduced to determine whether the intersection in the sub-region has ended the congestion.The combination with the results of short-term prediction provides a basis for selecting traffic guidance strategies.Considering the traffic condition within the sub-region and the traffic condition between the sub-region,the optimization objective function design of the traffic guidance cooperative control system is carried out.Finally,the simulations show that the collaborative traffic guidance control method proposed in this paper can make the intersection groups pass more traffic in the same time and improve the traffic efficiency of the intersection groups.