The Study Of Arterial Dynamic Coordinated Signal Control Based On Improved Fuzzy Control

With the rapid development of urbanization and increase of vehicle holding rate,traffic congestion has become the most severe traffic problem of a number of cities.Traffic congestion not only causes billions of dollars loses per year,but also leads to environmental pollution and traffic accidents.The intersection is the most important part of the road network.Because of the complication of traffic conditions at intersections,intersections have become the most common places of appearing traffic congestion.It is of significant importance to use appropriate signal control method to decrease average vehicle delay.With the development of intelligent control method and automatic technology,the application of intelligent control method has become the future trend of signal control.Based on the introduction of the study of signal control,a coordinated fuzzy control algorithm has been proposed.The coordinated fuzzy control algorithm contains seven fuzzy controllers.The first-stage fuzzy control algorithm is used to evaluate the workload of the green phase and red phase,and the red phase that in need of green time most desperately is selected as the candidate phase.The second-stage control algorithm is used to calculate the figure of the tendency to change phase based on the output of the first-stage fuzzy control algorithm.The third-stage fuzzy control algorithm is used to take consideration of the interaction of adjacent intersections and modify the output of second-stage fuzzy control algorithm.This algorithm is able to realize the coordinated signal control of adjacent intersections.Second,CTM model is introduced to predict the traffic flow in the future.Based on the flaws of the present CTM model,an improved CTM model that has considered the influence of intersections has been proposed.The volume of vehicles that has flowed out and into the intersection has been calculated by the density of traffic flow so that the length of CTM model can be changed.The influence of intersections has been considered to modify the traffic volume sent by the cell controlled by signal group.In order to predict the future traffic condition more accurately,intersection data and VISSIM have been used to standardize the parameters of CTM.MATLAB and VISSIM have been used to compare the output of cell density and average vehicle delay under the circumstance of signal timing control on the single intersection,fuzzy control on the single intersection,timing control on adjacent intersections and coordinated fuzzy control on adjacent intersections to verify the effect of the improved CTM.Last,according to the flaw that fuzzy control cannot change its subordinating degree function,the self-adapted genetic algorithm is used to optimize subordinating degree function.Compared with the traditional genetic algorithm,the self-adapted genetic algorithm is able to prevent the abandon of good individual.Using the predicted average delay of improved CTM as the object of optimization,the self-adapted genetic algorithm is used to optimize the subordinating degree function of seven fuzzy controllers.In this way,the coordinated signal control is able to apply to intersections under various traffic volume.Adjacent intersections of Chengdu is used to verify the effect of the coordinated fuzzy signal algorithm optimized by the self-adapted genetic algorithm.Under the traffic volume of current traffic volume and 0.8 times,1.2 times and 1.5 times of current traffic volume,coordinated fuzzy signal control algorithm optimized by the self-adapt genetic algorithm can decrease the average vehicle delay compared with the ordinary coordinated fuzzy signal algorithm and traditional signal timing control.The effectiveness of the optimized coordinated fuzzy signal control algorithm has been verified.