Based Q-iearning In Traffic Signal Control Of Multiple Intersection

The traffic problem has become a major bottleneck to restrict the urban’seconomic development, to solve the traffic congestion already imminent, the limitednature of urban space and other factors, such as economic, environmental, etc, thathinder the expansion of transport infrastructure. The introduction of artificialintelligence, computer simulation and other high-tech, to solve urban trafficcongestion and congestion, has become the hot spots of traffic signal control.In this thesis, after a brief overview of the signal to control the developmentstatus and Q-learning theory, focusing on the Q-learning theory applied to the trafficsignal control. On the one hand, is the green time optimization based on theQ-learning theory. For a fixed period and variable cycle two modes of singleintersection signal timing optimization study, construct saturation and delay minimumas the optimization objective reward function, established the two optimizationobjectives off-line Q-learning model. Through the VBA and Matlab programsexample, the thesis analysis the structure of the solution and the distribution of theoptimal solution of the4kinds of offline Q-learning model, and discusses theapplicability of offline Q-learning optimization model in the intersection signalcontrol. Then, the optimal solution is applied to real-time traffic control in VISSIM,and compared with the classical Webster algorithm, and the result shows that theQ-learning green optimization algorithm has very strong superiority.On the other hand, this thesis is based on the Q-learning theory at the manycrossroads optimization phase difference. This thesis studied optimization phasedifference for a fixed period mode, and integrated VISSIM-Excel and VBA-Matlabsimulation platform as technology platform.And this thesis taked VBA and Matlabprogramming,established offline Q-learning model,and taked the minimum delay asoptimal objective. Then the optimal solution is applied to VISSIM real-time trafficcontrol, and compared with MAXBAND, the results indicated that the Q-learningphase difference optimization algorithm has the very strong superiority.At the same time, in order to establish experimental condition of the algorithms,the thesis researched the integrated Vissim-Excel VBA-Matlab simulation platform,comprehensive the ability of the Vissim reliable microscopic traffic flow simulation,Excel VBA efficient programming efficiency and data communication ability, and Matlab complex intelligent traffic control algorithm.Through the Vissim-Excel VBAinterface technology, the thesis built traffic control real-time simulation platform. Atlast, the thesis summarized the work and put forward the problems that is need to befurther studied.