Research on traffic signal control algorithm based on self-organizing competitive neural network and optimization model

Intelligent transportation is a new discipline integrating information, sensing and other advanced technologies. It plays an important role in urban traffic management, design and control. This paper combines self-organizing competitive neural network with intelligent transportation. Through the process of neural network learning and model optimization, the method of self-organizing neural network is used to control the phase of signal light, and its principle and concrete implementation are simulated. According to the results of the experiment, it can be found that the model classification function of self-organizing competition network has the function of intelligent classification and control in the traffic condition of the intersection, which is beneficial to realize the intelligent control of the traffic light signal.