Real time dynamic regulation method of main road signal lights based on data clustering in the environment of internet of vehicles

Conventional trunk road signal light regulation has poor real-time performance and low regulation accuracy. This paper designs a real-time dynamic adjustment method of main road signal lights based on data clustering in the Internet of Vehicles environment. First of all, the cycle and traffic conditions of signal lights are analyzed to determine the change rule of signal lights. Then, calculate the capacity and determine the signal lamp control parameters. Finally, the similarity of signal lamp real-time control parameters is determined through data clustering, and the shortest signal cycle and the best cycle value are obtained. The real-time control model is built with OD matrix to achieve real-time dynamic control of signal lamp. The experimental results show that the real-time adjustment time of the method is within 11s, the adjustment accuracy reaches 90%. The new method can effectively improve the adjustment efficiency of trunk road signal light.