交通信号灯的智能化研究是智能交通系统(ITS)的一个重要研究领域。通过交通信号灯智能化的调整,可以对道路交通进行有效的无人化疏导,既节省了警力,又提高了效率。交通信号灯时间的调整,采样数据量大,并有很强的随机性。因此,本文基于数据挖掘技术,提出了一种学习模型——决策树的算法,作为交通信号灯智能化调整的依据,并通过一个路口的实际检测,取得了良好的效果,证明是一种简捷可行的方法。 The intelligent research of traffic lights is an important research field of Intelligent Transportation System (ITS). Through the intelligent adjustment of traffic lights, road traffic can be effectively unmanned, saving both police force and efficiency. Traffic signal time adjustment, a large amount of sampled data, and a strong randomness. Therefore, based on the data mining technology, this paper presents a learning model - a decision tree algorithm, as the basis for intelligent adjustment of traffic lights, and achieved good results through an actual test at an intersection proved to be a simple and feasible Methods.