一种交叉路口信号优化控制模型的研究与仿真

Study and Simulation on Traffic Signal Optimization Control Model of Intersection

交通信号优化是智能交通控制中的难点。对单交叉路口信号控制提出了一种优化控制模型,该模型先以三层BP人工神经网络对交叉路口的车辆到达进行预测,并根据交通流饱和度理论,用模糊控制器对路口各方向的绿灯时间进行调整。仿真研究表明提出的控制模型可以提高交叉路口通行能力,减少车辆延误,达到交通信号优化的目的,同时比传统方法能更好地适应变交通流的情形。如果做进一步的研究可将该控制方法应用于多路口的区域交通控制,有较强的实用性和推广价值。

The traffic signal optimization is the most difficult one of intelligent transportation control. A optimization control model is proposed at single intersection, in which a three layers BP manual neural network is used to forecast the quantity of vehicle which will arrive at intersection and a fuzzy controller which bases on the theory of traffic flow saturation degree is used to adjust the time of green light in intersection. The simulation experiment indicates that the proposed controlling model in this paper can improve the traffic capacity of intersection and reduce the delay time of vehicle and achieving the purpose that the traffic signal is optimized. At the same time the model can adapt the constantly changed traffic flow better than the traditional method. The controlling method which have stronger practicability and value to popularize can be used to control the area traffic control if we do further research.