【作者】 张宇； 段其昌； 张从力； 冯刚；

【Author】 Zhang Yu Duan Qichang Zhang Congli Feng Gang (Rockwell Automation Lab, Chongqing University, Chongqing 400030, China)

【机构】 重庆大学自动化学院罗克韦尔自动化实验室；

【摘要】 提出一种基于神经网络和模糊推理的相邻交通路口的协调算法,基于FNN(模糊神经网络)的多路口交通灯控制系统具有离线学习和在线自适应的能力,通过运用算法实现全局优化。采用PC和PLC实现交通灯控制驱动,开发了友好的人机界面。仿真实验结果表明提出的算法能够实现预期功能,系统结构简单,可以较好地应用于交通控制中。更多还原

【Abstract】 A concordance algorithm based on neural network and fuzzy reasoning is proposed for adjacent traffic intersections, also a traffic light control system based on FNN is made to be studying off-line and adjusting online. The algorithm can be used in city traffic light intelligent control system to realize global optimization and create command to computer. Global optimization command is sent to the PLC which is connected with computer. The PLC drives traffic lights and HMI program monitors the whole system. Simulation results and experiments reveal that the proposed algorithm can be used to reach the goal of making good using our traffic lights and better our traffic conditions.更多还原