交通信号公交优先控制策略及智能控制方法  

Traffic signal bus-priority control strategy and intelligent control method

作　　者：邝先验[1,2] 许伦辉[1] 黄艳国[1,2] 

机构地区：[1]华南理工大学土木与交通学院,广东广州510640 [2]江西理工大学电气工程与自动化学院,江西赣州341000

出　　处：《控制理论与应用》2012年第10期1284-1290,共7页Control Theory & Applications

基　　金：国家自然科学基金资助项目(60664001;51268017;61263024);江西省自然科学基金资助项目(2010GQS0076)

摘　　要：针对公交优先交通信号控制问题,研究了公交优先的信号控制策略,提出了一种变论域模糊神经网络公交优先智能控制方法.提出了基于相位优先度值的公交优先相位选择方法,并给出了其数学描述.建立了绿灯时间的3层模糊控制模型,分别为红灯排队疏散时间、绿灯延长时间和论域调节因子模糊控制器,其中红灯排队疏散时间和绿灯延长时间两个模糊控制器的输出变量均采用变论域,论域的变化考虑混合交通、天气情况、车流转向等因素由论域调节因子模糊控制器确定.模糊控制器采用粒子群优化神经网络实现.仿真结果表明该方法具有较好的公交优先控制效果.We investigate the intelligent control for the traffic signal with bus-priority strategy, and propose a control method with variable-universe fuzzy neural network. This strategy decides the bus-priority phase based on the prioritydegree, of which the mathematical description is developed. A three-layer fuzzy controller for the green-light time is built, that are queuing-evacuation time fuzzy controller, green-light extension time fuzzy controller, and the fuzzy controller for the regulation factor of the universe. Variable universes are employed for the output of the queuing evacuation time fuzzy controller and the output of the green-light extension time fuzzy controller. The variation of the universe reflects the mixed traffic flow, the weather and the traffic turning. The three-layer fuzzy controller is implemented by using the particle-swarm optimization neural network. Results show that the proposed method has good bus-priority control effects.

关 键 词：交通控制 公交优先 模糊控制 变论域 粒子群优化神经网络 

分 类 号：U491.54[交通运输工程—交通运输规划与管理]