摘要
提出了一种基于模糊神经网络的道路交叉口交通控制方法,分别把关键车流信息和非关键车流信息作为控制输入,采用两级控制器结构,综合形成控制策略。仿真结果表明,与传统的定时控制方法和只考虑关键车流的情形相比,所提出的两级神经网络控制方法在车辆平均延误时间和排队长度方面都有较大改进。
A traffic control method based on fuzzy neural network is proposed for isolated intersection. According to this method, the detected vehicle flow data in four directions is taken into account and the hierarchical FNN control structure is used to determine the control strategy. Compared with the ordinary traffic control system, the hierarchical FNN control system is proved to be useful and effective with simulation results and is improved in the average delay of vehicles as well as the queue length.
出处
《计算机工程》
CAS
CSCD
北大核心
2004年第14期146-148,共3页
Computer Engineering
基金
江苏省教育厅自然科学基金资助项目(01KJD510013)
关键词
交通系统
模糊神经网络
交通信号控制
交通流仿真
Traffic system
Fuzzy neural network
Traffic signal control
Traffic flow simulation
