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利用大系统的分解-协调思想、模糊理论和神经网络技术来进行城市交通干线的实时协调控制.把交通干线作为一个大系统,子系统为干线上的各个交叉口,在此基础上,设计了一种城市交通干线的两级模糊协调控制算法并用BP神经网络实现.控制级在线调整各子系统的信号周期和绿信比;而协调级则根据测得的交通信息协调相邻子系统间的车辆数.控制目标是使干线交通畅通并使平均车辆延误时间尽可能小.最后进行了仿真研究,结果表明,该方法比车辆全感应式控制能有效地减小平均车辆延误.
In this paper, the real-time coordinated control of city traffic trunk is carried out by using the decomposition of large-scale system, coordination theory, fuzzy theory and neural network technology. Taking the communication trunk as a large system and the subsystem as the intersections on the main line, A two-level fuzzy coordination control algorithm for urban traffic trunk is realized by BP neural network.The control level adjusts the signal period and the green ratio of each subsystem online, while the coordination level coordinates the coordination between adjacent subsystems based on the measured traffic information The objective of control is to make the trunk traffic flow and the average vehicle delay time as small as possible.Finally, a simulation study is carried out, and the results show that this method can reduce the average vehicle delay effectively than the vehicle full-induction control.