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题名	交通灯自适应控制算法研究
作者	黎威
学位类别	硕士
答辩日期	2014-05-28
授予单位	中国科学院沈阳自动化研究所
导师	曹云侠
关键词	交通信号灯 单路口 模糊控制 粒子群优化算法 干线协调控制
其他题名	Research on Adaptive Control Algorithm of Traffic Lights
学位专业	控制理论与控制工程
中文摘要	近年来，随着国内城市机动车辆的数量不断增加，城市环境污染、交通拥堵问题日益严重，道路拥堵问题已经成为制约我国城市经济发展和城市化进程的瓶颈。 在城市交通控制过程中，由于交通流具有随机性、不确定性和时变性等特点，使得基于交通数学模型的传统信号灯控制方法很难获得最佳的控制效果，因此，信号灯智能控制方法目前成为了交通控制领域的主要研究方向之一。本文从信号灯智能控制方向出发，融合模糊控制和粒子群算法，对城市交通信号灯智能控制展开研究，主要内容和研究成果如下： 第一，首先以单交叉口信号灯为研究对象，设计了一个信号灯两级模糊控制器，提出了四相位模糊控制算法。采用MATLAB编写了仿真程序，和信号灯定时控制方式的控制效果做了比较，仿真结果显示，模糊控制方式能够更大程度地降低车辆平均延误时间，因此验证了该方法的有效性。 第二，虽然基于模糊逻辑的信号灯控制方式不需要建立精确的交通系统数学模型，但是模糊控制这种智能控制自身也存在一些缺陷，比如，模糊变量隶属度函数选取和控制器模糊控制规则确定没有统一的标准，很大程度上依赖设计者的工程经验。针对这一问题，本文提出了一种改进的量子粒子群算法（IQPSO），并采用该优化算法对信号灯模糊控制器控制规则进行优化，仿真结果显示，信号灯模糊控制器经过优化之后，能够进一步地降低车辆在交叉口的平均延误时间。 第三，在单路口信号灯模糊控制的研究基础上，将研究对象推广到干线上相邻的几个交叉口，提出了一种干线信号灯模糊协调控制方案并进行了仿真，仿真结果显示，和单点控制方式相比，干线信号灯模糊协调控制能够降低车队在干线上行驶的平均延误时间。 最后，对本文的研究进行了总结，指出了本文研究的不足和待研究的内容，对信号灯的未来发展趋势进行了展望。
索取号	TP273/L27/2014
英文摘要	In these years, with the rapid growth of urban vehicles, traffic congestion and pollutions are becoming severe; traffic congestion at intersections has become a bottleneck to urban economy rising and development. In urban traffic control, traditional signal control methods based on accurate traffic mathematic model cannot guarantee the best performance for the reason of time-variable, stochastic and uncertain characteristics of traffic flow. Traffic signal intelligent control methods have begun to act as a main way in urban traffic signal control research field. Therefore, in this paper, traffic signal intelligent control method combined with fuzzy logic and Particle Swarm Optimization (PSO) is analyzed. The main points and research results are as follows: Firstly, the research object is limited to a single intersection. A two-level signal fuzzy controller is designed and four-phase fuzzy control algorithm is put forward. The simulation platform is MATLAB. Compared with traditional signal fixed-time control method, the two-level fuzzy control method put forward in this paper has better performance in the aspect of reducing average vehicles’ delay, which proves that signal fuzzy method is effective. Secondly, though signal fuzzy logic control does not need to set up precise mathematic model, however, it has drawbacks, for instance, there is no standard way to determine the fuzzy control rules and membership functions, which largely depends on the experienced designers. In order to solve this problem, improved quantum particle swarm optimization (IQPSO) artefical algorithm is adopted in this paper to optimize the fuzzy rules of signal controller. The simulation results show that signal control with optimization has better performance in the aspect of reducing average vehicles delay than method without optimization. Thirdly, taking the mutual influence of adjacent intersections in the same arterial into consideration, arterial signals coordinated fuzzy control are analyzed. An coordinated fuzzy control method is proposed in this paper. The simulation result shows that coordinated fuzzy control method can further reduce vehicles’ delay while driving through several intersections in arterial than isolated control method. Finally, the research needing to be improved in this paper is point out and future prospects in signal control are drawn.
语种	中文
产权排序	1
页码	71页
分类号	TP273
内容类型	学位论文
源URL	[http://ir.sia.ac.cn/handle/173321/14778]
专题	沈阳自动化研究所_智能检测与装备研究室
推荐引用方式 GB/T 7714	黎威. 交通灯自适应控制算法研究[D]. 中国科学院沈阳自动化研究所. 2014.

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