城市干线交通信号协调模糊控制算法的研究

发布时间：2019-03-27 21:48

【摘要】：随着社会经济的快速发展,人民生活水平的不断提高,更多的车辆开始进入每个家庭,使城市交通的拥堵情况更加严重,如何利用道路资源,通过制定科学合理的智能控制方法,最大限度的提高城市道路的通行能力就显得尤其重要。主干道承载着城市交通的主要部分,它的畅通与否直接决定着整个交通系统的正常运行。因此,本文以城市交通干线为研究对象,对干线交通信号的协调模糊控制算法展开研究。考虑到城市交通的复杂性和现有控制方法的不足,本文以减小干线交通系统中的平均排队长度为控制目标,将模糊理论与遗传算法用于干线协调控制研究中,此研究对城市干线协调控制的发展具有一定的理论和现实意义。首先对干线协调控制的研究现状进行了阐述,详细介绍了本文研究所需要的理论知识。根据干线系统形成的条件,建立了干线系统模型;针对车流信息获取的问题,在建立模型的基础上介绍了车辆检测器的设置方法,并给出了干线各个路口车流协调一致的模型;根据对干线系统模型的分析,设计了干线协调模糊控制整体方案。其次,对干线协调模糊控制整体方案进行了深入细致的研究。此方案主要由协调级和控制级组成,协调级主要根据双向滤波原理和每个路口之间的交通流情况,为每个路口提供优化的周期和相位差,并根据具体的交通流情况对协调级的控制算法及模糊控制器进行了设计;控制级主要是把单个路口作为研究对象,对每个路口进行信号配时优化,针对控制单元传统的两级模糊控制算法存在的问题,对其进行了改进,用改进的算法来决定是否进行相位切换,并设计了改进的两级模糊控制器。以焦作市塔南路干线上站前路、工业路和建设路三个路口为仿真对象进行仿真验证,证明改进的协调模糊控制算法能减小路口的平均排队长度,提高塔南路干线交通的通行能力。最后,针对模糊控制器中的模糊规则库不能根据交通流的剧烈变化而动态调整的问题,用自适应遗传算法对模糊规则进行优化,使模糊控制规则能根据交通流的不同自适应的变化。根据焦作市塔南路干线上的实际交通流情况进行仿真,与未优化的两级模糊控制器对比,证明优化后的模糊控制器能取得更好的控制效果。
[Abstract]:With the rapid development of the social economy and the continuous improvement of the people's living standard, more and more vehicles begin to enter every family, which makes the traffic congestion in the city more serious. How to utilize the road resources? By making scientific and reasonable intelligent control methods, it is particularly important to improve the capacity of urban roads to the maximum extent. The main road carries the main part of the urban traffic, its smooth or not directly determines the normal operation of the whole traffic system. Therefore, this paper takes the urban traffic trunk line as the research object, and studies the coordinated fuzzy control algorithm of the trunk traffic signal. Considering the complexity of urban traffic and the deficiency of existing control methods, this paper takes reducing the average queue length in trunk traffic system as the control objective, and applies fuzzy theory and genetic algorithm to the study of coordinated control of trunk lines. This research is of theoretical and practical significance to the development of coordinated control of urban trunk lines. Firstly, the research status of coordinated control of trunk lines is described, and the theoretical knowledge required in this paper is introduced in detail. According to the forming condition of the trunk line system, the model of the trunk line system is established, aiming at the problem of obtaining the traffic flow information, the method of setting up the vehicle detector is introduced on the basis of establishing the model, and the model of the coordination and consistency of the traffic flow at each intersection of the trunk line is given. According to the analysis of the trunk system model, the overall scheme of coordinated fuzzy control is designed. Secondly, the whole scheme of coordinated fuzzy control of trunk line is studied deeply and meticulously. This scheme is mainly composed of coordination level and control level. According to the principle of two-way filtering and the traffic flow between each intersection, the coordination stage provides the optimal period and phase difference for each intersection. According to the specific traffic flow, the control algorithm and fuzzy controller of coordination level are designed. The control level mainly takes a single intersection as the research object and optimizes the signal timing of each intersection. Aiming at the problems existing in the traditional two-level fuzzy control algorithm of the control unit, it is improved. An improved two-stage fuzzy controller is designed to determine whether to switch phase or not. The simulation results show that the improved coordinated fuzzy control algorithm can reduce the average queue length of the intersection, taking the front road, industrial road and construction road of Tannan Road in Jiaozuo City as the simulation objects, and it is proved that the improved coordinated fuzzy control algorithm can reduce the average queue length of the intersection. Improve the traffic capacity of the Tannan Road main Line. Finally, aiming at the problem that the fuzzy rule base in the fuzzy controller can not be dynamically adjusted according to the drastic change of traffic flow, an adaptive genetic algorithm is used to optimize the fuzzy rules. The fuzzy control rules can be changed adaptively according to different traffic flow. According to the actual traffic flow on the Tannan Road of Jiaozuo City, the simulation results show that the optimized fuzzy controller can achieve better control effect compared with the unoptimized two-stage fuzzy controller.
【学位授予单位】：河南理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U491.54

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