城市交叉口感应式信号控制机工作原理研究

毕业论文

论文题目：城市交叉口感应式信号控制机工作原理研究

系部：电子信息工程系

专业名称：电子信息技术

班级: 08431 学号：52

姓名：郭世朋

指导老师：吕磊

完成时间：2011 年 5 月 13 日

【摘要】：目前，交通拥挤问题是世界各国的普遍性问题，它直接影响经济的发展和人们的生活。智能交通系统(ITS)是在不重修道路的情况下解决这一日益严重的问题的有效途径。在ITS中，交通数据采集设备占据重要位置，只有在掌握大量的交通数据的前提下，才可能实现智能交通。车辆检测器就担负着交通数据采集的任务，因而具有重要的研究意义。环形线圈车辆检测器具有性能稳定，性价比高，适应性强等优点，市场应用最为广泛。本文设计了一种基于DSP的环形线圈车辆检测器，并以此车检器采集的数据为基础，设计了基于车辆排队长度的单交叉口模糊控制器。具体来说，本论文主要开展了如下方面的研究：(1)对交通进行有效的控制必须以采集到正确、实时交通流量信息为基础，为了准确检测车流量，完成了基于DSP的环形线圈车辆检测器的软硬件设计。(2)在本设计中充分考虑到目前环形线圈车辆检测器的一些问题，如误检率较高、灵敏度变化范围较小、不能存储历史交通数据等，运用软硬件手段加以解决，得到了比较好的效果。(3)对该检测器进行了验证实验，证明了其正确性和有效性，并对实验结果进行分析；运用阈值滤波方法进行了车辆分类研究，将通过的车辆分成大型、中型和小型及非机动车辆，在对历史交通数据作分析时有一定的现实意义。

(4)运用采集到的交通流量数据，完成基于车辆排队长度的单交叉口模糊控制器的设计，进行了Matlab仿真，并跟定时控制的结果进行了对比。

关键字：城市交叉口感应式检测器信号控制机

【Abstract】:Currently, the traffic congestion problem is the universality of the world, which directly affects economic development and people's lives. Intelligent Transportation Systems (ITS) is not restored in the case of the road to address this growing problem and effective way. In the ITS, the traffic data collection equipment occupies an important position, only to master a large number of traffic data under the premise of intelligent transportation is possible. Vehicle detector to shoulder the task of traffic data collection, and thus has important research significance.Loop Vehicle Detector with stable performance, cost-effective, adaptable, etc., the most widely used market. This paper presents a DSP-based vehicle detector loop coil, and as vehicle inspection device based on data collected, the vehicle queue length is designed based on a single intersection of fuzzy controller. Specifically, this paper carried out the following aspects: (1) effective control of traffic must be properly collected, based on real-time traffic information, in order to accurately detect the traffic flow at the completion of Loop DSP-based vehicle detector hardware and software design. (2) In this design, full account of the current loop vehicle detector loop problems such as high false detection rate, sensitivity, small range, can not store historical traffic data, etc., the use of hardware and software tools to solve, has been compared good results. (3) to verify the detector test to prove its correctness and validity of the experimental results were analyzed; threshold filtering method using vehicle classification, the vehicles will be divided into large, medium and small and non-motorized vehicles, in the analysis of historical traffic data for a certain practical significance. (4) the use of traffic data collected to complete the queue