基于地磁传感器的交通流量无线检测技术研究

发布时间：2018-11-10 12:23

【摘要】：城市交通拥堵加剧导致了城市交通运行效率的低下,降低了社会生产力,成为制约我国城市发展的重要因素之一。智能交通系统(ITS)作为改善城市交通拥堵提高交通运行效率的手法之一,日渐受到各国的关注。车辆检测技术作为智能交通系统中重要的组成部分,通过它准确实的获取实时基础交通信息,为ITS提供必要的数据来源,进而实现交通的实时监控和智能管理。基于磁阻传感器的车辆检测器具有体积小、灵敏度高、易安装等特点,很好的弥补了传统检测器的不足。同时,城市网络的日益复杂,大多交通指挥设备没有与监控中心联网,对现有设备进行网络化的升级势在必行,为车辆检测技术的发展提供了新的方向。本论文的研究内容和成果包括以下几个方面:1、本文着重研究了智能交通系统中的车辆检测技术以及交通监控设备网络化升级方法,设计了基于磁阻传感器的新型车辆检测器以及基于STM32F407的智能网关。在节点数据采集方面,设计了基于ZigBee无线传感网络的交通数据采集优化模型和算法,实现了车流量、车速、车型分类等交通数据的实时判别。无线传感网络无需布线、组网灵活可大规模部署。2、综合研究分析了国内外交通监控设备联接网络的方法,设计了一款基于STM32F407的智能网关模块。同时设计了协调器与智能网关的数据传输协议,协议中主要包含主机ID、节点ID、系统时间、车流量等信息,网关接收到的数据以txt格式保存到SD卡中。该网关模块具有低功耗、高性能、低成本易于开发使用等优势,实现了交通数据的上传、存储、WEB访问等功能,达到了车辆检测系统的网络化的目标。3、对无线地磁传感节点以及智能网关模块进行了整体的软硬件设计。利用车辆检测器采集车辆通过检测区域时的实验数据,深入分析了车辆检测信号,并在此基础上提出了基于自适应阈值的均方差车辆检测算法,通过分析处理实验数据,本文设计的车辆检测算法检测精度达到了99.4%。对于速度检测,通过采用双节点测速的方法,检测精度可达90%。实验结果表明本文设计的算法检测精度高,漏检、误检率低,能够及时准确的检测路口车辆信息,为路口红绿灯的动态调节提供了及时高效的车流量数据。
[Abstract]:The aggravation of urban traffic congestion leads to the low efficiency of urban traffic operation, reduces the social productivity, and becomes one of the important factors restricting the urban development of our country. Intelligent Transportation system (ITS), as one of the methods to improve traffic congestion and improve traffic efficiency, has been paid more and more attention by many countries. As an important part of intelligent transportation system, vehicle detection technology can obtain real-time traffic information accurately and provide the necessary data source for ITS, so as to realize real-time traffic monitoring and intelligent management. The vehicle detector based on the magnetoresistive sensor has the advantages of small size, high sensitivity and easy installation, which makes up for the deficiency of the traditional detector. At the same time, with the increasing complexity of the urban network, most of the traffic command equipment is not connected with the monitoring center. It is imperative to upgrade the existing equipment network, which provides a new direction for the development of vehicle detection technology. The research contents and achievements of this paper include the following aspects: 1. This paper focuses on the vehicle detection technology in intelligent transportation system and the network upgrade method of traffic monitoring equipment. A new vehicle detector based on magnetoresistive sensor and an intelligent gateway based on STM32F407 are designed. In the aspect of node data acquisition, the traffic data acquisition optimization model and algorithm based on ZigBee wireless sensor network are designed, and the real-time identification of traffic data such as vehicle flow, speed and vehicle classification is realized. Wireless sensor networks need not be wired and can be deployed on a large scale flexibly. 2. The method of connecting domestic and foreign traffic monitoring equipment is studied and analyzed, and an intelligent gateway module based on STM32F407 is designed. At the same time, the data transfer protocol between the coordinator and the intelligent gateway is designed. The protocol mainly includes the information of the host ID, node ID, system time, traffic flow and so on. The data received by the gateway is saved to the SD card in txt format. The gateway module has the advantages of low power consumption, high performance, low cost and easy to develop and use. It realizes the functions of traffic data upload, storage and WEB access, and achieves the goal of networking vehicle detection system. The hardware and software of the wireless geomagnetic sensor node and the intelligent gateway module are designed. The vehicle detection signal is deeply analyzed by using vehicle detector to collect the experimental data of vehicle passing through the detection area. On this basis, an adaptive threshold based mean square error vehicle detection algorithm is proposed, and the experimental data are analyzed and processed. The detection accuracy of the vehicle detection algorithm designed in this paper reaches 99.4%. For velocity detection, the accuracy can reach 90 by adopting the method of two-node velocity measurement. The experimental results show that the algorithm designed in this paper has the advantages of high detection accuracy, missing detection and low false detection rate. It can detect the traffic information of intersection in time and accurately, and provide timely and efficient traffic flow data for the dynamic regulation of traffic lights.
【学位授予单位】：合肥工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U491.11

【参考文献】