基于物联网的交叉口智能交通灯控制系统设计与实现

摘****要

智能视频监控技术是近年来新兴的一种利用计算机视觉技术,人工智能技术和数字视频处理技术对监控视频的目标进行识别,通过对此的分析处理,从而对视频监控系统进行控制,智能视频监控技术是一项较为复杂的课题。特别是对运动物体的识别检测并跟踪显示是智能视频监控领域的一项热点研究问题,如何在复杂的环境下准确的识别出物体特征仍是该领域内研究的难点。

随着我国微型电子技术和嵌入式系统的发展,目前行业内相对比较传统的交通灯无法满足客户的需求。为了改进传统交通灯在控制上得短板问题,在本次毕业设计中,将使用相对先进、快捷、智能的控制机制。该系统的控制大脑为核心控制器51系列嵌入式开发系统,主要采用数字控制技术,将输入的连续模拟电压信号转换成离散的数字信号,传输给液晶显示器。该交通灯设计具有智能控制、数字显示等功能,而且性价比高、度准确、能耗较低、制作简易、称重方便快捷等特点,给人民生活带来了很大的影响,在市场上很受欢迎。

本文主要探讨并提出一种了利用视频监控系统采集路面通过车辆的图像信息,以三种视频监控算法光流法、帧间差分法、背景差分法为基础,计算监控道路的车流量,根据车流量与下位机的配合,合理分配交通灯的时间,以减缓交通压力,以便更快更迅速地疏导道路交通。为了验证设计系统,在实验阶段,依靠嵌入式平台开发了一套仿真验证模型,分别在该嵌入式平台及上位机平台上,用相同的核心图像处理算法,进行了实验验证,取得了良好的效果。

该智能控制系统设计主要从国内外发展状况,硬件控制部件选择,根据控制原理绘制硬件电路,控制系统软件程序设计开发等方面进行详细讲解。该控制系统使用STC89C52RC嵌入式开发系统、电路显示部分、按键电路等组成智能交通灯控制系统。

关键词:交通灯;单片机;显示;视频监控;车流量

Abstract

Intelligent video surveillance technology is a new technology in recent years, which uses computer vision technology, artificial intelligence technology and digital video processing technology to identify the target of surveillance video, through the analysis and processing of this, so as to control the video surveillance system, intelligent video surveillance technology is a relatively complex subject. In particular, the recognition, detection and tracking display of moving objects is a hot research issue in the field of intelligent video surveillance. How to accurately identify object features in a complex environment is still a difficulty in this field.

With the development of micro-electronic technology and embedded system in our country, the current industry relatively traditional traffic lights can not meet customer needs. In order to improve the traditional traffic lights in the control of the short board problem, in this graduation design, will use relatively advanced, fast, intelligent control mechanism. The control brain of the system is the core controller 51 series embedded development system, which mainly uses digital control technology to convert the input continuous analog voltage signal into discrete digital signal, which is transmitted to the LCD. The traffic light design has intelligent control, digital display and other functions, and cost-effective, accurate, low energy consumption, simple production, weighing convenient and fast characteristics, to people's lives has brought a great impact on the market is very popular.

This paper mainly discusses and proposes a video surveillance system to collect the road through the vehicle image information, on the basis of three video surveillance algorithms optical flow method, frame difference method, background difference method, calculation monitoring road traffic flow, according to the traffic flow and the coordination of the lower machine, reasonable allocation of traffic light time, in order to slow down the traffic pressure, in order to more quickly and more quickly the road traffic. In order to verify the design system, in the experimental stage, a set of simulation verification model is developed based on the embedded platform. The same core image processing algorithm is used to carry out experimental verification on the embedded platform and the upper computer platform respectively, and good results are obtained.

The intelligent control system design mainly from the domestic and foreign development status, hardware control components selection, according to the control principle to draw the hardware circuit, control system software programming and development are explained in detail. The control system uses STC89C52RC embedded development system, circuit display part, key circuit and so on to form intelligent traffic light control system.

Key words: Single chip microcomputer; Video surveillance;Timing;traffic

完整论文点击如下链接下载:

https://download.csdn.net/download/weixin_45905610/88573345

基于物联网的交叉口智能交通灯控制系统设计与实现资源-CSDN文库

matlab建模仿真点击如下链接下载:

https://download.csdn.net/download/weixin_45905610/88573415

基于物联网的交叉口智能交通灯控制系统设计与实现-matlab仿真资源-CSDN文库

单片机程序+原理图+proteus仿真点击如下链接下载:

https://download.csdn.net/download/weixin_45905610/88573350

基于物联网的交叉口智能交通灯控制系统设计与实现-proteus仿真资源-CSDN文库

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