智能交通系统信息采集终端的研究与实现

发布时间：2018-06-27 20:31

本文选题：交通图像 + 车数提取　；参考：《西安建筑科技大学》2015年硕士论文

【摘要】：随着社会的不断发展以及国民生活水平的提高,我国汽车的保有量也随之增加,进而造成越来越严重的交通拥堵,给人们的出行带来诸多不便,开发出一套行之有效的智能交通系统对监测和缓解交通拥堵具有重要的现实意义。本课题以智能交通信息采集终端为研究对象,以路况图像检测为研究重点,开展智能交通系统信息采集终端的研究。主要研究内容如下:首先开展对图像的预处理以及和背景图片相比较等算法的研究,进行图像信息和车流速信息的整合算法的研究,进行对现有算法的整合,设计出适合本系统的最优算法,通过这些算法来实现交通流量检测和交通路况的判定,并利用MATLAB进行仿真,以验证该算法的可行性和精度。其次是进行智能交通系统信息采集终端的硬件设计。该硬件系统包括:交通图像信息的采集模块,利用测速线圈进行的车速检测模块,数据的存储模块和图像处理模块。通过设计该硬件的具体电路将各个模块整合在一起,组成所需要特定功能的硬件系统,之后再对该系统的各个模块进行测试,检查各个模块是否能正常工作以及检查模块之间是否连接正确。最后是算法移植,将整合后的算法移植到本系统采用的DSP中,利用Visual DSP++5.1集成开发环境,调试基于ADSP-BF533的智能交通系统信息采集处理算法,实现系统的模拟运行。实验表明,系统能够将从交通图像中提取出的车数信息和模拟出的车速数据进行整合,并能准确判断出该研究路段的路况。
[Abstract]:With the continuous development of society and the improvement of national living standards, the number of cars in our country has also increased, which has caused more and more serious traffic congestion, and brought a lot of inconvenience to people's travel. It is very important to develop an effective intelligent transportation system for monitoring and alleviating traffic congestion. In this paper, the intelligent transportation information acquisition terminal is taken as the research object, and the road condition image detection is the focus of the research, and the research of the intelligent transportation system information acquisition terminal is carried out. The main research contents are as follows: firstly, the image preprocessing and background image comparison algorithms are studied, and the integration algorithms of image information and vehicle velocity information are studied, and the existing algorithms are integrated. An optimal algorithm is designed for this system, which can be used to detect traffic flow and determine traffic condition. MATLAB is used to simulate to verify the feasibility and accuracy of the algorithm. Secondly, the hardware design of intelligent transportation system information acquisition terminal is carried out. The hardware system includes: traffic image information acquisition module, speed detection module using speed coil, data storage module and image processing module. By designing the specific circuit of the hardware, the modules are integrated together to form a hardware system with specific functions, and then the modules of the system are tested. Check that each module works properly and that the connection between modules is correct. Finally, the algorithm is transplanted, the integrated algorithm is transplanted to the DSP used in this system, and the intelligent transportation system information collection and processing algorithm based on ADSP-BF533 is debugged by using Visual DSP 5.1 integrated development environment to realize the simulation operation of the system. The experimental results show that the system can integrate the vehicle number information extracted from the traffic image and the simulated speed data, and can accurately judge the road condition of the studied section.
【学位授予单位】：西安建筑科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U495;TP391.41

【参考文献】