基于手机定位的高速公路特殊路况识别研究

发布时间：2018-02-08 09:32

本文关键词： 高速公路手机定位模糊聚类分析车辆识别路况识别　出处：《长安大学》2016年硕士论文　论文类型：学位论文

【摘要】：自上世纪九十年代以来,我国高速公路蓬勃发展,总里程也在2012年超越美国跃居世界第一位。高速公路作为陆路运输的主要通道,但其运营问题也越来越突出。由于自然灾害、车辆事故、设施损坏等原因造成的不良路况,对高速公路运行安全与效率产生巨大影响。高速公路的特性,也使得高速公路事故的严重性要高于一般道路的交通事故。高速公路不良路况的实时识别,对高速公路运营安全与效率具有重要意义。传统的高速公路信息识别方法,多需要布设固定的检测设备,无法实现高速路网的覆盖。随着手机和移动通信网络的普及和覆盖率提高,利用手机作为探测器的交通信息识别方兴未艾,是智能交通研究的重点内容。本文研究了利用车载手机定位信息的高速公路特殊路况识别方法,围绕此课题主要做了以下几点研究:第一,参阅大量的国内外文献资料,分析国内手机的普及率和高速公路运行特性,论证利用手机定位方法识别高速公路路况信息的可行性,并进行了高速公路路况识别方案研究。第二,研究了高速公路数据采集方法,通过分析各种定位技术的适用性,确定信息采集方式,然后根据高速公路运行特性进行数据筛选,最后利用地图匹配技术,得到修正过的手机定位数据,用作系统识别。第三,研究了利用模糊聚类分析的高速公路车辆识别方法和路况识别方法,确定了系统初始的判别关键参数指标。并根据研究的识别方法,利用MATLAB分不同的情况进行仿真数据分析,取得较好的识别效果。最后,论述了研究内容的实例应用案例,详细叙述了基于研究技术的系统功能实现过程。本文主要创新点包括:第一,利用模糊聚类分析进行高速公路独立车辆识别,并采用(Fλ-Fα)差值最大的F检验方法,确定最佳聚类阈值和聚类结果。第二,高速公路车辆识别,车型划分速度指标的确定。第三,基于模糊聚类识别的高速公路特殊路况识别及事故车辆特性指标的确定。
[Abstract]:Since -10s, the highway of our country has been booming, and the total mileage has surpassed the United States in 2012 to become the first in the world. Expressway is regarded as the main passage of overland transportation, but its operation problem is more and more prominent. Due to natural disasters, The bad road conditions caused by vehicle accidents and facilities damage have a great impact on the safety and efficiency of expressway operation. It also makes the severity of highway accidents higher than that of ordinary road accidents. The real-time identification of bad highway conditions is of great significance to the safety and efficiency of expressway operation. With the popularization and increase of coverage of mobile phone and mobile communication network, traffic information identification using mobile phone as detector is in the ascendant. It is the key content of intelligent transportation research. This paper studies the identification method of freeway special road condition based on mobile phone positioning information, and does the following research around this topic: first, referring to a large number of domestic and foreign literature, This paper analyzes the popularization rate of domestic mobile phones and the characteristics of expressway operation, demonstrates the feasibility of using mobile phone positioning method to identify highway road condition information, and makes a study on expressway road condition recognition scheme. Second, This paper studies the method of highway data acquisition, through analyzing the applicability of various positioning techniques, determines the way of information collection, then selects the data according to the operating characteristics of the highway, and finally uses the map matching technology. The modified mobile phone location data is obtained for system recognition. Thirdly, the highway vehicle recognition method and road condition recognition method based on fuzzy clustering analysis are studied. The key parameters of the system are determined at the beginning of the system. According to the identification method studied, the simulation data are analyzed by using MATLAB in different cases, and good recognition results are obtained. Finally, the application case of the research content is discussed. The realization process of the system function based on the research technology is described in detail. The main innovations of this paper are as follows: first, using fuzzy clustering analysis to identify the freeway independent vehicles, and adopting the F test method with the maximum difference of F 位 -F 伪. Determine the best clustering threshold and clustering results. Second, freeway vehicle identification, vehicle classification speed index determination. Third, based on fuzzy clustering recognition of expressway special road condition recognition and accident vehicle characteristics index determination.
【学位授予单位】：长安大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：U495

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