基于RFID数据的城市道路交通状态判别方法

发布时间：2018-03-29 06:15

本文选题：交通状态判别　切入点：射频识别技术(RFID)　出处：《东南大学》2015年硕士论文

【摘要】：实时、准确的交通状态判别是交通管理、交通诱导和交通控制实现的前提和基础。城市交通状态的判别,必须依赖于交通信息采集技术和数据处理技术的发展。基于射频识别技术(RFID, Radio Frequency Identification Technology)和视频检测技术的综合交通数据采集可以获得地点速度和路段行程时间,基于上述数据,本文城市道路交通状态判别方法进行研究,主要研究内容如下。首先,在进行交通状态判别文献研究的基础上,根据基于RFID技术的交通数据采集原理和特点,提出了通过建立基站网络、匹配起终点基站过车数据和数据汇集得到平均行程时间的数据处理方法；介绍了基于视频检测技术的交通数据采集原理和根据采集到的原始数据获得平均地点速度的方法。并将交通状态划分为畅通、缓行和拥堵三种状态,研究了通过多人观看各基站的实时视频获得道路上实际交通状态的方法。其次,论文选择了特定的城市路网,包括43个基站,建立了61个基站对,采集了6个月的RFID数据,进行行程时间的计算,并对行程时间进行了多方面的分析,结果表明,基于RFID技术获得的行程时间数据可以很好的反映交通运行情况,可作为交通状态判别指标。再次,研究了以视频采集技术获得的平均地点速度为指标,结合实际交通状态,考虑到不同基站的具体情况,确定各基站的交通状态判别阂值的方法,并以南京市100个基站为实例对判别效果进行评价。最后,提出了以基于视频技术获取的起点基站平均地点速度和终点基站平均地点速度以及基于RFID技术获取的基站对平均行程时间为指标,基于模糊评判的交通状态判别方法,并以南京市某基站对为实例,将交通状态判别结果与实际交通状态进行对比,评价判别效果。将综合交通数据采集技术应用于交通状态判别是智能交通重要发展方向之一,在本文的研究基础上,对未来的研究方向进行了展望。
[Abstract]:Real-time and accurate identification of traffic state is the premise and foundation of traffic management, traffic guidance and traffic control. It must depend on the development of traffic information acquisition technology and data processing technology. The integrated traffic data acquisition based on RFID (Radio Frequency Identification Technology) and video detection technology can obtain the location speed and section travel time, based on the above data, The main contents of this paper are as follows: firstly, based on the research of traffic status discrimination literature, according to the principle and characteristics of traffic data collection based on RFID technology, A data processing method is proposed to get the average travel time by setting up the base station network and matching the traffic passing data and data collection of the terminal base station. This paper introduces the principle of traffic data acquisition based on video detection technology and the method of getting average location speed according to the original data collected. The traffic state is divided into three states: smooth, slow and congested. This paper studies the method of obtaining the actual traffic state on the road by watching the real-time video of each base station by many people. Secondly, the paper selects a specific urban network, including 43 base stations, establishes 61 base station pairs, and collects RFID data for 6 months. The results show that the travel time data based on RFID technology can well reflect the traffic situation, and can be used as a traffic state discrimination index. This paper studies the method of determining the threshold value of traffic state of each base station according to the actual traffic state and considering the specific conditions of different base stations, taking the average site speed obtained by video capture technology as the index, and considering the specific conditions of different base stations. And take 100 base stations in Nanjing as an example to evaluate the discriminant effect. Finally, Based on the average location speed of the base station and the average location speed of the terminal base station obtained by video technology and the average travel time of the base station acquired by RFID technology, the traffic state discrimination method based on fuzzy evaluation is proposed. Taking a base station pair in Nanjing as an example, the result of traffic condition discrimination is compared with the actual traffic state, and the discriminant effect is evaluated. It is one of the important development directions of intelligent transportation to apply comprehensive traffic data acquisition technology to traffic condition discrimination. Based on the research in this paper, the future research direction is prospected.
【学位授予单位】：东南大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U491

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