基于GPS浮动车的城市交通状态时空分布规律研究

发布时间：2019-02-14 21:04

【摘要】：城市道路作为城市交通运输的基础设施,为城市居民生活,工作,文化娱乐活动提供出行便利,其运行状态和效率越来越受到人们的关注。由于城市发展的不平衡性,在开发比较早、比较成熟的区域,出行的车流量和人流量往往比较多,在开发比较迟的区域,出行的人流量和车流量则相对比较少,这使得城市道路交通状态在空间上的分布具有差异性；由于人们在不同的时间具有不同的出行需求,造成城市交通状态在时间上的分布也会具有差异性。因而如何获取和掌握城市道路交通状态的时空分布特点和规律成为出行者和交通规划管理者都比较关注的问题。随着GPS定位技术,无线定位与传输技术的发展,移动式交通信息采集技术使城市交通信息的采集变得更高效快捷,覆盖范围更广,为研究城市交通状态时空分布规律提供了数据支持。论文以昆明市GPS浮动出租车采集的数据和昆明市路网数据为例,研究了昆明市的交通状态时空分布规律。首先,数据预处理及地图匹配。在对GPS浮动车数据特征分析的基础上对浮动车数据做了预处理,剔除影响提取交通参数精度的数据,并对浮动车数据的坐标做了转换,通过地图匹配使浮动车数据匹配到相应的道路上。其次,路段交通参数提取及交通状态分类。回顾和总结了GPS浮动车数据估计路段交通参数的方法及模型,阐述了路段平均行程速度估计方法,并利用浮动车数据提取了段平均行程速度,建立交通状态评价指标体系,依据路段平均行程速度和分类标准对路段交通状态分类。再次,交通状态时空分布规律研究。根据城市交通状态的时间和空间属性,构建了昆明市交通状态时空数据库,并在ArcGIS10.1平台上实现了时空数据的动态可视化。在交通状态评价指标及时空数据库基础上分析了昆明市交通状态的时空分布规律,并获得了有效结论。最后,对全文的研究工作做了总结,并提出了论文研究的不足及对后续的研究工作的展望。
[Abstract]:As the infrastructure of urban transportation, urban roads provide convenient travel for urban residents' life, work, cultural and recreational activities. People pay more and more attention to the operation state and efficiency of urban roads. Because of the imbalance in urban development, in the areas where the development is relatively early and mature, the traffic flow and passenger flow are often higher, while in the areas where the development is relatively late, the number of people traveling and the traffic flow are relatively low. This makes the distribution of urban road traffic state in the space has the difference; Because people have different travel demand at different time, the distribution of urban traffic state will be different in time. Therefore, how to obtain and master the spatial and temporal distribution of urban road traffic status has become a problem that both travelers and traffic planning managers pay more attention to. With the development of GPS location technology, wireless location and transmission technology, mobile traffic information acquisition technology makes the collection of urban traffic information more efficient, faster and wider coverage. It provides data support for studying the temporal and spatial distribution of urban traffic state. Taking the data collected by GPS floating taxi and road network data of Kunming as an example, this paper studies the temporal and spatial distribution of traffic state in Kunming. First, data preprocessing and map matching. On the basis of analyzing the characteristics of GPS floating vehicle data, the floating vehicle data is preprocessed, and the data which affect the precision of extracting traffic parameters are eliminated, and the coordinate of the floating vehicle data is transformed. The floating vehicle data is matched to the corresponding road by map matching. Secondly, the extraction of traffic parameters and traffic state classification. This paper reviews and summarizes the methods and models of GPS floating vehicle data to estimate the traffic parameters of road sections, expounds the method of estimating the average travel speed of road sections, and extracts the average travel speed of sections by using the data of floating vehicles, and establishes the evaluation index system of traffic status. According to the average travel speed and classification standard, the traffic state of road section is classified. Thirdly, the temporal and spatial distribution of traffic state is studied. According to the temporal and spatial attributes of urban traffic state, the temporal and spatial database of traffic state in Kunming is constructed, and the dynamic visualization of space-time data is realized on ArcGIS10.1 platform. Based on the evaluation index of traffic state and spatiotemporal database, the temporal and spatial distribution of traffic state in Kunming is analyzed, and an effective conclusion is obtained. Finally, the research work of this paper is summarized, and the deficiency of the thesis and the prospect of the future research work are put forward.
【学位授予单位】：昆明理工大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：U495;P208

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