基于GPS轨迹的道路拓扑构建和路径选择方法研究
发布时间：2019-03-30 20:38
【摘要】：当前,我国城市道路建设速度远远落后于汽车数量增长的速度,再加上交通资源配置不合理,造成了经常性的交通拥堵,导致严重的资源浪费和环境污染。智能交通系统作为一种新型运输系统,可以合理分配资源、提高道路通行能力,有效地改善交通状况。电子地图是智能交通系统的最基本元素,其基本功能包括路网显示、实时导航、路径推荐等等,因其信息丰富、交互性好等优点,极大地方便了人们的出行。但是,传统的电子地图制作方法成本高、更新慢,难以适应当前路网更新频繁的现状,因此,研究如何快速有效地更新路网信息,从而为人们提供最新的导航、路径推荐等功能,具有很强的现实意义和广阔的应用前景。GPS数据记载了移动对象的轨迹信息,如果对这些数据加以分析,就可以为路网更新提供辅助信息,节省电子地图的制作成本。此外,带有定位功能的硬件设备价格降低和智能手机的迅速普及,使得人们可以很容易收集到道路GPS数据。因此,基于GPS轨迹的时空数据挖掘技术逐渐成为了智能交通系统领域的研究热点之一。出租车作为商业性的交通工具,具有行驶时间长、轨迹范围广、车辆基数大、数据收集成本低的优点,因此,使用出租车GPS轨迹数据进行路网更新及路径选择具有非常大的优势。本文采用微软亚洲研究院(MSRA)提供的公开数据集(2007年4月到2010年10月的北京市出租车GPS数据),主要做了以下三个方面的工作:(1)GPS轨迹预处理。首先去除带有误差的数据,再利用滚动式聚类算法得到所有轨迹数据区域内主干道的道路,最后通过与Google Map对比,证明了路网的准确性;(2)提出一种基于出租车GPS轨迹的路网拓扑构建方法。它是路径导航和道路选择的前提。为了获得最新的道路及其连接关系,本文采用基于出租车GPS轨迹的路口识别方法,利用(1)中获得的道路,考虑路口处道路点数目要多的特征提取出路口,并进一步完成路网的拓扑构建,最后通过与Google Map、北京市shp地图对比,证明了路口的准确性;(3)提出了一种基于四叉堆的道路选择方法。根据(1)中的道路以及(2)中获得的拓扑关系和各条道路段长度,结合历史GPS轨迹数据,使用一个基于四叉堆优先队列的Dijkstra方法进一步实现了最短、最优路径选择的功能。
[Abstract]:At present, the speed of urban road construction in our country lags far behind the increasing speed of the number of cars, coupled with the unreasonable allocation of traffic resources, resulting in frequent traffic congestion, resulting in serious waste of resources and environmental pollution. As a new type of transportation system, intelligent transportation system can allocate resources reasonably, improve traffic capacity and improve traffic condition effectively. Electronic map is the most basic element of intelligent transportation system. Its basic functions include road network display, real-time navigation, path recommendation and so on. Because of its rich information, good interaction and other advantages, it greatly facilitates people to travel. However, the traditional electronic map making method has high cost and slow updating, so it is difficult to adapt to the current situation of frequent road network updating. Therefore, how to update the road network information quickly and effectively is studied, so as to provide people with the latest navigation. Path recommendation and other functions have a strong practical significance and broad application prospects. GPS data records the trajectory information of moving objects, and if these data are analyzed, it can provide auxiliary information for road network updating. Save the cost of making electronic maps. In addition, the reduced price of hardware devices with positioning capabilities and the rapid popularity of smartphones make it easy to collect road GPS data. Therefore, spatio-temporal data mining technology based on GPS trajectory has gradually become one of the research hotspots in the field of intelligent transportation system. As a commercial means of transportation, taxi has the advantages of long driving time, wide range of tracks, large cardinality of vehicles and low cost of data collection. The use of taxi GPS track data for road network updating and path selection has great advantages. Based on the open data set provided by Microsoft Asia Research Institute (MSRA) (Beijing taxi GPS data from April 2007 to October 2010), the following three aspects of work have been done: (1) GPS track preprocessing. Firstly, the data with errors is removed, and then the roads of the main roads in all trajectory data regions are obtained by using the rolling clustering algorithm. Finally, the accuracy of the road network is proved by comparing with Google Map. (2) A road network topology construction method based on taxi GPS trajectory is proposed. It is the premise of path navigation and road selection. In order to obtain up-to-date road and its connection relationship, this paper adopts the intersection recognition method based on taxi GPS track, using the road obtained in (1), taking into account the features of the number of road points at the intersection to extract the intersection. And further complete the road network topology construction, finally through the comparison with Google Map, Beijing shp map, proved the accuracy of the intersection; (3) A road selection method based on quad reactor is proposed. According to the path in (1) and the topological relation and the length of each road segment obtained in (2), combined with the historical GPS trajectory data, a Dijkstra method based on quad-heap priority queue is used to further realize the function of shortest and optimal path selection.
【学位授予单位】：湖南科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U495;TP311.13
本文编号：2450463
[Abstract]:At present, the speed of urban road construction in our country lags far behind the increasing speed of the number of cars, coupled with the unreasonable allocation of traffic resources, resulting in frequent traffic congestion, resulting in serious waste of resources and environmental pollution. As a new type of transportation system, intelligent transportation system can allocate resources reasonably, improve traffic capacity and improve traffic condition effectively. Electronic map is the most basic element of intelligent transportation system. Its basic functions include road network display, real-time navigation, path recommendation and so on. Because of its rich information, good interaction and other advantages, it greatly facilitates people to travel. However, the traditional electronic map making method has high cost and slow updating, so it is difficult to adapt to the current situation of frequent road network updating. Therefore, how to update the road network information quickly and effectively is studied, so as to provide people with the latest navigation. Path recommendation and other functions have a strong practical significance and broad application prospects. GPS data records the trajectory information of moving objects, and if these data are analyzed, it can provide auxiliary information for road network updating. Save the cost of making electronic maps. In addition, the reduced price of hardware devices with positioning capabilities and the rapid popularity of smartphones make it easy to collect road GPS data. Therefore, spatio-temporal data mining technology based on GPS trajectory has gradually become one of the research hotspots in the field of intelligent transportation system. As a commercial means of transportation, taxi has the advantages of long driving time, wide range of tracks, large cardinality of vehicles and low cost of data collection. The use of taxi GPS track data for road network updating and path selection has great advantages. Based on the open data set provided by Microsoft Asia Research Institute (MSRA) (Beijing taxi GPS data from April 2007 to October 2010), the following three aspects of work have been done: (1) GPS track preprocessing. Firstly, the data with errors is removed, and then the roads of the main roads in all trajectory data regions are obtained by using the rolling clustering algorithm. Finally, the accuracy of the road network is proved by comparing with Google Map. (2) A road network topology construction method based on taxi GPS trajectory is proposed. It is the premise of path navigation and road selection. In order to obtain up-to-date road and its connection relationship, this paper adopts the intersection recognition method based on taxi GPS track, using the road obtained in (1), taking into account the features of the number of road points at the intersection to extract the intersection. And further complete the road network topology construction, finally through the comparison with Google Map, Beijing shp map, proved the accuracy of the intersection; (3) A road selection method based on quad reactor is proposed. According to the path in (1) and the topological relation and the length of each road segment obtained in (2), combined with the historical GPS trajectory data, a Dijkstra method based on quad-heap priority queue is used to further realize the function of shortest and optimal path selection.
【学位授予单位】：湖南科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U495;TP311.13
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