Developing an enhanced weight-based topological map-matching algorithm for intelligent transport systems

Map-matching (MM) algorithms integrate positioning data from a Global Positioning System (or a number of other positioning sensors) with a spatial road map with the aim of identifying the road segment on which a user (or a vehicle) is travelling and the location on that segment. Amongst the family of MM algorithms consisting of geometric, topological, probabilistic and advanced, topological MM (tMM) algorithms are relatively simple, easy and quick, enabling them to be implemented in real-time. Therefore, a tMM algorithm is used in many navigation devices manufactured by industry. However, existing tMM algorithms have a number of limitations which affect their performance relative to advanced MM algorithms. This paper demonstrates that it is possible by addressing these issues to significantly improve the performance of a tMM algorithm. This paper describes the development of an enhanced weight-based tMM algorithm in which the weights are determined from real-world field data using an optimisation technique. Two new weights for turn-restriction at junctions and link connectivity are introduced to improve the performance of matching, especially at junctions. A new procedure is developed for the initial map-matching process. Two consistency checks are introduced to minimise mismatches. The enhanced map-matching algorithm was tested using field data from dense urban areas and suburban areas. The algorithm identified 96.8% and 95.93% of the links correctly for positioning data collected in urban areas of central London and Washington, DC, respectively. In case of suburban area, in the west of London, the algorithm succeeded with 96.71% correct link identification with a horizontal accuracy of 9.81 m (2σ). This is superior to most existing topological MM algorithms and has the potential to support the navigation modules of many Intelligent Transport System (ITS) services.     

基于距离准则的地图匹配算法研究

为了弥补车辆导航中位置点匹配算法的不足,对轨迹曲线匹配的思想进行了必要的介绍,并重点从距离要素出发,对匹配准则进行了研究。在分析了各种常见距离定义的不足后,提出了基于面积法的距离匹配准则,并对距离准则的算法设计和适用性进行了详细的分析和描述。结论表明,采用该算法后的总体定位精度优于GPS的定位精度,算法准确性也比位置点匹配高。     

基于DAB信号的城市车辆定位方法研究

通过阐述数字音频广播的特点,发现DAB／GIS组合定位是一个高精度、高可靠性、经济、适用于车辆在复杂城市环境中的定位方案。同时,基于DAB定位伪距测量的原理和定位实现方法,可有效分析DAB信号定位技术的特点。该方法可对现有定位技术如GPS定位形成有益的补充。     

Map-matching poor-quality GPS data in urban environments: the pgMapMatch package

Global Positioning System (GPS) data have become ubiquitous in many areas of transportation planning and research. The usefulness of GPS data often depends on the points being matched to the true sequence of edges on the underlying street network – a process known as ‘map matching.’ This paper presents a new map-matching algorithm that is designed for use with poor-quality GPS traces in urban environments, where drivers may circle for parking and GPS quality may be affected by underground parking and tall buildings. The paper is accompanied by open-source Python code that is designed to work with a PostGIS spatial database. In a test dataset that includes many poor-quality traces, our new algorithm accurately matches about one-third more traces than a widely available alternative. Our algorithm also provides a ‘match score’ that evaluates the likelihood that the match for an individual trace is correct, reducing the need for manual inspection.     

卫星定位不停车收费中基于决策圈的路径识别方法

首次提出在复杂区域使用决策圈的方法进行地图匹配,并提出一种GPS地图匹配和设置决策圈结合的新的路段识别方法,用于解决高速公路卫星收费系统或车栽导航中复杂路段地图匹配不准确的问题.对常规地图匹配算法GPS由于精度难以匹配的路段区域设定决策圈,对决策圈内路段进行特殊匹配处理.在处理方法上利用预先采集到的路段上的准确点代替电...     

实时分布式地图匹配系统的设计与实现

在智能交通系统的基础上,设计实现了基于实时浮动车数据的分布式地图匹配系统.分布式架构的应用旨在提高系统数据接收和处理的实时性.同时提出了一种基于道路网格和最短路径的快速地图匹配算法,通过网格划分确定候选路段,根据二次网格划分、GPS角度和数量对候选路段权重进行修正,并利用最短路径算法寻求最符合路径,在保证处理效率的同时匹配的精度也有所提升.仿真实验选用三台匹配处理节点,经验证,完成大连市1000辆出租车约130万个GPS点的地图匹配用时为1分37秒,算法的平均正确匹配率为93.3％.实验结果满足实际智能交通系统的基本要求.     

基于GPS数据采集的出租汽车交通运行特点研究

对装载GPS的出租汽车采集到的数据进行预处理和地图匹配,实现了出租汽车路径的跟踪,确定了出租汽车上下客点的位置,据此可得到反映出租汽车交通运行特点的相关数据,为出租汽车交通管理乃至城市交通管理提供了科学依据.以深圳市装载GPS的出租汽车数据为例进行分析,通过一定的数据处理方法,利用Visual Basic和ArcView的组件Mapobject相结合进行编程,得到了深圳市出租汽车交通运行的特点,如出租汽车交通出行需求的空间分布、出租汽车出行距离分布、出租汽车出行时长分布等.     

浮动车系统地图的匹配精度

从地图匹配精度指标出发,针对浮动车系统的配置计划中的浮动车系统信息采集周期这一重要参数进行研究。分析浮动车系统数据特点,说明浮动车系统采集周期对浮动车服务质量的重要性;分析城市路网条件下精度随不同采集周期的变化情况,建立基于城市路网特征描述变量和采集周期等特征向量的地图匹配精度模型。模型由于包含城市路网特征描述向量,具有较高的移植性,应用此模型可以得到期望精度下采集周期的预测值,为浮动车系统的配置计划提供参考依据。     

卫星收费系统GPS定位信息和路段匹配方法研究

描述了1种GPS定位信息和电子地图收费路段匹配的方法,分为地图精简和地图匹配2部分。根据GPS定位收费系统对地图及地图匹配的要求,对电子地图进行了精简。路段识别采用了GPS位置点和路段收费位置节点的匹配方法,通过设定收费标示值,配合路段间拓扑关系、路段的收费属性值信息,进行地图匹配计算,判断当前车辆是否行驶在收费路段上,从而对行驶在收费路段的车辆进行通行费用计算、对收费地图信息进行精简处理、探讨分析影响地图匹配精度的因素、描述地图匹配的方法。该方法经过实验检测,并在高速公路卫星收费实验系统中实际运行,效果良好。