基于地理格网的复杂路线车辆通行时间估算方法

车辆通行时间隐含了特定时隙的交通状况,准确地汁算该时间在交通监测和路径规划中具有重要意义。现有研究通常利用车辆历史轨迹佔算一定距离内选定路径的通行时间,然而当路径距离较长时,限于很难找到完整穿越指定路径的历史轨迹而无法对其通行时间进行准确估计;此外,海量历史轨迹在估计路径通行时间时会产生巨大的数据管理和计算压力因此,本文引入地理格网,首先构建统一的时空索引,将路网及其历史轨迹分别划分为-系列落在地理格网单;(Cell)中的路段模式及轨迹段;然肩利用一系列频繁共享轨迹在Cell中的停留时间计算车辆在当前路段模式的通行时间;最肩通过一组防史时段相似路径模式的通行时间估算较长路线的车辆通行时间通过对北京市10000辆出租车一周的轨迹数据进行试验,验证了本文方法在处理海量历史轨迹数据上的有效性,以及在估算较氏路径上车辆通行时间的优越性。     

出租车GPS轨迹集聚和精细化路网提取

针对利用GPS数据提取双向路网和交叉路口转向信息精度低的不足,本文提出一种顾及位置与行驶方向的轨迹集聚和精细化路网提取方法,实现了精细化路网提取。为提高交叉路口路网的提取精度,首先剔除原始轨迹中的离散和异常轨迹点,并按一定的步长对轨迹段进行加密;然后引入行驶方向角来表达车辆在轨迹点处的行驶方向,顾及位置和行驶方向获取每个轨迹点的相似轨迹点集合;接着依次计算每个轨迹点的偏移距离,通过对轨迹点的迭代偏移完成轨迹集聚;最后剔除未成功集聚的轨迹点,将完成集聚的轨迹点连成轨迹线并作缓冲区,运用栅格数据数字化方法提取得到能够反映道路精细转向关系的道路网。以福州市出租车GPS数据进行轨迹集聚和路网提取试验,结果表明:本文方法能有效地将GPS轨迹按车辆行驶方向分别进行集聚,提取的道路网为双向道路并且能反映交叉路口处道路的精细转向关系。     

基于GPS与GIS集成的车辆导航系统设计与实现

介绍了基于GPS与GIS集成的车辆导航系统设计与实现 ,探讨了导航系统中电子地图的空间数据组织 ,提出了GPS信号与GIS路网数据匹配、快速的邮路选择、最佳路径选择、地图随驾驶方向快速实时旋转技术及语音提示、语音识别技术的使用。     

城市道路复杂度的浮动车自适应采样算法

基于浮动车的城市交通信息采集技术是智能交通系统获取实时交通信息的重要手段之一。针对浮动车的城市交通信息等间距采样的不足,本文设计了一种基于城市道路复杂度的自适应采样算法:①根据道路属性定义道路结点对城市道路网络复杂度的影响因子;②利用四叉树对城市道路网络复杂度进行描述;③根据浮动车的瞬时速度和道路复杂度自适应计算浮动车的采样周期。通过仿真和试验表明,新算法能够在不同复杂程度的道路情况下自适应提供有效、可靠的采样周期。     

提供导航支持的车辆监控系统

本文对GPS与GIS的集成方式、GPS信号的解析、地图匹配、最短路径算法进行了研究，通过GPRS（通用分组无线业务）信息的传输实现监控中心与车辆之间的无线通信和信息交互，来实现车辆导航监控。     

A Chain-Code-Based Map Matching Algorithm for Wheelchair Navigation

Accurate vehicle tracking is essential for navigation systems to function correctly. Unfortunately, GPS data is still plagued with errors that frequently produce inaccurate trajectories. Research in map matching algorithms focuses on how to efficiently match GPS tracking data to the underlying road network. This article presents an innovative map matching algorithm that considers the trajectory of the data rather than merely the current position as in the typical map matching case. Instead of computing the precise angle which is traditionally used, a discrete eight-direction chain code, to represent a trend of movement, is used. Coupled with distance information, map matching decisions are made by comparing the differences between trajectories representing the road segments and GPS tracking data chain-codes. Moreover, to contrast the performance of the chain-code algorithm, two evaluation strategies, linear and non-linear, are analyzed. The presented chain-code map matching algorithm was evaluated for wheelchair navigation using university campus sidewalk data. The evaluation results indicate that the algorithm is efficient in terms of accuracy and computational time.     

一种改进的浮动车地图匹配算法

现有地图匹配算法应用于低频方式采样的浮动车GPS数据时匹配准确度与匹配效率不能同时兼顾。基于此,本文提出了一种改进的浮动车地图匹配算法,基于改进的自适应电子地图网格划分方法快速确定待匹配定位点候选路段集,基于最短距离权重、车辆航向权重、最短路径权重及轨迹方向权重的总权重准确确定最优匹配路段及匹配点。试验结果表明,该算法在保证匹配效率的同时提高了算法的匹配准确度。     

基于GPS时空轨迹的路网拓扑自动变化检测

充分利用出租车GPS时空轨迹数据分布广和时效性强的特点,提出一种基于车载GPS轨迹数据的路网拓扑自动变化检测新方法。该方法首先利用向量相似性度量模型,度量GPS轨迹向量与路网局部拓扑向量之间的相似性,检测疑似道路拓扑变化点,然后通过比较疑似道路拓扑变化点与路网拓扑关系,完成新增、废弃、改建等道路变化,实现基于车载GPS轨迹的路网拓扑自动变化检测。实验结果表明,该方法不仅有效地检测出道路新增、道路废弃与道路改扩建等变化,而且能利用出租车实时和大范围分布特点来实现城市路网大范围实时变化检测。     

城市汽车导航中一种改进的D-S证据理论地图匹配算法

车联网中基于D-S证据理论的地图匹配算法,通常考察定位点到候选道路的投影距离和车辆行驶方向与候选道路的角度差这两种证据。目前城市交通网络结构日趋复杂,此算法得到的匹配结果有一定的局限性,匹配精度也无法满足车联网技术的需求。随着GPS等定位设备的不断发展与改进,车辆的行驶速度与定位时间间隔等数据已可以准确获取,在此基础上,本文对车辆的可达性信息进行考察,作为新的证据与传统证据融合后得到的结果进行D-S证据的二次融合。除此之外,本文针对城市环境中不同道路拓扑结构,对传统算法中的位置信息和车辆行驶方向信息的可靠性参数进行仿真训练,得出更为精确的可靠性参数值以供改进的算法使用。通过仿真实验表明,改进后的算法的匹配精度和稳定性得到了极大的提高,可以更好地适用于城市复杂路网中地图匹配的问题。     

基于STL的A*路径规划算法设计与实验

以图论作为理论基础分析道路网络数据,采用C 标准模板库(STL),针对道路网络的特征,分析设计了A*路径规划算法并给出实例。     

A general map matching algorithm for transport telematics applications

This paper describes a map-matching algorithm designed to support the navigational functions of a real-time vehicle performance and emissions monitoring system currently under development, and other transport telematics applications. The algorithm is used together with the outputs of an extended Kalman filter formulation for the integration of GPS and dead reckoning data, and a spatial digital database of the road network, to provide continuous, accurate and reliable vehicle location on a given road segment. This is irrespective of the constraints of the operational environment, thus alleviating outage and accuracy problems associated with the use of stand-alone location sensors. The map-matching algorithm has been tested using real field data and has been found to be superior to existing algorithms, particularly in how it performs at road intersections.     

嵌入式GIS中最优路径规划算法研究与实现

针对现有大区域范围路径规划算法存在的一些问题,提出一种多比例尺最优路径规划算法。该算法在进行路径规划时,在小区域范围内根据道路的属性信息对路网进行分层,在大区域范围内根据多比例尺信息对路网进行分级,在每级或每层内采用基于弧段的改进型A*算法。从实例分析可以看出,该算法能较好满足车载导航系统的需求。     

Improving Spatial Accuracy of Roadway Networks and Geocoded Addresses

Exposure to traffic‐related pollutants is associated with both morbidity and mortality. Because vehicle‐exhaust are highly localized, within a few hundred meters of heavily traveled roadways, highly accurate spatial data are critical in studies concerned with exposure to vehicle emissions. We compared the positional accuracy of a widely used U.S. Geological Survey (USGS) roadway network containing traffic activity data versus a global positioning system (GPS)‐validated road network without traffic information; developed a geographical information system (GIS)‐based methodology for producing improved roadway data associated with traffic activities; evaluated errors from geocoding processes; and used the CALINE4 dispersion model to demonstrate potential exposure misclassifications due to inaccurate roadway data or incorrectly geocoded addresses. The GIS‐based algorithm we developed was effective in transferring vehicle activity information from the less accurate USGS roadway network to a GPS‐accurate road network, with a match rate exceeding 95%. Large discrepancies, up to hundreds of meters, were found between the two roadway networks, with the GPS‐validated network having higher spatial accuracy. In addition, identifying and correcting errors associated with geocoding resulted in improved address matching. We demonstrated that discrepancies in roadway geometry and geocoding errors, can lead to serious exposure misclassifications, up to an order of magnitude in assigned pollutant concentrations.     

Extracting spatial patterns in bicycle routes from crowdsourced data

Much is done nowadays to provide cyclists with safe and sustainable road infrastructure. Its development requires the investigation of road usage and interactions between traffic commuters. This article is focused on exploiting crowdsourced user‐generated data, namely GPS trajectories collected by cyclists and road network infrastructure generated by citizens, to extract and analyze spatial patterns and road‐type use of cyclists in urban environments. Since user‐generated data shows data‐deficiencies, we introduce tailored spatial data‐handling processes for which several algorithms are developed and implemented. These include data filtering and segmentation, map‐matching and spatial arrangement of GPS trajectories with the road network. A spatial analysis and a characterization of road‐type use are then carried out to investigate and identify specific spatial patterns of cycle routes. The proposed analysis was applied to the cities of Amsterdam (The Netherlands) and Osnabrück (Germany), proving its feasibility and reliability in mining road‐type use and extracting pattern information and preferences. This information can help users who wish to explore friendlier and more interesting cycle patterns, based on collective usage, as well as city planners and transportation experts wishing to pinpoint areas most in need of further development and planning.     

图卷积网络在道路网选取中的应用

针对现有制图综合中的道路网自动选取方法不能有效地利用道路网的空间特征问题,该文把道路网抽象为图结构,提出了使用图卷积网络来进行道路网的自动选取,并比较分析了不同的图卷积网络在道路网选取中的适用性。结果表明,图卷积网络可以通过多层卷积来自动提取不同局部范围的空间特征,从而减少空间特征的人工构建,相比传统的多层感知机(MLP)等人工智能选取方法,具有更高的选取精度。对于不同的图卷积网络模型,使用最大池化聚合的GraphSAGE获得了最优的性能。     

顾及多要素影响的路网匹配改进算法

针对导航地图中现有的匹配算法在复杂路段的匹配效果一般较差的问题,本文提出一种改进的匹配算法。首先,引入分块思想,提出将路网中的每个路段按规则分为简单路段块和复杂路段块,不同路段块采取不同的匹配算法;其次,充分利用车辆行驶的连续性,综合考虑了车辆行驶方向、车速与交叉口距离等多种因素对匹配结果的影响,在选取正确的匹配路段时合理利用了历史数据信息。实验表明,该算法不但对能够改善复杂路段的匹配效果,而且还能够对匹配点沿路段方向上的误差进行实时校正。     

Integrated compression of vehicle spatio‐temporal trajectories under the road stroke network constraint

With fast growth of all kinds of trajectory datasets, how to effectively manage the trajectory data of moving objects has received a lot of attention. This study proposes a spatio‐temporal data integrated compression method of vehicle trajectories based on stroke paths coding compression under the road stroke network constraint. The road stroke network is first constructed according to the principle of continuous coherence in Gestalt psychology, and then two types of Huffman tree—a road strokes Huffman tree and a stroke paths Huffman tree—are built, based respectively on the importance function of road strokes and vehicle visiting frequency of stroke paths. After the vehicle trajectories are map matched to the spatial paths in the road network, the Huffman codes of the road strokes and stroke paths are used to compress the trajectory spatial paths. An opening window algorithm is used to simplify the trajectory temporal data depicted on a time–distance polyline by setting the maximum allowable speed difference as the threshold. Through analysis of the relative spatio‐temporal relationship between the preceding and latter feature tracking points, the spatio‐temporal data of the feature tracking points are all converted to binary codes together, accordingly achieving integrated compression of trajectory spatio‐temporal data. A series of comparative experiments between the proposed method and representative state‐of‐the‐art methods are carried out on a real massive taxi trajectory dataset from five aspects, and the experimental results indicate that our method has the highest compression ratio. Meanwhile, this method also has favorable performance in other aspects: compression and decompression time overhead, storage space overhead, and historical dataset training time overhead.     

利用道路网眼实现路网的增量式更新

获取现势性的交通道路数据是数字城市和智慧城市建设的基础,基于传统测绘的道路网更新方法存在一定局限性,而基于众源数据及行车轨迹数据更新道路网近年来则倍受关注。首先提出了一种新的道路变化增量更新方法,该方法先对历史道路网建立面拓扑结构,生成由道路网组成的最小闭合面域（道路网眼）;然后以道路网眼为基本控制单元,综合利用轨迹点上下文距离信息和隐马尔可夫模型（hidden Markov model,HMM）,提取失配轨迹点和失配轨迹段;最后采用缓冲区分析和最大密度法对失配轨迹提取骨架线,创建新增道路,增量更新历史道路网。实验结果表明,以道路网眼为控制单元,利用轨迹点上下文距离分析和HMM捕获失配轨迹点,可提高失配轨迹点的提取效率,改善道路网更新效果。该方法可用于大规模路网的增量式更新。     

Personalized travel route recommendation using collaborative filtering based on GPS trajectories

Travelling is a critical component of daily life. With new technology, personalized travel route recommendations are possible and have become a new research area. A personalized travel route recommendation refers to plan an optimal travel route between two geographical locations, based on the road networks and users’ travel preferences. In this paper, we define users’ travel behaviours from their historical Global Positioning System (GPS) trajectories and propose two personalized travel route recommendation methods – collaborative travel route recommendation (CTRR) and an extended version of CTRR (CTRR+). Both methods consider users’ personal travel preferences based on their historical GPS trajectories. In this paper, we first estimate users’ travel behaviour frequencies by using collaborative filtering technique. A route with the maximum probability of a user’s travel behaviour is then generated based on the naïve Bayes model. The CTRR+ method improves the performances of CTRR by taking into account cold start users and integrating distance with the user travel behaviour probability. This paper also conducts some case studies based on a real GPS trajectory data set from Beijing, China. The experimental results show that the proposed CTRR and CTRR+ methods achieve better results for travel route recommendations compared with the shortest distance path method.     

车辆轨迹数据提取道路交叉口特征的决策树模型

众源车辆轨迹数据隐含最新的道路分布信息,研究利用轨迹数据提取道路特征有益于基础路网数据的快速建库与更新。道路网由交叉口和连接交叉口的道路线构成,其中交叉口特征识别是整个道路网生成的关键。由于缺乏精细的交叉口识别模型,轨迹数据生成的道路网容易出现路口遗漏、结构失真等现象。针对这一问题,本文提出一种利用轨迹数据提取道路交叉口的方法。首先,分析车辆在交叉口与非交叉口区域移动轨迹几何形态及隐含动力学特征的变化情形;然后,利用决策树方法构建轨迹片段分类模型,并结合移动开窗式的轨迹线剖分模型建立交叉口区域变道轨迹片段提取方法;最后,依据Hausdorff距离对交叉口区域轨迹片段进行聚类,并提取中心线获得完整的道路交叉口结构。采用真实的车辆轨迹线作为测试数据,验证了本文提出方法的有效性。