A Trajectory-Oriented, Carriageway-Based Road Network Data Model, Part 2： Methodology

IntroductionIf let roadway entities be denoted by arcs and in-tersections be denoted by nodes, then a road net-work can be represented with node-arc model. Be-cause the designation of nodes can be determinedby arcs according to the definition of node-arc mod-el, howto designate arcs becomes the key of repre-senting a road network. As described in the firstpaper of the series, all four kinds of roadway enti-ties (i.e., streets, road segments, carriageways,and lanes) can be represented by arcs. …     

A trajectory-oriented carriageway-based road network data model,part 1: Background

This is the first of a three-part series of papers which introduces a general background of building trajectory-oriented road network data models, including motivation, related works, and basic concepts. The purpose of the series is to develop a trajectory-oriented road network data model, namely carriageway-based road network data model (CRNM). Part 1 deals with the modeling background. Part 2 proposes the principle and architecture of the CRNM. Part 3 investigates the implementation of the CRNM in a case study. In the present paper, the challenges of managing trajectory data are discussed. Then, developing trajectory-oriented road network data models is proposed as a solution and existing road network data models are reviewed. Basic representation approaches of a road network are introduced as well as its constitution.     

A trajectory-oriented carriageway-based road network data model, part 1: Background

Introduction Withthedramaticdevelopmentofpositioning andtelecommunicationtechnologies,lotsoftraj ectorydataofmovingvehiclescanbecalculated,collected,andtransferred.Inthemeanwhile,thisdevelopmentandtheavailabilityoftrajectory datahavealsomotivatedresearche…     

A Trajectory-Oriented Carriageway-Based Road Network Data Model, Part 3: Implementation

IntroductionThe LRM based on the CRNMis a kind oflink-and-node LRM. As introduced in the firstpaper of the series ,the link-and-node LRMdoesnot designate any fixed reference point along aroad segment in advance but employs the nodesin the node-arc model d…     

A trajectory-oriented carriageway-based road network data model,part 3: Implementation

This is the final of a three-part series of papers which mainly discusses the implementation issues of the CRNM. The first two papers in the series have introduced the modeling background and methodology, respectively. An overall architecture of the CRNM has been proposed in the last paper. On the basis of the above discusses, a linear reference method (LRM) for providing spatial references for location points of a trajectory is developed. A case study is introduced to illustrate the application of the CRNM for modeling a road network in the real world is given. A comprehensive conclusion is given for the series of papers.     

Interface Roughness by Optical Coherence MicroscopyZHU Yong-kai~(1),LI Ji-nian~(1)

IntroductionIf let roadway entities be denoted by arcs and in-tersections be denoted by nodes, then a road net-work can be represented with node-arc model. Be-cause the designation of nodes can be determinedby arcs according to the definition of node-arc …     

Rural Road Surface Extraction Using Mobile LiDAR Point Cloud Data

The existing roadway infrastructures are mostly archived with two-dimensional (2D) drawings that lack the possibility for three-dimensional (3D) interpretation and advanced 3D analysis. The mobile LiDAR system (MLS) is gaining popularity in 3D mapping applications along various types of road corridors. MLS achieves the highest data quality and completeness among the traditional roadway data collection methods. The rural roads in different countries especially in India form a substantial portion of the road network. Therefore the proper maintenance and road safety analysis of rural roads are recommended activity, which could be addressed using detailed 3D road surface information. The absence of raised curb at road boundary, and presence of complexity, heterogeneity and occlusions along the rural roadway settings restrict the use of existing studies for road surface extraction using MLS point cloud data. Therefore considering the above requirement, this research paper proposes a two-stage method. The first stage extract planar ground surfaces which are further used to filter road surface in the second stage. Global properties of road, that is, topology and smoothness and its radiometric response to laser beam of MLS are used in the second stage. MLS point cloud data of rural roadway were used to test the proposed method. The road surface points were accurately extracted without being affected by the absence of raised curb and hanging objects over the road surface, that is, tree canopies and overhead power lines. The quantitative assessment of the proposed method was performed in terms of correctness, completeness and quality, which were 96.3, 94.2, and 90.9%, respectively.     

车辆轨迹数据的道路学习提取法

车辆轨迹数据的道路信息提取是地理信息领域的热点也是难点之一,深度学习的快速发展为该问题的解决提供了一种思路与方法。本文针对车辆轨迹数据的车行道级道路提取问题,引入深度学习领域的生成式对抗网络,利用残差网络构建深层网络和多尺度感受野感知轨迹数据不同细节特征,构建了基于条件生成式对抗网络的轨迹方向约束下车行道级道路提取模型。首先提出了朝向-颜色映射栅格化转换方法,实现轨迹朝向信息向HSV颜色空间的转换;然后利用样本数据学习模型参数;最后将训练模型应用到郑州、成都、南京3个试验区域提取车行道级道路数据。试验结果表明,本文方法能够有效地提取完整的车行道级道路数据。     

结合轨迹数据的混合多特征道路网选取方法

道路网选取是制图综合的重要内容,针对现有方法仅考虑道路网静态特征等问题,提出了一种结合轨迹数据的混合多特征选取方法。首先以stroke为基本选取单元,构建对偶图来描述路网的结构关系,采用长度、连通度、接近度和中介度等指标对道路的静态特征进行评价;然后结合轨迹数据特点,采用车流量、车辆速度和道路交叉口附近的车辆密度等指标对道路的动态特征进行评价;最后利用基于相互关系准则的标准重要性方法计算得到各指标的权值及各道路的综合重要性值。同时引入线Voronoi图对道路进行划分,得到道路的密度特征值,并将其作为道路网选取的约束指标。实验结果表明,所提方法能够保持道路的整体结构,同时顾及道路的连通性和密度分布,而且结合了轨迹数据的动态交通特性,选取结果符合实际情况,具有一定的实用性。     

基于地理实体的道路网络面向对象数据模型研究

城市交通迅速发展,道路网络呈现出空间结构复杂、数据量大、时效性强等特点。本文讨论了传统路网模型的特点,顾及道路的信息完整性、数据冗余性、管理高效性3个指标,研究了以道路实体为基本元素的路网模型;运用面向对象技术对路网模型进行了数据建模,并通过动态交通信息更新机制对路网的动态属性进行管理;构建了城市道路实体化实验系统,验证了该模型的有效性和可行性。     

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.     

基于时序数据库的空间数据处理

分析了空间数据和时间序列数据的基本概念,提出了引入时序数据库技术来解决传统数据库在处理海量数据时遇到的存储容量和访问效率方面的问题.使用时序数据库可以很好地解决目前时序数据所遇到的一些问题.最后介绍了一种特殊的时间序列数据库的技术架构和使用该架构时间序列数据库处理空间数据的相关案例.该种架构的时间序列数据库可以更好地处理时序数据和空间数据相结合的问题.     

基于多种相似度特征的道路实体融合方法

随着城市建设步伐的加快和基础地理信息应用领域的扩展,国家经济建设和人民群众生活对基础地理信息的需求越来越大,对基础地理信息的现势性和更新频率也提出了更高的要求。因此,对不同精度、不同来源的地理信息数据融合技术进行研究具有十分重要的意义。道路实体是重要的基础地理信息,尤其是铁路、高速、国省道、城市主干道。本文重点围绕道路实体研究数据间的差异性,建立了自动匹配评价指标;并基于FME平台搭建同名匹配、变化检测和增量更新模型,实现了道路实体自动更新和融合,缩短了道路实体更新周期。“十三五”第2轮基础测绘更新项目利用该技术完成了重要道路实体的融合,证明了该技术的可行性和准确性,为新型基础测绘体系的建设提供了技术支撑。     

基于形态分割的高分辨率遥感影像道路提取

基于灰度形态学,提出一种从高分辨率遥感图像提取道路网络的方法.首先利用灰度形态特征对遥感影像进行分割,进而得到基本的道路网络轮廓.然后在此基础上,利用线段特征匹配方法提取道路网络.提出的方法能适应于从道路和背景区别不很清楚的遥感图像中提取道路.实验结果也表明,本文方法能有效地从遥感影像中提取道路网络.     

嵌入式导航终端互补分级路网拓扑模型的研究及实现

路径分析是嵌入式导航终端的基本功能。在层次空间数据模型的基础上,本文提出了互补分级数据模型,将整个路网拓扑分为概括拓扑和辅助拓扑两级,并给出两级路网拓扑数据快速合并机制形成详细路网拓扑,使得嵌入式硬件平台上远距离路径分析效率更高。     

航拍图像跨数据域特征迁移道路提取方法

针对传统道路提取方法应用于新数据泛化能力不足的问题,研究了通过特征迁移和编解码网络实现跨数据域的道路提取方法。首先,构建了基于编解码网络的道路提取基本模型,用于实现单一数据来源的道路提取任务。然后,基于道路提取网络结构和循环一致性原则,提出了用于跨数据域图像特征迁移的循环生成对抗网络,使目标域图像映射入源域特征空间。使用预训练的道路提取模型处理特征迁移后的目标域图像,即可实现跨数据域道路提取任务。试验结果表明,本文所提方法能够拓展道路提取网络的泛化能力,准确有效地提取跨数据域图像中的道路目标。相较于未特征迁移的结果,本文所提方法大幅改善了道路提取指标,使得F1提升了50%以上。本文方法不需要目标域的标注信息,也不需要对道路提取网络进行微调训练,而只需训练由目标域向源域的特征迁移模型,所耗时间和人力成本较低,因而具有良好的应用价值。     

广州市公众地理信息服务平台的设计与开发

论述了城市基础测绘部门开发公众地理信息平台的必要性和优势,分析并讨论了公共地理信息服务平台中的公众地理信息服务平台、基础地理信息服务平台和政务地理信息服务平台在数据内容、功能框架、网络体系、服务对象上的不同,以广州市公众地理信息服务平台的开发为例,详细介绍了该平台的数据内容、功能框架和系统特色,该平台对其他城市开发类似的公众地理信息服务平台具有一定的参考作用。     

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.     

一种支持城市路网交通关系自动化的智能模型

针对车载导航、地图网站等应用中路网要素之间交通关系维护的难题,提出一种支持路网要素交通关系自动化的智能过程模型,将路网要素交通关系自动化过程理解为由路网要素间的空间和语义关系、规则集和控制系统组成的产生式系统.该产生式系统可在路网要素空间和语义信息基础上,通过定义可扩展的交通关系规则集,自动化地生成符合应用需求的路网要素间的交通关系.此外,在该产生式系统中引入触发器概念监控和响应几何网络及其交通关系规则集的变更,实时更新逻辑网络中的连通关系信息,实现几何网络、规则集和逻辑网络三者的一致性.同时,提出路网要素交通关系处理的控制策略和关键流程,并对该智能网络模型的有效性进行了验证.

Abstract：

Maintaining the traffic connectivity relations between road features has always been a time consuming task for in-vehicle navigation, map website, and other traveling service related applications. Such a task has been commonly conducted artificially and inevitably inefficient, yet makes data quality control difficult. Considering the intrinsic rules of traffic connectivity formed by the geometrical structures, spatial and semantic relationships between road features in city road networks, an intelligent processing model is set forward in this paper for traffic connectivity automation. It is argued that traffic connectivity automation between road features is fundamentally a production system composed of the spatial and semantic relations between road features, connectivity rules and control system. With the implementation of an extendable connectivity rule set, the traffic connectivity relations between road network features are built automatically based on the spatial and semantic information of road network. The trigger concept is adopted to monitor and respond the changes in geometrical network and connectivity rules, and then dynamically updates the traffic connectivity between road network features in logical network so as to guarantee the consistence between geometrical network, connectivity rules and logical network. A series of control strategies and a conducting engine are developed to maintain the traffic connectivity relations. A case study conducted on a real road network verifies the effects of the proposed intelligent model.     

“数字成都”地理空间框架数据生产及关键技术探讨

"数字城市"地理空间框架建设的重点是通过对地理信息数据的整合,在共享与交换平台的基础上,为公共管理与社会公众提供服务。其中,数据建设是地理空间框架建设的基础。通过介绍"数字成都"地理空间框架项目中地理实体与电子地图的生产流程,并探讨了生产过程中存在的关键技术,对其他城市开展地理空间框架数据建设具有借鉴意义。