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Techniques for Updating Pedestrian Network Data Including Facilities and Obstructions Information for Transportation of Vulnerable People

机译:更新包括弱势人群交通设施和障碍物信息在内的行人网络数据的技术

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摘要

Demand for a Pedestrian Navigation Service (PNS) is on the rise. To provide a PNS for the transportation of vulnerable people, more detailed information of pedestrian facilities and obstructions should be included in Pedestrian Network Data (PND) used for PNS. Such data can be constructed efficiently by collecting GPS trajectories and integrating them with the existing PND. However, these two kinds of data have geometric differences and topological inconsistencies that need to be addressed. In this paper, we provide a methodology for integrating pedestrian facilities and obstructions information with an existing PND. At first we extracted the significant points from user-collected GPS trajectory by identifying the geometric difference index and attributes of each point. Then the extracted points were used to make an initial solution of the matching between the trajectory and the PND. Two geometrical algorithms were proposed and applied to reduce two kinds of errors in the matching: on dual lines and on intersections. Using the final solution for the matching, we reconstructed the node/link structure of PND including the facilities and obstructions information. Finally, performance was assessed with a test site and 79.2% of the collected data were correctly integrated with the PND.
机译:对行人导航服务(PNS)的需求正在上升。为了为弱势人群的运输提供PNS,应在用于PNS的行人网络数据(PND)中包含更多行人设施和障碍物的详细信息。通过收集GPS轨迹并将其与现有的PND集成,可以有效地构造此类数据。但是,这两种数据具有几何差异和拓扑不一致性,需要解决。在本文中,我们提供了一种将行人设施和障碍物信息与现有PND集成的方法。首先,我们通过识别几何差异指数和每个点的属性,从用户收集的GPS轨迹中提取重要点。然后,将提取的点用于对轨迹和PND之间的匹配进行初始求解。提出了两种几何算法并将其应用于减少匹配中的两种误差:双线和交点。使用最终的匹配解决方案,我们重建了PND的节点/链接结构,其中包括设施和障碍物信息。最后,通过测试站点评估性能,并将79.2%的收集数据与PND正确集成。

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