Updating road network databases using GNSS

C. Boucher, J. Noyer
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Abstract

This paper presents a method to detect missing roads and to update GIS map databases from GPS data. It relies on an extended Kalman filter that fuses, in a centralized fusion scheme, available GPS and road map data. The map is modeled as an additional sensor which allows a direct modeling of the map errors and uncertainties. A probabilistic map-matching algorithm is used to manage the road network database through the computation of the Mahalanobis distance. We show experimental results from an urban transport network scenario where roads are missing, due to an outdated database.
利用GNSS更新道路网数据库
本文提出了一种基于GPS数据的道路缺失检测和GIS地图数据库更新方法。它依赖于一个扩展的卡尔曼滤波器,在一个集中的融合方案中融合可用的GPS和路线图数据。地图被建模为一个附加的传感器,它允许对地图误差和不确定性进行直接建模。通过计算马氏距离,采用概率地图匹配算法对路网数据库进行管理。我们展示了一个城市交通网络场景的实验结果,其中由于数据库过时,道路缺失。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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