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Automatic estimation of road inclinations by fusing GPS readings with OSM and ASTER GDEM2 data

机译:通过将GPS读数与OSM和ASTER GDEM2数据融合来自动估计道路倾角

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This work focuses on a method of estimating the slope of road networks that are ground-modeled by OSM originally. The aim is to get 3-D road vectors including their 2-D location and inclination, that is an important parameter to ensure more reliable route planning. This is done from GPS data that are collected by a vehicle traveling on an existing OSM road network whose a DEM, like SRTM or ASTER data, provides a modeling of the terrain surface. GPS, OSM and DEM data are modeled as measurement equations in order to account for their errors through an UKF that fuses them in a centralized scheme. Here, the key step is to match GPS/OSM/DEM measurements successively by computing statistical Mahalanobis distances. The experimental framework show some results of road inclinations estimation and the significant contribution of a DEM as baseline.
机译:这项工作着重于一种估计最初由OSM进行地面建模的道路网络的坡度的方法。目的是获得包括其2D位置和倾斜度的3D道路矢量,这是确保更可靠的路线规划的重要参数。这是通过在现有OSM道路网络上行驶的车辆收集的GPS数据完成的,该OSM道路网络的DEM(例如SRTM或ASTER数据)提供了地形表面的建模。 GPS,OSM和DEM数据被建模为测量方程,以便通过UKF解决它们的错误,该UKF将它们融合在集中式方案中。在这里,关键步骤是通过计算统计马氏距离来连续匹配GPS / OSM / DEM测量值。实验框架显示了道路倾斜度估算的一些结果以及DEM作为基线的重要贡献。

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