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A map matching algorithm based on a particle filter

机译:一种基于粒子滤波器的地图匹配算法

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Map matching is the process of finding a match for each GPS point in a vehicle's trajectory to roads on a digital map. Extensive research has been conducted during the last years yielding many algorithms based on different approaches. One of the challenges that face those algorithms is the interruption of GPS signals that occurs specially in dense urban environments. In these cases on-board sensors like odometers and accelerometers can be used temporarily for positioning, however due to the poor accuracy of these methods, the quality of map matching decreases significantly. In this paper, we propose a method that improves the quality of map matching when GPS signals are not available. This method is based on a particle filter using heading and velocity measurement. We evaluate this method through its integration with an existing topological map matching algorithm. We compare the performances when this algorithm is used alone and when associated with the particle filter.
机译:地图匹配是在数字地图上的道路上查找车辆轨迹中每个GPS点的匹配过程。在过去几年中进行了广泛的研究,从而获得了基于不同方法的许多算法。面临这些算法的挑战之一是在密集的城市环境中出现的GPS信号的中断。在这些情况下,机舱传感器,如管道和加速度计可以暂时用于定位,但由于这些方法的准确性差,地图匹配质量显着降低。在本文中,我们提出了一种提高GPS信号不可用的地图匹配质量的方法。该方法基于使用标题和速度测量的粒子滤波器。我们通过与现有拓扑地图匹配算法集成来评估该方法。当单独使用该算法和与粒子滤波器相关联时,我们比较表演。

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