Map construction algorithms: an evaluation through hiking data

David Duran, Vera Sacristán Adinolfi, Rodrigo I. Silveira
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引用次数: 10

Abstract

We study five existing map construction algorithms, designed and tested with urban vehicle data in mind, and apply them to hiking trajectories with different terrain characteristics. Our main goal is to better understand the existing algorithms and to what extent they apply in a wider context. Indeed, our data differs from the one previously used to evaluate map construction algorithm in several aspects: higher GPS error, narrow and winding paths, and trajectories with its own characteristics in terms of speed or direction. We have chosen four different areas of varied geographic features. For each of them we have considered a set of hiking GPS trajectories, each with a total number of nodes between 38,000 and 288,000. For each algorithm we have analyzed the parameters it uses, and adjusted them to each data set. We present an analysis of the generated maps produced by each algorithm on each data set, and a discussion of the most important artifacts detected. We consider that this analysis sheds new light into the current challenges for map construction algorithms, and will be of help for designing new and better methods.
地图构建算法:通过徒步旅行数据进行评估
我们研究了五种现有的地图构建算法,并在城市车辆数据的基础上进行了设计和测试,并将它们应用于具有不同地形特征的徒步旅行轨迹。我们的主要目标是更好地理解现有的算法,以及它们在多大程度上适用于更广泛的环境。事实上,我们的数据与之前用于评估地图构建算法的数据在以下几个方面有所不同:更高的GPS误差,狭窄曲折的路径,以及在速度或方向上具有自身特征的轨迹。我们选择了四个具有不同地理特征的不同地区。对于它们中的每一个,我们都考虑了一组徒步GPS轨迹,每个轨迹的节点总数在38,000到288,000之间。对于每个算法,我们都分析了它使用的参数,并根据每个数据集进行了调整。我们对每个算法在每个数据集上生成的地图进行了分析,并讨论了检测到的最重要的工件。我们认为,这一分析揭示了当前地图构建算法面临的挑战,并将有助于设计新的和更好的方法。
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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