Map-matching is a popular method that uses spatial information to improve the accuracy of positioning methods. The performance of map matching methods is closely related to spatial characteristics. Although several studies have demonstrated that certain map matching algorithms are affected by some spatial structures (e.g., parallel paths), they focus on the analysis of single map matching method or few spatial structures. In this study, we explored how the most commonly-used four spatial characteristics (namely forks, open spaces, corners, and narrow corridors) affect three popular map matching methods, namely particle filtering (PF), hidden Markov model (HMM), and geometric methods. We first provide a theoretical analysis on how spatial characteristics affect the performance of map matching methods, and then evaluate these effects through experiments. We found that corners and narrow corridors are helpful in improving the positioning accuracy, while forks and open spaces often lead to a larger positioning error. We hope that our findings are helpful for future researchers in choosing proper map matching algorithms with considering the spatial characteristics.

中文翻译：

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特征对基于地图匹配的室内定位的影响评估

地图匹配是一种流行的方法，它使用空间信息来提高定位方法的准确性。地图匹配方法的性能与空间特征密切相关。尽管一些研究表明某些地图匹配算法受某些空间结构（例如，平行路径）的影响，但它们专注于分析单个地图匹配方法或很少的空间结构。在这项研究中，我们探讨了最常用的四个空间特征（即叉子，开放空间，拐角和狭窄的走廊）如何影响三种流行的地图匹配方法，即粒子滤波（PF），隐马尔可夫模型（HMM）和几何方法。我们首先提供有关空间特征如何影响地图匹配方法性能的理论分析，然后通过实验评估这些效果。我们发现，拐角和狭窄的走廊有助于提高定位精度，而货叉和开放空间通常会导致更大的定位误差。我们希望我们的发现对将来的研究人员在考虑空间特征的情况下选择合适的地图匹配算法有帮助。