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 strategies and their limitations, in order to shed new light into the current challenges for map construction algorithms. We carefully analyze the results obtained by each algorithm focusing on the local details of the generated maps. Our analysis includes the characterization of 10 types of common artifacts, which occur in the results of more than one algorithm, and 7 algorithmic-specific artifacts, which are consequences of different algorithmic strategies. This allows us to extract systematic conclusions about the main challenges to fully automatize the construction of maps from trajectory data, to detect the strengths and weaknesses of the potential different strategies, and to suggest possible ways to design higher-quality map construction methods. We consider that this analysis will be of help for designing new and better methods that perform well in wider and more realistic contexts, not only for road map or hiking reconstruction, but also for other types of trajectory data.

中文翻译：

---

地图构建算法：通过远足数据进行本地评估

我们研究了五种现有的地图构建算法，这些算法在设计和测试时都考虑了城市车辆数据，并将其应用于具有不同地形特征的远足轨迹。我们的主要目标是更好地了解现有策略及其局限性，以便为地图构建算法的当前挑战提供新的思路。我们仔细分析每种算法针对生成的地图的局部细节获得的结果。我们的分析包括对不止一种算法的结果中出现的10种常见工件的特征进行表征，以及7种特定于算法的工件的特征，这是不同算法策略的结果。这使我们能够提取有关主要挑战的系统结论，以根据轨迹数据完全自动化地构建地图，以发现潜在的不同策略的优点和缺点，并提出设计高质量地图构建方法的可能方法。我们认为，这种分析将有助于设计新的更好的方法，这些方法不仅在路线图或徒步旅行重建中，而且在其他类型的轨迹数据中，都可以在更广泛，更现实的环境中发挥良好的作用。