Towards an extensive map-oriented trace basis for human mobility modeling
Towards an extensive map-oriented trace basis for human mobility modeling
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DOI：
10.1109/pccc.2016.7820643
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发表时间：
2016-12
期刊：
影响因子：
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通讯作者：
Matthias Schwamborn;N. Aschenbruck
中科院分区：
文献类型：
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作者：
Matthias Schwamborn;N. Aschenbruck
人体流动性分析和建模是一个非常跨学科的研究领域。移动性模型在评估移动的和机会网络的仿真性能方面起着重要的作用。然而，大多数这些模型所基于的移动轨迹大多存在几个缺点。在本文中，我们使用广泛的洛桑数据收集活动（LDCC）的流动性跟踪为基础，进一步面向地图的处理。地图匹配和合理添加点之间的最佳路线可以缓解GPS空间噪声、匿名化和数据缺口等问题。此外，进行停留点提取作为元素统计迁移率特性分析的准备。一个示例性的接触统计的影响评估表明，所得到的地图导向的跟踪基础确实适合于大规模的流动性分析和模拟。
Human mobility analysis and modeling is a very interdisciplinary field of research. Mobility models play an important role particularly in assessing the simulative performance of mobile and opportunistic networks. The mobility traces, which most of these models are based on, however, mostly suffer from several shortcomings. In this paper, we use the extensive Lausanne Data Collection Campaign (LDCC) mobility trace as basis for further map-oriented processing. Map-matching and sensible addition of optimal routes between points mitigate problems like GPS spatial noise, anonymization, and data gaps. Moreover, stay point extraction is performed as a preparation for the analysis of elemental statistical mobility characteristics. An exemplary impact evaluation of contact statistics shows that the resulting map-oriented trace basis is indeed suited for large-scale mobility analysis and simulation.