Map matching queries on realistic input graphs under the Fréchet distance

IF 0.9 3区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS
Joachim Gudmundsson, Martin P. Seybold, Sampson Wong
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引用次数: 0

Abstract

Map matching is a common preprocessing step for analysing vehicle trajectories. In the theory community, the most popular approach for map matching is to compute a path on the road network that is the most spatially similar to the trajectory, where spatial similarity is measured using the Fréchet distance. A shortcoming of existing map matching algorithms under the Fréchet distance is that every time a trajectory is matched, the entire road network needs to be reprocessed from scratch. An open problem is whether one can preprocess the road network into a data structure, so that map matching queries can be answered in sublinear time.

In this paper, we investigate map matching queries under the Fréchet distance. We provide a negative result for geometric planar graphs. We show that, unless SETH fails, there is no data structure that can be constructed in polynomial time that answers map matching queries in O((pq)1 − δ) query time for any δ > 0, where p and q are the complexities of the geometric planar graph and the query trajectory, respectively. We provide a positive result for realistic input graphs, which we regard as the main result of this paper. We show that for c-packed graphs, one can construct a data structure of \(\tilde{O}(cp) \) size that can answer (1 + ε)-approximate map matching queries in \(\tilde{O}(c^4 q \log ^4 p) \) time, where \(\tilde{O}(\cdot) \) hides lower-order factors and dependence on ε.

弗雷谢特距离下现实输入图的地图匹配查询
地图匹配是分析车辆轨迹的常见预处理步骤。在理论界,最流行的地图匹配方法是在道路网络上计算出一条与轨迹在空间上最相似的路径,空间相似度用弗雷谢特距离来衡量。使用弗雷谢特距离的现有地图匹配算法的一个缺点是,每次匹配轨迹时,都需要从头开始重新处理整个道路网络。一个悬而未决的问题是,能否将道路网络预处理成一种数据结构,从而在亚线性时间内回答地图匹配查询。本文研究了弗雷谢特距离下的地图匹配查询。我们为几何平面图提供了一个否定结果。我们表明,除非 SETH 失效,否则没有数据结构可以在多项式时间内构建,从而在任意 δ > 0 条件下以 O((pq)1 - δ) 查询时间回答地图匹配查询,其中 p 和 q 分别是几何平面图和查询轨迹的复杂度。我们为现实输入图提供了一个正面结果,并将其视为本文的主要结果。我们证明,对于 c-packed 图,我们可以构建一个 \(\tilde{O}(cp) \) 大小的数据结构,它可以在 \(\tilde{O}(c^4 q \log ^4 p) \) 时间内回答 (1 + ε)-approximate map matching 查询,其中 \(\tilde{O}(\cdot) \) 隐藏了低阶因子和对ε的依赖。
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来源期刊
ACM Transactions on Algorithms
ACM Transactions on Algorithms COMPUTER SCIENCE, THEORY & METHODS-MATHEMATICS, APPLIED
CiteScore
3.30
自引率
0.00%
发文量
50
审稿时长
6-12 weeks
期刊介绍: ACM Transactions on Algorithms welcomes submissions of original research of the highest quality dealing with algorithms that are inherently discrete and finite, and having mathematical content in a natural way, either in the objective or in the analysis. Most welcome are new algorithms and data structures, new and improved analyses, and complexity results. Specific areas of computation covered by the journal include combinatorial searches and objects; counting; discrete optimization and approximation; randomization and quantum computation; parallel and distributed computation; algorithms for graphs, geometry, arithmetic, number theory, strings; on-line analysis; cryptography; coding; data compression; learning algorithms; methods of algorithmic analysis; discrete algorithms for application areas such as biology, economics, game theory, communication, computer systems and architecture, hardware design, scientific computing
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