Map matching queries on realistic input graphs under the Fréchet distance
CoRR(2022)
摘要
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 Õ(cp) size that can answer (1+ε)-approximate
map matching queries in Õ(c^4 q log^4 p) time, where Õ(·) hides lower-order factors and dependence of ε.
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关键词
realistic input graphs,fréchet distance,map,queries
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