Route Planning and Map Inference with Global Positioning Traces
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Navigation systems assist almost any kind of motion in the physical world including sailing, flying, hiking, driving and cycling. On the other hand, traces supplied by global positioning systems (GPS) can track actual time and absolute coordinates of the moving objects.
Consequently, this paper addresses efficient algorithms and data structures for the route planning problem based on GPS data; given a set of traces and a current location, infer a short(est) path to the destination.
The algorithm of Bentley and Ottmann is shown to transform geometric GPS information directly into a combinatorial weighted and directed graph structure, which in turn can be queried by applying classical and refined graph traversal algorithms like Dijkstras’ single-source shortest path algorithm or A*.
For high-precision map inference especially in car navigation, algorithms for road segmentation, map matching and lane clustering are presented.
KeywordsGlobal Position System Cluster Center Road Segment Global Position System Data Route Planning
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