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In addition, we show that the extremely biased nature of the trajectory dataset, which is typical of volunteered user-generated data, can be of high importance in terms of popularity-based routing.

Instead of solely relying on the geometric features of the trajectories, such as heading changes, which may indicate turning points and consequently intersections, we extract semantic features of the trajectories in form of sequences of stops and moves .

Import and export various file types via GPSBabel See real-time GPS position (but not on Windows as no GPSD support on this platform). If you're having a hard time visualizing it: check out the [Screenshots], screencasts and then download it to try it out.

It is written in C with the GTK 2 toolkit, available for Linux, other POSIX operating systems, and Windows, and is licensed under the GNU GPLv2 .

Under this spatiotemporal prism, the extracted semantic information which indicates where vehicles stop can reveal important locations, such as junctions.

The advantage of the proposed approach in comparison with existing turning-points oriented approaches is that it can detect intersections even when not all the crossing road segments are sampled and therefore no turning points are observed in the trajectories.

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OSM has quickly established itself as a popular resource for bicycle routing; however, its high-level of detail presents challenges for its applicability to popularity-based routing.

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