License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.GIScience.2021.II.12
URN: urn:nbn:de:0030-drops-147717
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Behr, Timon ; van Dijk, Thomas C. ; Forsch, Axel ; Haunert, Jan-Henrik ; Storandt, Sabine

Map Matching for Semi-Restricted Trajectories

LIPIcs-GIScience-2021-II-12.pdf (5 MB)


We consider the problem of matching trajectories to a road map, giving particular consideration to trajectories that do not exclusively follow the underlying network. Such trajectories arise, for example, when a person walks through the inner part of a city, crossing market squares or parking lots. We call such trajectories semi-restricted. Sensible map matching of semi-restricted trajectories requires the ability to differentiate between restricted and unrestricted movement. We develop in this paper an approach that efficiently and reliably computes concise representations of such trajectories that maintain their semantic characteristics. Our approach utilizes OpenStreetMap data to not only extract the network but also areas that allow for free movement (as e.g. parks) as well as obstacles (as e.g. buildings). We discuss in detail how to incorporate this information in the map matching process, and demonstrate the applicability of our method in an experimental evaluation on real pedestrian and bicycle trajectories.

BibTeX - Entry

  author =	{Behr, Timon and van Dijk, Thomas C. and Forsch, Axel and Haunert, Jan-Henrik and Storandt, Sabine},
  title =	{{Map Matching for Semi-Restricted Trajectories}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part II},
  pages =	{12:1--12:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-208-2},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{208},
  editor =	{Janowicz, Krzysztof and Verstegen, Judith A.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-147717},
  doi =		{10.4230/LIPIcs.GIScience.2021.II.12},
  annote =	{Keywords: map matching, OpenStreetMap, GPS, trajectory, road network}

Keywords: map matching, OpenStreetMap, GPS, trajectory, road network
Collection: 11th International Conference on Geographic Information Science (GIScience 2021) - Part II
Issue Date: 2021
Date of publication: 14.09.2021
Supplementary Material: Software: archived at:

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