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A pedestrian network construction algorithm based on multiple GPS traces

Kasemsuppakorn, P and Karimi, HA (2013) A pedestrian network construction algorithm based on multiple GPS traces. Transportation Research Part C: Emerging Technologies, 26. 285 - 300. ISSN 0968-090X

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Currently, pedestrian networks are not as widely available as road networks are for many areas; this is partly due to the high demand for applications such as car navigation. However, this situation is rapidly changing as GPS-enabled mobile devices are increasingly becoming commonplace for pedestrian applications and as they are potential for volunteered data collection. For this reason, the development of efficient and cost-effective techniques appropriate for collecting and constructing pedestrian network databases is needed. This paper presents an algorithm for automatically identifying geometries of pedestrian path segments and constructing a pedestrian network from multiple GPS traces. The algorithm was experimented by using two sets of data sources, self-collected walking traces and OpenStreetMap (OSM) walking traces. The experiment with self-collected data was validated by comparing the constructed pedestrian network with a network baseline and calculating the quality measurements in three environment settings. The experiment with OSM traces was validated by visually inspecting maps overlaid on high-resolution images. Evaluation results show that the algorithm can automatically construct pedestrian networks. © 2012 Elsevier Ltd.


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Item Type: Article
Status: Published
CreatorsEmailPitt UsernameORCID
Kasemsuppakorn, P
Karimi, HAhkarimi@pitt.eduHKARIMI0000-0001-5331-5004
Date: 1 January 2013
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Journal or Publication Title: Transportation Research Part C: Emerging Technologies
Volume: 26
Page Range: 285 - 300
DOI or Unique Handle: 10.1016/j.trc.2012.09.007
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISSN: 0968-090X
Date Deposited: 25 Jun 2013 16:43
Last Modified: 11 Apr 2020 14:55


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