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ISPRS Int. J. Geo-Inf. 2017, 6(3), 64; doi:10.3390/ijgi6030064

Towards a Landmark-Based Pedestrian Navigation Service Using OSM Data

GIScience Research Group, University of Heidelberg, 69117 Heidelberg, Germany
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Author to whom correspondence should be addressed.
Academic Editors: Georg Gartner, Haosheng Huang and Wolfgang Kainz
Received: 22 November 2016 / Revised: 10 February 2017 / Accepted: 21 February 2017 / Published: 25 February 2017
(This article belongs to the Special Issue Location-Based Services)
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Abstract

With the advent of location-aware smartphones, the desire for pedestrian-based navigation services has increased. Unlike car-based services where instructions generally are comprised of distance and road names, pedestrian instructions should instead focus on the delivery of landmarks to aid in navigation. OpenStreetMap (OSM) contains a vast amount of geospatial information that can be tapped into for identifying these landmark features. This paper presents a prototype navigation service that extracts landmarks suitable for navigation instructions from the OSM dataset based on several metrics. This is coupled with a short comparison of landmark availability within OSM, differences in routes between locations with different levels of OSM completeness and a short evaluation of the suitability of the landmarks provided by the prototype. Landmark extraction is performed on a server-side service, with the instructions being delivered to a pedestrian navigation application running on an Android mobile device. View Full-Text
Keywords: landmarks; navigation; mobile applications; pedestrian; OpenStreetMap; OSM; routing landmarks; navigation; mobile applications; pedestrian; OpenStreetMap; OSM; routing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Rousell, A.; Zipf, A. Towards a Landmark-Based Pedestrian Navigation Service Using OSM Data. ISPRS Int. J. Geo-Inf. 2017, 6, 64.

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