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Open AccessArticle

A General Framework for 3-D Parameters Estimation of Roads Using GPS, OSM and DEM Data

by *,†,‡ and
Laboratoire d’Informatique Signal et Image de la Côte d’Opale, Université du Littoral Côte d’Opale, 59183 Dunkerque, France
*
Author to whom correspondence should be addressed.
Current address: 50 rue Ferdinand Buisson, BP 719, 62228 Calais CEDEX, France.
These authors contributed equally to this work.
Sensors 2018, 18(1), 41; https://doi.org/10.3390/s18010041
Received: 11 November 2017 / Revised: 18 December 2017 / Accepted: 19 December 2017 / Published: 25 December 2017
A growing number of applications needs GIS mapping information and commercial 3-D roadmaps especially. This paper presents a solution of accessing freely to 3-D map information and updating in the context of transport applications. The method relies on the OSM road networks that is 2-D modeled intrinsically. The objective is to estimate the road elevation and inclination parameters by fusing GPS, OSM and DEM data through a nonlinear filter. An experimental framework, using ASTER GDEM2 data, shows some results of the improvement of the roads modeling that includes their slopes also. The map database can be enriched with the estimated inclinations. The accuracy depends on the GPS and DEM elevation errors (typically a few meters with the GNSS sensors used and the DEM under consideration). View Full-Text
Keywords: multi-sensor fusion; non-linear filtering; GNSS-based navigation; land-vehicle localization; digital road maps; digital elevation models multi-sensor fusion; non-linear filtering; GNSS-based navigation; land-vehicle localization; digital road maps; digital elevation models
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Boucher, C.; Noyer, J.-C. A General Framework for 3-D Parameters Estimation of Roads Using GPS, OSM and DEM Data. Sensors 2018, 18, 41.

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