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

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

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 intri...

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Main Authors: Christophe Boucher, Jean-Charles Noyer
Format: Article
Language:English
Published: MDPI AG 2017-12-01
Series:Sensors
Subjects:
multi-sensor fusion
non-linear filtering
GNSS-based navigation
land-vehicle localization
digital road maps
digital elevation models
Online Access:https://www.mdpi.com/1424-8220/18/1/41
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spelling doaj-25788a8a9185422881e3124ea92c3a3b2020-11-25T00:09:36ZengMDPI AGSensors1424-82202017-12-011814110.3390/s18010041s18010041A General Framework for 3-D Parameters Estimation of Roads Using GPS, OSM and DEM DataChristophe Boucher0Jean-Charles Noyer1Laboratoire d’Informatique Signal et Image de la Côte d’Opale, Université du Littoral Côte d’Opale, 59183 Dunkerque, FranceLaboratoire d’Informatique Signal et Image de la Côte d’Opale, Université du Littoral Côte d’Opale, 59183 Dunkerque, FranceA 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).https://www.mdpi.com/1424-8220/18/1/41multi-sensor fusionnon-linear filteringGNSS-based navigationland-vehicle localizationdigital road mapsdigital elevation models
collection DOAJ
language English
format Article
sources DOAJ
author Christophe Boucher
Jean-Charles Noyer
spellingShingle Christophe Boucher
Jean-Charles Noyer
A General Framework for 3-D Parameters Estimation of Roads Using GPS, OSM and DEM Data
Sensors
multi-sensor fusion
non-linear filtering
GNSS-based navigation
land-vehicle localization
digital road maps
digital elevation models
author_facet Christophe Boucher
Jean-Charles Noyer
author_sort Christophe Boucher
title A General Framework for 3-D Parameters Estimation of Roads Using GPS, OSM and DEM Data
title_short A General Framework for 3-D Parameters Estimation of Roads Using GPS, OSM and DEM Data
title_full A General Framework for 3-D Parameters Estimation of Roads Using GPS, OSM and DEM Data
title_fullStr A General Framework for 3-D Parameters Estimation of Roads Using GPS, OSM and DEM Data
title_full_unstemmed A General Framework for 3-D Parameters Estimation of Roads Using GPS, OSM and DEM Data
title_sort general framework for 3-d parameters estimation of roads using gps, osm and dem data
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2017-12-01
description 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).
topic multi-sensor fusion
non-linear filtering
GNSS-based navigation
land-vehicle localization
digital road maps
digital elevation models
url https://www.mdpi.com/1424-8220/18/1/41
work_keys_str_mv AT christopheboucher ageneralframeworkfor3dparametersestimationofroadsusinggpsosmanddemdata
AT jeancharlesnoyer ageneralframeworkfor3dparametersestimationofroadsusinggpsosmanddemdata
AT christopheboucher generalframeworkfor3dparametersestimationofroadsusinggpsosmanddemdata
AT jeancharlesnoyer generalframeworkfor3dparametersestimationofroadsusinggpsosmanddemdata
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