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A General Framework for 3-D Parameters Estimation of Roads Using GPS, OSM and DEM Data
Christophe Boucher1, Jean-Charles Noyer2
1Laboratoire d'Informatique Signal et Image de la Côte d'Opale, Université du Littoral Côte d'Opale, 59183 Dunkerque, France. christophe.boucher@univ-littoral.fr.
Sensors (Basel, Switzerland)
|January 4, 2018
Summary
This study enhances 3D road mapping by estimating elevation and inclination using GPS, OpenStreetMap (OSM), and Digital Elevation Model (DEM) data. This improves transport applications with more accurate road network modeling.
Area of Science:
- Geographic Information Systems (GIS)
- Geomatics Engineering
- Transportation Engineering
Background:
- Increasing demand for 3D road mapping in transport applications.
- Limitations of existing 2D road network models from OpenStreetMap (OSM).
Purpose of the Study:
- To develop a method for accessing and updating free 3D map information for transport.
- To estimate road elevation and inclination parameters.
Main Methods:
- Fusing Global Positioning System (GPS), OSM, and Digital Elevation Model (DEM) data.
- Utilizing a nonlinear filter for parameter estimation.
- Employing ASTER GDEM2 data for experimental validation.
Main Results:
- Demonstrated improvement in 3D road modeling, including slope estimation.
- Successful enrichment of map databases with estimated road inclinations.
- Identified accuracy dependency on GPS and DEM elevation errors.
Conclusions:
- The proposed method effectively enhances 3D road modeling for transport applications.
- Fusion of GPS, OSM, and DEM data provides valuable road inclination information.
- Further improvements are contingent on reducing GPS and DEM elevation uncertainties.
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