Name
Abstract | ||
|---|---|---|
In this paper, we tackle the problem of map estimation from small set of vehicular GPS traces collected from low cost devices. Contrary to the existing works, we rely only on GPS information. First, we propose a fast implementation of Kalman filtering of spline-based road modeling. Our approach demonstrates a significant boost of the computation speed while maintained a good estimation error. Secondly, we perform an evaluation of our algorithm on real world data. Our estimation is compared to a high grade Inertial Navigation System and vectorial data gathered from major map providers. Our results suggest that a good performance can be achieved from the fusion of multiple GPS traces collected from multiple vehicles and drivers. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/IROS.2014.6943160 | Intelligent Robots and Systems |
Keywords | DocType | ISSN |
Global Positioning System,Kalman filters,path planning,road vehicles,splines (mathematics),GPS-based preliminary map estimation,Kalman filtering,autonomous vehicle mission preparation,estimation error,high grade inertial navigation system,low cost devices,map providers,spline-based road modeling,vectorial data,vehicular GPS traces | Conference | 2153-0858 |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yohan Dupuis | 1 | 61 | 10.12 |
| Merriaux, P. | 2 | 25 | 4.21 |
| Subirats, P. | 3 | 0 | 0.68 |
| R. Boutteau | 4 | 47 | 8.69 |