Updating road network databases using GNSS

Author

Boucher, Christophe ; Noyer, Jean-Charles

Author_Institution

ULCO-LISIC, Univ. Lille Nord-de-France, Calais, France

fYear

2011

fDate

4-7 April 2011

Firstpage

288

Lastpage

291

Abstract

This paper presents a method to detect missing roads and to update GIS map databases from GPS data. It relies on an extended Kalman filter that fuses, in a centralized fusion scheme, available GPS and road map data. The map is modeled as an additional sensor which allows a direct modeling of the map errors and uncertainties. A probabilistic map-matching algorithm is used to manage the road network database through the computation of the Mahalanobis distance. We show experimental results from an urban transport network scenario where roads are missing, due to an outdated database.

Keywords

Kalman filters; cartography; geographic information systems; object detection; pattern matching; probability; satellite navigation; sensor fusion; traffic engineering computing; GIS map databases; GNSS; Mahalanobis distance; centralized fusion scheme; extended Kalman filter; global navigation satellite systems; missing roads detection; probabilistic map-matching algorithm; road map data; road network databases; urban transport network scenario; Covariance matrix; Databases; Estimation; Global Positioning System; Roads; Vehicle dynamics; Vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems Conference (SysCon), 2011 IEEE International

Conference_Location

Montreal, QC

Print_ISBN

978-1-4244-9494-1

Type

conf

DOI

10.1109/SYSCON.2011.5929042

Filename

5929042