Titre :

Intelligent geo-localisation in urban areas using global positioning systems, 3dimensional geographic information systems, and vision

Auteur(s) :

Cappelle, Cindy [Auteur]
Laboratoire Systèmes et Transports [SET]
Autonomous intelligent machine [MAIA]
El Badaoui El Najjar, Maan [Auteur]
Systèmes Tolérants aux Fautes [STF]
Autonomous intelligent machine [MAIA]
Pomorski, Denis [Auteur]
Systèmes Tolérants aux Fautes [STF]
Charpillet, François [Auteur]
Autonomous intelligent machine [MAIA]

Titre de la revue :

Journal of Intelligent Transportation Systems: Technology, Planning, and Operations

Pagination :

3 - 12

Éditeur :

Taylor & Francis: STM, Behavioural Science and Public Health Titles

Date de publication :

2010

ISSN :

1547-2450

Discipline(s) HAL :

Informatique [cs]/Robotique [cs.RO]

Résumé en anglais : [en]

This article tackles the problem of a vehicle's geolocalization in urban areas. For this purpose, Global Positioning System (GPS) receiver is the main sensor. However, the use of GPS alone is not sufficient in many urban ...
Lire la suite >This article tackles the problem of a vehicle's geolocalization in urban areas. For this purpose, Global Positioning System (GPS) receiver is the main sensor. However, the use of GPS alone is not sufficient in many urban environments. GPS has to be helped with dead-reckoned sensors, map data, and cameras. A novel observation of the absolute pose of the vehicle is proposed to back up GPS and the drift of dead-reckoned sensors. This approach uses a new source of information that is a geographical 3-dimensional (3D) model of the environment in which the vehicle navigates. This virtual 3D city model is managed in real time by a 3D geographical information system (3D GIS). This pose's observation is constructed by matching the virtual image provided by the 3D GIS and the real image acquired by an onboard camera. An extended Kalman filter combines the sensors measurements to produce an estimation of the vehicle's pose. Experimental results using data from an odometer, a gyroscope, a GPS receiver, a camera, and an accurate geographical 3D model of the environment illustrate the developed approach.Lire moins >

Langue :

Anglais

Vulgarisation :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL