Abstract
This article presents an effective solution for the localization of a vehicle in dense urban areas where GNSS-based methods fail because of poor satellite visibility. It advocates the use of a visual-based method processing georeferenced landmarks obtained after a learning path and stored in a new layer of the geographical information system (GIS) used for navigation. Real-time localization gives, with few failures, accurate results in the areas covered by the GIS. The integrity of the localization is obtained by running another algorithm in parallel, processing odometric data combined with the geometric model of the drivable area and, when available, GNSS data in tight coupling. An ellipsoidal confidence domain is updated by using both extended Kalman filtering (EKF) and set-membership estimation. Although less accurate, this estimation is reliable and, when the visual method fails, the availability of a confidence domain enables us to speed up the restart of the visual method while navigating cautiously. A large-scale experiment (>4 km) was conducted in the centre of Paris. We compare the absolute localization results with the ground truth obtained by combining RTK-GPS and a high-end inertial measurement unit (IMU).
Highlights
This article addresses the question of the integrity of the accurate localization of a vehicle in dense urban areas
This article presents an effective solution for the localiza‐ tion of a vehicle in dense urban areas where Global navigation satellite systems (GNSSs)-based methods fail because of poor satellite visibility
The integrity of the localization is obtained by running another algorithm in parallel, processing odometric data combined with the geometric model of the drivable area and, when available, GNSS data in tight coupling
Summary
This article addresses the question of the integrity of the accurate localization of a vehicle in dense urban areas. The ego-localization of a vehicle has been based on GPS coupled with odometry or inertial sensors, which has proven to be an efficient solution except in places where the visibility of the sky - and of the satellites - is problematic, for instance in urban canyons in city centres. This is why attention has been paid to other sensing modalities. We discuss implementa‐ tion issues and the large amount of processed data which lead us to consider exceptional behaviours of the visual algorithm that emphasize the necessity of its collabora‐ tion with another method to achieve the integrity of the localization
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