LIDAR-Based road signs detection For Vehicle Localization in an HD Map

Abstract : Self-vehicle localization is one of the fundamental tasks for autonomous driving. Most of current techniques for global positioning are based on the use of GNSS (Global Navigation Satellite Systems). However, these solutions do not provide a localization accuracy that is better than 2-3 m in open sky environments [1]. Alternatively, the use of maps has been widely investigated for localization since maps can be pre-built very accurately. State of the art approaches often use dense maps or feature maps for localization. In this paper, we propose a road sign perception system for vehicle localization within a third party map. This is challenging since third party maps are usually provided with sparse geometric features which make the localization task more difficult in comparison to dense maps. The proposed approach extends the work in [2] where a localization system based on lane markings has been developed. Experiments have been conducted on a Highway-like test track using GNSS/INS with RTK corrections as ground truth (GT). Error evaluations are given as cross-track and along-track errors defined in the curvilinear coordinates [3] related to the map.
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Farouk Ghallabi, Ghayath El-Haj-Shhade, Marie-Anne Mittet, Fawzi Nashashibi. LIDAR-Based road signs detection For Vehicle Localization in an HD Map. IV’19 - IEEE Intelligent Vehicles Symposium, Jun 2019, Paris, France. ⟨hal-02117395⟩

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