LIDAR-Based Lane Marking Detection For Vehicle Positioning in an HD Map

Abstract : Accurate self-vehicle localization is an important task for autonomous driving and ADAS. Current GNSS-based solutions do not provide better than 2-3 m in open-sky environments. Moreover, map-based localization using HD maps became an interesting source of information for intelligent vehicles. In this paper, a Map-based localization using a multi- layer LIDAR is proposed. Our method mainly relies on road lane markings and an HD map to achieve lane-level accuracy. At first, road points are segmented by analysing the geometric structure of each returned layer points. Secondly, thanks to LIDAR reflectivity data, road marking points are projected onto a 2D image and then detected using Hough Transform. Detected lane markings are then matched to our HD map using Particle Filter (PF) framework. Experiments are conducted on a Highway-like test track using GPS/INS with RTK correction as ground truth. Our method is capable of providing a lane-level localization with a 22 cm cross-track accuracy.
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https://hal.archives-ouvertes.fr/hal-01891764
Contributor : Farouk Ghallabi <>
Submitted on : Tuesday, October 9, 2018 - 9:50:12 PM
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Farouk Ghallabi, Fawzi Nashashibi, Ghayath El-Haj-Shhade, Marie-Anne Mittet. LIDAR-Based Lane Marking Detection For Vehicle Positioning in an HD Map. 2018 IEEE 21th International Conference on Intelligent Transportation Systems (ITSC), Nov 2018, Maui, Hawaii,, United States. ⟨hal-01891764⟩

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