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Stable and Precise Multi-Lane Detection Algorithm Using Lidar in Challenging Highway Scenario
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 Title & Authors
Stable and Precise Multi-Lane Detection Algorithm Using Lidar in Challenging Highway Scenario
Lee, Hanseul; Seo, Seung-Woo;
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Lane detection is one of the key parts among autonomous vehicle technologies because lane keeping and path planning are based on lane detection. Camera is used for lane detection but there are severe limitations such as narrow field of view and effect of illumination. On the other hands, Lidar sensor has the merits of having large field of view and being little influenced by illumination because it uses intensity information. Existing researches that use methods such as Hough transform, histogram hardly handle multiple lanes in the co-occuring situation of lanes and road marking. In this paper, we propose a method based on RANSAC and regularization which provides a stable and precise detection result in the co-occuring situation of lanes and road marking in highway scenarios. This is performed by precise lane point extraction using circular model RANSAC and regularization aided least square fitting. Through quantitative evaluation, we verify that the proposed algorithm is capable of multi lane detection with high accuracy in real-time on our own acquired road data.
3D Lidar;circle model RANSAC;Multi lane detection;Particle Filter;regularization;
 Cited by
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