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Open AccessArticle

Real-Time Road Lane Detection in Urban Areas Using LiDAR Data

by 1 and 2,*
1
Department of Software Convergence, Kyung Hee University, Yongin 17104, Korea
2
Department of Computer Science and Engineering, Kyung Hee University, Yongin 17104, Korea
*
Author to whom correspondence should be addressed.
Electronics 2018, 7(11), 276; https://doi.org/10.3390/electronics7110276
Received: 6 September 2018 / Revised: 14 October 2018 / Accepted: 24 October 2018 / Published: 26 October 2018
The generation of digital maps with lane-level resolution is rapidly becoming a necessity, as semi- or fully-autonomous driving vehicles are now commercially available. In this paper, we present a practical real-time working prototype for road lane detection using LiDAR data, which can be further extended to automatic lane-level map generation. Conventional lane detection methods are limited to simple road conditions and are not suitable for complex urban roads with various road signs on the ground. Given a 3D point cloud scanned by a 3D LiDAR sensor, we categorized the points of the drivable region and distinguished the points of the road signs on the ground. Then, we developed an expectation-maximization method to detect parallel lines and update the 3D line parameters in real time, as the probe vehicle equipped with the LiDAR sensor moved forward. The detected and recorded line parameters were integrated to build a lane-level digital map with the help of a GPS/INS sensor. The proposed system was tested to generate accurate lane-level maps of two complex urban routes. The experimental results showed that the proposed system was fast and practical in terms of effectively detecting road lines and generating lane-level maps. View Full-Text
Keywords: road lane detection; map generation; driving assistance; autonomous driving road lane detection; map generation; driving assistance; autonomous driving
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Jung, J.; Bae, S.-H. Real-Time Road Lane Detection in Urban Areas Using LiDAR Data. Electronics 2018, 7, 276.

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