Recently, lane detection algorithms have played significant roles in the field of vehicle technology. While many well working algorithms have been developed, they are hard to use in complex urban environments. In this paper, we propose an efficient approach for detecting lane markings using image information and LIDAR reflectance. The proposed algorithm has three phases: ground extraction, lane detection, and combining lane information. The proposed algorithm was implemented on a real vehicle and validated in various traffic environments, including the 2014 Hyundai Autonomous Vehicle Competition (AVC).
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|저 자||Seunghak Shin, Inwook Shim, In So Kweon|
|학 회||The 12th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)|
|Notes||The Authors gratefully acknowledge the support from UTRC(Unmanned Technology Research Center) at KAIST(Korea Advanced Institute of Science and Technology), originally funded by DAPA, ADD.|