Robust Lane Tracking for Harsh Driving Environments

Seunghyon Lee, Hyuk-Ju Kwon, Sung-Hak Lee
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Abstract

Recently, the industry for autonomous driving is expanding rapidly. Therefore for a safe system, it require high lane detection performance. In this paper, we propose robust lane detection and a tracking algorithm even though under harsh environments. High lane detection accuracy can make more safe Lane Keeping Assist System(LKAS).
针对恶劣驾驶环境的稳健车道跟踪
最近,自动驾驶产业正在迅速扩张。因此,对于一个安全的系统来说,对车道检测性能的要求很高。在本文中,我们提出了即使在恶劣环境下,鲁棒车道检测和跟踪算法。提高车道检测精度可以提高车道保持辅助系统(LKAS)的安全性。
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