Lane detection is crucial for vehicle localization which makes it the foundation for automated
driving and many intelligent and advanced driving assistant systems. Available vision-based …

Existing lane detection methods have achieved remarkable performance in complex real-
world scenarios, but many of them still have some problems, such as poor anti-interference …

Lane detection is a vital component of intelligent driving systems, offering indispensable
functionality to keep the vehicle within its designated lane, thereby reducing the risk of lane …

For self‐driving vehicles, detecting lane lines in changeable scenarios is a fundamental yet
challenging task. The rise of deep learning in recent years has contributed to the thriving of …

Lane detection, as one of the most important core functions in the autonomous driving
environment, is still an open problem. In particular, pursuing high accuracy in complex …

Accurate and reliable lane detection is vital for the safe performance of lane‐keeping
assistance and lane departure warning systems. However, under certain challenging …

Lane detection serves as a fundamental task for automated vehicles and Advanced Driver
Assistance Systems. However, current lane detection methods can not deliver the versatility …

Lane detection is an important component of advanced driving aided system (ADAS). It is a
combined component of the planning and control algorithms. Therefore, it has high …

Lane detection is still a problem to be solved due to the complex and dynamic autonomous
driving environment. In this work, we propose a robust lane detection model via vertical …

Lane detection is a fundamental task for autonomous driving. Most existed deep learning-
based methods use a combination of semantic segmentation and post-processing for lane …