Driver inattention and distraction are the main causes of road accidents, many of which
result in fatalities. To reduce road accidents, the development of information systems to …

In the context of autonomous vehicles on highways, one of the first and most important tasks
is to localize the vehicle on the road. For this purpose, the vehicle needs to be able to take …

Lane is critical in the vision navigation system of the intelligent vehicle. Naturally, lane is a
traffic sign with high-level semantics, whereas it owns the specific local pattern which needs …

This paper presents a novel parametric curve-based method for lane detection in RGB
images. Unlike state-of-the-art segmentation-based and point detection-based methods that …

High-definition (HD) map provides abundant and precise environmental information of the
driving scene, serving as a fundamental and indispensable component for planning in …

Vectorized high-definition map online construction has garnered considerable attention in
the field of autonomous driving research. Most existing approaches model changeable map …

Methods for 3D lane detection have been recently proposed to address the issue of
inaccurate lane layouts in many autonomous driving scenarios (uphill/downhill, bump, etc.) …

Modern deep-learning-based lane detection methods are successful in most scenarios but
struggling for lane lines with complex topologies. In this work, we propose CondLaneNet, a …

Vectorized high-definition map (HD-map) construction, which focuses on the perception of
centimeter-level environmental information, has attracted significant research interest in the …

Lane detection is a challenging task that requires predicting complex topology shapes of
lane lines and distinguishing different types of lanes simultaneously. Earlier works follow a …