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 …

Autonomous vehicles have received considerable attention, yet high-speed path following
control remains a critical and challenging issue. At high speeds, achieving perfect control …

Monocular 3D lane detection has become a fundamental problem in the context of
autonomous driving which comprises the tasks of finding the road surface and locating lane …

The infrared (IR) horizon is an essential reference for near-ground state awareness and
target detection. The traditional horizon detection algorithms based on hand-crafted features …

Abstract After the 2017 TuSimple Lane Detection Challenge, its dataset and evaluation
based on accuracy and F1 score have become the de facto standard to measure the …

Lane detection is essential for autonomous vehicles, and vision-based lane detection is
widely used in the field of intelligent driving cars because of its low cost. Aiming to solve the …

Autonomous vehicles have increasingly become a critical technology with advantages of
safety, effectiveness, and convenience after major advancements in both vehicle sensor …

Lane marks regulate the routes and define the prior drivable areas for a vehicle. Robust
detection of lanes plays a vital role in intelligent vehicle navigation. Lane detection …

With the rapid development of urban ground transportation, lane line detection is gradually
becoming a major technological direction to help to realize safe vehicle navigation …

In this paper we present a novel sequence generation-based framework for lane detection
called Lane2Seq. It unifies various lane detection formats by casting lane detection as a …