Self-driving cars, Autonomous vehicles (AVs), Lane Detection.
Abstract
Lane detection is a critical component of autonomous vehicle (AV) technology, enabling vehicles to navigate safely within their designated lanes. This paper provides an overview of the current state-of-the-art techniques and challenges in lane detection for AVs. By analyzing various approaches and methodologies, including object detection and deep learning algorithms, the paper highlights the complexities involved in accurately detecting lanes under diverse environmental conditions and driving scenarios. Furthermore, it discusses the technical issues, advantages, and challenges associated with lane detection, emphasizing the need for robust systems that can adapt to dynamic road conditions. The proposed system architecture and implementation details are also presented, aiming to enhance the capabilities of AVs and ensure their safe integration into society.
Article Details
Unique Paper ID: 162987
Publication Volume & Issue: Volume 10, Issue 11
Page(s): 564 - 568
Article Preview & Download
Share This Article
Join our RMS
Conference Alert
NCSEM 2024
National Conference on Sustainable Engineering and Management - 2024