Abstract

Abstract: Curved lane detection is a critical componentof advanced driver assistance systems (ADAS) and autonomous vehicles, playing a pivotal role in ensuring safeand efficient navigation on complex roadways. In the pursuitof enhancing accuracy and expediting processing speed in road lane detection, researchers have proposed numerous methodologies. Despite these efforts, several challenges persist, including variations in lane markings, fluctuations in lighting conditions, and the emergence of shadows. Addressing these obstacles is crucial for establishing dependable lane detection systems. The curve lane detection algorithm exhibits a robust performance, as evidenced by the experimental results, which consistently reveal a notably high success rate in accurately identifying and delineating curved lanes

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