Sharp Curve Lane Detection for Autonomous Driving

Sharp curve lane detection is one of the challenges of visual environment perception technology for autonomous driving. In this paper, a new hyperbola fitting based method of curve lane detection is proposed. The method mainly includes three parts: extraction, clustering, and hyperbola fitting of lane feature points. We compared our method with the Bezier curve fitting based, the least squares curve fitting based, the spline fitting based methods, and an existing hyperbola fitting based method. Experiments show that our method performs better than these methods.

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