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At present, the number of vehicle owners is increasing, and the cars with autonomous driving functions have attracted more and more attention. The lane detection combined with cloud computing can effectively solve the drawbacks of traditional lane detection relying on feature extraction and high definition, but it also faces the problem of excessive calculation.

Lane detection is an important foundation in the development of intelligent vehicles. To address problems such as low detection accuracy of traditional methods and poor real-time performance of deep learning-based methodologies, a lane detection algorithm for intelligent vehicles in complex road conditions and dynamic environments was proposed.

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