TFALDA is a lane detection algorithm which is simple, robust, and efficient, thus suitable for real-time processing in cluttered road environments without a priori knowledge of them. Out of the many possible lane boundary candidates, the best one is chosen as the one at a minimum distance from the previous lane vector according to a weighted distance metric in which each feature is assigned a different weight. An evolutionary algorithm then finds the optimal weights that minimize the misclassification rate. The proposed algorithm was successfully applied to a series of road following experiments using the PRV (Postech Research Vehicle) II.


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    Title :

    Three-feature based automatic lane detection algorithm (TFALDA) for autonomous driving


    Contributors:
    Younguk Yim (author) / Se-Young Oh (author)


    Publication date :

    1999-01-01


    Size :

    540762 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    Three-Feature Based Automatic Lane Detection Algorithm (TFALDA) for Autonomous Driving

    Yim, Y. / Oh, S. Y. / IEEE et al. | British Library Conference Proceedings | 1999



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