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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    Titel :

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


    Beteiligte:
    Younguk Yim (Autor:in) / Se-Young Oh (Autor:in)


    Erscheinungsdatum :

    01.01.1999


    Format / Umfang :

    540762 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    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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