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.
Three-feature based automatic lane detection algorithm (TFALDA) for autonomous driving
01.01.1999
540762 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Three-Feature Based Automatic Lane Detection Algorithm (TFALDA) for Autonomous Driving
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