The goal of this thesis has been to create a map of road lanes from piece-wisedetections. Using images from a stereo camera, an existing algorithm is able todetect lane tracks in real-time. With a basis spline (B-spline) representation ofthe tracks, these curve features are converted into point features. These are combinedoff-line with an odometric estimate for the creation of a motion and lanetrack map. Fusion of odometric and feature measurements is done using an optimizationbased simultaneous localization and mapping (slam) method. By use of visual inspection and a differential global positioning system (dgps) theresult is validated. The method is able to improve on existing motion estimatorsby using the curvature of lane tracks. A projection of the resulting map is usedto automatically label lane tracks as seen from camera view with accuracy andrange exceeding that of the real-time algorithm.


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    Titel :

    Automatic Lane Labeling Using an Off-line Smoothing Stereo-lane Algorithm


    Beteiligte:

    Erscheinungsdatum :

    2017-01-01


    Medientyp :

    Hochschulschrift


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629




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