It is crucial for autonomous vehicles to navigate at intersections. The accurate location of intersections and the orientation of each branches are necessary for decision making and path planning. In this paper, a unified method is proposed to estimate orientations of each branch at an intersection and to locate the position of the intersection. First, based on vehicle dynamics, a densifying method is used to obtain dense point-cloud data using 3D-LIDAR sensor. Then, according to the data of Open Street Map, the regions-of-interest are extracted and the points are interpolated to transform into an elevation image. Finally, a support vector regression model is employed to estimate the position and orientation of each branch and a fusion method is used to locate the intersection. The experimental results demonstrate the accuracy and robustness of the proposed algorithm.


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    Titel :

    3D-LIDAR based branch estimation and intersection location for autonomous vehicles


    Beteiligte:
    Wang, Liang (Autor:in) / Wang, Jun (Autor:in) / Wang, Xiaonian (Autor:in) / Zhang, Yihuan (Autor:in)


    Erscheinungsdatum :

    2017-06-01


    Format / Umfang :

    1078186 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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