Vehicle self-localization in complex scenarios is a critical problem for autonomous driving system. Current localization techniques perform well in open-sky areas, while in closed-sky areas, localization accuracy is rapidly degenerated due to unfavorable factors as denied satellite signal, accumulated error and traffic congestion. Therefore, we proposed a novel system in this work, which is able to achieve lane-level vehicle self-localization in special roads under bridges or viaducts without the help of Global Navigation Satellite System (GNSS). In the system, all data is collected by stereo camera and inertial sensors, and fused in three different levels for reducing the uncertainty of data and acquiring a more accurate localization result. The proposed system is proved to be effective and robust through experiments conducted in Shinjuku, Tokyo.


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    Titel :

    Lane-level vehicle self-localization in under-bridge environments based on multi-level sensor fusion


    Beteiligte:
    Xie, Lijia (Autor:in) / Gu, Yanlei (Autor:in) / Kamijo, Shunsuke (Autor:in)


    Erscheinungsdatum :

    01.10.2017


    Format / Umfang :

    613689 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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