Over the last years, radar based driver assistance and active safety systems have found wide spread application in nearly all vehicle brands all over the world. With the market introduction of the 2014 Mercedes-Benz S-Class vehicle equipped with six radar sensors covering the vehicles environment 360° in the near and far range, autonomous driving has become a reality even in low speed highway scenarios. This paves the way for a fast evolution of highly automated driving that also will extend to rural and urban traffic situations. One big straight ahead was made in August 2013. A Mercedes-Benz S-Class vehicle — Mercedes-internally called “Bertha”- drove completely autonomously for about 100 km from Mannheim to Pforzheim, Germany. It followed the well-known historic Bertha Benz Memorial Route. This was done on the basis of one stereo vision system, eight serial radar sensors and a huge amount of radar based innovative perception algorithms. These new algorithms taking into account that urban scenarios are characterized by dramatic shorter reaction and observation times, shorter mean free distances, a 360° interaction zone and a large variety of object types to be considered. Automotive radar has been the backbone of driver assistance systems and the innovation driver in this field. The question which came up was, will it be able to meet the requirements of eruptive innovations like autonomous driving. The article describes the main challenges, which Daimler radar researches had to face and their solutions to make Bertha see. It will also outline the remaining challenges for radar research and product development.


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    Titel :

    Radar contribution to highly automated driving


    Beteiligte:
    Dickmann, Juergen (Autor:in) / Appenrodt, Nils (Autor:in) / Bloecher, Hans-Ludwig (Autor:in) / Brenk, C. (Autor:in) / Hackbarth, Thomas (Autor:in) / Hahn, Markus (Autor:in) / Klappstein, Jens (Autor:in) / Muntzinger, Marc (Autor:in) / Sailer, Alfons (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2014-10-01


    Format / Umfang :

    433231 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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