The automotive world is striving to reduce traffic fatalities to a minimum. As human errors are the main cause of accidents, the industry is pushing advanced driver assistance features. On the route towards autonomous driving, boring routine tasks for the driver will gradually become obsolete. As driver assistance features and navigation systems rely on maps, autonomous driving will need the most recent, most up-to-date maps possible. This becomes clear when investigating the limitations of the range of ego sensors or recognition algorithms as well as information, e.g. legal traffic regulations per country, which cannot be derived from sensor observations.


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    Titel :

    Sensor-based learning algorithms pave the way towards autonomous driving


    Beteiligte:

    Kongress:

    AmE 2017 – Automotive meets Electronics - 8. GMM-Fachtagung ; 2017 ; Dortmund, Deutschland



    Erscheinungsdatum :

    2017-01-01


    Format / Umfang :

    6 pages



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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