The correct handling of complex traffic-light-controlled intersections is still a challenge for automated vehicles. While a number of image-based approaches tackle close-range recognitions, an early traffic light detection at high distances is of great importance in the area of energy-efficient driving. For this reason, a traffic light detection system consisting of multiple on-board cameras is presented in this work, enabling the detection of traffic lights even from a distance of more than 200m. Furthermore, the presented system is based on tracking techniques using a Labeled Multi-Bernoulli filter in combination with the fusion of classifications based on the Dempster-Shafer theory of evidence. The system was tested on a real world data set collected in Germany and an increase in performance was demonstrated by a multi-camera approach.


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    Titel :

    Multi-camera traffic light recognition using a classifying Labeled Multi-Bernoulli filter


    Beteiligte:
    Bach, Martin (Autor:in) / Reuter, Stephan (Autor:in) / Dietmayer, Klaus (Autor:in)


    Erscheinungsdatum :

    2017-06-01


    Format / Umfang :

    306580 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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