Machine-learning models are described detecting the signaling state of a traffic signaling unit. A system can obtain an image of the traffic signaling unit, and select a model of the traffic signaling unit that identifies a position of each traffic lighting element on the unit. First and second neural network inputs are processed with a neural network to generate an estimated signaling state of the traffic signaling unit. The first neural network input can represent the image of the traffic signaling unit, and the second neural network input can represent the model of the traffic signaling unit. Using the estimated signaling state of the traffic signaling unit, the system can inform a driving decision of a vehicle.


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    Titel :

    DETECTING TRAFFIC SIGNALING STATES WITH NEURAL NETWORKS


    Weitere Titelangaben:

    ERKENNUNG VON VERKEHRSSIGNALISIERUNGSZUSTÄNDEN MIT NEURONALEN NETZWERKEN
    DÉTECTION D'ÉTATS DE SIGNALISATION DE TRAFIC AVEC DES RÉSEAUX NEURONAUX


    Beteiligte:
    HSIAO EDWARD (Autor:in) / OUYANG YU (Autor:in) / YAO MAOQING (Autor:in)

    Erscheinungsdatum :

    24.05.2023


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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