Traffic light recognition is an important task for automatic driving support systems. Conventional traffic light recognition techniques are categorized into model-based methods, which frequently suffer from environmental changes such as sunlight, and machine-learning-based methods, which have difficulty detecting distant and occluded traffic lights because they fail to represent features efficiently. In this work, we propose a method for recognizing distant traffic lights by utilizing a semantic segmentation for extracting traffic light regions from images and a convolutional neural network (CNN) for classifying the state of the extracted traffic lights. Since semantic segmentation classifies objects pixel by pixel in consideration of the surrounding information, it can successfully detect distant and occluded traffic lights. Experimental results show that the proposed semantic segmentation improves the detection accuracy for distant traffic lights and confirms the accuracy improvement of 12.8 % over the detection accuracy by object detection. In addition, our CNN-based classifier was able to identify the traffic light status more than 30 % more accurately than the color thresholding classification.


    Zugriff

    Download

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Distant Traffic Light Recognition Using Semantic Segmentation


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:


    Erscheinungsdatum :

    07.07.2021




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Domain-Incremental Semantic Segmentation for Traffic Scenes

    Liu, Yazhou / Chen, Haoqi / Lasang, Pongsak et al. | IEEE | 2025




    TRAFFIC LIGHT RECOGNITION DEVICE AND TRAFFIC LIGHT RECOGNITION METHOD

    YAMANOI DAIKI / MATSUO HARUO / OKI TAKAHIKO et al. | Europäisches Patentamt | 2019

    Freier Zugriff