In recent years, there has been a persistent increase in the number of road accidents worldwide. The US National Highway Traffic Safety Administration reports that distracted driving is responsible for approximately 45% of road accidents. In this study, we tackle the challenge of automating the detection and classification of driver distraction, along with the monitoring of risky driving behavior. Our proposed solution is based on the Pyramid Scene Parsing Network (PSPNet), which is a semantic segmentation model equipped with a pyramid parsing module. This module leverages global context information through context aggregation from different regions. We introduce a lightweight model for driver distraction classification, where the final predictions benefit from the combination of both local and global cues. For model training, we utilized the publicly available StateFarm Distracted Driver Detection Dataset. Additionally, we propose optimization techniques for classification to enhance the model’s performance.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Pyramid Scene Parsing Network for Driver Distraction Classification


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Farhaoui, Yousef (Herausgeber:in) / Hussain, Amir (Herausgeber:in) / Saba, Tanzila (Herausgeber:in) / Taherdoost, Hamed (Herausgeber:in) / Verma, Anshul (Herausgeber:in) / Khadraoui, Abdelhak (Autor:in) / Zemmouri, Elmoukhtar (Autor:in)

    Kongress:

    The International Conference on Artificial Intelligence and Smart Environment ; 2023 ; Errachidia, Morocco November 23, 2023 - November 25, 2023



    Erscheinungsdatum :

    2024-01-30


    Format / Umfang :

    6 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Driver distraction

    Skewes, D. | British Library Online Contents | 1997


    Driver distraction

    Kinnear, Neale / Stevens, Alan | ELBA - Bundesanstalt für Straßenwesen (BASt) | 2017

    Freier Zugriff


    Driver distraction determination

    OLSSON CLAES / GONZALEZ PINTOR SEBASTIAN / BRANNLUND OLLE | Europäisches Patentamt | 2020

    Freier Zugriff

    DRIVER DISTRACTION DETECTION

    HERMAN DAVID MICHAEL | Europäisches Patentamt | 2021

    Freier Zugriff