In this article, we propose malfunction classifications for trucks, a novel idea for smart fleet management systems. In the proposed cooperative cooperative intelligent transportation (C-ITS), the developed neural network work with information from truck fleets to select the trucks that need a service. From the results returned from the deep neural network classifier, the applied heuristic algorithm uses the classification outputs to select the most important results. The proposed process is multithreaded; thus, the composed system gains additional efficiency. The implemented deep learning model achieved an accuracy above 98%, and an above 95% recall. The developed solution was tested on the Scania Truck data collection. The research results show the importance of the advances and validate our concept for potential further development.


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    Titel :

    Deep Neural Network Heuristic Hierarchization for Cooperative Intelligent Transportation Fleet Management


    Beteiligte:
    Ke, Qiao (Autor:in) / Silka, Jakub (Autor:in) / Wieczorek, Michal (Autor:in) / Bai, Zongwen (Autor:in) / Wozniak, Marcin (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2022-09-01


    Format / Umfang :

    4409892 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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