As the main pillar of the Smart City, Smart Highway manifests the centralized connectivity concept between the self-driving vehicles. Internet of Vehicle or IoV is the solution for improved connectivity between driverless vehicles. One of the major challenges in IoV research is the lack of datasets available. That is why the Internet of vehicles is one of the hot topics in research nowadays. IoV field is still a new topic in research, which leaves a huge shortage in the datasets available to train any Artificial Intelligent (AI) model for IoV systems. IoV systems have many research points such as resources mapping and car paths predictions, which requires datasets from real-life traffic and cities road to train AI models. The goal of this research is to design a simulation for the IoV system by creating a city model that simulates any realistic city traffic, roads, different places, and cars with its resources. Having this city model, datasets could be obtained to train AI models to get more knowledge about the IoV systems.


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    Titel :

    A Probabilistic City Model Generation for Application in Internet of Vehicles Technology


    Beteiligte:
    Barakat, Mohannad (Autor:in) / Magdy, Noha (Autor:in) / El-Shimy, Mohamed (Autor:in) / Mokhtar, Bassem (Autor:in)


    Erscheinungsdatum :

    2021-12-12


    Format / Umfang :

    1106954 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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