Unmanned Vehicular System (UVS) is the next revolutionary innovations of Intelligent Transport System powered by high-rate data transmission of 6G. The prime agenda of UVS is to offer a driver less car service from source to destination points with more emphasis over the accuracy and precision towards following the specified path. At present, such UVS is mechanized and look forward for travelling small distance traffic lanes with highly controlled environment. However, such UVS when exposed to real-time traffic system will be exposed to dynamic traffic density and only way to solve this challenge is to embed a proper decision making system within the vehicular node. Hence, Artificial Intelligence (AI) could significantly assist in doing so. Review of existing AI based mechanism towards traffic mobility and vehicular network has made couple of improvement; however, such improvements still fall very short when it comes to use AI on UVS. Therefore, the proposed study addresses this open-end challenge by developing a novel computational framework where AI is used for analysing the traffic attributes of lane system following by yielding a higher granularity in decision making for proper navigation of driver less car. An urban traffic environment is developed followed by configuring the network devices to acquire the traffic related information, which are then aggregated and forwarded to AI-based processor inside the vehicle. The outcome of the study is benchmarked with the existing schemes to find that proposed scheme offers better accuracy and safer driving experience on near-real world traffic system.


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    Titel :

    Novel Artificial-Intelligence Based Navigation Modelling for Unmanned Vehicular System


    Beteiligte:
    K C, Rajani (Autor:in) / K N, Manjunath (Autor:in) / Latha, D.Kusuma (Autor:in) / C, Thriveni (Autor:in)


    Erscheinungsdatum :

    07.12.2024


    Format / Umfang :

    782995 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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