In this work, we focus on the major cause of car accidents - driver errors, which include recognition, decision, performance and non-performance errors. Non-performance errors are critical for assessing driver’s error because they involve situations where the driver fails to take any action to keep the vehicle on the road or avoid an accident, such as falling asleep at the wheel. To assess driver decisions in real-time, we propose a fuzzy logic system that calculates the Driver’s Error Value (DEV). We demonstrate the impact of each parameter and suggest preventive measures to avoid accidents when the driver’s error value is high. Our system is implemented in vehicles in a Vehicular Ad hoc Network (VANET) environment, where real-time information exchange enables drivers to be alerted of potential dangerous situations based on the DEV output.


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    Titel :

    A Fuzzy-Based Error Driving System: Effect of Non Performance Error for Improving Driving Performance in VANETs


    Weitere Titelangaben:

    Lect. Notes on Data Eng. and Comms.Technol.


    Beteiligte:
    Barolli, Leonard (Herausgeber:in) / Qafzezi, Ermioni (Autor:in) / Bylykbashi, Kevin (Autor:in) / Higashi, Shunya (Autor:in) / Ampririt, Phudit (Autor:in) / Matsuo, Keita (Autor:in) / Barolli, Leonard (Autor:in)

    Kongress:

    International Conference on Network-Based Information Systems ; 2023 ; Chiang Mai University, Thailand September 06, 2023 - September 08, 2023



    Erscheinungsdatum :

    24.08.2023


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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