The primary reason for car accidents is caused by driver’s error. In this work, we consider some critical factors related to driver’s behavior that can lead to a car accident such as recognition error, decision error and performance error. We propose a fuzzy logic system to determine the Driver’s Error Value (DEV) for evaluating the driver’s decision in real-time. We show through simulations the effect of each considered parameter and demonstrate some actions to prevent a possible crash when the driver shows a high error value. The fuzzy logic system is implemented in vehicles in a Vehicular Ad hoc Network (VANET) environment which are able to exchange information with each-other in real time and based on the DEV output the drivers are informed when they have approached a potential dangerous situation.


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    Titel :

    A Fuzzy-Based Error Driving System 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:

    Conference on Complex, Intelligent, and Software Intensive Systems ; 2023 ; Toronto Metropolitan University, ON, Canada July 05, 2023 - July 07, 2023



    Erscheinungsdatum :

    19.06.2023


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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