The present study aims to provide answers and explanations resulting from statistical analyses to critical questions related to the reliability of autonomous driving systems. The objective of the paper is to define for how long and what distances they need to be tested, until their reliable operation is proven. While the technology itself has the potential to significantly reduce the frequency of accidents in road traffic, the obtained results demonstrate that fully self-driving cars necessitate covering hundreds of thousands, or even tens of millions of kilometers to prove their reliability. This means that current fleets would require decades, or even centuries to reach these milestones – an unfeasible task if the objective is to prove their performance before they are allowed to drive on public roads. The findings of this study support the need for alternative methods to supplement real-world tests in assessing their functional safety, while also developing appropriate policies and regulations.


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    Titel :

    Failure Rate Analysis of Driverless Car Reliability Using Different Confidence Intervals


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Baranyi, Péter (Herausgeber:in) / Palkovics, László (Herausgeber:in) / Zöldy, Máté (Herausgeber:in) / Ferencz, Csanád (Autor:in) / Zöldy, Máté (Autor:in)

    Kongress:

    IEEE International Conference on Cognitive Mobility ; 2023 ; Budapest, Hungary October 19, 2023 - October 20, 2023



    Erscheinungsdatum :

    28.04.2025


    Format / Umfang :

    14 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






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