There is a lot of focus right now on how to build an autonomous vehicle, which can handle all the situations that a human driver is experiencing. Less is done on how to ensure that these vehicles are safe enough to be released to the public. Using traditional statistical methods would require one to drive extensive distances without incidents to prove the safety to a sufficient degree. Recent research has shown the possibility of using near-collisions in order to estimate the frequency of actual collisions using Extreme Value Theory. In order to trust these estimations, the precision of these estimates needs to be validated. The results from a 250 000 km field test shows that the Extreme Value estimations are reasonable in relation to a crash statistics estimate for rear-end collisions. This further suggests that extreme value is a method that can be used to predict collision frequencies from data containing no collisions.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Validation of collision frequency estimation using extreme value theory


    Contributors:


    Publication date :

    2017-10-01


    Size :

    201627 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Data-driven mid-air collision risk modelling using extreme-value theory

    Figuet, Benoit / Monstein, Raphael / Waltert, Manuel et al. | Elsevier | 2023


    Error Probability Estimation Using Bivariate Extreme-Value Theory

    Ashlock, John C. / Posner, Edward C. | IEEE | 1966


    The extreme value theory approach to safety estimation

    Songchitruksa, Praprut / Tarko, Andrew P. | Elsevier | 2006


    Collision prediction in roundabouts: a comparative study of extreme value theory approaches

    Orsini, Federico / Gecchele, Gregorio / Gastaldi, Massimiliano et al. | Taylor & Francis Verlag | 2019