In the developement of safe intelligent vehicles, intentions of other road users need to be estimated in order to plan a safe and convenient trajectory. The present work tries to approach the answer to the question of how a prediction could be assessed holistically using the example of pedestrian prediction. Recently used metrics are compared on a state of the art (SOTA) prediction method. A good prediction does not only have to verify itself on a limited data set, so machine versus human pedestrian prediction are compared. A study with test persons points out the similarity of human predictions compared to SOTA prediction. However, further research is required since we cannot propose a holistic metric that answers the question in the title, yet.


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    Titel :

    What Does a Good Prediction Look Like?


    Beteiligte:
    Wirth, Florian (Autor:in) / Krane, Stephan (Autor:in) / Loos, Melanie (Autor:in) / Rehder, Eike (Autor:in) / Fernandez, Carlos (Autor:in)


    Erscheinungsdatum :

    01.10.2019


    Format / Umfang :

    1486733 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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