In a double-blind experimental design three premium class vehicles are evaluated psychoacoustically with respect to the annoyance of instationary wind noise in vehicles. The study comprises a set of methods for optimizing psychological scaling of basic attributes in order to maximize the measurable differences between the vehicles. Starting with standard methods of attribute elicitation (focus-group, expert panel, repertory grid) and attribute scaling (semantic differential), the obtained data are aggregated via factor analysis. Three factors prove to be statistically consistent and can be interpreted as (fl) proximity, (f2) harshness, and (f3) loudness. Results are discussed with respect to their potential of predicting the annoyance of turbulent flow in highway situations based on wind tunnel data by means of multiple regression. The systematical extraction of attributes and use of semantic differential by experts showed up to be a reliable empirical basis for evaluating psychoacoustical properties of instationary wind noise transmissioned into vehicles. Attribute ratings can be aggregated to three factors interpreted as 'proximity', 'harshness', and 'loudness'. Data from wind tunnel allow a prediction of annoyance for highway situations best out of the selected attributes. Due to statistical optimizing with respect to the three premium vehicles under question, a broader data basis might even increase the potential of the presented approach.


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    Titel :

    Psychoacoustic evaluation of instationary wind noise transmissioned into vehicles


    Weitere Titelangaben:

    Psychoakustische Bewertung des in Fahrzeuge übertragenen instatioären Windgeräusches


    Beteiligte:
    Graf, Ralf (Autor:in) / Miehling, Hans (Autor:in) / Maier, Kathrin (Autor:in) / Lindener, Norbert (Autor:in) / Hellbrueck, Juergen (Autor:in)


    Erscheinungsdatum :

    2009


    Format / Umfang :

    4 Seiten, 2 Bilder, 7 Quellen



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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