A new method of predicting automobile occupant posture is presented. The Cascade Prediction Model approach combines multiple independent predictions of key postural degrees of freedom with inverse kinematics guided by data-based heuristics. The new model, based on posture data collected in laboratory mockups and validated using data from actual vehicles, produces accurate posture predictions for a wide range of passenger car interior geometries. Inputs to the model include vehicle package dimensions, seat characteristics, and occupant anthropometry. The Cascade Prediction Model was developed to provide accurate posture prediction for use with any human CAD model, and is applicable to many vehicle design and safety assessment applications.


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    Title :

    Automobile Occupant Posture Prediction for Use with Human Models


    Additional title:

    Sae Technical Papers



    Conference:

    International Congress & Exposition ; 1999



    Publication date :

    1999-03-01




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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