Automobile Occupant Posture Prediction for Use with Human Models University of Michigan Transportation Research Institute

Format:

Conference/Event

Author/Creator:

Reed, Matthew P., author.

Conference Name:

International Congress & Exposition (1999-03-01 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 1999

Summary:

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

Notes:

Vendor supplied data

Publisher Number:

1999-01-0966

Access Restriction:

Restricted for use by site license