Digital human model for driver seat adjustment range determination

Jared Gragg, Jingzhou Yang, James David Long

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations


Digital human modeling and simulation allows a designer to test a product early in the design process. Accounting for variability in the human population which the product is intended for is difficult without developing physical prototypes and conducting population testing. Digital human modeling allows a designer to test a product without a physical prototype in a simulated environment using digital humans. Using digital humans, or manikins, of various sizes, a designer can test for variability in the human population before any physical prototype is needed. This paper proposes an optimization-based approach to determine the seat adjustment range in the interior cab design of a vehicle. Previous methods of cab design include population sampling and stochastic posture prediction. This paper places boundary anthropometric digital human models, a 95% male and a 5% female, in a 3D test environment. The boundary manikins perform reach tests to establish the optimum driver seat adjustment range. The models employ an optimization-based approach that predicts the optimum posture of the seated driver. The simulation also gives an indication of how comfortable the driver is while seated in the predicted posture.

Original languageEnglish
JournalSAE Technical Papers
StatePublished - 2010
EventSAE 2010 World Congress and Exhibition - Detroit, MI, United States
Duration: Apr 13 2010Apr 13 2010


  • digital human modeling
  • optimization
  • posture prediction
  • seat adjustment range


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