• Journal of Korean Institute of Industrial Engineers
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• v.34 no.1
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• pp.57-65
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• 2008

In the vehicle design, the research on driving posture has stood out as one of the important issues. Recently, the research on 3D human modeling focused on more exact implementation of real driving posture. However, prediction of driving posture through the 3D human modeling fail to reflect on the model the phenomenon called sagging, which refers to the retraction or shrinking of the torso while driving. 30 male subjects participated in the experiment where total subjects were divided into four groups according to height percentile(under 50%ile, 51%ile to 75%ile, 76%ile to 95%ile, over 95%ile). The independent variables were seat back angle(4 levels) and seat pan angle(2 levels). The dependent variable was capacity or the degree of retraction of the torso. First this study measured the sagging capacity by using a paired T-test between erect and retracted posture. Secondly it was tried to find out significant anthropometric variables that were statistically correlated by the analysis of correlation. Finally, a prediction model was derived which explains the capacity of sagging.

• IE interfaces
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• v.23 no.2
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• pp.100-107
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• 2010

For proper ergonomic evaluation using a digital human model simulation (DHMS) system such as $RAMSIS^{(R)}$, the postures of humanoids for designated tasks need to be predicted accurately. The present study (1) evaluated the accuracy of driving postures of humanoids predicted by RAMSIS, (2) proposed a method to improve its accuracy, and (3) examined the effectiveness of the proposed method. The driving postures of 12 participants in a seating buck were measured by a motion capture system and compared with their corresponding postures predicted by RAMSIS. Significant discrepancies ($8.7^{\circ}$ to $74.9^{\circ}$) between predicted and measured postures were observed for different body parts and driving tasks. Two methods (constraints addition and user-defined posture) were proposed and their effects on posture estimation accuracy were examined. Of the two proposed methods, the user-defined posture method was found preferred, reducing posture estimation errors by 11.5% to 84.9%. Both the posture prediction accuracy assessment protocol and user-defined posture method would be of use for practitioners to improve the accuracy of predicted postures of humanoids in virtual environments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.162-172
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• 2014

A three-dimensional dynamic model for simulating various motions of full vehicle is presented. The model has 16 independent degrees of freedom (DOF) consisting of three kinds of components; a vehicle body of 6 DOF, 4 independent suspensions equipped at every corner of the body, and 4 tire models linked with each suspension. The dynamic equations are represented in six coordinate frames such as world fixed coordinate, vehicle fixed coordinate, and four wheel fixed coordinate frames. Then these lead to the approximated prediction model of vehicle posture. Both lateral and longitudinal dynamics can be computed simultaneously under the conditions of which various inputs including steering command, driving torque, gravity, rolling resistance of tire, aerodynamic resistance, etc. are considered. It is shown through simulations that the proposed 3D model can be useful for precise design and performance analysis of any full vehicle control systems.