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Driving posture study is essential for the evaluation of the occupant packaging. This paper presents a method of reconstructing driver’s postures in a real vehicle using a 3D laser scanner and Human Builder (HB), the digital human modeling tool under CATIA. The scanning data was at first converted into the format readable by CATIA, and then a personalized HB manikin was generated mainly using stature, sitting height and weight. Its pelvis position and joint angles were manually adjusted so as to match the manikin with the scan envelop. If needed, a fine adjustment of some anthropometric dimensions was also preceded. Finally the personalized manikin was put in the vehicle coordinate system, and joint angels and joint positions were extracted for further analysis.

Realistic simulation of human posture and movement is one of key requirements for digital human models for workplace design. In a recent European research project REAL MAN (IST 2000-29357), we have suggested a data-based motion simulation approach, which includes motion capture, model-based motion reconstruction, motion analysis and data structuration, motion simulation and discomfort estimation. After the REAL MAN project, we have decided to apply this approach and to create a complete in-vehicle reach motion database for car interior design. The objective of this paper is to show our in-vehicle reach motion database. Two female and four male subjects participated in motion data collection. Each subject carried out 64 reach movements which covered 17 common driver’s control command reaches. Motion data were analyzed in order to identify key kinematic characteristics of each motion and then structured according to subject’s anthropometric information; task and command location.

Realistic motion reconstruction is the first step for ‘human like’ motion simulation by a digital human. In a recent European research project REALMAN (IST 2000-29357), a model-based motion reconstruction method from external marker trajectories was developed. It consists of two steps. The first one is to define a digital twin of a real subject using the technique of superimposing a digital human model upon at least two photos of different view, and identifying marker positions on it. In a second step, joint angles are estimated by using a kinematic model of the human body which is described using natural coordinates: coordinates of points and components of unit vectors for defining the joint locations. The model includes a detailed description of the torso, arms and legs, with simplified hands and feet. A total of 26 joints are used, connecting 27 rigid links, among them 6 located on the spine.

An airplane passenger seat, like other seats in transportation, is used by thousands or millions of people. The seat should be designed to accommodate the maximum number of a target population by taking into account the variability of body size and also the environment’s constraints. Thanks to a fully adjustable experimental seat recently built at IFSTTAR, data of the preferred seat profile and compressed seat pan surface were collected in function of seat pan and backrest angle from a sample of 36 differently sized participants. Parametric models were obtained to predict optimal seat profile parameters in function of a sitter’s anthropometric characteristics, seat pan angle and seat back angle. Using a population simulation approach, a sample of 500 males and 500 females were generated randomly based on the distribution of relevant anthropometric dimensions.