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This paper focuses on full body dynamical analysis of car ingress/egress motion. It aims at proposing an experimental protocol adapted for analysing joint loads using inverse dynamics. Two preliminary studies were first performed in order to 1/ define the main driver/car interactions so as to allow measuring the contact forces at all possible contact zones and 2/ identify the design parameters that mainly influence the discomfort. In order to verify the feasibility of the protocol, a laboratory study was carried out, during which two subjects tested two car configurations. The experimental equipment was composed of a variable car mock-up, an optoelectronic motion tracking system, two 6D-force plates installed on the ground next to the doorframe and on the car floor, a 6D-Force sensor between the steering wheel and the steering column, and two pressure maps on the seat. Motions were reconstructed from measured surface markers trajectories using inverse kinematics.

This paper presents the first experiment managed within the framework of the regional French project ST2 (French acronym for Sciences and Technologies for Safety in Transports). This program aims to study human pre-crash behavior in order to improve the efficiency of passive safety protection systems. An experiment was carried out using a driving simulator of LAMIH for investigating drivers frontal pre-crash postural changes. A scenario of an unavoidable crash was designed. To increase the level of realism during the crash, a real impact was added between the windscreen and a foam rubber block in addition to a truck horn sound. Risk car driver postures just before a frontal crash have been determined. The results have shown that none of the subjects adopted the standardized driving position during the collision and 30% of the subjects adopted a position with the left hand placed in front of steering wheel which can be considered as a risk position.

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.

Monitoring driver’s postures has extensive applications. The postural information could be used for the development of smart airbags, for detecting possible fatigue in long travel and for recognizing activities which may determine if the driver has enough time to take over the control in an intelligent vehicle when encountering hazardous situations. Microsoft Kinect is one of the best candidates for monitoring driver’s posture thanks to its innovative feature of real time motion capture without use of markers and its low cost. However, when body parts are partially occluded, the accuracy of Kinect data will drop markedly. Inspired by previous researches, the present work focused on testing a data driven approach for improving driver’s upper body movement reconstruction with a Kinect camera. Firstly, we organize a database of accurately captured driver poses from different motion clips with filtered structures, including a global motion graph and multiple local motion graphs.

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.

Recently, we proposed a unified data based approach which aimed at predicting both reach envelopes and reach discomfort for a digital human model [1]. In this approach, four reach surfaces, from half-flexed arm distance to maximum reach with torso participation, need to be defined. The discomfort associated with a point on each surface is defined at first. Then, the discomfort of an intermediate distance between two reach distances is interpolated. The proposed approach was demonstrated on a reaching task corresponding to push a toggle switch from a seated posture without seat back. As data were collected in an environment which is different from the driving situation, these data can not be directly applied to driver's reach capacity and discomfort. In this study, we will apply this approach for in-car driver's reach for predicting different reach envelopes and discomfort.

Improvement in the accessibility assessment of the seatbelts using a Digital Human Model requires a precise description of driver belt donning movement and of the associated discomfort. In order for automotive designers to be able to simulate seatbelt reaching movement, a general approach of motion simulation for complex and specific tasks has been proposed in this paper. It consists of three steps: constitution of a structured database, selection of an appropriate movement and its adaptation to meet new constraints. From an experiment, a database of 644 movements of automotive seatbelt reaching movements has been built-up. In order to structure the database, the temporal and spatial characteristics of the trajectories of main markers (e.g. markers attached to the hand and the torso) as well as joint movements were analysed, allowing us to identify motion control strategies.