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[국내논문] A Classification of Sitting Strategies based on Driving Posture Analysis 원문보기

Journal of the Ergonomics Society of Korea = 大韓人間工學會誌, v.33 no.2, 2014년, pp.87 - 96  

Park, Jangwoon (POSTECH: Department of Industrial and Management Engineering) ,  Choi, Younggeun (POSTECH: Department of Industrial and Management Engineering) ,  Lee, Baekhee (POSTECH: Department of Industrial and Management Engineering) ,  Jung, Kihyo (University of Ulsan: School of Industrial Engineering) ,  Sah, Sungjin (HYUNDAI MOTOR: Research & Development Division) ,  You, Heecheon (POSTECH: Department of Industrial and Management Engineering)

Abstract AI-Helper 아이콘AI-Helper

Objective: The present study is intended to objectively classify upper- & lower-body sitting strategies and identify the effects of gender and OPL type on the sitting strategies. Background: A sitting strategy which statistically represents comfortable driving posture can be used as a reference post...

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AI 본문요약
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제안 방법

  • 2cm) were attached on whole body of participant. In the measurement step, the participant was asked to sit on the driver mock-up with his/her preferred seating position and adjust seat configurations during 10-minute self-adjustment driving. After 10-minute self-adjustment driving, the preferred driving posture with both hands on 3-to-9 steering wheel positions was measured using the motion capture system in coupe, sedan, and SUV conditions.
  • In the synchronization of reference point and measured marker step, the adjusted reference points on the humanoid were used to synchronize with the measured markers in driving posture using RAMSIS Animation Simulator (38 reference points can be synchronized with measured markers at once) in order to reconstruct each participant’s driving posture using RAMSIS humanoid.
  • , gender, OPL condition) for the sitting strategy were not clearly identified. On the other hand, this study objectively classified sitting strategies using cluster analysis and statistically identified factors for the sitting strategies. Therefore, the classified sitting strategies can be used as a reference data for driver workspace design/evaluation using digital human model simulation at specific gender and OPL conditions.
  • The measured driving postures of the participants were reconstructed in three steps (generation of reference points, adjustment of reference point locations, and synchronization of reference points and measured markers) using RAMSIS® (Human Solution GmbH, Germany) humanoid.
  • The preferred driving postures of various body size drivers were measured in 3 occupant package layout (OPL) conditions (coupe, sedan, and SUV) using a motion capture system. The measured driving postures were statistically classified using a cluster analysis. The present study also analyzed the gender and OPL condition effect on the identified sitting strategies.

대상 데이터

  • The participants were recruited evenly for three stature groups (small: < 33rd %ile, medium: 33rd~66th %ile, large: > 66th %ile) formed by referring to corresponding Size Korea (2010) male and female anthropometric data (6 males for small, 6 for medium, and 8 for large group; 5 females for small, 8 females for medium, and 7 females for large group).

이론/모형

  • In the selection of proper number of cluster step, the number of clusters was selected based on a visual analysis of Euclidean distances between each cluster on a dendrogram plot from Ward's method.
  • Next, 21 anthropometric dimensions of the participant were obtained by following RAMSIS anthropometry protocol (Speyer, 2005) using a Martin's anthropometer (TTM, Tsutsumi Co., Japan).
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참고문헌 (12)

  1. Andreoni, G., Santambrogio, G.C., Rabuffetti, M. and Pedotti, A., Method for the analysis of posture and interface pressure of car drivers, Applied Ergonomics, 33, 511-522, 2002. 

  2. Cappozzo, A., Catani, F., Leardini, A., Benedetti, M.G. and Della Croce, U., Position and orientation in space of bones during movement: Experimental artifacts, Clinical Biomechanics, 11(2), 90-100, 1996. 

  3. Choi, Y., Park, J., Lee, B., Jung, K., Sah, S. and You, H., A classification of sitting strategies based on seating pressure distribution, Journal of the Korean Institute of Industrial Engineers, 39(2), 105-108, 2013. 

  4. Grieco, A., Sitting posture: an old problem and a new one, Ergonomics, 29(3), 345-362, 1986. 

  5. Kyung, G. and Nussbaum, M.A., Specifying comfortable driving postures for erfonomic design and evaluation of the driver workspace using digital human models, Ergonomics, 52(8), 939-953, 2009. 

  6. Park, J., Jung, K., Chang, J., Kwon, J. and You, H., Evaluation of predicted driving postures in RAMSIS digital human model simulation, IE Interfaces, 23(2), 101-108, 2010. 

  7. Park, S., Kim, C., Kim, C. and Lee, J., Comfortable driving postures for Koreans, International Journal of Industrial Ergonomics, 26, 489-497, 2000. 

  8. Park, S., Estimation of driver's standard postures by a multivariate analysis method, Journal of the Ergonomics Society of Korea, 25(1), 27-33, 2006. 

  9. Reed, M.P., Manary, M.A., Flannagan, C.A.C. and Schneider, L.W., A statistical method for predicting automobile driving posture, Human Factors, 44(4), 557-568, 2002. 

  10. Ryu, T., A Direct Estimation of Anatomical Landmark Positions from Skin Markers by Identifying the Displacement Relationship (Unpublished doctoral dissertation), POSTECH, Pohang, South Korea, 2006. 

  11. Size Korea, Report on the Fifth Survey of Korean Anthropometry, Retrieved June 26, 2010 from http://sizekorea.kats.go.kr/ 

  12. Speyer, H., RAMSIS Definition of Anthropometric Measurements, Human Solutions GmbH, Germany, 2005. 

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