Advertisement

Finite Element Model of a High-Stature Male Pedestrian for Simulating Car-to-Pedestrian Collisions

  • Wansoo Pak
  • Yunzhu Meng
  • Jeremy Schap
  • Bharath Koya
  • Scott F. Gayzik
  • Costin D. UntaroiuEmail author
Article

Abstract

Among road traffic deaths, pedestrian accounted for 22 % of all fatalities in the world, 26 % in Europe, and 22 % in the U.S. To investigate the injury risk of the high-stature population, a Finite Element (FE) model corresponding to a male 95th percentile (M95) pedestrian was developed and validated in this study. The model mesh was obtained by morphing the Global Human Body Models Consortium male 50th percentile pedestrian model to the reconstructed geometry of a recruited high-stature human subject. The lower extremity, shoulder, and upper body of the FE model were validated against the Post Mortem Human Surrogate (PMHS) test data recorded in valgus bending, lateral, and anterior-lateral blunt impact tests. Then, a vehicle-pedestrian impact simulation was performed using the whole-body model. In the component validations, the M95 pedestrian model showed higher stiffness than the PMHS test corridors developed for 50th percentile male. The kinematic trajectories predicted by the FE model were well-correlated to the corresponding PMHS test data in whole-body validation. Therefore, the model could be used to investigate various pedestrian accidents and/or to improve safety regulations and vehicle front-end design for high-stature pedestrian protection.

Key Words

Finite element modeling Impact biomechanics Pedestrian protection 

Nomenclature

ACL

anterior cruciate ligament

ATD

anthropometric test device

CPC

car-to-pedestrian collisions

CG

center of gravity

Euro NCAP

european new car assessment program

FE

finite element

GHBMC

global human body models consortium

PMHS

post mortem human surrogate

LCL

lateral collateral ligament

M50-PS

male 50th percentile pedestrian simplified model

M95

male 95th percentile

M95-PS

male 95th percentile pedestrian simplified model

MCL

medial collateral ligament

NURBS

non-uniform rational basis spline

T1

first thoracic vertebra

TDAS

telemetry data acquisition system

WAD

wrap around distance

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgement

Funding for this study was provided by the Global Human Body Models Consortium (GHBMC). All findings and views reported in this manuscript are based on the opinions of the authors and do not necessarily represent the consensus or views of the funding organization.

References

  1. Arnoux, P. J., Cesari, D., Behr, M., Thollon, L. and Brunet, C. (2005). Pedestrian lower limb injury criteria evaluation: A finite element approach. Traffic Injury Prevention 6, 3, 288–297.CrossRefzbMATHGoogle Scholar
  2. Baker, W. A., Chowdhury, M. R. and Untaroiu, C. D. (2018a). A finite element model of an anthropomorphic test device lower limb to assess risk of injuries during vertical accelerative loading. J. Biomechanics, 81, 104–112.CrossRefGoogle Scholar
  3. Baker, W. A., Chowdhury, M. R. and Untaroiu, C. D. (2018b). Validation of a booted finite element model of the WIAMan ATD lower limb in component and wholebody vertical loading impacts with an assessment of the boot influence model on response. Traffic Injury Prevention 19, 5, 549–554.CrossRefGoogle Scholar
  4. Baker, W. A., Untaroiu, C. D., Crawford, D. M. and Chowdhury, M. R. (2017). Mechanical characterization and finite element implementation of the soft materials used in a novel anthropometric test device for simulating underbody blast loading. J. Mechanical Behavior of Biomedical Materials, 74, 358–364.CrossRefGoogle Scholar
  5. Bolte Iv, J. H., Hines, M. H., Herriott, R. G., Mcfadden, J. D. and Donnelly, B. R. (2003). Shoulder impact response and injury due to lateral and oblique loading. Stapp Car Crash Journal, 47, 35–53.Google Scholar
  6. Bolte, J. H., Hines, M. H., Mcfadden, J. D. and Saul, R. A. (2000). Shoulder response characteristics and injury due to lateral glenohumeral joint impacts. Stapp Car Crash Journal, 44, 261–280.Google Scholar
  7. Bose, D., Bhalla, K. S., Untaroiu, C. D., Ivarsson, B. J., Crandall, J. R. and Hurwitz, S. (2008). Injury tolerance and moment response of the knee joint to combined valgus bending and shear loading. J. Biomechanical Engineering 130, 3, 031008.CrossRefGoogle Scholar
  8. Compigne, S., Caire, Y., Quesnel, T. and Verries, J.-P. (2004). Non-injurious and injurious impact response of the human shoulder three-dimensional analysis of kinematics and determination of injury threshold. Stapp Car Crash Journal, 48, 89–123.Google Scholar
  9. Euro-Ncap (2018). Pedestrian Testing Protocol Version 9.0.2. November 2017 edn. Euro NCAP.Google Scholar
  10. Fredriksson, R., Rosén, E. and Kullgren, A. (2010). Priorities of pedestrian protection — A real-life study of severe injuries and car sources. Accident Analysis & Prevention 42, 6, 1672–1681.CrossRefGoogle Scholar
  11. Fredriksson, R., Shin, J. and Untaroiu, C. D. (2011). Potential of pedestrian protection systems—a parameter study using finite element models of pedestrian dummy and generic passenger vehicles. Traffic Injury Prevention 12, 4, 398–411.CrossRefGoogle Scholar
  12. Gayzik, F., Moreno, D., Danelson, K., Mcnally, C., Klinich, K. and Stitzel, J. D. (2012). External landmark, body surface, and volume data of a mid-sized male in seated and standing postures. Annals of Biomedical Engineering 40, 9, 2019–2032.CrossRefGoogle Scholar
  13. Gayzik, F., Moreno, D., Geer, C., Wuertzer, S., Martin, R. and Stitzel, J. (2011). Development of a full body CAD dataset for computational modeling: A multi-modality approach. Annals of Biomedical Engineering 39, 10, 2568–2583.CrossRefGoogle Scholar
  14. Gordon, C. C., Churchill, T., Clauser, C. E., Bradtmiller, B. and Mcconville, J. T. (1989). Anthropometric Survey of US Army Personnel: Methods and Summary Statistics 1988. DTIC Document.Google Scholar
  15. Han, Y., Yang, J. K., Mizuno, K. and Matsui, Y. (2012). Effects of vehicle impact velocity, vehicle front-end shapes on pedestrian injury risk. Traffic Injury Prevention 13, 5, 507–518.CrossRefGoogle Scholar
  16. Iwamoto, M., Omori, K., Kimpara, H., Nakahira, Y., Tamura, A., Watanabe, I., Miki, K., Hasegawa, J. and Oshita, F. (2003). Recent Advances in THUMS: Development of Individual Internal Organs, Brain, Small Female, and Pedestrian Model. Ulm, Germany.Google Scholar
  17. Kerrigan, J. R., Crandall, J. R. and Deng, B. (2007). Pedestrian kinematic response to mid-sized vehicle impact. Int. J. Vehicle Safety 2, 3, 221–240.CrossRefGoogle Scholar
  18. Kerrigan, J. R., Parent, D. P., Untaroiu, C., Crandall, J. R. and Deng, B. (2009). A new approach to multibody model development: Pedestrian lower extremity. Traffic Injury Prevention 10, 4, 386–397.CrossRefGoogle Scholar
  19. Koh, S.-W., Cavanaugh, J. M., Mason, M. J. and Petersen, S. A. (2005). Shoulder injury and response due to lateral glenohumeral joint impact: An analysis of combined data. Stapp Car Crash Journal, 49, 291–322.Google Scholar
  20. Kothari, V. and Gangal, M. (1994). Assessment of frictional properties of some woven fabrics. Indian J. Fibre & Textile Research 19, 3, 151–155.Google Scholar
  21. Lu, Y. C. and Untaroiu, C. D. (2014). A statistical geometrical description of the human liver for probabilistic occupant models. J. Biomechanics 47, 15, 3681–3688.CrossRefGoogle Scholar
  22. Marth, D. R. (2002). Biomechanics of the Shoulder in Lateral Impact. Ph. D. Dissertation. Wayne State University. Detroit, Michigan, USA.Google Scholar
  23. Martin, J.-L., Lardy, A. and Laumon, B. (2011). Pedestrian injury patterns according to car and casualty characteristics in France. Annals of Advanced in Automotive Medicine, 55, 137–146.Google Scholar
  24. Meng, Y., Pak, W., Guleyupoglu, B., Koya, B., Gayzik, F. S. and Untaroiu, C. D. (2017). A finite element model of a six-year-old child for simulating pedestrian accidents. Accident Analysis & Prevention, 98, 206–213.CrossRefGoogle Scholar
  25. Okamoto, Y., Sugimoto, T., Enomoto, K. and Kikuchi, J. (2003). Pedestrian head impact conditions depending on the vehicle front shape and its construction—full model simulation. Traffic Injury Prevention 4, 1, 74–82.CrossRefGoogle Scholar
  26. Petitjean, A., Trosseille, X., Yoganandan, N. and Pintar, F. A. (2015). Normalization and scaling for human response corridors and development of injury risk curves. Accidental Injury, 769–792.Google Scholar
  27. Putnam, J. B., Somers, J. T. and Untaroiu, C. D. (2014). Development, calibration, and validation of a head-neck complex of THOR mod kit finite element model. Traffic Injury Prevention 15, 8, 844–854.CrossRefGoogle Scholar
  28. Saez, L. M., Casanova, L. J. G., Fazio, E. A. and Alvarez, A. G. (2012). Behaviour of high bumper vehicles in pedestrian scenarios with full finite element human models. Int. J. Crashworthiness 17, 1, 1–10.CrossRefGoogle Scholar
  29. Schwartz, D., Guleyupoglu, B., Koya, B., Stitzel, J. D. and Gayzik, F. S. (2015). Development of a computationally efficient full human body finite element model. Traffic Injury Prevention 16, Supplement 1, S49–S56.CrossRefGoogle Scholar
  30. Takahashi, Y., Kikuchi, Y., Konosu, A. and Ishikawa, H. (2000). Development and validation of the finite element model for the human lower limb of pedestrians. Stapp car Crash Journal, 44, 335–355.Google Scholar
  31. Untaroiu, C., Darvish, K., Crandall, J., Deng, B. and Jenne-Tai, W. (2005). A finite element model of the lower limb for simulating pedestrian impacts. Stapp Car Crash Journal, 49, 157–181.Google Scholar
  32. Untaroiu, C., Shin, J., Ivarsson, J., Crandall, J., Takahashi, Y., Akiyama, A. and Kikuchi, Y. (2007a). Pedestrian kinematics investigation with finite element dummy model based on anthropometry scaling method. Proc. 20th Int. Technical Conf. Enhanced Safety of Vehicles, Lyon, France.Google Scholar
  33. Untaroiu, C. D., Crandall, J. R., Takahashi, Y., Okamoto, M., Ito, O. and Fredriksson, R. (2010a). Analysis of running child pedestrians impacted by a vehicle using rigid-body models and optimization techniques. Safety Science 48, 2, 259–267.CrossRefGoogle Scholar
  34. Untaroiu, C. D., Kerrigan, J., Kam, C., Crandall, J., Yamazaki, K., Fukuyama, K., Kamiji, K., Yasuki, T. and Funk, J. (2007b). Correlation of strain and loads measured in the long bones with observed kinematics of the lower limb during vehicle-pedestrian impacts. Stapp Car Crash Journal, 51, 433–466.Google Scholar
  35. Untaroiu, C. D., Meissner, M. U., Crandall, J. R., Takahashi, Y., Okamoto, M. and Ito, O. (2009). Crash reconstruction of pedestrian accidents using optimization techniques. Int. J. Impact Engineering 36, 2, 210–219.CrossRefGoogle Scholar
  36. Untaroiu, C. D., Pak, W., Meng, Y., Schap, J., Koya, B. and Gayzik, S. (2018). A finite element model of a midsize male for simulating pedestrian accidents. J. Biomechanical Engineering 140, 1, 011003.CrossRefGoogle Scholar
  37. Untaroiu, C. D., Putnam, J. B., Schap, J., Davis, M. L. and Gayzik, F. S. (2015). Development and preliminary validation of a 50th percentile pedestrian finite element model. Proc. ASME Int. Design Engineering Technical Conf. & Computer and Information in Engineering Conf. Boston, Massachusetts, USA.Google Scholar
  38. Untaroiu, C. D., Shin, J., Crandall, J. R., Fredriksson, R., Bostrom, O., Takahashi, Y., Akiyama, A., Okamoto, M. and Kikuchi, Y. (2010b). Development and validation of pedestrian sedan bucks using finite-element simulations: A numerical investigation of the influence of vehicle automatic braking on the kinematics of the pedestrian involved in vehicle collisions. Int. J. Crashworthiness 15, 5, 491–503.CrossRefGoogle Scholar
  39. Untaroiu, C. D., Yue, N. and Shin, J. (2013). A finite element model of the lower limb for simulating automotive impacts. Annals of Biomedical Engineering 41, 3, 513–526.CrossRefGoogle Scholar
  40. Vavalle, N. A., Schoell, S. L., Weaver, A. A., Stitzel, J. D. and Gayzik, F. S. (2014). Application of radial basis function methods in the development of a 95th percentile male seated fea model. Stapp Car Crash Journal, 58, 361–384.Google Scholar
  41. Viano, D. C. (1989). Biomechanical responses and injuries in blunt lateral impact. SAE Paper No. 892432.Google Scholar
  42. Watanabe, R., Katsuhara, T., Miyazaki, H., Kitagawa, Y. and Yasuki, T. (2012). Research of the relationship of pedestrian injury to collision speed, car-type, impact location and pedestrian sizes using human FE model (THUMS Version 4). Stapp Car Crash Journal, 56, 269–321.Google Scholar
  43. Weiss, J. A. and Gardiner, J. C. (2001). Computational modeling of ligament mechanics. Critical Reviews in Biomedical Engineering 29, 4, 1–70.Google Scholar
  44. WHO (2016). Road Traffic Injuries. World Health Organization. http://www.who.int/mediacentre/factsheets/fs358/en
  45. Yates, K. M., Lu, Y. C. and Untaroiu, C. D. (2016). Statistical shape analysis of the human spleen geometry for probabilistic occupant models. J. Biomechanics 49, 9, 1540–1546.CrossRefGoogle Scholar
  46. Yates, K. M. and Untaroiu, C. D. (2018). Finite element modeling of the human kidney for probabilistic occupant models: Statistical shape analysis and mesh morphing. J. Biomechanics, 74, 50–56.CrossRefGoogle Scholar
  47. Yue, N. and Untaroiu, C. D. (2014). A numerical investigation on the variation in hip injury tolerance with occupant posture during frontal collisions. Traffic Injury Prevention 15, 5, 513–522.CrossRefGoogle Scholar
  48. Zegeer, C. V. and Bushell, M. (2012). Pedestrian crash trends and potential countermeasures from around the world. Accident Analysis & Prevention 44, 1, 3–11.CrossRefGoogle Scholar

Copyright information

© KSAE 2019

Authors and Affiliations

  • Wansoo Pak
    • 1
  • Yunzhu Meng
    • 1
  • Jeremy Schap
    • 2
  • Bharath Koya
    • 2
  • Scott F. Gayzik
    • 2
  • Costin D. Untaroiu
    • 1
    Email author
  1. 1.Department of Biomedical Engineering and MechanicsVirginia Polytechnic Institute and State UniversityBlacksburgUSA
  2. 2.Department of Biomedical EngineeringWake Forest UniversityWinston-SalemUSA

Personalised recommendations