Prediction of Injury Risk in Pedestrian Accidents Using Virtual Human Model VIRTHUMAN: Real Case and Parametric Study 2016-01-1511
In this work we present the VIRTHUMAN model as a tool for injury risk assessment in pedestrian crash scenarios. It is a virtual human body model formed of a multibody structure and deformable segments to account for the mechanical response of soft tissues. Extensive validation has been performed to ensure its biofidelity. Due to the scaling algorithm implemented, variations in the human population in terms of height, weight, gender and age can be considered. Assessment of the injury risk is done via automatic evaluation software developed. Injury criteria for individual body parts are evaluated using accelerations, forces and displacements of certain points. Injury risk is indicated by the colour of particular body parts in accordance with NCAP rating. A real accident is investigated in this work. A 60-year-old female was hit laterally by a passenger vehicle with the impact velocity of 40 km/h. The accident is reconstructed using VIRTHUMAN as pedestrian representative. Good agreement of the simulation and real data in terms of falling distance and injury sustained by pedestrian is obtained. Finally, a parametric study is performed based on the real accident. Crash scenarios with vehicle hitting various pedestrian representatives at 40 km/h and 45 km/h are analyzed. The results indicate the injury patterns sustained by pedestrians are dependent on their height.
Citation: Vychytil, J., Hyncik, L., Manas, J., Pavlata, P. et al., "Prediction of Injury Risk in Pedestrian Accidents Using Virtual Human Model VIRTHUMAN: Real Case and Parametric Study," SAE Technical Paper 2016-01-1511, 2016, https://doi.org/10.4271/2016-01-1511. Download Citation
Author(s):
Jan Vychytil, Ludek Hyncik, Jaroslav Manas, Petr Pavlata, Radim Striegler, Tomas Moser, Radek Valasek
Affiliated:
University of West Bohemia, Mecas ESI s.r.o., Vision Consulting Automotive s.r.o., Transport Research Centre, IDIADA CZ a.s., BRANO a.s.
Pages: 11
Event:
SAE 2016 World Congress and Exhibition
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Risk assessments
Injuries
Mathematical models
Crashes
Parts
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