PIPER - Position and Personalise Advanced Human Body Models for Injury Prediction
Overview
Background & policy context:
In passive safety, human variability is currently difficult to account for using crash test dummies and regulatory procedures. However, vulnerable populations such as children and elderly need to be considered in the design of safety systems in order to further reduce the fatalities by protecting all users and not only so called averages.
Based on the finite element method, advanced Human Body Models for injury prediction have the potential to represent the population variability and to provide more accurate injury predictions than alternatives using global injury criteria.
However, these advanced HBM are underutilised in industrial R&D. Reasons include difficulties to position the models – which are typically only available in one posture – in actual vehicle environments, and the lack of model families to represent the population variability (which reduces their interest when compared to dummies).
Objectives:
The main objective of the project will be to develop new tools to position and personalise these advanced HBM. Specifications will be agreed upon with future industrial users, and an extensive evaluation in actual applications will take place during the project. The tools will be made available by using an Open Source exploitation strategy and extensive dissemination driven by the industrial partners. Proven approaches will be combined with innovative solutions transferred from computer graphics, statistical shape and ergonomics modelling.
The consortium will be balanced between industrial users (with seven European car manufacturers represented), academic users involved in injury biomechanics, and partners with different expertise with strong potential for transfer of knowledge.
By facilitating the generation of population and subject-specific HBM and their usage in production environments, the tools will enable new applications in industrial R&D for the design of restraint systems as well as new research applications.
Share this page