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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.

Traffic accidents cause one of the highest numbers of severe injuries in the whole population. The numbers of deaths or seriously injured citizens prove that traffic accidents and their consequences are still a serious problem to be solved. A lot of effort is devoted to both passive and active safety systems development. The transportation standards usually define safety requirements by regulations (e.g. ECE-R94, 96/79/EC and ECE-R95, 96/27/EC in Europe) with specific dummies for children to be used. The dummies include hardware sensors for monitoring accelerations, loads and other signals and each dummy is developed for a specific scenario, but there are limitations of these dummies, such as only a specific age or calibration just for a specific test.

The paper contributes to the field of vehicle safety technology by the virtual approach using biomechanical virtual human body models. The goal of the paper is to exploit the previously developed scaling algorithm to create several virtual human models of a given age and body proportions and to assess the impact analysis using the sensitivity approach. Based on a validated reference model, the previously developed scaling algorithm develops virtual human body models for given height, mass, age and gender. Particular body segments are scaled based on the anthropometrical database concerning the body dimensions taking also percentiles into account. The body stiffness is driven by age dependent flexindex. Several virtual models of human bodies representing particular cadavers were generated via the automatic scaling algorithm. The frontal sled test response of three models was successfully compared to the available experimental data previously.