Government agencies, globally, often strive to minimize the risk of human death and serious injury on road transport systems. Multi-national projects like Vision Zero have been developed with this objective in mind. Therefore, from an engineering design standpoint, the minimization of these road impact effects on occupants becomes a major design goal. This necessitates a need to quantify and manage injury risks on the human body in terms of different vehicular impact variables and their associated uncertainties for different crash scenarios.
In this paper, we present a decision-based robust design framework to quantify and manage the impact-based injury risks on occupants for different computational model-based car crash scenarios. The key functionality offered is the designer’s capability to carry out robust design studies with a focus on managing the selected impact variables and associated uncertainties, such that injury risks are controlled within acceptable levels. The efficacy of the framework is tested for near side impact scenarios with impact velocity and angle of impact as the critical variables of interest. Two injury criteria, namely, Head Injury Criterion (HIC) and Lateral Neck Injury Criteria (Lateral Nij) are selected to quantitatively measure the head and neck injury risks in crash simulations. Using the framework, a robust design problem is formulated to explore the combination of impact variables that best satisfice the injury goals defined. The framework and associated design constructs are generic and support the formulation and decision-based robust design of vehicle impact scenarios for managing injury risks.