Why 3D Modeling Could be the Key to Improved Car Safety

Dr. Hu noticed that although the automobile industry continuously tests its products, their safety tests simply don’t take into account the diversity of body types found throughout the population. Car crash dummies typically come in three formats: large adult male, mid-sized adult male and small female. But what about everyone else who doesn’t come in those sizes? Even child-sized dummies tend to be just scaled down versions of adult-sized dummies, and as a result don’t mimic any of the skeletal characteristics common in children.

Essentially, car safety features are optimized to protect a “normal”, healthy adult. But this leaves the most vulnerable parts of the population at even greater risk; for example older people, children, pregnant or obese adults. Imagine a healthy adult body holding up in a crash, compared to the considerably more fragile body of an older man or woman. In the same way, the bones of a child will also be more at risk during a car crash as they are not as fully-formed as those of an adult. Pregnant and obese adults are also at a higher risk due to their increased mass and body shape. This means a seatbelt won’t fit well and will be unable to do its job properly.

In his paper, Dr. Hu explains how he and his team developed a parametric human Finite Element (FE) model. Their model would allow the user to predict the effects of a crash impact on any member of the population. It would need to have geometric, compositional and material characteristics that are parametric (or to be precise, a constant factor along which variable factors can be compared) with age, gender, stature, and body mass index (BMI). The model is based on population simulations. In other words, Dr. Hu built a model that has the constant factors of geometric, compositional, and material characteristics, and alongside those constants, the variable factors of age, gender, stature and BMI can be measured to represent almost anyone from the general population. By developing the model, car safety test designs could be optimized around all members of the population, and in particular, those most at risk. The method presented in the paper outlines and proves the feasibility of the project. Hopefully the Mimics Innovation Award prize money will help Dr. Jingwen Hu to further develop these life-changing innovations.

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