The development of automated driving systems is raising new challenges for passengers safety. One of the reasons is that the driver and the passengers can engage in a wider range of activities. Thus, their posture varies more from what is nowadays considered to be conventional. Being less expensive, finite element methods are used to investigate new crash scenarios, including those in which passengers are sitting in non-conventional positions. However, positioning a human body model in a non-conventional posture is a very demanding process. The combination of machine learning and artificial intelligence allows to reduce the order of a model, thus drastically lowering both time and computing effort.