Research of processes and consequences of relevant accident scenarios is an elementary factor for the best possible protection of people on the road. In order to precisely decipher accident patterns and causes, we collect data on real accidents in cooperation with the Audi Accident Research Unit (AARU). These and other data from international accident databases are evaluated by machine learning methods in order to visualize highly complex correlations.  

This knowledge enables us to give statements on the effectiveness of safety functions for the traffic of the future. Combined with FEM simulations we develop innovative protection systems for occupants in, for example, autonomous vehicles.  

In the mobility concepts of the future, occupant positions are possible in which current dummies reach the limits of their range of measurement. Our research therefore focuses on the continuous further development of virtual human models with regard to injury biomechanics and biofidelity as well as the development of injury risk functions – all with the ultimate aim of providing effective concepts for the protection of people in the traffic of the future.

We are also developing sensor algorithms for accident detection and classification that control and regulate the best possible protection systems in the vehicle in order to protect occupants and other road users. For this purpose, we use the method known as Core Competence in Integrated Security Systems (KISS). In addition, we develop suitable sensor systems for the vehicle interior in order to precisely record the position and status of occupants.

The essence of our approach involves considering the entire scope of safety engineering, from accident analysis and accident detection to the optimum protection of all people involved. We offer all necessary expertise from one single source.

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Our biomechanics experts develop and improve models of the human body in order to make them as realistic as possible.

In addition to dummies, we also use virtual human body models to developoccupant protection systems for the future.

Using finite element methods (FEM) and machine learning methods, we develop sensor algorithms to detect and classify accidents as early as possible.