Operator State DetectionCopyright: © Frank Flemisch
As automated systems become more widespread, good cooperation and interaction between humans and machines is playing an increasingly important role. Especially cooperative systems such as partially and highly automated driving require that not only normal operation, but also possible system limits or system failures are taken into account already during development.
To this end, we identify suitable cooperation and interaction patterns between humans and machines that minimize potential risks while still taking advantage of the opportunities offered by automation. In particular, our many years of experience in the field of driver attention and the detection of the condition the operator is in (e.g. by means of body posture or eye tracking) as well as groundbreaking research on the design of automated systems, e.g. in the context of DFG projects, enable us to develop concepts together that are both on a high scientific level and feasible.
As a basis for good cooperation, we focus on human intention recognition in order to provide automation with an understanding of its human counterpart. To this end, we are developing and researching methods for recognizing human cognitive or attentional states, which are then used to improve interaction. We are already successfully applying these research findings in industrial projects with companies in the automotive, mechanical engineering and plant construction sectors.