Creating and designing interfaces for human-machine systems demands not only an understanding of the task and its environment, but also an appreciation of the capabilities and cognitive demands of the users. This becomes more and more important because of the growing information density and growing degree of automation of human-machine systems. Considering the environment, an important issue is what kind of interface supports cognitive processes best, and how can an interface be designed to match the future user requirements best. The work presented here makes a contribution to integrate cognitive aspects of skill- and rule-based activities during human-machine interaction into the development process of human-machine systems.
In all stages of the development, process cognitive modeling can be applied to evaluate human- machine interfaces. Using formal cognitive user models to simulate the future user behavior and requirements allow us to analyze the behavior on a detailed level. This helps to detect errors in the interaction design of interfaces and gives indications about the cognitive demands of the future users. But cognitive modeling is seldom used because of the high effort and a lack of tools for the development and analysis of cognitive user models.
The Department of Human-Machine Systems focuses on two different areas of user modeling. First, the development of methods and tools to support the modeling and evaluation of user models in the context of human-machine systems. Second, the development of user models for interaction processes to simulate typical human-machine scenarios (e.g. driver modeling).