Nowadays, subject testing represents a well established methodology to evaluate different properties of driver information systems and driver assistance systems. Among several criteria, learnability is one important system property. User and usage strategies are dependent of the subject's learning state, e.g. to switch attendance between driving task and operation of a driver information system. Also, the intended usage of driver assistance systems in given driving situations is influenced by user's experience. A suitable way to investigate related questions is to conduct a typical learning experiment and to analyse data with the given methodology. In this type of experiment, the familiarity and training state of the subject are set as independent variable. Beside learnability, other properties of human machine interaction are to be investigated and evaluated. In this case, however, the learning effectuated by a subject is an important dependent variable or even noise in sense of measurement theory that might cover a given main effect. After some empirical examples, possible solutions will be discussed that help to manage this problem with justifiable expense. (Author/publisher)
Abstract