Finding appropriate measures to trigger machine changes remains a huge challenge in the field of adaptive automation. Trigger candidates include ECG measures and EEG frequencies, which have been linked to various mental states. The aim of such a system would be to avoid both underload and overload situations; which may both be viewed as a predictor of unsafe driving. When driving, task demands and mental effort investment may be regulated by changing driving speed. This could be handled by a biocybernetic system monitoring mental effort investments. To explore which EEG frequencies and locations are most promising to serve as input for such a system, an experiment was conducted (n=34) in which participants were exposed to a range of driving speeds, relative to the driver’s preferred speeds in a rural environment. To increase lateral demand even further, participants were required to stay below several target levels of swerving behavior (standard deviation of the lateral position). These targets were set, relative to the participants normal swerving behaviour. It will be discussed to what extent an EEG based adaptive cruise control is feasible.
|Publication status||Published - 2012|
|Event||Fifth International Conference on Traffic and Transport Psychology - University Medical Hospital premises , Groningen, Netherlands|
Duration: 29-Aug-2012 → 31-Aug-2012
|Conference||Fifth International Conference on Traffic and Transport Psychology|
|Period||29/08/2012 → 31/08/2012|