Inferring driver´s turning direction through detection of error related brain activity

This work presents EEG-based Brain-computer interface (BCI) that uses error related brain activity to improve the prediction of driver´s intended turning direction. In experiments while subjects drive in a realistic car simulator, we show a directional cue before reaching intersection, and analyze error related EEG potential to infer if the presented direction coincides with the driver´s intention. In this protocol, the directional cue provides an initial estimation of the driving direction (based on EEG, environmental or previous driving habits), and we focus on the recognition of error-potentials it may elicit. Experiments with 7 healthy human subjects yield an average classification 0.69±0.16, which confirms the feasibility of decoding these signals to help estimating driver´s turning direction. This study can be further exploited by intelligent cars to tune their driving assistant systems to improve their performance and enhance the driving experience.