Driver State Regulation via Real-Time Neurofeedback in Partially Automated Driving

Abstract

Improving driver performance in critical driving situations is the key to increased road safety. In SAE Level 3 of automation, the driver is retained as a fallback in critical situations. Once the system reaches its limits, the distracted driver must overtake the driving task and is responsible for the present and upcoming situations. This contribution proposes a new method to impact driver performance by regulating the driver's arousal level. The arousal level of the driver is determined by detecting the driver's brain activity, and proper auditory feedback is issued to reduce the arousal towards the optimal value. The suggested approach utilizes neurofeedback to downregulate the driver's arousal via self-regulation in critical driving situations. The results show that the proposed neurofeedback supports the drivers to self-regulate their arousal during simple and difficult driving tasks and reach the optimal arousal level. The proposed approach is especially helpful in driving intervals with high criticality where the driver has to consecutively make decisions and react under demanding conditions.