A brain signals-based interface between drivers and in-vehicle devices

In this paper, we propose a novel interface between drivers and in-vehicle devices by using steady-state visual evoked potential (SSVEP) of brain signals. The SSVEP is detected by a canonical correlation analysis (CCA) classifier and applied to turn on and turn off in-vehicle devices. The proposed interface is built and tested online in a driving simulator by requiring drivers to use the interface to interact with the in-vehicle device while performing the primary driving tasks including lane keeping and obstacle avoidance. The pilot experimental results show the feasibility of the proposed interface.