Applications of event-related-potential-based brain computer interface to intelligent transportation systems

In this paper, an event-related-potential (ERP)-based brain computer interface (BCI) is proposed for the application of intelligent transportation systems (ITS). It consists of a virtual-reality (VR) motion simulation platform and an electroencephalographic signal detection and analysis system. The goals are to demonstrate the feasibility of detecting and analyzing multiple streams of ERP signals that organize operators' cognitive states and responses to task events, and to develop an ERP-based brain computer interface to meet the requirements of public security of intelligent transportation systems. We setup detailed experimental procedures to perform the cognitive tasks and collect high-fidelity ERP signals in the well-controlled VR-based laboratory environments. The independent component analysis (ICA) algorithms are applied to separate and get noise-free ERP signals from the multi-channel measured signals. Experimental results show that the separated ERP signals achieve a satisfactory result and can be further classified and transformed as the control/monitoring signals of safety-driving system for ITS.