Abstract
Brain-controlled intelligent vehicles (BCIVs) refer to intelligent vehicles, where brain-computer interfaces (BCIs) are applied to help a person operate (or teleoperate) a vehicle by decoding human intention from brain signals. Existing studies on BCIVs are focused on the single-task operation scenario. Considering that the multitask operation is common in practice, in this article, we design a multitask-oriented BCIV system for the first time by integrating a novel neural decoding method of driver-secondary-task intention with an adaptive brain–machine collaborative controller. We build an experimental platform of the proposed multitask-oriented BCIV system and test the performance of both the primary and secondary tasks by human-and-hardware-in-the-loop experiments. Experimental results show that the proposed multitask-oriented BCIV system performs well. This work has essential values in moving the exploration of brain-controlled systems toward a new step of the multitask operation and opens a new avenue for cognitive neuroscience to be applied to intelligent systems and human–machine integration.
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