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Directly using brain signals to steer a vehicle may not only help disabled people to control an assistive vehicle,but also provide a complementary means of control for a wider driving community.To simulate and predict the performance of driver steering a vehicle with brain signals,we proposed a driver brain-controlled steering model by integrating a Queuing network-based brain-controlled lateral model with a brain-computer interface(BCI)model representing the performance of the BCI system that can output three kinds of steering commands(i.e.,turning left and right as well as going forward).Experimental results indicate that the proposed model shows good agreement with that of real drivers using the BCI to steer a vehicle.We investigated the effects of the parameters(i.e.,mean accuracy and response time)of the BCI model on the performance of brain-controlled vehicles.Results show us the basic requirements of the parameters(i.e.,mean accuracy exceed 68%and response time less than 1.8s)of the BCI model to drive a brain-controlled vehicle.