A shared controller for brain-controlled assistive vehicles

The limitations of brain-computer interfaces (BCI) lead to a poor control performance of brain-controlled assistive vehicles through a BCI. To improve the control performance and safety of brain-controlled assistive vehicles, this paper proposes a novel assistant controller designed by using the model predictive control method. The proposed controller combines the tracking of the driver's intention and safety of the vehicle into an optimization problem so as to make the driver be in charge of the vehicle as much as possible when the vehicle is safe. The simulation result shows that the assistive system can improve the control performance and safety of the brain-controlled vehicles.

[1]  Kyuwan Choi.  Control of a vehicle with EEG signals in real-time and system evaluation , 2011, European Journal of Applied Physiology.

[2]  Sridha Sridharan,et al.  Use of brain computer interface to drive: preliminary results , 2012, AutomotiveUI.

[3]  Yili Liu,et al.  A Head-Up Display-Based P300 Brain–Computer Interface for Destination Selection , 2013, IEEE Transactions on Intelligent Transportation Systems.

[4]  Yili Liu,et al.  Using a Head-up Display-Based Steady-State Visually Evoked Potential Brain–Computer Interface to Control a Simulated Vehicle , 2014, IEEE Transactions on Intelligent Transportation Systems.

[5]  Christoph Guger,et al.  Controlling a robot with a brain-computer interface based on steady state visual evoked potentials , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

[6]  Luzheng Bi,et al.  Queuing Network Modeling of Driver EEG Signals-Based Steering Control , 2017, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[7]  Kyuwan Choi,et al.  Control of a Wheelchair by Motor Imagery in Real Time , 2008, IDEAL.

[8]  Yili Liu,et al.  Development of a Driver Lateral Control Model by Integrating Neuromuscular Dynamics Into the Queuing Network-Based Driver Model , 2015, IEEE Transactions on Intelligent Transportation Systems.

[9]  Rajesh Rajamani,et al.  Vehicle dynamics and control , 2005 .

[10]  Miguel Castelo-Branco,et al.  Visual P300-based BCI to steer a wheelchair: A Bayesian approach , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[11]  Yili Liu,et al.  EEG-Based Brain-Controlled Mobile Robots: A Survey , 2013, IEEE Transactions on Human-Machine Systems.

[12]  Raúl Rojas,et al.  Semi-autonomous Car Control Using Brain Computer Interfaces , 2012, IAS.