Driver-vehicle Interaction And Control Of Brain-controlled Vehicles

A brain-controlled vehicle is a vehicle that is directly controlled by the human “mind”The research about brain-controlled vehicles involves many disciplines, including vehicledynamics, ergonomics, information and control science, and brain and neural science. Intheory, the research can not only help discover cortex neural representation and cognitivemechanism of driver behavior, but it also can provide a theoretical basis for brain-machineintegration and intelligent medical and rehabilitation equipments based on biological andmechatronics integration. In practice, the research can help the severely disabled users todirectly control a vehicle with their EEG signals for improving their mobility, and it canalso facilitate the development of human-centric intelligent driver assistance systems tobetter assist drivers in driving a vehicle and thus to improve the driving safety andperformance. Thus, the study regarding brain-controlled vehicles has important scientificsignificance and practical value.This dissertation focused on driver-vehicle interaction and control of brain-controlledvehicles. It covers the following contents:1) the brain-vehicle interaction system forvehicle destination selection and influences of environmental factors on the systemperformance) the translation of signals associated with drivers’ motion controlcommands and the model of vehicle motion control based on the interpreted commands,and3) the driver-vehicle-road model of brain-controlled vehicles based on motion controland the influence mechanism of the brain-vehicle interaction performance on theperformance of brain-controlled vehicles. The dissertation achieved the following researchaccomplishments:1. It built a driver-vehicle-road model of brain-controlled vehicles based on motioncontrol and revealed the effects of brain-vehicle interface parameters on the performance ofbrain-controlled vehicles and brain-actuated mechanism by using the proposed model.2. It proposed a novel brain-vehicle interaction method based on a hybridbrain-computer interface (BCI) with P300and steady-state visual evoked potential (SSVEP)and built a vehicle destination selection system by using the proposed method.3. It examined the performance of the vehicle destination selection system in the realdriving conditions, found the effects of environmental factors on the system performance, and revealed the physiological basis of the effects.4. It proposed a recognition method of motion control commands based on SSVEP andAlpha wave and built a vehicle motion control model on the basis of the recognizedcommands. Furthermore, it analyzed the feasibility and validation of using the human“mind” to control a vehicle.These achievements can help promote the research of basic issues and key technequesabout brain-controlled vehicles and lay the foundation of building the theory ofbrain-controlled vehicles.