A Brain-Controlled Vehicle System Based on Steady State Visual Evoked Potentials

Abstract

In this paper, we propose a human-vehicle cooperative driving system. The objectives of this research are twofold: (1) providing a feasible brain-controlled vehicle (BCV) mode; (2) providing a human-vehicle cooperative control mode. For the first aim, through a brain-computer interface (BCI), we can analyse the EEG signal and get the driving intentions of the driver. For the second aim, the human-vehicle cooperative control is manifested in the BCV combined with the obstacle detection assistance. Considering the potential dangers of driving a real motor vehicle in the outdoor, an obstacle detection module is essential in the human-vehicle cooperative driving system. Obstacle detection and emergency braking can ensure the safety of the driver and the vehicle during driving. EEG system based on steady-state visual evoked potential (SSVEP) is used in the BCI. Simulation and real vehicle driving experiment platform are designed to verify the feasibility of the proposed human-vehicle cooperative driving system. Five subjects participated in the simulation experiment and real the vehicle driving experiment. The outdoor experimental results show that the average accuracy of intention recognition is 90.68 ± 2.96% on the real vehicle platform. In this paper, we verified the feasibility of the SSVEP-based BCV mode and realised the human-vehicle cooperative driving system.

Novel welch-transform based enhanced spectro-temporal analysis for cognitive microsleep detection using a single electrode EEG

“…With cognitive AI, machines get trained to be able to think, reason, and make decisions much like humans do! [19][20][21] Although existing research work had restricted scopes due unavailability of real-world datasets and problematic experimental conditions, researchers yielded results using indirect methods like observing subject's typical sleep patterns in the vehicle [22,23,23], or experimented with decreased cognitive response time using alcohol [24,25] or conducted repetitive tasks to elicit tiredness [26,27,27]. When it comes to sleep, there is no such thing as a typical state of being.…”

Multiclass Classification of Visual Electroencephalogram Based on Channel Selection, Minimum Norm Estimation Algorithm, and Deep Network Architectures

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Fog Computing for Control of Cyber-Physical Systems in Industry Using BCI

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