Abstract
AbstractIn 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.
Publisher
Springer Science and Business Media LLC
Subject
Cognitive Neuroscience,Computer Science Applications,Computer Vision and Pattern Recognition
Reference44 articles.
1. Naresh B, Rambabu S, Basha DK. ARM controller and EEG based drowsiness tracking and controlling during driving. International Journal of Reconfigurable and Embedded Systems (IJRES). 2018;6:127–32.
2. Dev A, Rahman MA, Mamun N. Design of an EEG-based brain controlled wheelchair for quadriplegic patients. IEEE 3rd international conference for convergence in technology (I2CT), Pune, India, 6–8 April 2018, pp 1–5.
3. Lu Y, Bi L. EEG signals-based longitudinal control system for a brain-controlled vehicle. IEEE Trans Neural Syst Rehabil Eng. 2019;27(2):323–32.
4. Sparrow Robert; Howard Mark. When human beings are like drunk robots: driverless vehicles, ethics, and the future of transport. Transportation Research Part C: Emerging Technologies. 2017;80:206–15.
5. Wang L, Sun P, et al. Advanced driver-assistance system (ADAS) for intelligent transportation based on the recognition of traffic cones. Advances in Civil Engineering. 2020;4:1–8.
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