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dc.contributor.author
Zhang, Zhao  
dc.contributor.author
Han, Shuning  
dc.contributor.author
Yi, Huaihai  
dc.contributor.author
Duan, Feng  
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Kang, Fei  
dc.contributor.author
Sun, Zhe  
dc.contributor.author
Solé Casals, Jordi  
dc.contributor.author
Caiafa, César Federico  
dc.date.available
2023-10-09T16:02:22Z  
dc.date.issued
2022-09  
dc.identifier.citation
Zhang, Zhao; Han, Shuning; Yi, Huaihai; Duan, Feng; Kang, Fei; et al.; A Brain-Controlled Vehicle System Based on Steady State Visual Evoked Potentials; Springer; Cognitive Computation; 15; 1; 9-2022; 159-175  
dc.identifier.issn
1866-9956  
dc.identifier.uri
http://hdl.handle.net/11336/214541  
dc.description.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.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Springer  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by/2.5/ar/  
dc.subject
BRAIN-COMPUTER INTERFACE (BCI)  
dc.subject
BRAIN-CONTROLLED VEHICLE (BCV)  
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ELECTRO-ENCEPHALOGRAM (EEG)  
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INTELLIGENT DRIVING TECHNOLOGY  
dc.subject
STEADY-STATE VISUAL EVOKED POTENTIAL (SSVEP)  
dc.subject.classification
Ciencias de la Información y Bioinformática  
dc.subject.classification
Ciencias de la Computación e Información  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
A Brain-Controlled Vehicle System Based on Steady State Visual Evoked Potentials  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2023-09-25T14:52:47Z  
dc.identifier.eissn
1866-9964  
dc.journal.volume
15  
dc.journal.number
1  
dc.journal.pagination
159-175  
dc.journal.pais
Alemania  
dc.journal.ciudad
Berlin  
dc.description.fil
Fil: Zhang, Zhao. Civil Aviation University Of China; China  
dc.description.fil
Fil: Han, Shuning. Universitat de Vic - Universitat Central de Catalunya ; España  
dc.description.fil
Fil: Yi, Huaihai. China University Of Geosciences; China  
dc.description.fil
Fil: Duan, Feng. Nankai University; China  
dc.description.fil
Fil: Kang, Fei. Maebashi Institute Of Technology; Japón  
dc.description.fil
Fil: Sun, Zhe. Riken; Japón  
dc.description.fil
Fil: Solé Casals, Jordi. Universitat de Vic - Universitat Central de Catalunya; España. Nankai University; China. University of Cambridge; Reino Unido  
dc.description.fil
Fil: Caiafa, César Federico. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Argentino de Radioastronomía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Argentino de Radioastronomía; Argentina. Nankai University; China  
dc.journal.title
Cognitive Computation  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/10.1007/s12559-022-10051-1  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1007/s12559-022-10051-1