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dc.contributor.authorZamora Izquierdo, Miguel A. 
dc.contributor.authorToledo Moreo, Rafael 
dc.contributor.authorValdés Vela, M. 
dc.contributor.authorGil Galván, D. 
dc.date.accessioned2008-06-30T10:42:06Z
dc.date.available2008-06-30T10:42:06Z
dc.date.issued2007
dc.identifier.citationZAMORA-IZQUIERDO, M.A., TOLEDO-MOREO, R., VALDÉS-VELA, M, GIL-GALVÁN, D. Neuro-fuzzy based maneuver detection for collision avoidance in road vehicles. Lecture Notes in Computer Sciences, 429-438, 2007.es
dc.description.abstractThe issue of collision avoidance in road vehicles has been investigated from many different points of view. An interesting approach for Road Vehicle Collision Assistance Support Systems (RVCASS) is based on the creation of a scene of the vehicles involved in a potentially conflictive traffic situation. This paper proposes a neuro-fuzzy approach for dynamic classification of the vehicles roles in a scene. For that purpose, different maneuver state models for longitudinal movements of road vehicles have been defined, and a prototype has been equipped with INS (Inertial Navigation Systems) and GPS (Global Positioning System) sensors. Trials with real data show the suitability of the proposed neurofuzzy approach for solving support to the problem under consideration.es
dc.description.sponsorshipMinisterio de Fomento de España y la Agencia Espacial Europea (ESA) patrocinadores de la actividad FOM/3929/2005 and GIROADS 332599 respectivamente.
dc.formatapplication/pdf
dc.language.isoenges
dc.publisherSpringer-Verlages
dc.rightsPublicación original disponible en www.springerlink.com
dc.titleNeuro-fuzzy based maneuver detection for collision avoidance in road vehicleses
dc.typeinfo:eu-repo/semantics/articlees
dc.subject.otherTecnología Electrónicaes
dc.date.created2007
dc.identifier.urihttp://hdl.handle.net/10317/319
dc.contributor.departmentElectrónica, Tecnología de Computadoras y Proyectoses
dc.identifier.doi10.1007/978-3-540-73055-2_45


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