Supervised dFasArt: A Neuro-Fuzzy Dynamic Architecture of Maneuver Detection in Road Vehicle Collision Avoidance Support Systems.
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Toledo Moreo, RafaelÁrea de conocimiento
Tecnología ElectrónicaFecha de publicación
2007Editorial
Springer-verlagCita bibliográfica
TOLEDO MOREO, R., PINZOLAS PRADO, J., CANO IZQUIERDO, J.M. Supervised dFasArt: a Neuro-Fuzzy Dynamic Architecture for Maneuver Detection in Road Vehicle Collision Avoidance Support System. Lecture Notes in Computer Sciences: 419-428, 2007Palabras clave
dFasArtCollision Avoidance
Resumen
The 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.
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