DocumentCode
2188796
Title
Adaptive neural-fuzzy inference system based method to modeling of vehicle crash
Author
Lin Zhao ; Pawlus, Witold ; Karimi, Hamid Reza ; Robbersmyr, K.G.
Author_Institution
Dept. of Eng., Univ. of Agder, Grimstad, Norway
fYear
2013
fDate
Feb. 27 2013-March 1 2013
Firstpage
370
Lastpage
375
Abstract
Various areas of research need to be considered in order to establish a mathematical model of a vehicle crash. To enhance the modeling process, a novel ANFIS-based approach to reconstruct behavior of impacting vehicles is presented in this paper. Kinematics of center of gravity (COG) a vehicle involved in an oblique barrier collision is reproduced by application of a five-layered ANFIS structure. Then, the same ANFIS system is used to simulate a different collision type than the one which was used in the training stage. The points of interests are selected to be the locations of accelerometers mounting. The accuracy of the proposed method is evaluated by the comparative analysis with the reference measurements from full-scale vehicle collisions.
Keywords
fuzzy reasoning; traffic engineering computing; vehicles; COG; accelerometers mounting; adaptive neural-fuzzy inference system based method; center of gravity; full-scale vehicle collisions; mathematical model; oblique barrier collision; reference measurements; structure; vehicle crash; Acceleration; Accelerometers; Kinematics; Training; Training data; Vehicle crash testing; Vehicles; ANFIS-based modeling; artificial intelligence methods; kinematics reconstruction; vehicle crash simulation;
fLanguage
English
Publisher
ieee
Conference_Titel
Mechatronics (ICM), 2013 IEEE International Conference on
Conference_Location
Vicenza
Print_ISBN
978-1-4673-1386-5
Electronic_ISBN
978-1-4673-1387-2
Type
conf
DOI
10.1109/ICMECH.2013.6518565
Filename
6518565
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