A hierarchical prediction model for lane-changes based on combination of fuzzy C-means and adaptive neural network

•A hierarchical prediction model is proposed to predict steering angles.•The model combines fuzzy c-means and adaptive neural network.•A clustering learning method is adopted to optimize parameters of sub neural network.•Experiments are conducted in the driving simulator under different scenarios.•P...

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Veröffentlicht in:	Expert systems with applications Jg. 130; S. 265 - 275
Hauptverfasser:	Tang, Jinjun, Yu, Shaowei, Liu, Fang, Chen, Xinqiang, Huang, Helai
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Elsevier Ltd 15.09.2019 Elsevier BV
Schlagworte:	Adaptive algorithms Advanced driver assistance systems Artificial neural networks Clustering Computer simulation Driving prediction Driving simulation Environmental impact Fuzzy C-means algorithm Fuzzy logic Lane changes Lane changing Neural network Neural networks Supervised learning Teaching methods Vehicle safety Driving simulation Lane changes Neural network Fuzzy C-means algorithm Driving prediction
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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