An Adaptive Rear-End Collision Warning System for Drivers That Estimates Driving Phase and Selects Training Data

The paper proposes a rear-end collision warning system for drivers, where the collision risk is adaptively set from driving signals. The system employs the inverse of the time-to-collision with a constant relative acceleration as the risk and the one-class support vector machine as the anomaly detec...

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Veröffentlicht in:	Shisutemu Seigyo Jouhou Gakkai rombunshi Control and Information Engineers, 2011, Vol.24(8), pp.193-199
Hauptverfasser:	Ikeda, Kazushi, Mima, Hiroki, Inoue, Yuta, Shibata, Tomohiro, Fukaya, Naoki, Hitomi, Kentaro, Bando, Takashi
Format:	Artikel
Sprache:	eng
Schlagworte:	advanced driver assistance system hidden Markov model machine learning risk index support vector machine
Online-Zugang:	Volltext
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