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Abnormal Driving Behavior Detection Using a Linear Non-Gaussian Acyclic Model for Causal Discovery

Abnormal Driving Behavior Detection Using a Linear Non-Gauss...

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FISITA 2012 World Automotive Congress--Volume 9: Automotive Safety Technology

作者： Zujie Zhang Yuta Inoue Kazushi Ikeda Tomohiro Shibata takashi bandou Takayuki Miyahara Nara Institute of Science and Technology.Nara Japan DENSO CORPORATION.Kariya.Japan

This paper proposed a causal discovery method for driving behavior signals representing explicit driving actions to gain a better understanding in driving actions and to apply them to improve advanced driver assistance *** first-and second-order statistics have only correlation information and hence they cannot tell anything on *** other words,causality appears in higherorder *** utilize such information,we apply a linear non-Gaussian acyclic model（LiNGAM） that assumes non-Gaussian observation noise to the driving ***-Gaussian assumption makes it possible to use ICA to estimate the mixing matrix of observed *** mixing matrix can transform to a triangular matrix that expresses *** method is called ***-LiNGAM can extract causality in time-series of *** actions are time-series of vectors that play an essential role in the safe *** obtain driving data,we carried out experiments in which subjects drove a freeway without any instruction except for its *** our method,both instantaneous and lagged causal influences have been considered by using the Structural Vector Autoregression（SVAR） to the continuous time series *** model is a generalization of LiNGAM model so the assumption of independence and nonGaussianity is ensured for ICA-LiNGAM *** conventional LiNGAM can be regarded as a special case of SVAR when the autoregressive order is *** the experiment ICA-LiNGAM worked well with SVAR model and the analysis result showed a clear causal relationship between lagged variables of driving action *** experiment shows that ICA-LiNGAM can find out both the obvious and latent causal relations between driving behaviors.

关键词： Driver behavior signal processing Causal inference Linear nonGaussian acyclic model Independent component analysis

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