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Sensors 2014, 14(6), 9546-9561; doi:10.3390/s140609546

Robust Sensing of Approaching Vehicles Relying on Acoustic Cues

1,* , 2
1 Kyushu Institute of Technology, 1-1 Sensui-cho, Tobata-ku, Kitakyushu, Fukuoka 804-8550, Japan 2 Nissan Motor Co., Ltd., 1-1 Aoyama, Morinosato, Atsugi, Kanagawa 243-0123, Japan 3 National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan 4 The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
* Author to whom correspondence should be addressed.
Received: 14 March 2014 / Revised: 22 May 2014 / Accepted: 26 May 2014 / Published: 30 May 2014
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The latest developments in automobile design have allowed them to be equipped with various sensing devices. Multiple sensors such as cameras and radar systems can be simultaneously used for active safety systems in order to overcome blind spots of individual sensors. This paper proposes a novel sensing technique for catching up and tracking an approaching vehicle relying on an acoustic cue. First, it is necessary to extract a robust spatial feature from noisy acoustical observations. In this paper, the spatio-temporal gradient method is employed for the feature extraction. Then, the spatial feature is filtered out through sequential state estimation. A particle filter is employed to cope with a highly non-linear problem. Feasibility of the proposed method has been confirmed with real acoustical observations, which are obtained by microphones outside a cruising vehicle.
Keywords: active safety system; driver support system; acoustical sensing; spatio-temporal gradient method; particle filter active safety system; driver support system; acoustical sensing; spatio-temporal gradient method; particle filter
This is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Mizumachi, M.; Kaminuma, A.; Ono, N.; Ando, S. Robust Sensing of Approaching Vehicles Relying on Acoustic Cues. Sensors 2014, 14, 9546-9561.

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