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  1. A500 情報学部/情報学研究科・情報文化学部・情報科学研究科
  2. A500g COE
  3. 社会情報基盤のための音声映像の知的統合

MODELING OF INDIVIDUALITIES IN DRIVING THROUGH SPECTRAL ANALYSIS OF BEHAVIORAL SIGNALS

http://hdl.handle.net/2237/10456
http://hdl.handle.net/2237/10456
22cc3678-c5c9-4dba-9e63-df0d8305df8d
名前 / ファイル ライセンス アクション
p45-48_Modeling_of_Individualities.pdf p45-48_Modeling_of_Individualities.pdf (15.4 MB)
Item type 会議発表論文 / Conference Paper(1)
公開日 2008-08-26
タイトル
タイトル MODELING OF INDIVIDUALITIES IN DRIVING THROUGH SPECTRAL ANALYSIS OF BEHAVIORAL SIGNALS
言語 en
著者 Ozawa, Koji

× Ozawa, Koji

WEKO 24478

en Ozawa, Koji

Search repository
Wakita, Toshihiro

× Wakita, Toshihiro

WEKO 24479

en Wakita, Toshihiro

Search repository
Miyajima, Chiyomi

× Miyajima, Chiyomi

WEKO 24480

en Miyajima, Chiyomi

Search repository
Itou, Katsunobu

× Itou, Katsunobu

WEKO 24481

en Itou, Katsunobu

Search repository
Takeda, Kazuya

× Takeda, Kazuya

WEKO 24482

en Takeda, Kazuya

Search repository
アクセス権
アクセス権 open access
アクセス権URI http://purl.org/coar/access_right/c_abf2
抄録
内容記述 Driving behavior modeling using such driving signals as velocity, following distance, and gas or brake pedal operations, has been investigated for accident prevention and vehicle design. Driving behaviors are different among drivers, and research on driver modeling has also been carried out from different points of view in cognitive and engineering approaches. In this paper, driver's characteristics in driving behaviors are modeled with a Gaussian mixture model(GMM) using "cepstral features" obtained through spectral analysis of gas pedal operation signals. The GMM driver model based on cepstral features in evaluated in driver identification experiments and compared with a conventional GMM driver model that uses raw driving signals without spectral analysis. Experimental results show that the proposed driver model achieves an 89.6% driver identification rate, resulting in 61% error reduction over the conventional driver model.
言語 en
内容記述タイプ Abstract
出版者
言語 en
出版者 INTELLIGENT MEDIA INTEGRATION NAGOYA UNIVERSITY / COE
言語
言語 eng
資源タイプ
資源 http://purl.org/coar/resource_type/c_5794
タイプ conference paper
書誌情報 en : Third Symposium on "Intelligent Media Integration for Social Information Infrastructure" December 6, 2005

p. 45-48, 発行日 2005-12
フォーマット
application/pdf
著者版フラグ
値 publisher
URI
識別子 http://hdl.handle.net/2237/10456
識別子タイプ HDL
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