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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. A500a 雑誌掲載論文
  3. 学術雑誌

Stochastic modeling of vehicle trajectory during lane-changing

http://hdl.handle.net/2237/13898
http://hdl.handle.net/2237/13898
9b21e84c-f913-4aaf-bd36-a0f842f29ec7
名前 / ファイル ライセンス アクション
Nishiwaki_ICASSP2009-04.pdf Nishiwaki_ICASSP2009-04.pdf (688.6 kB)
Item type 学術雑誌論文 / Journal Article(1)
公開日 2010-07-30
タイトル
タイトル Stochastic modeling of vehicle trajectory during lane-changing
言語 en
著者 Nishiwaki, Yoshihiro

× Nishiwaki, Yoshihiro

WEKO 38113

en Nishiwaki, Yoshihiro

Search repository
Miyajima, Chiyomi

× Miyajima, Chiyomi

WEKO 38114

en Miyajima, Chiyomi

Search repository
Kitaoka, Hidenori

× Kitaoka, Hidenori

WEKO 38115

en Kitaoka, Hidenori

Search repository
Takeda, Kazuya

× Takeda, Kazuya

WEKO 38116

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
権利
言語 en
権利情報 ©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
キーワード
主題Scheme Other
主題 Driving Behavior
キーワード
主題Scheme Other
主題 Dynamic System
キーワード
主題Scheme Other
主題 Sampling
キーワード
主題Scheme Other
主題 hidden Markov model
抄録
内容記述 A signal processing approach for modeling vehicle trajectory during lane changing driving is discussed. Because individual driving habits are not a deterministic process, we developed a stochastic method. The proposed model consists of two parts: a dynamic system represented by a hidden Markov model and a cognitive distance space derived from the range distance distribution. The first part models the local dynamics of vehicular movements and generates a set of probable trajectories. The second part selects an optimal trajectory by stochastically evaluating the distances from surrounding vehicles. From experimental evaluation, we show that the model can predict the vehicle trajectory at given traffic conditions with 17.6 m prediction error for two different drivers.
言語 en
内容記述タイプ Abstract
出版者
言語 en
出版者 IEEE
言語
言語 eng
資源タイプ
資源タイプresource http://purl.org/coar/resource_type/c_6501
タイプ journal article
出版タイプ
出版タイプ VoR
出版タイプResource http://purl.org/coar/version/c_970fb48d4fbd8a85
DOI
関連タイプ isVersionOf
識別子タイプ DOI
関連識別子 https://doi.org/10.1109/ICASSP.2009.4959849
ISSN
収録物識別子タイプ PISSN
収録物識別子 1520-6149
書誌情報 en : IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2009)

p. 1377-1380, 発行日 2009-04-19
フォーマット
application/pdf
著者版フラグ
値 publisher
URI
識別子 http://hdl.handle.net/2237/13898
識別子タイプ HDL
URI
識別子 http://dx.doi.org/10.1109/ICASSP.2009.4959849
識別子タイプ DOI
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