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  1. B200 工学部/工学研究科
  2. B200a 雑誌掲載論文
  3. 学術雑誌

Modeling of Cyclists' Decision for Left-Turn Vehicle at Unsignalized Intersection using Logistic Regression Model and Gaussian Mixuter Model

http://hdl.handle.net/2237/0002012751
http://hdl.handle.net/2237/0002012751
951c4abf-f332-419d-85d9-b75305d22def
名前 / ファイル ライセンス アクション
SII2025_wakisaka_final.pdf SII2025_wakisaka_final.pdf (4.2 MB)
アイテムタイプ itemtype_ver1(1)
公開日 2025-05-15
タイトル
タイトル Modeling of Cyclists' Decision for Left-Turn Vehicle at Unsignalized Intersection using Logistic Regression Model and Gaussian Mixuter Model
言語 en
著者 Wakisaka, Ryo

× Wakisaka, Ryo

en Wakisaka, Ryo

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Yamaguchi, Takuma

× Yamaguchi, Takuma

en Yamaguchi, Takuma

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Ban, Kazunori

× Ban, Kazunori

en Ban, Kazunori

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Okuda, Hiroyuki

× Okuda, Hiroyuki

en Okuda, Hiroyuki

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Suzuki, Tatsuya

× Suzuki, Tatsuya

en Suzuki, Tatsuya

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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
権利情報 “© 2025 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”
言語 en
内容記述
内容記述タイプ Abstract
内容記述 In this paper, the cyclists’ decision-making behavior in the interaction with a car at unsignaled intersection is measured and analyzed. Based on the measured data, the cyclists’ decision-making model is identified by using logistic regression model. Since the data collection in the real world is hard to realize, we have used an interactive simulator in which the cycling simulator and the driving simulator are connected via network, and share the same virtual traffic environment. The cyclist’s decision states are defined by three states regarding their operation, pedaling-on, pedaling-off and brake-on. The models to estimate these three states were constructed using the logistic regression model and the Gaussian mixture model, respectively. Finally the accuracy of the constructed models are verified, and compared with each other.
言語 en
出版者
出版者 IEEE
言語 en
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 AM
出版タイプResource http://purl.org/coar/version/c_ab4af688f83e57aa
関連情報
関連タイプ isVersionOf
識別子タイプ DOI
関連識別子 https://doi.org/10.1109/SII59315.2025.10870955
収録物識別子
収録物識別子タイプ EISSN
収録物識別子 2474-2325
書誌情報 en : 2025 IEEE/SICE International Symposium on System Integration, SII 2025

p. 789-796, 発行日 2025-01
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