| アイテムタイプ |
会議発表論文 / Conference Paper(1) |
| 公開日 |
2025-06-17 |
| タイトル |
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タイトル |
Motion Sickness Modeling with Visual Vertical Estimation and Its Application to Autonomous Personal Mobility Vehicles |
| 言語 |
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言語 |
eng |
| 資源タイプ |
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資源タイプ |
conference paper |
| アクセス権 |
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アクセス権 |
open access |
| 著者 |
Liu, Hailong
Inoue, Shota
和田, 隆広
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| 抄録 |
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内容記述タイプ |
Abstract |
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内容記述 |
Passengers (drivers) of level 3-5 autonomous personal mobility vehicles (APMV) and cars can perform non-driving tasks, such as reading books and smartphones, while driving. It has been pointed out that such activities may increase motion sickness. Many studies have been conducted to build countermeasures, of which various computational motion sickness models have been developed. Many of these are based on subjective vertical conflict (SVC) theory, which describes vertical changes in direction sensed by human sensory organs vs. those expected by the central nervous system. Such models are expected to be applied to autonomous driving scenarios. However, no current computational model can integrate visual vertical information with vestibular sensations. We proposed a 6 DoF SVC-VV model which add a visually perceived vertical block into a conventional six-degrees-of freedom SVC model to predict VV directions from image data simulating the visual input of a human. Hence, a simple image-based VV estimation method is proposed. As the validation of the proposed model, this paper focuses on describing the fact that the motion sickness increases as a passenger reads a book while using an AMPV, assuming that visual vertical (VV) plays an important role. In the static experiment, it is demonstrated that the estimated VV by the proposed method accurately described the gravitational acceleration direction with a low mean absolute deviation. In addition, the results of the driving experiment using an APMV demonstrated that the proposed 6 DoF SVC-VV model could describe that the increased motion sickness experienced when the VV and gravitational acceleration directions were different. |
| 書誌情報 |
en : Proceedings of IEEE Intelligent Vehicles Symposium 2022
p. 1415-1422,
発行日 2022-07-19
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| 会議情報 |
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会議名 |
IEEE Intelligent Vehicles Symposium 2022 |
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開始年 |
2022 |
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開始月 |
06 |
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開始日 |
04 |
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終了年 |
2022 |
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終了月 |
06 |
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終了日 |
09 |
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開催期間 |
2022-06-04 - 2022-06-09 |
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開催地 |
Aachen, Germany |
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開催国 |
DEU |
| 出版者 |
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出版者 |
IEEE |
| 出版者版DOI |
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関連タイプ |
isVersionOf |
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識別子タイプ |
DOI |
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関連識別子 |
https://doi.org/10.1109/IV51971.2022.9827161 |
| 出版者版URI |
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関連タイプ |
isVersionOf |
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識別子タイプ |
URI |
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関連識別子 |
https://ieeexplore.ieee.org/document/9827161 |
| 権利 |
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権利情報 |
Copyright $00A9 2022 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. |
| 著者版フラグ |
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出版タイプ |
AM |
| 助成情報 |
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助成機関名 |
Japan Science and Technology Agency(JST) |
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研究課題番号 |
JPMJTR20RR |
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研究課題名 |
自動運転車による移動中の生産性を高める乗物酔い低減技術 |
| 助成情報 |
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助成機関名 |
Japan Society for the Promotion of Science (JSPS) |
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研究課題番号 |
21K18308 |
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研究課題名 |
有人宇宙活動に向けた重力方向知覚に基づく宇宙酔いモデリングへの挑戦 |
fulltext (3.2 MB)
