2024/03/06 更新

写真a

マツバヤシ ショウタ
松林 翔太
MATSUBAYASHI Shota
所属
未来社会創造機構 モビリティ社会研究所 先進ビークル研究部門 特任助教
職名
特任助教
外部リンク

学位 3

  1. 情報科学学位(博士) ( 2020年3月   名古屋大学 ) 

  2. 情報科学学位(修士) ( 2012年3月   名古屋大学 ) 

  3. 情報文化学学位(学士) ( 2010年3月   名古屋大学 ) 

研究分野 3

  1. 人文・社会 / 認知科学

  2. 人文・社会 / 実験心理学  / 認知心理学

  3. 情報通信 / ヒューマンインタフェース、インタラクション

経歴 5

  1. 名古屋大学   未来社会創造機構 モビリティ社会研究所   特任助教

    2020年8月 - 現在

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  2. 名古屋大学   情報学研究科   研究員

    2019年4月 - 2020年7月

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  3. 名古屋大学   未来社会創造機構   研究員

    2018年10月 - 2019年3月

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  4. 名古屋大学   未来社会創造機構   リサーチアシスタント

    2015年10月 - 2018年9月

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  5. 株式会社NTTドコモ

    2012年4月 - 2015年8月

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学歴 3

  1. 名古屋大学   情報科学研究科   メディア科学専攻 博士後期課程

    2015年10月 - 2018年9月

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    国名: 日本国

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  2. 名古屋大学   情報科学研究科   メディア科学専攻 博士前期課程

    2010年4月 - 2012年3月

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    国名: 日本国

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  3. 名古屋大学   情報文化学部   社会システム情報学科

    2006年4月 - 2010年3月

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    国名: 日本国

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所属学協会 3

  1. Cognitive Science Society

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  2. 日本認知科学会

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  3. 日本交通心理学会

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受賞 3

  1. Best Paper Award

    2023年6月   International Academy, Research, and Industry Association   Distinct Characteristics Between "Anshin" and Feeling of Safety Evaluations

    Shota Matsubayashi, Kazuhisa Miwa, Hitoshi Terai, Yuki Ninomiya

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    受賞区分:国際学会・会議・シンポジウム等の賞  受賞国:イタリア共和国

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  2. Best Paper Award

    2019年4月   International Academy, Research, and Industry Association   Short- and Long-Term Effects of an Advanced Driving Assistance System on Driving Behavior and Usability Evaluation

    Shota Matsubayashi, Kazuhisa Miwa, Takuma Yamaguchi, Tatsuya Suzuki

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    受賞区分:国際学会・会議・シンポジウム等の賞  受賞国:ギリシャ共和国

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  3. Best Paper Award

    2017年6月   International Academy, Research, and Industry Association   Empirical Investigation of Changes of Driving Behavior and Usability Evaluation Using an Advanced Driving Assistance System

    Shota Matsubayashi, Kazuhisa Miwa, Takuma Yamaguchi, Takafumi Kamiya, Tatsuya Suzuki, Ryojun Ikeura, Soichiro Hayakawa, Takafumi Ito

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    受賞区分:国際学会・会議・シンポジウム等の賞  受賞国:スペイン

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論文 15

  1. Index of Braking Behaviour in Two Dimensions within Risk Perception

    Shota Matsubayashi, Kazuhisa Miwa, Hitoshi Terai, Yuki Ninomiya

    Transportation Research Part F: Traffic Psychology and Behaviour     2024年

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    記述言語:英語   掲載種別:研究論文(学術雑誌)  

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  2. Self-Benefit and Others' Benefit in Cooperative Behavior in Shared Space

    Matsubayashi, S; Miwa, K; Terai, H; Shimojo, A; Ninomiya, Y

    HUMAN FACTORS   66 巻 ( 4 ) 頁: 961 - 974   2022年8月

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    記述言語:英語   掲載種別:研究論文(学術雑誌)   出版者・発行元:Human Factors  

    Objective: The objective is to clarify the nature of cooperative moving behavior that realizes smooth traffic with others from the viewpoint of the trade-off between self-benefit and others’ benefit in the shared space. Background: The shared space is not constrained by formal rules or behavioral norms, and is a potentially ambiguous situation where it is not clear who has priority. Therefore, the nature of cooperative behavior in the shared space is unclear. Method: An experimental task was conducted to compare cooperative and nonurgent moving behavior regarding completion time (self-benefit), the amount of interruption (others’ benefit), and the amount of operation (cognitive effort). Results: First, cooperative behavior benefits others. Second, although cooperative behavior decreases self-benefit compared to the baseline without any instructions, it can obtain relatively more self-benefit than nonurgent behavior without considering self-benefit. Third, cooperative behavior requires cognitive effort. Conclusion: Cooperative behavior provides benefit to both oneself and others by spending cognitive effort in not interrupting others. Application: If the nature of the cooperative behavior can be clarified, a cooperative module can be implemented into the algorithms of various mobilities.

    DOI: 10.1177/00187208221121404

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    その他リンク: http://journals.sagepub.com/doi/full-xml/10.1177/00187208221121404

  3. 変則的挙動への認知的処理に関する記憶ベース方略の効用

    松林 翔太, 三輪 和久, 寺井 仁

    認知科学   26 巻 ( 3 ) 頁: 332 - 342   2019年9月

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    記述言語:日本語   掲載種別:研究論文(学術雑誌)   出版者・発行元:日本認知科学会  

     Users often observe anomalous behaviors of systems, such as machine failures, autonomous agents, and natural phenomena. We analyze the features and the benefits of the memory-based strategy, which focuses on memorization of instances to predict anomalous and regular behaviors of the system. In this study, we develop our previous research and investigate the cognitive processes and the benefits of the memory-based strategy with ACT-R model simulations. We set the parameters defining the encoding processes of anomalous instances and regular instances in the model of the memory-based strategy and performed simulations to verify how these two parameters influence prediction performance. The results of simulations showed that (1) anomalous instances are encoded and regular instances are not encoded in the memory-based strategy and that (2) such inactivity on regular instances suppresses commission errors of regular instances and does not suppress commission errors of anomalous instances and omission errors, which leads to correct prediction of systems' behaviors.

    DOI: 10.11225/jcss.26.332

    CiNii Research

  4. 変則的挙動に対する記憶ベース方略に関する実験的検討 査読有り

    松林 翔太, 三輪 和久, 寺井 仁

    心理学研究   90 巻 ( 3 ) 頁: 274 - 283   2019年

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    記述言語:日本語   掲載種別:研究論文(学術雑誌)   出版者・発行元:公益社団法人 日本心理学会  

    <p>We often encounter various anomalous behaviors of systems, such as machine failures, unexpected behaviors of intelligent agents, and irregular natural phenomena. In order to predict these anomalous behaviors, it is a useful strategy to infer the causal structure of target domains (the inference-based strategy). However, we assume another strategy, the memory-based strategy, to memorize the anomalous behaviors for the predictions. In the present study, we analyzed the features and benefits of the memory-based strategy using the spatial movement prediction task. Experiments 1 and 2 revealed that participants who were instructed to apply the memory-based strategy encoded only the anomalous instances, and not the regular instances. Additionally, the inference-based strategy was more effective for identifying the anomalous instances in a low-complexity task, whereas the memory-based strategy was more effective in a high-complexity task. Experiment 3 revealed that it was difficult to spontaneously select an appropriate strategy based on task complexity and to make benefits of the memory-based strategy for a high-complexity task even if the strategy was applied.</p>

    DOI: 10.4992/jjpsy.90.18018

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  5. How impressions of other drivers affect one's behavior when merging lanes

    Shimojo A., Ninomiya Y., Miwa K., Terai H., Matsubayashi S., Okuda H., Suzuki T.

    Transportation Research Part F: Traffic Psychology and Behaviour   89 巻   頁: 236 - 248   2022年8月

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    記述言語:日本語   掲載種別:研究論文(学術雑誌)   出版者・発行元:Transportation Research Part F: Traffic Psychology and Behaviour  

    In recent years, systems have been developed to realize automatic driving based on objective information such as the relative distance and relative speed between vehicles. However, humans still must drive in complex situations, for instance, when merging lanes. In such driving situations, it is possible that people make decisions based not only on objective information, but also on subjective information. This study examined how subjective information, specifically, a driver's impression of the other vehicle, affects the decision to merge in front of or behind the other vehicle when merging lanes on a highway. Twenty participants (nmale = 10; nfemale = 10; Mage = 43.92 [SDage = 11.40]) joined two experiments, Days 1E and 2E, using a driving simulator. Two months after participating in Day 1E the participants joined Day 2E. In the Day 1E, they drove either on the merging lane or the main lane and merged lanes while considering the other vehicle driving along the adjacent lane. This experiment measured the probability that the participants drove in front of another vehicle upon merging, which is defined as “lead probability.” The Day 2E was similar to 1E, except for the manipulation of the participants’ impression of the other vehicle as being aggressive/cautious via acceleration/deceleration of the other vehicle, and through the contents of the instructions regarding the other vehicle's driving characteristics. In the Day 2E, the participants were randomly assigned to two: Aggressive or Cautious conditions. As the result of comparing the lead probabilities, it was found that only when the participants were driving on the merging lane and had the impression that the other vehicle is aggressive, the impression lowered the lead probability. The result indicates that people make decisions based not only on objective information but also on subjective information for specific driving situations, such as merging lanes. These findings can help in the development of automated driving systems that allow safer merging.

    DOI: 10.1016/j.trf.2022.06.007

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  6. Navigation Style Classification Using Persistent Homology

    Akai, N; Matsubayashi, S; Miwa, K; Hirayama, T; Murase, H

    2022 IEEE/SICE INTERNATIONAL SYMPOSIUM ON SYSTEM INTEGRATION (SII 2022)     頁: 161 - 164   2022年

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    記述言語:英語   掲載種別:研究論文(学術雑誌)   出版者・発行元:2022 IEEE/SICE International Symposium on System Integration, SII 2022  

    Recently, many researchers in the mobile robot field study how to realize socially-aware navigation in human-robot coexisting spaces. However, we have fundamental questions: how can be the socially-aware behavior defined and classified? Our work aims to provide the answers and is divided into two major studies; defining the socially-aware behavior in terms of the traffic psychology and extracting specific patterns to understand the behavior. For the first study, we designed simulation experiments based on the traffic psychology. In the experiments, participants operated an ego-agent to a destination with three different instructions; cooperative, urgent, and non-urgent. We also analyzed differences of the navigation styles and found that the statistical trend of the ego-motion is different in each style. However, it is difficult to find specific patterns in relation between the ego-motion and surrounding situations. This paper focuses on the second study and presents a classification method of the navigation styles using persistent homology (PH). We consider that implicit patterns could be extracted from surrounding situations by PH because it could enable to find specific patterns from data even when they seem to be distributed randomly. Results show the possibility that the PH-based method could acquire effective information for the classification.

    DOI: 10.1109/SII52469.2022.9708804

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  7. What is the Cooperative Behavior of Moving in Shared Spaces?

    Matsubayashi S., Miwa K., Terai H., Shimojo A., Ninomiya Y.

    Proceedings of the 43rd Annual Meeting of the Cognitive Science Society: Comparative Cognition: Animal Minds, CogSci 2021     頁: 2444 - 2449   2021年

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    記述言語:日本語   掲載種別:研究論文(学術雑誌)   出版者・発行元:Proceedings of the 43rd Annual Meeting of the Cognitive Science Society: Comparative Cognition: Animal Minds, CogSci 2021  

    The development of mobility technologies has led to the concept of shared spaces. In the shared space, mobilities and pedestrians share a single common space. Compared to conventional separated spaces, cooperative behaviors are critical in shared spaces because all agents can move freely at their own speed and in their directions with few constraints. An experiment was conducted using indices for own cost, others’ benefit, and own loss to reveal the nature of the cooperative behaviors associated with moving. We found that compared to when people are encouraged to behave without urgency, they frequently change their speed and direction so as not to interrupt others and reach their destination more quickly when people are required to behave cooperatively. Therefore, it was concluded that both others’ benefit and one’s own benefit are critical for cooperative behaviors when moving in shared spaces.

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  8. Verification of Coaching effect by Instructor-like Assistance System Based on Model Predictive Constraint Satisfaction

    Yamaguchi, T; Matsubayashi, S; Suzuki, T; Miwa, K

    IECON 2021 - 47TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY   2021-October 巻   2021年

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    記述言語:英語   掲載種別:研究論文(学術雑誌)   出版者・発行元:IECON Proceedings (Industrial Electronics Conference)  

    Safety and acceptability are the main concerns in the design of driver assistance systems. However, these two requirements sometimes conflict with each other depending on the situation and the driver. This conflict is particularly emphasized in the case of elderly drivers. To solve this problem, this paper proposes a driver-vehicle cooperation scheme, an "instructor-like assisting control"consisting of model predictive constraint satisfaction and a multi-modal human-machine inter-face. The proposed assisting scheme is expected to improve the drivers' inherent driving characteristics, which is recognized as a "coaching effect"in cognitive science. This effect was verified by long-term experiments over one month using a driving simulator.

    DOI: 10.1109/IECON48115.2021.9589646

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  9. Development of a driving model that understands other drivers’ characteristics

    Matsubayashi S., Terai H., Miwa K.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   12213 LNCS 巻   頁: 29 - 39   2020年

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    記述言語:英語   掲載種別:研究論文(学術雑誌)   出版者・発行元:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)  

    In this study, a driving model that observes others’ behaviors and that makes its decisions based on the estimated characteristics of the other driver in the situation where two lanes merge on a highway was developed. Additionally, drivers’ probabilities of decisions in relation to their primary characteristics was interpreted. We presumed various drivers have different characteristics such as aggression and caution that affect their making decisions. We simulated the merging behaviors of two drivers in a merging lane and in a main lane after the driver in the merging lane had estimated the characteristics of the driver in the main lane as a typical case. The results of the estimation-success case revealed that two drivers changed lanes immediately after selecting and canceling their decisions several times. However, the results of the estimation-failure case revealed that if a standoff between two drivers occurred, it would take longer to change lanes than in the estimation-success case. Furthermore, the lateral swaying of the cars was worse in the estimation-failure case than in the estimation-success case because the two drivers allocated much cognitive resources and time to monitor of the other car. The importance of understanding others and building a model that understands others in traffic is discussed.

    DOI: 10.1007/978-3-030-50537-0_3

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  10. Model-based Approach with ACT-R about Benefits of Memory-based Strategy on Anomalous Behaviors

    Matsubayashi S., Miwa K., Terai H.

    Proceedings of the 41st Annual Meeting of the Cognitive Science Society: Creativity + Cognition + Computation, CogSci 2019     頁: 776 - 781   2019年

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    記述言語:日本語   掲載種別:研究論文(学術雑誌)   出版者・発行元:Proceedings of the 41st Annual Meeting of the Cognitive Science Society: Creativity + Cognition + Computation, CogSci 2019  

    Users sometimes face anomalous behaviors of systems, such as machine failures and autonomous agents. Predicting such behaviors of systems is difficult. We investigate the benefits of the memory-based strategy, which focuses on memorization of instances to predict anomalous and regular behaviors of the system, with ACT-R simulations with a cognitive model. In this study, we presumed the parameters defining the encoding processes on anomalous instances and regular instances in the model of the memory-based strategy and performed simulations to verify how these two parameters influence prediction performance. The results of simulations showed that (1) regular instances are not encoded as default values in the memory-based strategy and that (2) such inactivity on regular instances suppresses commission errors of regular instances and does not suppress commission errors of anomalous instances nor omission errors.

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  11. 先進的運転支援システムにおける情報提示と行動介入の認知的・行動的影響に関する検討 査読有り

    松林 翔太, 三輪 和久, 山口 拓真, 神谷 貴文, 鈴木 達也, 池浦 良淳, 早川 聡一郎, 伊藤 隆文

    認知科学   25 巻 ( 3 ) 頁: 324 - 337   2018年

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    記述言語:日本語   掲載種別:研究論文(学術雑誌)   出版者・発行元:日本認知科学会  

    &ensp;Advanced driving assistance system supports human drivers in two ways. First, the system provides information about the surrounding environment and encourages drivers to change their behavior. Second, the system intervenes in driving behavior directly to assure the safety. Such a system makes two different effects on drivers. The first is a cognitive effect, which includes drivers' subjective evaluations about the system. The second is a behavioral effect, which includes drivers' behavioral changes after driving with the system. We examined how information presentation and behavioral intervention affect drivers in both cognitive and behavioral aspects. The results show that information presentation makes a significant effect on drivers' behavioral changes after driving with the system while behavioral intervention makes a significant effect on drivers' evaluations about the system.

    DOI: 10.11225/jcss.25.324

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  12. 想定外に生じる例外の対処行動に関する実験的検討

    松林 翔太, 三輪 和久, 寺井 仁

    人工知能学会研究会資料 先進的学習科学と工学研究会   79 巻 ( 0 ) 頁: 10   2017年3月

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    記述言語:日本語   掲載種別:研究論文(学術雑誌)   出版者・発行元:一般社団法人 人工知能学会  

    DOI: 10.11517/jsaialst.79.0_10

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  13. Empirical Investigation of Changes of Driving Behavior and Usability Evaluation Using an Advanced Driving Assistance System

    Matsubayashi, S; Miwa, K; Yamaguchi, T; Kamiya, T; Suzuki, T; Ikeura, R; Hayakawa, S; Ito, T

    THIRTEENTH INTERNATIONAL CONFERENCE ON AUTONOMIC AND AUTONOMOUS SYSTEMS (ICAS 2017)     頁: 36 - 39   2017年

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    記述言語:英語   掲載種別:研究論文(学術雑誌)  

    Web of Science

  14. 説明転換における事実参照に関する実験的検討 査読有り

    寺井 仁, 三輪 和久, 松林 翔太

    認知科学   22 巻 ( 2 ) 頁: 223 - 234   2015年

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    記述言語:日本語   掲載種別:研究論文(学術雑誌)   出版者・発行元:日本認知科学会  

    Reconstructing explanations perform a crucial role not only in the progress of science,<br>but in educational practice and daily activities including comprehension of phenomena.<br> We focused on the transition of attention on a key fact that contradicts the preceding<br> explanation and has a central role in its reconstruction. We used a short story as an<br> experimental material in which the participants first constructed a prior explanation<br> and reconstructed it. The experimental results are summarized as follows. First, when<br> the prior explanation was rejected, a new explanation was required, after attention on<br> the key fact was inhibited. Second, hypothesized premises not inconsistent with the<br> prior explanation were sought to protect the prior explanation. Third, the explanation<br> reconstruction was facilitated by having the participants focus on the key fact. Last,<br>attention on the key fact was recovered through explanation reconstruction.

    DOI: 10.11225/jcss.22.223

  15. Explanation Reconstruction through Reinterpretation of Key Facts

    Terai H., Miwa K., Matsubayashi S.

    Building Bridges Across Cognitive Sciences Around the World - Proceedings of the 34th Annual Meeting of the Cognitive Science Society, CogSci 2012     頁: 2411 - 2416   2012年

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    記述言語:日本語   掲載種別:研究論文(学術雑誌)   出版者・発行元:Building Bridges Across Cognitive Sciences Around the World - Proceedings of the 34th Annual Meeting of the Cognitive Science Society, CogSci 2012  

    Reconstructing explanations is crucial for the progress of science. We focused on the transition of interest in a key fact that contradicts the preceding explanation and has a central role in its reconstruction. We used a short story as an experimental material in which the participants first constructed a naïve explanation and reconstructed it. First, when the naïve explanation was rejected, a new explanation was required, after interest in the key fact was inhibited. Second, hypothesized premises not inconsistent with the naïve explanation were sought to protect the naïve explanation. Third, interest in the key fact was recovered through the process of the explanation reconstruction. Last, we facilitated the explanation reconstruction by having the participants focus on the key fact.

    Scopus

▼全件表示

書籍等出版物 1

  1. 高齢社会における人と自動車

    青木, 宏文, 赤松, 幹之, 上出, 寛子( 担当: 分担執筆)

    コロナ社  2021年1月  ( ISBN:9784339027723

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    総ページ数:vii, 228p   担当ページ:79-87   記述言語:日本語

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講演・口頭発表等 36

  1. Assessment of the Detectability of Vulnerable Road Users: An Empirical Study

    Wentong Yang, Shota Matsubayashi, Kazuhisa Miwa, Shinya Kitayama, Manabu Otsuka, Koji Hamada

    8th International Conference on Human Computer Interaction Theory and Applications (HUCAPP 2024)  2024年2月27日 

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    開催年月日: 2024年2月

    記述言語:英語   会議種別:口頭発表(一般)  

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  2. Effects of Self and Other's Intentions on Moving Behavior in Crossing Interactions

    Shota Matsubayashi, Kazuhisa Miwa, Hitoshi Terai, Yuki Ninomiya

    The 2023 IEEE Conference on Systems, Man, and Cybernetics (IEEE SMC 2023)  2023年10月2日 

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    開催年月日: 2023年10月

    記述言語:英語   会議種別:口頭発表(一般)  

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  3. ゲームを用いた運の信念と能力が運の知覚に与える影響についての検討

    楊文通, 松林翔太, 三輪 和久

    日本認知科学会第40回大会  2023年9月9日 

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    開催年月日: 2023年9月

    記述言語:英語   会議種別:口頭発表(一般)  

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  4. インタラクティブな対人移動行動における個人差の表現

    松林翔太, 三輪和久, 寺井仁, 二宮由樹

    日本認知科学会第40回大会  2023年9月8日 

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    開催年月日: 2023年9月

    記述言語:英語   会議種別:口頭発表(一般)  

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  5. 先進的運転支援システム 情報提示と行動介入の影響について

    松林翔太

    日本交通心理学会 第88回名古屋大会  2023年8月5日 

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    開催年月日: 2023年8月

    記述言語:英語   会議種別:シンポジウム・ワークショップ パネル(指名)  

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  6. Navigation Style Classification Using Persistent Homology.

    Naoki Akai, Shota Matsubayashi, Kazuhisa Miwa, Takatsugu Hirayama, Hiroshi Murase

    2022 IEEE/SICE International Symposium on System Integration (SII)  2022年 

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    開催年月日: 2022年

    記述言語:英語   会議種別:口頭発表(一般)  

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    その他リンク: https://dblp.uni-trier.de/db/conf/sii/sii2022.html#AkaiMMHM22

  7. 歩車混在空間における協調的行動

    松林 翔太, 三輪 和久, 寺井 仁, 下條 朝也, 二宮 由樹

    日本認知科学会第38回大会  2021年9月3日 

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    開催年月日: 2021年9月

    記述言語:英語   会議種別:ポスター発表  

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  8. What is the Cooperative Behavior of Moving in Shared Spaces?

    Shota Matsubayashi, Kazuhisa Miwa, Hitoshi Terai, Asaya Shimojo, Yuki Ninomiya

    CogSci 2021 

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    開催年月日: 2021年7月

    記述言語:英語   会議種別:ポスター発表  

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  9. Verification of Coaching effect by Instructor-like Assistance System Based on Model Predictive Constraint Satisfaction

    Takuma Yamaguchi, Syota Matsubayashi, Tatsuya Suzuki, Kazuhisa Miwa

    IECON 2021 - 47TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY  2021年  IEEE

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    開催年月日: 2021年

    記述言語:英語   会議種別:口頭発表(一般)  

    Safety and acceptability are the main concerns in the design of driver assistance systems. However, these two requirements sometimes conflict with each other depending on the situation and the driver. This conflict is particularly emphasized in the case of elderly drivers. To solve this problem, this paper proposes a driver-vehicle cooperation scheme, an "instructor-like assisting control" consisting of model predictive constraint satisfaction and a multi-modal human-machine interface. The proposed assisting scheme is expected to improve the drivers' inherent driving characteristics, which is recognized as a "coaching effect" in cognitive science. This effect was verified by long-term experiments over one month using a driving simulator.

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    その他リンク: https://dblp.uni-trier.de/db/conf/iecon/iecon2021.html#YamaguchiMSM21

  10. 先進的運転支援システムに対する評価手法の考察ーユーザビリティ評価の横断的分析ー

    松林 翔太, 前東 晃礼, 三輪 和久, 青木 宏文, 山口 拓真, 鈴木 達也

    日本認知科学会第37回大会  2020年9月17日 

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    開催年月日: 2020年9月

    記述言語:英語   会議種別:口頭発表(一般)  

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  11. Building Mental Model Applied to Smartphone Application with ACT- R Cognitive Architecture

    Yang Ze, Matsubayashi Shota, Miwa Kazuhisa, Yao Xin

    日本認知科学会第37回大会  2020年9月17日 

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    開催年月日: 2020年9月

    記述言語:英語   会議種別:口頭発表(一般)  

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  12. Decision-Making in Interactions Between Two Vehicles at a Highway Junction

    Asaya Shimojo, Yuki Ninomiya, Shota Matsubayashi, Kazuhisa Miwa, Hitoshi Terai, Hiroyuki Okuda, Tatsuya Suzuki

    HCI in Mobility, Transport, and Automotive Systems. Driving Behavior, Urban and Smart Mobility  2020年  Springer International Publishing

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    開催年月日: 2020年

    記述言語:英語   会議種別:口頭発表(一般)  

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  13. Development of a Driving Model That Understands Other Drivers’ Characteristics

    Shota Matsubayashi, Hitoshi Terai, Kazuhisa Miwa

    HCI in Mobility, Transport, and Automotive Systems. Driving Behavior, Urban and Smart Mobility  2020年  Springer International Publishing

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    開催年月日: 2020年

    記述言語:英語   会議種別:口頭発表(一般)  

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  14. Model-based Approach with ACT-R about Benefits of Memory-based Strategy on Anomalous Behaviors.

    Shota Matsubayashi, Kazuhisa Miwa, Hitoshi Terai

    2019年 

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    開催年月日: 2019年

    記述言語:英語   会議種別:口頭発表(一般)  

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  15. 想定外に生じる例外の対処行動に関する実験的検討

    松林 翔太, 三輪 和久, 寺井 仁

    先進的学習科学と工学研究会  2017年3月8日 

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    記述言語:日本語   会議種別:口頭発表(一般)  

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  16. Empirical Investigation of Changes of Driving Behavior and Usability Evaluation Using an Advanced Driving Assistance System 国際会議

    Shota Matsubayashi, Kazuhisa Miwa, Takuma Yamaguchi, Takafumi Kamiya, Tatsuya Suzuki, Ryojun Ikeura, Soichiro Hayakawa, Takafumi Ito

    THIRTEENTH INTERNATIONAL CONFERENCE ON AUTONOMIC AND AUTONOMOUS SYSTEMS (ICAS 2017)  2017年 

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    記述言語:英語   会議種別:口頭発表(一般)  

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  17. 運転支援方法とユーザビリティ・行動変容の関係に関する実験的検討

    松林翔太, 松林翔太, 松林翔太, 三輪和久, 山口拓真, 山口拓真, 神谷貴文, 鈴木達也, 池浦良淳, 早川聡一郎, 伊藤隆文, 武藤健二

    日本認知科学会大会発表論文集(CD-ROM)  2016年 

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    記述言語:日本語   会議種別:口頭発表(一般)  

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  18. 説明転換における事実参照に関する検討

    寺井仁, 三輪和久, 松林翔太, 遠山直宏

    日本認知科学会大会発表論文集(CD-ROM)  2015年 

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    記述言語:日本語   会議種別:口頭発表(一般)  

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  19. 文章洞察課題を用いた説明の再構築に関する実験的検討

    松林翔太, 寺井仁, 三輪和久

    人工知能学会先進的学習科学と工学研究会資料  2012年3月7日 

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    記述言語:日本語   会議種別:口頭発表(一般)  

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  20. 文章洞察問題を用いた再解釈と説明に関する実験的検討

    松林翔太, 寺井仁, 三輪和久

    日本認知科学会大会発表論文集(CD-ROM)  2011年 

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    記述言語:日本語   会議種別:口頭発表(一般)  

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  21. 指導員型運転支援の反復利用による運転行動特性変化の検証

    山口拓真, 金田直輝, 松林翔太, 奥田裕之, 鈴木達也, 三輪和久

    自動車技術会大会学術講演会講演予稿集(CD-ROM)  2019年5月17日 

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    記述言語:日本語   会議種別:口頭発表(一般)  

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  22. 想定外事象に対する認知プロセスと検証手法 ―実験・シミュレーション・実践― 招待有り

    松林 翔太

    第48回 KG CAPSセミナー  2021年6月9日 

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    記述言語:英語   会議種別:口頭発表(一般)  

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  23. 想定外に生じる例外の対処行動に関する実験的検討

    松林翔太, 三輪和久, 寺井仁

    人工知能学会先進的学習科学と工学研究会資料  2017年3月1日 

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    記述言語:日本語   会議種別:口頭発表(一般)  

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  24. 変則的挙動に対する記憶ベース方略のACT‐Rモデル検討

    松林翔太, 三輪和久, 寺井仁

    日本認知科学会大会発表論文集(CD-ROM)  2018年 

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    記述言語:日本語   会議種別:口頭発表(一般)  

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  25. 変則事例に対する記述的対処方略に関する実験的検討

    松林翔太, 三輪和久, 寺井仁

    日本認知科学会大会発表論文集(CD-ROM)  2017年 

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    記述言語:日本語   会議種別:口頭発表(一般)  

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  26. 先読み運転を可能にするスーパーバイザ型運転支援の提案と実車実証

    二宮芳樹, 竹内栄二朗, 山口拓真, 新村文郷, 吉原佑器, 赤木康宏, 川西康友, 松林翔太, 三輪和久, 出口大輔, 早川聡一郎, 鈴木達也, 村瀬洋

    自動車技術会大会学術講演会講演予稿集(CD-ROM)  2016年10月17日 

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    記述言語:日本語   会議種別:口頭発表(一般)  

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  27. スーパーバイザ型運転支援による運転行動改善の検証

    山口拓真, 松林翔太, 奥田裕之, 鈴木達也, 三輪和久

    計測自動制御学会システム・情報部門学術講演会講演論文集(CD-ROM)  2018年11月25日 

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    記述言語:日本語   会議種別:口頭発表(一般)  

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  28. スーパーバイザ型協調制御の実験的検証

    神谷貴文, 山口拓真, 奥田裕之, 鈴木達也, 松林翔太, 三輪和久, 武藤健二, 伊藤隆文

    自動車技術会大会学術講演会講演予稿集(CD-ROM)  2016年5月23日 

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    記述言語:日本語   会議種別:口頭発表(一般)  

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  29. アプリケーション使用時におけるメンタルモデルの修正の検討

    姚昕, 松林翔太, 三輪和久

    日本認知科学会第36回大会  2019年9月5日 

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    記述言語:日本語   会議種別:ポスター発表  

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  30. Short- and Long-Term Effects of an Advanced Driving Assistance System on Driving Behavior and Usability Evaluation 国際会議

    The Twelfth International Conference on Advances in Computer-Human Interactions (ACHI 2019)  2019年2月26日 

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    記述言語:英語   会議種別:口頭発表(一般)  

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  31. Model-based Approach with ACT-R about Benefits of Memory-based Strategy on Anomalous Behaviors 国際会議

    Shota Matsubayashi, Kazuhisa Miwa, Hitoshi Terai

    CogSci 2019  2019年7月25日 

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    記述言語:英語   会議種別:口頭発表(一般)  

    開催地:Palais des congrès de Montréal  

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  32. Explanation Reconstruction through Reinterpretation of Key Facts.

    Hitoshi Terai, Kazuhisa Miwa, Shota Matsubayashi

    Proceedings of the 34th Annual Meeting of the Cognitive Science Society, CogSci 2012, Sapporo, Japan, August 1-4, 2012  2012年 

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    記述言語:英語   会議種別:口頭発表(一般)  

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    その他リンク: http://dblp.uni-trier.de/db/conf/cogsci/cogsci2012.html#conf/cogsci/TeraiMM12

  33. Shared spaceの移動における思いやり度を示す指標の開発

    松林 翔太, 三輪 和久, 寺井 仁, 二宮 由樹, 下條 朝也

    日本認知科学会第39回大会  2022年9月8日 

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    記述言語:英語   会議種別:口頭発表(一般)  

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  34. 自律エージェントの利用する情報の顕著性が行動ルールの言語的・非言語的推定に与える影響

    二宮 由樹, 下條 朝也, 寺井 仁, 松林 翔太, 三輪 和久

    日本認知科学会第39回大会  2022年9月9日 

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    記述言語:英語   会議種別:口頭発表(一般)  

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  35. Distinct Characteristics between “Anshin” and Feeling of Safety Evaluations

    Shota Matsubayashi, Kazuhisa Miwa, Hitoshi Terai, Yuki Ninomiya

    The Sixteenth International Conference on Advances in Computer-Human Interactions (ACHI 2023)  2023年4月25日 

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    記述言語:英語   会議種別:口頭発表(一般)  

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  36. Effects of Saliency of an Agent’s Input Information on Estimation of Mental States toward the Agent

    Yuki Ninomiya, Asaya Shimojo, Shota Matsubayashi, Hitoshi Terai, Kazuhisa Miwa

    The Sixteenth International Conference on Advances in Computer-Human Interactions (ACHI 2023)  2023年4月25日 

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    記述言語:英語   会議種別:口頭発表(一般)  

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▼全件表示

その他研究活動 1

  1. 電通育英会 大学院奨学生 第5期生

    2010年4月
    -
    2012年3月

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    電通育英会 大学院奨学生 第5期生

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科研費 1

  1. 行動誘導型運転支援の実現に向けた他者モデルの導入

    2019年6月 - 2019年9月

    公益財団法人 立石科学技術振興財団  2019年度前期 国際交流助成 短期在外研究 

    松林 翔太

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    担当区分:研究代表者  資金種別:競争的資金

    配分額:729000円 ( 直接経費:700000円 、 間接経費:29000円 )

    共同研究者:Frank E. Ritter (Pennsylvania State University)
    自動車運転における集団の協調運転の実現を目指し,人間の認知モデルを実装するフレームワークとして知られるACT-Rをベースにし,他者理解に関する技術として他者モデルの具体的な記述方法を確立する。

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担当経験のある科目 (本学以外) 2

  1. 面接法

    2020年4月 - 現在 東海学園大学)

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  2. 認知科学B

    2017年10月 - 現在 大同大学)

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