Updated on 2024/06/03

写真a

 
MATSUBAYASHI Shota
 
Organization
Graduate School of Informatics Department of Cognitive and Psychological Sciences 1 Designated associate professor
Title
Designated associate professor
External link

Degree 3

  1. Information Science ( 2020.3   Nagoya University ) 

  2. Information Science ( 2012.3   Nagoya University ) 

  3. Informatics and Science ( 2010.3   Nagoya University ) 

Research Areas 3

  1. Humanities & Social Sciences / Cognitive science

  2. Humanities & Social Sciences / Experimental psychology  / Cognitive Psychology

  3. Informatics / Human interface and interaction

Research History 5

  1. Nagoya University   Institute of Innovation for Future Society Mobility Research Course   Designated assistant professor

    2020.8

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  2. Nagoya University   Graduate School of Informatics   Researcher

    2019.4 - 2020.7

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  3. Nagoya University   Institute of Innovation for Future Society (MIRAI)   Researcher

    2018.10 - 2019.3

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  4. Nagoya University   Institute of Innovation for Future Society (MIRAI)   Research Assistant

    2015.10 - 2018.9

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  5. NTT DOCOMO, INC.

    2012.4 - 2015.8

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Education 3

  1. Nagoya University   Graduate School of Information and Science   Department of Media Science, Doctor Course

    2015.10 - 2018.9

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    Country: Japan

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  2. Nagoya University   Graduate School of Information and Science   Department of Media Science, Master Course

    2010.4 - 2012.3

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    Country: Japan

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  3. Nagoya University   School of Informatics and Sciences   Department of Social and Human Science Information

    2006.4 - 2010.3

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    Country: Japan

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Professional Memberships 3

  1. JAPANESE COGNITIVE SCIENCE SOCIETY

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  2. Cognitive Science Society

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  3. 日本交通心理学会

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Awards 3

  1. Best Paper Award

    2023.6   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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    Award type:Award from international society, conference, symposium, etc.  Country:Italy

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  2. Best Paper Award

    2019.4   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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    Award type:Award from international society, conference, symposium, etc.  Country:Greece

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  3. Best Paper Award

    2017.6   International Academy, Research, and Industry Association   Empirical Investigation of Changes of Driving Behavior and Usability Evaluation Using an Advanced Driving Assistance System

    Shota MatsubayashiKazuhisa MiwaTakuma, YamaguchiTakafumi KamiyaTatsuya, SuzukiRyojun IkeuraSoichiro, HayakawaTakafumi Ito

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    Award type:Award from international society, conference, symposium, etc.  Country:Spain

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Papers 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

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    Language:English   Publishing type:Research paper (scientific journal)  

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

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

    Human Factors: The Journal of the Human Factors and Ergonomics Society   Vol. 66 ( 4 ) page: 961 - 974   2022.8

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:SAGE Publications  

    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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    Other Link: http://journals.sagepub.com/doi/full-xml/10.1177/00187208221121404

  3. Benefits of Cognitive Processes of Memory-Based Strategy on Anomalous Behaviors

    Matsubayashi Shota, Miwa Kazuhisa, Terai Hitoshi

    Cognitive Studies: Bulletin of the Japanese Cognitive Science Society   Vol. 26 ( 3 ) page: 332 - 342   2019.9

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Japanese Cognitive Science Society  

     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

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  4. Empirical investigation of memory-based strategy on anomalous behavior Reviewed

    Shota Matsubayashi, Kazuhisa Miwa, Hitoshi Terai

    Shinrigaku Kenkyu   Vol. 90 ( 3 ) page: 274 - 283   2019

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:The Japanese Psychological Association  

    © 2019 Japanese Psychological Association. All rights reserved. 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.

    DOI: 10.4992/jjpsy.90.18018

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

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

    Transportation Research Part F: Traffic Psychology and Behaviour   Vol. 89   page: 236 - 248   2022.8

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Elsevier BV  

    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)     page: 161 - 164   2022

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher: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     page: 2444 - 2449   2021

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher: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

    Takuma Yamaguchi, Syota Matsubayashi, Tatsuya Suzuki, Kazuhisa Miwa

    IECON 2021 - 47TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY   Vol. 2021-October   2021

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:IEEE  

    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.

    DOI: 10.1109/IECON48115.2021.9589646

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

    Shota Matsubayashi, Hitoshi Terai, Kazuhisa Miwa

      Vol. 12213 LNCS   page: 29 - 39   2020

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Springer International Publishing  

    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     page: 776 - 781   2019

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher: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. Cognitive and Behavioral Effects on Driving by Information Presentation and Behavioral Intervention in Advanced Driving Assistance System Reviewed

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

    Cognitive Studies   Vol. 25 ( 3 ) page: 324 - 337   2018

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Japanese Cognitive Science Society  

     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. Empirical Investigation of Unexpected Events Handling: Preliminary Discussion

    MATSUBAYASHI Shota, MIWA Kazuhisa, TERAI Hitoshi

    JSAI Technical Report, SIG-ALST   Vol. 79 ( 0 ) page: 10   2017.3

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:The Japanese Society for Artificial Intelligence  

    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)     page: 36 - 39   2017

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    Language:English   Publishing type:Research paper (scientific journal)  

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  14. An Experimental Study on Explanation Reconstruction through Reinterpretation of Key Facts. Reviewed

    Terai Hitoshi, Miwa Kazuhisa, Matsubayashi Shota

    Cognitive Studies   Vol. 22 ( 2 ) page: 223 - 234   2015

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Japanese Cognitive Science Society  

    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     page: 2411 - 2416   2012

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher: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.

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Books 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( Role: Contributor)

    コロナ社  2021.1  ( ISBN:9784339027723

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    Total pages:vii, 228p   Responsible for pages:79-87   Language:Japanese

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Presentations 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)  2024.2.27 

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    Event date: 2024.2

    Language:English   Presentation type:Oral presentation (general)  

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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)  2023.10.2 

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    Event date: 2023.10

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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  2023.9.9 

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    Event date: 2023.9

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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  2023.9.8 

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    Event date: 2023.9

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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  2023.8.5 

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    Event date: 2023.8

    Language:English   Presentation type:Symposium, workshop panel (nominated)  

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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 

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    Event date: 2022

    Language:English   Presentation type:Oral presentation (general)  

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    Other Link: https://dblp.uni-trier.de/db/conf/sii/sii2022.html#AkaiMMHM22

  7. Cooperative Behavior in the Shared Space

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

    2021.9.3 

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    Event date: 2021.9

    Language:English   Presentation type:Poster presentation  

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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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    Event date: 2021.7

    Language:English   Presentation type:Poster presentation  

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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  IEEE

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    Event date: 2021

    Language:English   Presentation type:Oral presentation (general)  

    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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    Other Link: https://dblp.uni-trier.de/db/conf/iecon/iecon2021.html#YamaguchiMSM21

  10. Discussion for Evaluation Method toward Advanced Driving Assistance Systems

    Shota Matsubayashi, Akihiro Maehigashi, Kazuhisa Miwa, Hirofumi Aoki, Takuma Yamaguchi, Tatsuya Suzuki

    2020.9.17 

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    Event date: 2020.9

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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

    2020.9.17 

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    Event date: 2020.9

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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  Springer International Publishing

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    Event date: 2020

    Language:English   Presentation type:Oral presentation (general)  

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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  Springer International Publishing

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    Event date: 2020

    Language:English   Presentation type:Oral presentation (general)  

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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 

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    Event date: 2019

    Language:English   Presentation type:Oral presentation (general)  

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  15. Empirical Investigation of Unexpected Events Handling : Preliminary Discussion

    松林 翔太, 三輪 和久, 寺井 仁

    先進的学習科学と工学研究会  2017.3.8 

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    Language:Japanese   Presentation type:Oral presentation (general)  

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  16. The modification of mental model for users who use application

    Yao Xin, Shota Matsubayashi, Kazuhisa Miwa

    2019.9.5 

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  17. Short- and Long-Term Effects of an Advanced Driving Assistance System on Driving Behavior and Usability Evaluation International conference

    Shota Matsubayashi, Kazuhisa Miwa, Takuma Yamaguchi, Tatsuya Suzuki

    The Twelfth International Conference on Advances in Computer-Human Interactions (ACHI 2019)  2019.2.26 

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

    Shota Matsubayashi, Kazuhisa Miwa, Hitoshi Terai

    CogSci 2019  2019.7.25 

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    Language:English   Presentation type:Oral presentation (general)  

    Venue:Palais des congrès de Montréal  

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  19. 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 

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    Language:English   Presentation type:Oral presentation (general)  

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    Other Link: http://dblp.uni-trier.de/db/conf/cogsci/cogsci2012.html#conf/cogsci/TeraiMM12

  20. Empirical Investigation of Changes of Driving Behavior and Usability Evaluation Using an Advanced Driving Assistance System International conference

    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 

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  21. 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)  2016.5.23 

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    Language:Japanese   Presentation type:Oral presentation (general)  

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  22. 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 

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  23. 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 

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  24. 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  2012.3.7 

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  25. 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 

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  26. 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)  2019.5.17 

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  27. 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― Invited

    松林 翔太

    第48回 KG CAPSセミナー  2021.6.9 

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  28. 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  2017.3.1 

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  29. ACT-R Modeling for Memory-based Strategy for Anomalous Behaviors

    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 

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  30. Empirical Investigation of Descriptive Handling Strategy on Anomalous Instances

    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 

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  31. 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

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    自動車技術会大会学術講演会講演予稿集(CD-ROM)  2016.10.17 

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  32. 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)  2018.11.25 

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  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  2022.9.8 

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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  2022.9.9 

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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)  2023.4.25 

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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)  2023.4.25 

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Other research activities 1

  1. 電通育英会 大学院奨学生 第5期生

    2010.4
    -
    2012.3

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    電通育英会 大学院奨学生 第5期生

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KAKENHI (Grants-in-Aid for Scientific Research) 1

  1. Studies of Human Driver Models for a Cognitive Science-based Technology for Driving Assistance

    2019.6 - 2019.9

    Tateishi Science and Technology Foundation  Short-term Foreign Research for International Interaction 2019 First Semester 

    Shota MATSUBAYASHI

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    Authorship:Principal investigator  Grant type:Competitive

    Grant amount:\729000 ( Direct Cost: \700000 、 Indirect Cost:\29000 )

    Co-researcher: Frank E. Ritter (Pennsylvania State University)
    In this study, I develop the driving behavior model with the intention estimations to realize the machine coexisting with human drivers, pedestrians, or other traffic participants. The driver model is built with the cognitive architecture ACT-R and I elaborate on the detailed structure of the model.

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Teaching Experience (Off-campus) 2

  1. Interviewing Method

    2020.4 Tokai Gakuen University)

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  2. Cognitive Science B

    2017.10 Daido University)

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