Updated on 2023/03/27

写真a

 
YAMAGUCHI Takuma
 
Organization
Graduate School of Engineering Mechanical Systems Engineering 2 Assistant Professor
Graduate School
Graduate School of Engineering
Undergraduate School
School of Engineering Mechanical and Aerospace Engineering
Title
Assistant Professor

Degree 3

  1. 博士(工学) ( 2014.3   名古屋大学 ) 

  2. 修士 ( 2011.3   名古屋大学 ) 

  3. 学士 ( 2009.3   名古屋大学 ) 

Research Interests 4

  1. Automobile

  2. probability theory

  3. mathematical optimization

  4. control theory

Research Areas 3

  1. Manufacturing Technology (Mechanical Engineering, Electrical and Electronic Engineering, Chemical Engineering) / Control and system engineering

  2. Informatics / Robotics and intelligent system

  3. Informatics / Human interface and interaction

Research History 4

  1. Nagoya University   Graduate School of Engineering Mechanical Systems Engineering   Assistant Professor

    2022.2

  2. Meijo University   Faculty of Science and Technology

    2020.4 - 2022.3

  3. Nagoya University   Graduate school of engineering   Designated assistant professor

    2019.4 - 2022.1

  4. Nagoya University   Institute of Innovation for Future Society   Designated assistant professor

    2014.4 - 2019.3

Professional Memberships 2

  1. THE SOCIETY OF INSTRUMENT AND CONTROL ENGINEERS

  2. SOCIETY OF AUTOMOTIVE ENGINEERS OF JAPAN

Committee Memberships 3

  1. 計測自動制御学会   中部支部 庶務  

    2022.1   

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    Committee type:Academic society

  2. 自働車技術会中部支部   幹事  

    2018   

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    Committee type:Academic society

  3. 計測自動制御学会 中部支部   運営委員  

    2016.4 - 2018.3   

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    Committee type:Academic society

Awards 3

  1. Best Paper Award Finalists

    2023.1   IEEE SICE   Analysis and Modeling of Traffic Participants Considering Interactions at Intersections Without Traffic Signals

    Toru Watanabe;Takuma Yamaguchi;Hiroyuki Okuda;Tatsuya Suzuki;Ryo Wakisaka;Kazunori Ban

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

  2. Best Paper Award

    2019.2   ACHI 2019 : The Twelfth International Conference on Advances in Computer-Human Interactions  

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

  3. Best Paper Award

    2017.5   ICAS 2017 : The Thirteenth International Conference on Autonomic and Autonomous Systems  

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

 

Papers 21

  1. Analysis and Modeling of Traffic Participants Considering Interactions at Intersections Without Traffic Signals Reviewed

    Toru Watanabe , Takuma Yamaguchi , Hiroyuki Okuda , Tatsuya Suzuki , Ryo Wakisaka , Kazunori Ban

    2023 IEEE/SICE International Symposium on System Integration (SII)     2023.1

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    Authorship:Corresponding author   Language:English   Publishing type:Research paper (international conference proceedings)  

    DOI: 10.1109/sii55687.2023.10039251

  2. 確率的な時変パラメータをもつ制御器モデルによる車線維持行動のモデル化 Reviewed

    辻 悠介 , 菅本 周作 , 奥田 裕之 , 山口 拓真 , 鈴木 達也

    計測自動制御学会論文集   Vol. 58 ( 12 ) page: 581 - 590   2022.12

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

    DOI: https://doi.org/10.9746/sicetr.58.581

  3. Proposal and evaluation of reference-free model predictive control incorporating human-like driving features Invited Reviewed

        2022.10

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    Authorship:Lead author  

    DOI: 10.1109/itsc55140.2022.9922106

  4. Indication of interaction plans based on model predictive interaction control: Cooperation between AMRs and pedestrians using eHMI Reviewed

    2022 61st Annual Conference of the Society of Instrument and Control Engineers (SICE)     2022.9

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  5. Evaluation of impact by control switching according to driving environment Reviewed

    2022 61st Annual Conference of the Society of Instrument and Control Engineers (SICE)     2022.9

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    Authorship:Corresponding author  

    DOI: 10.23919/sice56594.2022.9905761

  6. Model Predictive Collision Avoidance for Non-Convex Environment Using Projected C-Space Reviewed

    Tatsuya Ishiguro, Takuma Yamaguchi, Hiroyuki Okuda, Tatsuya Suzuki

    2022 IEEE/SICE International Symposium on System Integration (SII)     2022.1

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/sii52469.2022.9708875

  7. Modelling and Analysis for Interactive Crossing Decision of Pedestrian at Non-signalized Intersection Reviewed

    Takashi Nishimoto, Takuma Yamaguchi, Hiroyuki Okuda, Tatsuya Suzuki, Kentaro Haraguchi, Ryo Wakisaka, Kazunori Ban

    2022 IEEE/SICE International Symposium on System Integration (SII)   Vol. 2022 ( SII )   2022.1

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/sii52469.2022.9708841

    J-GLOBAL

  8. Modelling and Analysis for Interactive Crossing Decision of Pedestrian at Non-signalized Intersection Reviewed

    Yamaguchi Takuma, Kuroda Hayato, Okuda Hiroyuki, Suzuki Tatsuya, Haraguchi Kentaro, Wakisaka Ryo, Ban Kazunori

    Transactions of Society of Automotive Engineers of Japan   Vol. 52 ( 6 ) page: 1360 - 1367   2021.11

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    Authorship:Lead author   Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Society of Automotive Engineers of Japan  

    In the development of autonomous driving technology, simulation verification is an essential process, and pedestrian behavior is especially a key factor. However, the behavior and making-decision of humans are complex and indistinct. Therefore, the simulated behavior is assumed in a limited manner. To address this problem, we construct the pedestrian model of the crossing decision for a non-signalized intersection. The crossing decision is an interactive behavior that is influenced by other traffic participants. From this reason, we developed a multi-player interactive simulator, in which vehicles and a pedestrian can be controlled by the human. The model was constructed by the multi-class logistic regression to express human decision ambiguity. Finally, this model has validated whether the estimated decision was consistent with the ground truth data.

    DOI: 10.11351/jsaeronbun.52.1360

  9. Verification of Improvement of Driving Characteristics by Instructional Cooperative Assistance System Reviewed

    Takuma Yamaguchi, Shota Matsubayashi, Tatsuya Suzuki, Kazuhisa Miwa

    47th Annual Conference of the IEEE Industrial Electronics Society     2021.10

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    Authorship:Lead author   Language:English   Publishing type:Research paper (scientific journal)  

  10. Model Predictive Path Planning for Autonomous Parking Based on Projected C-Space Reviewed

    Takuma Yamaguchi, Tatsuya Ishiguro, Hiroyuki Okuda, Tatsuya Suzuki

    2021 IEEE International Intelligent Transportation Systems Conference (ITSC)     page: 929 - 935   2021.9

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    Authorship:Lead author   Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/itsc48978.2021.9564599

  11. 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

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    Language:English   Publishing type:Research paper (international conference proceedings)   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

    Web of Science

  12. Modeling and Analysis of Interactive Driving Behavior Based on Piecewise ARX Model Reviewed

    Takuma YAMAGUCHI, Hiroyuki OKUDA, Tatsuya SUZUKI

    Journal of Japan Society for Fuzzy Theory and Intelligent Informatics   Vol. 32 ( 3 ) page: 713 - 721   2020.6

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    Authorship:Lead author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:Japan Society for Fuzzy Theory and Intelligent Informatics  

    In real-world driving, one of the critical issues to be analyzed is an interaction with other traffic participants. This problem is easily solved in the case that direct communication between agents is available. Such direct communication, however, is not always available due to limited implementation of realtime on-board communication facilities. For sophisticated safety system design, the vehicle is highly requested to implement an interactive intelligence, which is mainly based on an understanding of interaction mechanism between traffic participants from observed sensing signals. In order to analyze the interactive behavior, this paper presents a modeling by using a PieceWise AutoRegressive eXogenous (PWARX) model. Since the PWARX model can describe continuous dynamics and discrete switching, interactive behavior is modeled and understood as the combination of primitive dynamics (operation) and mode transitions (decision making) of them. The usefulness of the proposed scheme is verified by applying to the modeling of interactive task of ‘bidirectional passing by task.’

    DOI: 10.3156/jsoft.32.3_713

    CiNii Books

  13. Realization and Evaluation of an Instructor-Like Assistance System for Collision Avoidance Reviewed

    Keji Chen, Takuma Yamaguchi, Hiroyuki Okuda, Tatsuya Suzuki, Xuexun Guo

    IEEE Transactions on Intelligent Transportation Systems     page: 1 - 10   2020

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Institute of Electrical and Electronics Engineers (IEEE)  

    DOI: 10.1109/tits.2020.2974495

  14. Short- and Long-Term Effects of an Advanced Driving Assistance System on Driving Behavior and Usability Evaluation Reviewed

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

    Proceedings. of The Twelfth International Conference on Advances in Computer-Human Interactions (ACHI 2019)     page: 1-6   2019

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

  15. INS とマルチレイヤー LiDAR を用いた自動運転車両のための高精度自己位置推定 Reviewed

    赤井直紀, 竹内栄二朗, 山口拓真, モラレス ルイス 洋一, 吉原佑器, 奥田裕之, 鈴木達也, 二宮芳樹

    自動車技術会論文集   Vol. 49 ( 3 ) page: 675 - 681   2018

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

  16. 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

    CiNii Books

  17. Identification of Personalized Potential Field and Its Application to Obstacle Avoidance Assisting Control(Second Report) Reviewed

      Vol. 48 ( 1 ) page: 97 - 102   2017

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

    CiNii Books

  18. Model Predictive Charging Control of In-vehicle Batteries for Home Energy Management based on Vehicle State Prediction Reviewed

    A. Ito, A. Kawashima, T. Suzuki, S. Inagaki, T. Yamaguchi, Z. Zhou

    IEEE Transactions on Control Systems Technology   Vol. 26 ( 1 ) page: 51 - 64   2017

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

    DOI: 10.1109/TCST.2017.2664727

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

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

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

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:IARIA XPS PRESS  

    It is known that the behavior of autonomous systems affects users' cognitive and behavioral aspects; however, further examination of sequential effects is required. We manipulated instructional information as cognitive guidance and the degree of behavioral intervention implemented by an advanced driving assistance system, and then assessed usability evaluation of the system and changes in user behavior. The results show that strict intervention reduces subjective evaluations, and the absence of instructional information hinders changes in user behavior.

    Web of Science

  20. Autonomous Driving Based on Accurate Localization Using Multilayer LiDAR and Dead Reckoning Reviewed

    N. Akai, L. Y. Morales, T. Yamaguchi, E. Takeuchi, Y. Yoshihara, H. Okuda, T. Suzuki, Y. Ninomiya

    IEEE Int. Conf. on Intelligent Transportation Systems     page: 1147 - 1152   2017

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    DOI: 10.1109/ITSC.2017.8317797

  21. Supervisory Interventional Driving Assistance Control and Its Verification Reviewed

      Vol. 48 ( 3 ) page: 717 - 724   2017

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

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MISC 10

  1. 「 ヒト ト ツナガル セイギョ システム ノ ミライ オ ノゾク 」 トクシュウゴウ

    奥田 裕之, 山口 拓真

    システム・制御・情報 = Systems, control and information : システム制御情報学会誌   Vol. 65 ( 9 ) page: 370 - 376   2021.9

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    Language:Japanese  

    CiNii Books

  2. Modelling and Analysis of Pedestrian Crossing Decisions Based on Gaze-Switching in Interactive Crossing Tasks

    西本宇志, 黒田颯人, 山口拓真, 奥田裕之, 鈴木達也, 脇坂龍, 伴和徳

    自動車技術会大会学術講演会講演予稿集(Web)   Vol. 2021   2021

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  3. Coordinated control between EVs and EMS in a smart community sharing on-board storage batteries for ancillary service participation

    原拓郎, 山口拓真, 稲垣伸吉, 鈴木達也

    自動制御連合講演会(CD-ROM)   Vol. 63rd (Web)   2020

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  4. Proposal of EV cooperative multi-base EMS using quadratic programming

    渋谷拓己, 鈴木達也, 山口拓真, 稲垣伸吉

    自動制御連合講演会(CD-ROM)   Vol. 63rd (Web)   2020

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  5. 市街地での合流時における運転指導下での高齢ドライバの運転行動解析

    奧田峻也, 山口拓真, 吉原佑器, 青木宏文, 山岸未沙子, 二宮芳樹, 竹内栄二朗, 奥田裕之, 鈴木達也

    自動車技術会大会学術講演会講演予稿集(CD-ROM)   Vol. 2018   page: ROMBUNNO.029   2018.5

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    Language:Japanese  

    J-GLOBAL

  6. Prediction of Car Use for Energy Management Systems

    INAGAKI Shinkichi, KAWASHIMA Akihiko, YAMAGUCHI Takuma, SUZUKI Tatsuya

    Journal of The Society of Instrument and Control Engineers   Vol. 56 ( 7 ) page: 509 - 514   2017

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    Language:Japanese   Publisher:The Society of Instrument and Control Engineers  

    DOI: 10.11499/sicejl.56.509

  7. INSとマルチレイヤーLIDARを用いた高精度自己位置推定に基づく一般公道での自動運転

    赤井直紀, 竹内栄二朗, 山口拓真, MORALES Luis Yoichi, 吉原佑器, 奥田裕之, 鈴木達也, 二宮芳樹

    自動車技術会大会学術講演会講演予稿集(CD-ROM)   Vol. 2017   2017

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  8. インピーダンス制御を用いた操舵介入支援における減衰比を用いた制御パラメータ設計

    石川拓磨, 早川聡一郎, 堤成可, 山口拓真, 池浦良淳, 鈴木達也

    自動車技術会大会学術講演会講演予稿集(CD-ROM)   Vol. 2017   2017

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  9. 車の駐車と移動の予測手法の提案

    清水修, 鈴木達也, 稲垣伸吉, 伊藤みのり, 川島明彦, 山口拓真

    自動車技術会大会学術講演会講演予稿集(CD-ROM)   Vol. 2017   2017

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  10. 減衰比に基づくインピーダンス制御型操舵介入支援システムのドライバ受容性評価

    田中捷, 石川拓磨, 早川聡一郎, 堤成可, 山口拓真, 池浦良淳, 鈴木達也

    計測自動制御学会システムインテグレーション部門講演会(CD-ROM)   Vol. 18th   2017

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KAKENHI (Grants-in-Aid for Scientific Research) 7

  1. Development of Model Predictive Interactive Intelligence and Its Application to Autonomous Drive

    Grant number:19H00763  2019.4 - 2022.3

    Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (A)

    Suzuki Tatsuya

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    Authorship:Coinvestigator(s) 

    In this project, a model predictive intelligence was developed, which exploits the model of others, behavior prediction based on others' model and real-time optimization. The proposed control architecture was implemented on a small personal mobility. The others' model embedded in the proposed architecture played an important role to realize an interactive intelligence between the vehicle and others. In this project, a model of decision making was particularly focused on and a new cost function of decision entropy of others has been defined. Since the decision entropy is a measure of the uncertainty of the decision of others, a natural human-like interaction between vehicle and others has been achieved by minimizing the decision entropy of others. The usefulness of the proposed architecture has been demonstrated by implementing on a real personal mobility which has interaction with pedestrians.

  2. Construction of decision-making scheme among drivers using dynamics model

    Grant number:18K18103  2018.4 - 2021.3

    Grants-in-Aid for Scientific Research  Grant-in-Aid for Early-Career Scientists

    Yamaguchi Takuma

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    Authorship:Principal investigator 

    Grant amount:\3770000 ( Direct Cost: \2900000 、 Indirect Cost:\870000 )

    This work targeted passing driving behavior around a parked car, and it was modeled and analyzed with the PWARX (PieceWise Autoregressive eXogenous) model, which is one of the hybrid dynamical systems.This target task involves a making decision, whether a driver gives way to an oncoming car or not.Besides, the decision needs to make taking into account other traffic participants, and this task is an interactive one.To achieve the goal, the driving behavior was modeled and analyzed with the PWARX model, and the model expressed the continuous driving behaviors and discrete decisions.This model can predicted the driving velocity with only 15% error.

  3. ダイナミクスモデルによるドライバ間の意思決定スキームの構築

    2018.4 - 2021.3

    日本学術振興会  科学研究費助成事業:若手B 

    山口 拓真

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    Authorship:Principal investigator  Grant type:Competitive

    Grant amount:\3770000

  4. Supervisory Driver Assistance Control and Its Verification

    Grant number:16H02353  2016.4 - 2019.3

    Suzuki Tatsuya

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    Authorship:Coinvestigator(s) 

    Safety and acceptability are main concerns in the design of driver assistance system. In fact, these two requirements sometimes may conflict with each other depending on e situation and driver. This conflict is more emphasized particularly in the case of considering elderly driver. In order to solve this problem, this paper proposes a new driver-vehicle cooperation scheme, a `supervisory cooperation control' which consists of model predictive constraint satisfaction and multimodal human-machine interface. The proposed cooperation scheme enables us to realize the safety without loosing acceptability.In addition, we have verified that the proposed assistance system improve the driver's original driving characteristics, i.e., the driver can learn how to realize the safety driving.

  5. 知能化自動車のためのスーパーバイザ型協調制御とその実証

    2016.4 - 2019.3

    日本学術振興会  科学研究費助成事業:基盤A(研究分担者) 

    鈴木達也

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    Grant type:Competitive

  6. Usage prediction of electric vehicle to achieve both traffic and energy management system

    Grant number:16K18167  2016.4 - 2018.3

    Yamaguchi Takuma

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    Authorship:Principal investigator 

    Grant amount:\2990000 ( Direct Cost: \2300000 、 Indirect Cost:\690000 )

    It is proposed that an electric vehicles are available as not only vehicles but also movable batteries because it has a high capacity. However, the movable battery function is available only when the driver does not use the vehicle. In order to integrate the electric vehicle into an energy management system, usage prediction is needed.
    This work established a usage prediction method of the electric vehicle considering driver's habits. The management method for electric vehicles which balances the usage as a vehicle and a storage battery was proposed, and its effectiveness was verified in the simulation experiment.

  7. 交通とエネルギーマネジメントを両立させる電気自動車の利用予測

    2016.4 - 2018.3

    日本学術振興会  科学研究費助成事業:若手B 

    山口 拓真

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    Authorship:Principal investigator  Grant type:Competitive

    Grant amount:\2990000

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