2024/10/29 更新

写真a

カラタス ニハン
KARATAS Nihan
KARATAS Nihan
所属
未来社会創造機構 HMI・人間特性研究部門 特任助教
職名
特任助教
 

論文 15

  1. Advancing ADAS Acceptance: Interventions and Comparative Analysis of Robotic Human Machine Interfaces

    Karatas N., Tanaka T., Yoshihara Y., Tanabe H., Takeuchi S., Yamamoto T., Harazawa M., Kamiya N.

    16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2024 - Adjunct Conference Proceedings     頁: 149 - 154   2024年9月

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    出版者・発行元:16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, AutomotiveUI 2024 - Adjunct Conference Proceedings  

    Advanced Driver Assistance Systems (ADAS) enhance vehicle safety by providing critical information, warning drivers, and automating control tasks to reduce manual operation. However, the acceptability of ADAS is often limited by the human-machine interface (HMI) used, due to issues such as perceived usefulness, ease of use and trust of the ADAS operations. This study proposes using a robotic human-machine interface (RHMI) to improve the acceptability of ADAS and explores whether a small humanoid robot or a minimally designed robot is more effective as an RHMI in widely used three ADAS operations: Adaptive Cruise Control (ACC), Lane Tracking Assistance (LTA), and Blind Spot Monitoring (BSM). We conducted three experimental conditions in a driving simulator using a within-subject design: only a conventional HMI (C-HMI), C-HMI and a humanoid RHMI (RoBoHoN), and C-HMI and a minimally designed RHMI prototype (RHMI-P) in a within-subject design. Participants' subjective assessments and eye gaze data were analyzed. The findings indicate that the acceptability of the BSM operation increased with RoBoHoN due to its familiar and human-like appearance. However, the objective measures revealed that RHMI-P increased gaze alertness and was perceived as more competent and trustworthy. This study highlights the importance of incorporating human-like elements and effectively using non-verbal cues when designing an interface for ADAS to improve the acceptability of ADAS operations and increase their usage for safer roads.

    DOI: 10.1145/3641308.3685039

    Scopus

  2. Robotic-Human-Machine-Interface for Elderly Driving: Balancing Embodiment and Anthropomorphism for Improved Acceptance

    Karatas N., Tanaka T., Yoshihara Y., Tanabe H., Kojima M., Endo M., Manabe S.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   14454 LNAI 巻   頁: 240 - 253   2024年

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    出版者・発行元:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)  

    Encouraging self-awareness among elderly drivers while driving with a passenger has the potential to reduce traffic accidents. Highly anthropomorphic Robotic-Human-Machine-Interfaces (RHMIs) have been shown to be effective in providing safe driving and review support by being perceived as fellow passengers. However, it remains unclear which specific anthropomorphic elements in the RHMI’s appearance are necessary to achieve this effect. Identifying these essential elements for elderly driving could lead to a minimal design approach and reduced installation costs in car dashboards. Therefore, in this study, we investigated the effects of RHMI embodiment and anthropomorphism level on drivers’ acceptability and user experience quality through a series of RHMI prototypes by conducting a crowdsource video experiment and a driving simulator experiment, respectively. The findings provide insights into the design of a low-cost, minimal, and efficient RHMI as a driving agent.

    DOI: 10.1007/978-981-99-8718-4_21

    Scopus

  3. Examining the Effectiveness of a Robotic-Human-Machine-Interface on Sleepiness During Highway Automated Driving

    Karatas N., Yoshihara Y., Tanabe H., Tanaka T., Fujikake K., Takeuchi S., Iwata K., Harazawa M., Kamiya N.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   14026 LNCS 巻   頁: 501 - 513   2023年

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    出版者・発行元:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)  

    The automation of vehicles is increasing and is expected to become a part of our daily lives in the near future. Furthermore, the progress in automated driving operations will change the driver’s role to that of a passive monitor. However, a lack of active involvement in driving situations and monotonous driving environments increase driver sleepiness. Considering the low automation levels in vehicles (i.e., Levels 2 and 3), drivers’ arousal levels and ability to monitor the road environment are critical. In this study, we examined the effectiveness of a robotic-human-machine-interface (RHMI) in alleviating the sleepiness level of drivers through random news information presentation. We conducted a within-subject experiment with 12 participants in a driving simulator environment and compared three conditions: no information was provided (the control condition); information was provided through a voice-only interface; and information was provided through an RHMI prototype. The qualitative and quantitative results of this experiment revealed that the information provision interfaces (voice-only and RHMI) had the potential to alleviate the sleepiness level in Level 2 highway automated driving. In addition, the RHMI prototype alleviated sleepiness and improved the arousal of drivers more than in the voice-only and no-information provision conditions.

    DOI: 10.1007/978-3-031-35927-9_34

    Scopus

  4. 通信型運転支援システムからの情報提示の誤報・未報と過信の影響

    原田 あすか, 金森 等, 阿賀 正己, 横井 康伸, Karatas Nihan, 吉原 佑器, 田中 貴紘

    自動車技術会論文集   54 巻 ( 5 ) 頁: 1060 - 1066   2023年

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    記述言語:日本語   出版者・発行元:公益社団法人 自動車技術会  

    自転車事故防止の通信型支援システムでは情報の正確性が課題,具体的には自転車の急な方向転換により遭遇しない(誤報)や情報発信無の自転車と遭遇する(未報)場合である.誤報や未報の程度と受容性の関係を調査した.未報時の過信抑制方策として,交通環境リスク提示による運転注意力維持を調査したので併せて紹介する.

    DOI: 10.11351/jsaeronbun.54.1060

    CiNii Research

  5. Exploring User Acceptance of Minimally Designed Driving Agents: An Online Video Experiment

    Karatas, N; Tanaka, T; Yoshihara, Y; Tanabe, H; Kojima, M; Endo, M; Manabe, S

    PROCEEDINGS OF THE 11TH CONFERENCE ON HUMAN-AGENT INTERACTION, HAI 2023     頁: 440 - 442   2023年

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    出版者・発行元:ACM International Conference Proceeding Series  

    A highly anthropomorphic Robotic Human Machine Interface (RHMI) integrated into car dashboards has shown effectiveness in promoting safe driving behaviors, as it is accepted as a driving agent. However, which anthropomorphic elements in the RHMI's appearance are essential for achieving driver acceptance remains unclear. Identifying these elements could facilitate the development of a minimal design and reduced installation costs for RHMIs on car dashboards. In this study, we conducted an online video experiment to explore the impact of RHMI embodiment and anthropomorphism levels on user acceptance. The findings provide insights for designing cost-effective and minimalist RHMIs as driving agents.

    DOI: 10.1145/3623809.3623956

    Web of Science

    Scopus

  6. Lessons Learned About Designing and Conducting Studies From HRI Experts

    Fraune, MR; Leite, I; Karatas, N; Amirova, A; Legeleux, A; Sandygulova, A; Neerincx, A; Tikas, GD; Gunes, H; Mohan, M; Abbasi, NI; Shenoy, S; Scassellati, B; de Visser, EJ; Komatsu, T

    FRONTIERS IN ROBOTICS AND AI   8 巻   頁: 772141   2022年1月

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    記述言語:英語   出版者・発行元:Frontiers in Robotics and AI  

    The field of human-robot interaction (HRI) research is multidisciplinary and requires researchers to understand diverse fields including computer science, engineering, informatics, philosophy, psychology, and more disciplines. However, it is hard to be an expert in everything. To help HRI researchers develop methodological skills, especially in areas that are relatively new to them, we conducted a virtual workshop, Workshop Your Study Design (WYSD), at the 2021 International Conference on HRI. In this workshop, we grouped participants with mentors, who are experts in areas like real-world studies, empirical lab studies, questionnaire design, interview, participatory design, and statistics. During and after the workshop, participants discussed their proposed study methods, obtained feedback, and improved their work accordingly. In this paper, we present 1) Workshop attendees’ feedback about the workshop and 2) Lessons that the participants learned during their discussions with mentors. Participants’ responses about the workshop were positive, and future scholars who wish to run such a workshop can consider implementing their suggestions. The main contribution of this paper is the lessons learned section, where the workshop participants contributed to forming this section based on what participants discovered during the workshop. We organize lessons learned into themes of 1) Improving study design for HRI, 2) How to work with participants - especially children -, 3) Making the most of the study and robot’s limitations, and 4) How to collaborate well across fields as they were the areas of the papers submitted to the workshop. These themes include practical tips and guidelines to assist researchers to learn about fields of HRI research with which they have limited experience. We include specific examples, and researchers can adapt the tips and guidelines to their own areas to avoid some common mistakes and pitfalls in their research.

    DOI: 10.3389/frobt.2021.772141

    Web of Science

    Scopus

    PubMed

  7. Effects of a Robot Human-Machine Interface on Emergency Steering Control and Prefrontal Cortex Activation in Automatic Driving

    Tanabe, H; Yoshihara, Y; Karatas, N; Fujikake, K; Tanaka, T; Takeuchi, S; Yamamoto, T; Harazawa, M; Kamiya, N

    ENGINEERING PSYCHOLOGY AND COGNITIVE ERGONOMICS, EPCE 2022   13307 巻   頁: 108 - 123   2022年

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    出版者・発行元:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)  

    Advanced driver assistance systems (ADASs) support drivers in multiple ways, such as adaptive cruise control, lane tracking assistance (LTA), and blind spot monitoring, among other services. However, the use of ADAS cruise control has been reported to delay reaction to vehicle collisions. We created a robot human-machine interface (RHMI) to inform drivers of emergencies by means of movement, which would allow drivers to prepare for the disconnection of autonomous driving. This study investigated the effects of RHMI on response to the emergency disconnection of the LTA function of autonomous driving. We also examined drivers’ fatigue and arousal using near-infrared spectroscopy (NIRS) on the prefrontal cortex. The participants in this study were 12 males and 15 females. We recorded steering torque and NIRS data in the prefrontal region across two channels during the manipulation of automatic driving with a driving simulator. The scenario included three events in the absence of LTA due to bad weather. All of the participants experienced emergencies with and without RHMI, implemented using two agents: RHMI prototype (RHMI-P) and RoBoHoN. Our RHMI allowed the drivers to respond earlier to emergency LTA disconnection. All drivers showed a gentle torque response for RoBoHoN, but some showed a steep response with RHMI-P and without RHMI. NIRS data showed significant prefrontal cortex activation in RHMI conditions (especially RHMI-P), which may indicate high arousal. Our RHMI helped drivers stay alert and respond to emergency LTA disconnection; however, some drivers showed a quick and large torque response only with RHMI-P.

    DOI: 10.1007/978-3-031-06086-1_9

    Web of Science

    Scopus

  8. 高齢ドライバ安全確認行動の主成分特徴分析

    吉原 佑器, 田中 貴紘, 大須賀 晋, 藤掛 和広, Karatas Nihan, 金森 等

    自動車技術会論文集   53 巻 ( 2 ) 頁: 385 - 390   2022年

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    記述言語:日本語   出版者・発行元:公益社団法人 自動車技術会  

    頭部動作は高齢ドライバの運転評価において有効であるが, 技術的な観点から開発された指標は, 一般のドライバにとって直観的ではない. 本稿では高齢ドライバのシミュレータ運転時の頭部動作に主成分分析を行い, 解釈しやすい直観的な評価軸を得た. さらに運転評価のためのフィードバックを考察した.

    DOI: 10.11351/jsaeronbun.53.385

    CiNii Research

  9. Workshop YOUR study design! Participatory Critique and Refinement of Participants' Studies

    Fraune, MR; Karatas, N; Leite, I

    HRI '21: COMPANION OF THE 2021 ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION     頁: 688 - 690   2021年

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    出版者・発行元:ACM/IEEE International Conference on Human-Robot Interaction  

    The purpose of this workshop is to help researchers develop methodological skills, especially in areas that are relatively new to them. With HRI researchers coming from diverse backgrounds in computer science, engineering, informatics, philosophy, psychology, and more disciplines, we can't be expert in everything. In this workshop, participants will be grouped with a mentor to enhance their study design and interdisciplinary work. Participants will submit 4-page papers with a small introduction and detailed method section for a project currently in the design process. In small groups led by a mentor in the area, they will discuss their method and obtain feedback. The workshop will include time to edit and improve the study. Workshop mentors include Drs. Cindy Bethel, Hung Hsuan Huang, Selma Sabanović, Brian Scassellati, Megan Strait, Komatsu Takanori, Leila Takayama, and Ewart de Visser, with expertise in areas of real-world study, empirical lab study, questionnaire design, interview, participatory design, and statistics.

    DOI: 10.1145/3434074.3444867

    Web of Science

    Scopus

  10. Analysis of Distraction and Driving Behavior Improvement Using a Driving Support Agent for Elderly and Non-Elderly Drivers on Public Roads

    Tanaka, T; Fujikake, K; Yoshihara, Y; Karatas, N; Shimazaki, K; Aoki, H; Kanamori, H

    2020 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV)     頁: 1029 - 1034   2020年

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  11. Utilization of human-robot interaction for the enhancement of performer and audience engagement in performing art

    Karatas N., Sekino H., Tanaka T.

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   12427 LNCS 巻   頁: 348 - 358   2020年

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    出版者・発行元:Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)  

    Recently, computer-supported interactive technologies have played a significant role as complementary tools in creation of extraordinary artworks. These technologies have been used in art to explore their utility to compose new creative concepts, and to enrich the dimensions of artistic performances to strengthen the engagement between the performer and the audience. Since integrating the audience into the artistic performance has a significant role in enhancing an individual pleasure, a robotic medium holds great potential in bringing about new opportunities for artistic performances. In this preliminary study, we observed the effects of eye gazing behaviours of a minimal robot on audience engagement and connectedness in regard to an artistic performance. With this paper, the results from the data of a limited number of participants show that the audience tended to be distracted by the robot’s existence, however, the gazing behavior of the robot maintain a feeling of connectivity between the robot and the audience.

    DOI: 10.1007/978-3-030-60152-2_26

    Scopus

  12. ドライバエージェントの継続利用に伴う受容性の変化

    藤掛 和広, 田中 貴紘, 吉原 佑器, Nihan KARATAS, 青木 宏文, 金森 等

    人間工学   56 巻 ( Supplement ) 頁: 2E2-04 - 2E2-04   2020年

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    記述言語:日本語   出版者・発行元:一般社団法人 日本人間工学会  

    DOI: 10.5100/jje.56.2e2-04

    CiNii Research

  13. Identifying High-Risk Older Drivers by Head-Movement Monitoring Using a Commercial Driver Monitoring Camera

    Yoshihara, Y; Tanaka, T; Osuga, S; Fujikake, K; Karatas, N; Kanamori, H

    2020 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV)     頁: 1021 - 1028   2020年

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  14. Evaluation of AR-HUD Interface During an Automated Intervention in Manual Driving

    Karatas, N; Tanaka, T; Fujikake, K; Yoshihara, Y; Fuwamoto, Y; Yoshida, M; Kanamori, H

    2020 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV)     頁: 2158 - 2164   2020年

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    出版者・発行元:IEEE Intelligent Vehicles Symposium, Proceedings  

    Automated driving systems are envisioned as the future mode of transportation owing to their projected ability to reduce human error and achieve more efficient and comfortable transportation. Accordingly, designing an interface that ensures the situational awareness of the human operator to reduce confusion, false expectations, and over-reliance on the automated system is important. When a human operator is in control, the automated system is expected to handle troublesome situations that the human is unable to manage. Thus, an interface is required to provide the appropriate information when necessary so that the human operator can easily perceive the reason for the sudden automated intervention. In this study, such a scenario is highlighted, in which a simulated automated intervention avoided a potential collision with a pedestrian who suddenly appeared on the roadside. To convey the reason for the automated intervention, an augmented reality-based head-up display (AR-HUD) cue that targets the pedestrian is developed. To understand the effects of the AR-HUD cue on the speed at which a human operator can recognize a pedestrian and the contribution of this visual cue to the perception of acceptability and credibility of the automated intervention, we compared AR-HUD with a static head-up display (S-HUD) that displays a pedestrian symbol at the bottom portion of the windshield. The results showed that the AR-HUD cue yielded faster recognition of the targeted pedestrian and provided a relatively more acceptable perception of the automated intervention.

    DOI: 10.1109/iv47402.2020.9304610

    Web of Science

    Scopus

  15. Study on Acceptability of and Distraction by Driving Support Agent in Actual Car Environment

    Tanaka, T; Fujikake, K; Yoshihara, Y; Karatas, N; Aoki, H; Kanamori, H

    PROCEEDINGS OF THE 7TH INTERNATIONAL CONFERENCE ON HUMAN-AGENT INTERACTION (HAI'19)     頁: 202 - 204   2019年

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    出版者・発行元:HAI 2019 - Proceedings of the 7th International Conference on Human-Agent Interaction  

    Cars represent an important mode of transportation for the elderly; however, in recent years, the number of traffic accidents caused by elderly drivers in Japan has increased. Thus, to ensure driving safety, we are researching a driver agent system that provides driving support and feedback support to elderly drivers to encourage them to improve their driving. In this paper, we report on a set of preliminary experiments using our agent in an actual car environment designed to evaluate the subjective acceptability of and distraction by the agent based on subjective evaluation and analysis of driver fixation points during driving. The results revealed that the acceptability of the agent was high and that the agent in an actual car environment did not distract the driver.

    DOI: 10.1145/3349537.3352765

    Web of Science

    Scopus

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