Publisher：Conference on Human Factors in Computing Systems Proceedings  

This pilot study examined the relationship between driving instructors’ approaches and risky driving behaviors among older drivers in three stages: driving school familiarization, on-road driving with behind-the-wheel training (BWT), and on-road driving with minimal intervention (MI). Two frameworks—goals for driver education (GDE) and internal-external focus—classified instructor utterances. Cluster analysis was applied to high-frequency words, and two-way ANOVA tests showed significant differences in instructional categorizations and stages for both frameworks. Correlation analyses indicated that under the BWT stage, riskier behaviors were inversely related to internal and internal × external instructions. Conversely, these behaviors were positively correlated with external, internal × external instructions, and GDE-based instructions in the MI stage, including the total number of instructor utterances. These results suggest instructors compensate for reduced physical intervention by increasing verbal instructions, emphasizing the need for adaptive training strategies, and the possibilities of external guidance elements and future advanced driver assistance systems incorporating internal.

DOI： 10.1145/3706599.3720166

Open Access

Web of Science

Scopus

Language：Japanese   Publisher：Society of Automotive Engineers of Japan  

In a driver assistance system, the information presented at inappropriate timing reduces reliability and acceptability. Therefore, we conducted a DS experiment to investigate the relationship between the necessity for notifying approaching bicycles and their position and speed. As a result, it was found that whether or not the notification is judged appropriate could be estimated by the TTC of the bicycle. it was also found that informing the reason is effective to help prevent distrust when the bicyclist changed his/her path after the notification.

DOI： 10.11351/jsaeronbun.56.26

Open Access

CiNii Research

Publisher：IEEE Intelligent Vehicles Symposium Proceedings  

To mitigate the occurrence of traffic accidents, addressing the human factors pertinent to road safety, particularly driver operational errors, is essential. Drivers in urban environments can benefit from readiness evaluations and feedback, which help mitigate errors, promote safer driving speeds, and enhance situational awareness. This study aimed to develop and validate a driver behavior assessment system centered around the concept of stepwise driver readiness. The system is designed to evaluate driver behavior and provide progressive feedback to improve performance. We extrapolated the original concept of driver readiness to create a stepwise readiness evaluation system, which was implemented and tested on urban roads to evaluate its effectiveness. The results demonstrate that the system effectively evaluates readiness, and the stepwise feedback mechanism significantly enhances driver performance. Notably, the success of the feedback process was influenced by the level of driver acceptance. These results highlight the importance of the expanded driver readiness concept in managing human factor-related driving risks and improving road safety.

DOI： 10.1109/IV64158.2025.11097655

Web of Science

Scopus

Publisher：Proceedings of the 2025 IEEE International Conference on Vehicular Electronics and Safety Icves 2025  

This study investigated the long-term effects of a voice-based stepwise driver-assistance system providing either real-time feedback alone or feedback plus advice. Ten experienced drivers completed six weekly drives on an urban route with two accident-prone areas. Weekly acceptance ratings and behavioral readiness metrics (stepwise score, mean speed, throttle-off count, foot-on-brake count, brake-on count, and lateral checks) were collected. Acceptance was analyzed via two-way ANOVA (Week × Group); behavioral retention in a pre feedback zone (Area 1) was assessed using linear mixed-effects models. Although both systems showed good acceptance, feedback with advice yielded significantly higher and more stable usefulness ratings. Advice recipients showed larger, sustained speed reductions (3.5-4.4 km/h from Week 4, p < 0.01) and persistent readiness-behavior improvements, unlike the feedback-only group, which showed limited improvement. Notably, in Area 1, advice-trained drivers maintained these improved behaviors without active feedback, indicating habit internalization. Thus, stepwise feedback and advice tailored to driver readiness may lower learning difficulty and psychological reactance to enhancing readiness behavior. Overall, this spaced-learning approach using feedback with advice appears effective for attenuating alert fatigue, maintaining acceptance, and transforming momentary corrections into lasting safe driving habits, even in experienced drivers.

DOI： 10.1109/ICVES65691.2025.11376422

Web of Science

Scopus

Publisher：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

Publisher：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

Language：Japanese   Publisher：Society of Automotive Engineers of Japan  

One of the challenging issues in V2X system to help prevent Car-to-Bicyclist crashes is the information reliability, to be more specific, for the cases where cars do not encounter bicyclists owing to their sudden direction change (false positive) or for those where cars encounter bicyclists with no signal transmission (true negative). Car drivers’ acceptance was investigated to understand the influence of the extent of false positive and that of true negative. To reduce adverse effect by highly relying on receiving the information, an extra investigation aiming to maintain driving attention by offering the fundamental traffic circumstance risk was performed.

DOI： 10.11351/jsaeronbun.54.1060

Open Access

CiNii Research

Publisher：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

Publisher：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

Language：English   Publisher：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

Open Access

Web of Science

Scopus

PubMed

Language：Japanese   Publisher：Society of Automotive Engineers of Japan  

Drivers' head movements are informative measures for evaluating the safety of elderly drivers. However, those measures are too technical for general elderly drivers to understand the meaning and how to improve them. This paper applied a principal component analysis (PCA) on elderly drivers' head movement measures driving a simulator, resulting in integrated head movement measures as principal axes that are easily interpretable: steadiness, quickness, and timeliness. Chart diagrams of PCA scores show an individual as well as group elderly drivers' characteristics. Based on the PCA scores, we discuss possible feedbacks for the elderly drivers.

DOI： 10.11351/jsaeronbun.53.385

Open Access

CiNii Research

Publisher：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

Publisher：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

DOI： 10.1109/IV47402.2020.9304569

Web of Science

Publisher：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

Language：Japanese   Publisher：Japan Ergonomics Society  

DOI： 10.5100/jje.56.2e2-04

CiNii Research

Web of Science

Publisher：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

Publisher：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