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

CiNii Research

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：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

DOI： 10.1007/978-3-031-06086-1_9

Web of Science

DOI： 10.1007/978-3-031-05061-9_11

Web of Science

DOI： 10.3389/fpsyg.2021.526942

Web of Science

DOI： 10.1145/3472307.3484160

Web of Science

Language：Japanese   Publisher：Society of Automotive Engineers of Japan  

This study investigated driver's face images on public roads using a commercial driver monitoring system, aiming to make feedbacks about how the drivers check the safety. The study focused on the head movements of older drivers versus middle-aged drivers, and high-speed drivers versus low-speed drivers, observed at stop-sign intersections. It tested several measures that characterize the temporal and spatial aspects of head movements. Two sample t-tests revealed the significant decrease in head speed, head angle, and the increase of the ratio of short duration in the high-risk driver groups, suggesting the usefulness of head movements for driving assist systems.

DOI： 10.11351/jsaeronbun.52.363

Language：Japanese   Publisher：The Japanese Society for Artificial Intelligence  

<p>In this paper, we examine the acceptability of the politeness strategy in the speech of driving support agents. The main speech of existing driving support agents corresponds to the off-record strategy in politeness theory. However, off-record strategies were not compared with other politeness strategies in the evaluation experiments of driving support agents in the previous studies, and the difference in the effects between the strategies was not clear. Therefore, we conducted a video-based subjective evaluation experiment to compare the acceptability of the off-record strategy, the positive politeness strategy, and the negative politeness strategy. The results of the experiment showed that the negative politeness strategy was rated significantly higher than the off-record strategy in the items related to functionality among the evaluation indicators of acceptability. This result suggests that it is useful for an agent to provide explicit instructions to a user with linguistic consideration when providing driving assistance.</p>

DOI： 10.11517/pjsai.jsai2021.0_4e3os11c04

CiNii Research

Web of Science

Language：Japanese   Publisher：Society of Automotive Engineers of Japan  

Recently, the number of traffic accidents involving elderly drivers has been increasing, and it is known that side collisions at the intersection are particularly frequent. Thus, we put on-dash cams for 22 drivers aged 50-82 years old to measure their driving behavior at stop intersections. The relation between emergency braking frequency and looking behavior, and cognitive/physical characteristics and driving attitude were investigated. The results show that some elderly drivers can perform compensatory driving behaviors such as looking both ways at stop intersections to reduce the frequency of emergency braking even though their cognitive and physical characteristics have deteriorated.

DOI： 10.11351/jsaeronbun.51.701

Web of Science

DOI： 10.1109/iv47402.2020.9304610

Web of Science

DOI： 10.1007/978-3-030-22666-4_17

Web of Science

Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japan Society for Fuzzy Theory and Intelligent Informatics  

<p>In this paper, we propose an agent which selects utterance strategy according to driver's attributes and situation based on politeness theory. The proposed agent system considers attribute information such as age, gender, personality, driving experience and driving characteristics of the driver, and selects and supports highly receptive utterance strategies. Here, as a survey for the development of the proposed system, an impression evaluation experiment on a driving support agent was conducted using a moving picture reflecting driving support scenes. In particular, we focused attention on the difference of the end-of-sentence style which is a representation method of distinctive psychological distances in Japanese conversation. As a result of the experiment, it is suggested that agents using non-polite words may be effective for improving familiarity. On the other hand, the agent using honorifics gives the impression that it is cautious, suggesting the possibility that it feels that information is conveyed accurately.</p>

DOI： 10.3156/jsoft.31.3_739

CiNii Books

Language：Japanese   Publisher：Society of Automotive Engineers of Japan  

In this study, we used robot which was the most acceptable among ´voice´, ´vision´ and ´robot´ as a driver-agent. We verified whether the driving behavior improvement by driving the driving simulator together with the agent. The agent's support was 3 kinds of "driving-support", "feedback" and "driving support and feedback". Driving-support was real-time support by robot's voice. Feedback looked back on unsafe driving behaviors with movie after driving. Driving-support and feedback was combined use of both. As a result, driving behavior was improvement by using an agent. Driving behavior was the most improved condition was "driving-support and feedback". And, the condition with higher subjective evaluation was "driving-support and feedback".

DOI： 10.11351/jsaeronbun.50.134

CiNii Books

DOI： 10.1145/3349537.3352765

Web of Science

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

DOI： 10.1145/3284432.3284444

Web of Science

Web of Science

Language：Japanese   Publisher：Society of Automotive Engineers of Japan  

This paper presents a high-accuracy localization method for autonomous cars. In the method, we use inertial navigation system (INS) and a multilayer light detection and ranging. Three-dimensional normal distributions transform scan matching is employed and its estimation result is fused with the result from INS on the basis of a Kalman filtering algorithm. To determine uncertainty of the scan matching result, we utilize Hessian of the cost function. The localization method robustly estimates smooth and accurate vehicle trajectory. We conducted autonomous driving demonstrations with the method in public roads and these results are used to show the performance.

DOI： 10.11351/jsaeronbun.49.675

CiNii Books

Language：Japanese   Publisher：Japan Society for Fuzzy Theory and Intelligent Informatics  

<p>The purpose of this research is to design a driving support agent that selects utterance strategy considering driver's attributes and driving situation based on the politeness theory. In the politeness theory, utterance strategy for constructing good relationship between people is systematized. As a concrete approach, we designed agent linguistic behaviors based on the positive politeness strategies and negative politeness strategies, which are representative utterance strategies defined in the politeness theory. In the experiment, we used two kinds of movies which reflect scenes where the driver is supported by speech synthesis utterance from agents. The utterance contents of agents were designed by us. Experiment participants watched two movies in a row and evaluated impressions for agents. Here we discuss the impression evaluation results and future development. Experiment participants are university students or graduate students with a driving experience of three years or less.</p>

DOI： 10.14864/fss.34.0_419

CiNii Books

DOI： 10.3389/fnhum.2017.00298

Web of Science

Web of Science

Web of Science

Web of Science

Web of Science

Publishing type：Research paper (scientific journal)   Publisher：Scientific Research Publishing, Inc.  

DOI： 10.4236/jtts.2017.72011

Other Link： http://file.scirp.org/xml/75461.xml

Language：Japanese   Publisher：Japan Ergonomics Society  

DOI： 10.5100/jje.56.2E2-04

Language：Japanese  

J-GLOBAL

Language：Japanese  

DOI： 10.5100/jje.55.2C3-6

J-GLOBAL

Language：Japanese  

J-GLOBAL

Language：Japanese  

J-GLOBAL

Language：Japanese   Publisher：Japan Ergonomics Society  

Language：English  

DOI： 10.1109/FUZZ-IEEE.2019.8858855

Language：Japanese  

J-GLOBAL

Language：Japanese   Publisher：公益社団法人 日本生体医工学会  

&lt;p&gt;Heart disease is a latent risk factor while driving that causes severe traffic accidents and often kill drivers themselves. Wearable devices for monitoring electrocardiogram (ECG) serves as a key to detect irregular heart activity. Automatic detection of anomaly in ECG must challenge variety of ECG shapes that contain environmental noise. One promising technique would be machine-learning, which compute difference between real data and normal ECG, given appropriate set of healthy subjects data as training dataset. It is not, however, easy to prepare sufficient amount of real data because irregularity may contaminate and must be cleansed, labor work that needs clinical experts. This report shows our challenge to construct a fully computational training dataset by means of a realistic ECG waveform generator and use it to train an auto encoder type neural network. We demonstrate that the trained network quantifies anomaly of patients ECGs with several different arrhythmias. &lt;/p&gt;

Language：Japanese  

J-GLOBAL

Language：Japanese  

Language：Japanese  

J-GLOBAL

Language：Japanese  

J-GLOBAL

J-GLOBAL

Language：English   Publisher：Institute of Electrical and Electronics Engineers Inc.  

In this study, we developed an autonomous driving system for mountainous public roads. Three-dimensional normal distribution transform (NDT) scan matching is employed for localization and a model predictive controller is utilized for vehicle motion control. In order to increase the robustness of the localization method, the estimated poses are computed by an extended Kalman filter using dead reckoning and NDT information. The uncertainty of the pose estimated by NDT is determined by using the Hessian matrix computed in the optimization process for scan matching. We conducted experiments in a public road environment over 20 times and all of the tests were successful. The experimental results confirmed that the autonomous driving system can operate reliably in mountainous public roads. In addition, the evaluation results obtained for the localization method showed that accurate and robust localization can be achieved in mountainous rural environments.

DOI： 10.1109/ITSC.2017.8317797

Scopus