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Soon, autonomous cars are expected to become widespread, but at present, it is still common for people to drive cars manually. A driving support agent (DSA) is used to support driving using the human-agent interaction approach. In previous research, it was shown that DSAs can be useful in assisting the user through voice utterances. However, previous studies focusing on DSA utterance design have not compared off-record strategies with other politeness strategies that explicitly communicate the speaker's intentions, and it was not clear whether DSA should provide explicit utterances to the user. Therefore, in this study, a video-based subjective evaluation experiment (n=240) was conducted to compare the acceptability of off-record strategies, positive politeness strategies, negative politeness strategies, and direct utterances without politeness strategies. The results of the experiment showed that the negative politeness strategy was evaluated significantly higher than the off-record strategy on evaluation items related to functionality. This result suggests the usefulness of providing explicit instructions with linguistic consideration (politeness) when DSA provides driving assistance to users. In addition to the above findings, there were several correlations between the user's personality characteristics and the subjective evaluation of the DSA. Specifically, there was a significant positive correlation between the level of conscientiousness of the user and the direct utterance evaluation value. For the positive politeness strategy and off-record strategy, there were no significant correlations between evaluation categories of the dislikeability and users' personality characteristics. These results suggest that individual differences in n egative impressions due to personality characteristics are small in the positive politeness and off-record strategies.

Japan has become a more aged society and there are more drivers, 65 years of age and above. Cars represent an important mode of transportation for the elderly; however, in recent years, the number of traffic accidents caused by elderly drivers has been on the rise, and this has become a social issue. Thus, for the elderly drivers to encourage them to improve their driving, we study a driver agent system which consists of smartphone, communication robot and cloud service and provides the driving support by attention awakening and the feedback support based on driving behavior evaluation. In this paper, we presented a summary of the proposed agent and reported on a set of preliminary experiments using our agent in an actual car environment. From the analysis of subjective evaluations and fixation points during driving, the results revealed the possibility that the drivers accept the agent and supports from the agent during driving and that the agent in an actual car environment did not distract the driver.

Humans obtain information from their five senses, which include vision. In recent decades, numerous displays have been developed as a result of technological advancements, and such apparatuses can be used in daily life. The development of evaluation indicators for gaze data is a very important research topic in the hygiene field. In this chapter, we outline the types of eye movements, such as the saccade, smooth pursuit eye movement, vergence eye movement, optokinetic nystagmus, vestibulo-ocular reflex, and rotational eye movement. Thereafter, we introduce several methods for measuring eye movements, including the magnetic search coil method, pupil center corneal reflection method, limbus tracking meth-od, image analysis method, and electrooculography. Based on the eye movements measured by noncontact devices, indices are developed to evaluate the severity of visually induced motion sickness.

Older drivers experience a high rate of crashes due to road intersections, unseen objects, and failure to find the traffic signals. These characteristics would be recognized if a system could watch and monitor the behaviors of the drivers inside their car. Therefore, in this study, current advances in driver monitoring cameras are used for measuring the head movements of older drivers to evaluate the visual intent of the driver. Several quantitative metrics that compute the temporal and spatial aspects of head movements allow for assessing the behaviors of older and middle-aged drivers. A driving simulator study using urban road scenarios shows that at high vehicle speed, on average, older drivers move their heads more slowly within a narrower range and glance too quickly to recognize surrounding traffic correctly. Correlation analysis validated the high prediction capabilities of head-movement measures towards the future evaluation of driving risks.

Japan has become a more aged society and there are more drivers, 65 years of age and above. Cars represent an important mode of transportation for the elderly; however, in recent years, the number of traffic accidents caused by elderly drivers has been on the rise, and this has become a social issue. Thus, to ensure driving safety, we study a driver agent system that provides driving and feedback support to the elderly drivers for encouraging them to improve their driving. In this paper, we present a summary of the proposed agent and report on a set of experiments using our agent for the elderly and non-elderly drivers in an actual environment with car on public roads. From the analysis of driving operations and fixation points during driving, the results revealed that the acceptability of the agent was high, the agent in the actual car environment did not distract the driver, and the agent could improve driving behavior.

In recent years, the number of traffic accidents caused by elderly drivers has increased in Japan. However, a car is an important mode of transportation for the elderly. Therefore, to ensure safe driving, a system that can assist elderly drivers is required. In this study, we propose a driver-agent system that provides support to elderly drivers during and after driving and encourages them to improve their driving. This paper describes the prototype system based on the analysis of the teaching records of a human instructor, and the subjective evaluation of driving support to elderly and non-elderly driver from three different agent forms, a voice, visual, and robot. The result revealed that the robot form is more noticeable, familiar, and acceptable to the elderly and non-elderly than other forms.

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.

The purpose of this research is to analyze overconfidence and dependence caused by receiving the utterance from a driving support robot when a driver drives a car. Comfortable driving can be performed by receiving support from the driving support robot. However, it is expected that drivers will lead to accidents by the dependence or overconfidence bias on support robots. The dependence bias is that driver decreases the quality of driving behavior with respect to the function of the safety system, and the overconfidence bias is that driver embraces expectations more than the performance of the driving support robot. Although this problem includes the fuzziness of human characteristics, the conventional driving support system does not take into consideration such influence of the overconfidence or dependent bias. In order to verify whether driver has the bias against driving support robot in this paper, we investigated the impression of the robot when the driving support with driving animation and robot and report the results.

In this research, we propose a driving support agent which speak based on politeness theory. Driving support agent is drawing attention as a new form of driving assistance for driving, but knowledge on effective utterance for driving support has not been established. The proposed agent selects an utterance based on the politeness theory in consideration of the age of driver, gender and driving characteristics. In the previous research, it has been pointed out that the driving support agent needs to be designed according to the driver’s age and ability. Experimental results suggest that agent using PPS is effective for improving familiarity between agent and participants. Since agent using NPS gave impression that it was carefully supporting, it was suggested that driver feel that they convey accurate information.

The viewers of three-dimensional (3D) movies often complain of blurring and bleeding. They sometimes experience visually induced motion sickness (VIMS). In this chapter, the effect of VIMS on body sway was examined using stabilograms. We measured the sway in the center of gravity before and during the exposure to images projected on a head-mounted display (HMD). Employing Double-Wayland algorithm, we measured the degree of determinism in the dynamics of the sway in the center of gravity with respect to viewing 3D movies on HMD. As a result, the dynamics of the sway during and before the exposure was considered to be stochastic. Thus, exposure to 3D movies would not change the dynamics to a deterministic one.

In recent years, the number of traffic accidents caused by elderly drivers in Japan has increased. Cars are an important mode of transportation for the elderly. Thus, to ensure their driving safety, a system that can assist elderly drivers is required. In this study, we propose a driver agent system that provides support to elderly drivers during and after driving and encourages them to improve their driving. In this paper, we describe the proposed driver agent system. We conducted an experiment to evaluate driving behavior improvement through three types of support: driving support, review support, and a combination of both. The results revealed that the combination of both supports lead to the greatest improvements in driving behavior and was most acceptable to elderly drivers.

In recent years, the number of traffic accidents caused by elderly drivers has increased in Japan. However, a car is an important mode of transportation for the elderly. Therefore, to ensure safe driving, a system that can assist elderly drivers is required. In this study, we propose a driver-agent system that provides support to elderly drivers during and after driving and encourages them to improve their driving. This paper describes the prototype system based on the analysis of the teaching records of a human instructor, and the subjective evaluation of driving support to elderly driver from three different agent forms, a voice, visual, and robot. The result revealed the robot form is more noticeable, familiar, and acceptable to the elderly than other forms.

The technology provides an enhanced visual experience with realistic scene portrayal, but is known to cause motion sickness when stereoscopic video clips of rotating or blurred images are viewed. Viewers complain of symptoms such as eye fatigue, nausea, and dizziness. The underlying cause of these symptoms has not been identified; therefore, an investigation to determine the mechanism for the motion sickness is necessary. Compared to the baseline test, the concentration of oxygenated hemoglobin in the occipital lobe increased significantly during a viewing for both background cases. The result is consistent with both visual recognition methods. Furthermore, for both background cases, the concentration in the upper occipital lobe significantly increased during peripheral viewing versus visual pursuit. Peripheral viewing might enhance the activity in the dorsal stream, which could serve as an indication to the mechanism causing 3D sickness.