• ETRI Journal
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• v.37 no.3
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• pp.626-636
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• 2015

This paper proposes an adaptive multimodal in-vehicle information system for safe driving. The proposed system filters input information based on both the priority assigned to the information and the given driving situation, to effectively manage input information and intelligently provide information to the driver. It then interacts with the driver using an adaptive multimodal interface by considering both the driving workload and the driver's cognitive reaction to the information it provides. It is shown experimentally that the proposed system can promote driver safety and enhance a driver's understanding of the information it provides by filtering the input information. In addition, the system can reduce a driver's workload by selecting an appropriate modality and corresponding level with which to communicate. An analysis of subjective questionnaires regarding the proposed system reveals that more than 85% of the respondents are satisfied with it. The proposed system is expected to provide prioritized information through an easily understood modality.

• Journal of Auto-vehicle Safety Association
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• v.16 no.2
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• pp.14-19
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• 2024

This paper describes autonomous emergency braking systems (AEB) for elderly drivers designed to consider their driving characteristics. With aging, perception-reaction time, and decision-making time increase accordingly. Without being aware of these performance degradations, however, changes in driving patterns due to increased alertness while driving lead to vehicle crashes. Therefore, it is necessary to develop an autonomous emergency braking system by incorporating the characteristics of the elderly driver. In order to enhance the driver acceptance of older people, perception-reaction time, alertness, and ride comfort need to be considered for conventional autonomous emergency braking systems (C-AEB). Proactive AEB(P-AEB) algorithm has been proposed to reflect human factor of elderly driver above. The performance of the proposed algorithm has been evaluated through MATLAB simulink simulation studies. It has been shown from the computer simulations that the proposed P-AEB algorithm enhances the driver acceptance of older people by improving ride comfort while ensuring safety of vehicle.

• Journal of the Korean Society of Safety
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• v.34 no.1
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• pp.70-75
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• 2019

The aging of society is not only Korea's challenge but also a global issue. This leads to an increase in the number of elderly drivers who are much more prone to major traffic accidents. Therefore, we need a system to test aged drivers' driving abilities. As part of efforts to establish such a system, researchers of KoROAD. have conducted a study on the correlation between aging and driving abilities by analyzing old drivers' reaction time. The study shows that there was a sharp increase in reaction time for drivers aged 65 and over. The current reaction time of 2.5 secs for the 85 percent of eligible drivers needs to be revised upward in aging societies. From now on, we need to come up with the traffic safety measures that can deal with the issue of drivers of old age.

• Journal of the Korean Society of Safety
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• v.21 no.5 s.77
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• pp.103-111
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• 2006

The purpose of this study was to analyse the relationships between cognitive abilities and driving characteristics of elderly drivers. Driving characteristics of elderly and younger drivers who were driving a fixed base driving simulator vehicle were examined. Participants consisted of 12 drivers over age 65 (the 'older' group) and 12 drivers between the ages of 25 and 55 (the "younger" group). As indices of cognitive ability, critical flicker fusion frequency (CFF) tests and cognitive reaction tests were given before the driving task. CFF was also tested after the simulated driving task for both groups. Cognitive reaction tests, which were composed of speed estimation tests, multiple choice reaction tests and obstacle avoidance tests, were developed by the Korean Road Traffic Safety Authority in 2003. CFF values between the two groups exhibited significant differences both before and after the task, with a p-value less than 0.01 and a t-value of -3.01 before the test and a p-value less than 0.031 and a t-value of -2.35 after the test. Older drivers' CFF values were lower than those of the younger. However, there was no difference in older or younger driver CFF values before and after the task within the same group. Except for the multiple choice reaction test, there was no difference in cognitive reaction test results between the two groups. The elderly drivers made more errors though they did not differ from the younger drivers in reaction times. At the simulated driving task the reaction time of the elderly driver was longer than that of the younger; however, the driving speed of the elderly was lower and the number of collisions greater. There was a positive correlation (r=.496) between the number of errors in the multiple choice reaction test and the number of collisions in the driving task. Therefore, it was identified that critical attributes contributing to automobile crashes involving elderly drivers included cognitive difficulty in judging and responding to complex situations.

• Journal of the Ergonomics Society of Korea
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• v.31 no.5
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• pp.657-670
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• 2012

Background: Today, numerous telematics technologies, i.e., technologies developed by integrating telecommunications with information processing, are applied in vehicles. One such developmental application of this technology to vehicles is to increase the safety or convenience of drivers by providing them with necessary information such as warnings and information on emergencies and traffic situations. However, under certain conditions, there is a high probability of traffic accidents if the driving workload is high. Nowadays, the navigation system is frequently used in the vehicles, this system provides various information including route to the driver. But, the existing navigation systems are not only considered a driver's reaction but also provide unilaterally to the information regardless of them. Such one-side information service type may miss important information to the driver. In addition, it sometimes interferes safety driving. Objective: To solve this problem, the intelligent navigation system needs to the providing way that it checks the driver's reactions after providing information. Namely, if the driver passes the information received from the navigation, then the intelligent system provides more loudly and more frequently. Method: Therefore, in this study we introduce the intelligent navigation system that it automatically controls modality type and its strength when the driver misses or overlooks the information for their safety and entertainment and we analyze the driver's cognitive responses about the modality type and its strength. Results: To evaluate the effectiveness of the proposed system, we analyzed the reaction time and driving workload for each type of the information, modality and its strength. Also we evaluated the users' subjective satisfaction and understanding based on a questionnaire.

• Science of Emotion and Sensibility
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• v.20 no.1
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• pp.115-132
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• 2017

Differences in reaction time and accuracy were compared among driver groups of middle-, old-, and stroke old-age drivers using various reaction time tasks including simple reaction task, 2-choice task, 4-choice task with different stimuli eccentricity, search task, and moving target detection task. The results can be summarized as followings. First, although overall reaction time tended to be slowed with age and stroke, stroke old drivers showed significantly slower reaction time than the other driver groups when the stimuli were presented in a large eccentricity. Second, differences in reaction time for 2-choice task and moving target detection task seemed to be determined mainly by participants' simple reaction time. Third, the search task which required temporary retention of previously presented stimuli was found to be more sensitive in discriminating difference in reaction time between middle-age drivers and old-age drivers (including stroke old drivers). Fourth, reaction accuracy of old (and stroke old) drivers decreased when more stimuli alternatives were presented and temporary retention for stimuli was required. Altogether, memory demand in reaction time task can be sensitive to evaluate performance for different age groups, whereas size of useful field of view for brain stroke.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.2
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• pp.134-139
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• 2021

Currently, the autonomous vehicle market is commercializing a level 3 autonomous vehicle, but it still requires the attention of the driver. After the level 3 autonomous driving, the most notable aspect of level 4 autonomous vehicles is vehicle stability. This is because, unlike Level 3, autonomous vehicles after level 4 must perform autonomous driving, including the driver's carelessness. Therefore, in this paper, we propose the Emergency-notification and Driver-response Confirmation System(EDCS) for an autonomousvehicle safety that notifies the driver of an emergency situation and recognizes the driver's reaction in a situation where the driver is careless. The EDCS uses the emergency situation delivery module to make the emergency situation to text and transmits it to the driver by voice, and the driver response confirmation module recognizes the driver's reaction to the emergency situation and gives the driver permission Decide whether to pass. As a result of the experiment, the HMM of the emergency delivery module learned speech at 25% faster than RNN and 42.86% faster than LSTM. The Tacotron2 of the driver's response confirmation module converted text to speech about 20ms faster than deep voice and 50ms faster than deep mind. Therefore, the emergency notification and driver response confirmation system can efficiently learn the neural network model and check the driver's response in real time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.145-152
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• 1998

Driving performance is characterized by many things such as driver's experience period, age, ability of information processing and reaction time of control devices and so forth. However, each factor of driving performance is needed to help and screen a poor driver for safe driving. In this paper, driving performance was estimated by reaction of manipulating brake, accelerator, steering wheel and speed. Subjects were grouped by experience of accident and age. Combinations of every group were analysed. For all the dependent variables, only steering wheel and speed were shown to have significant difference, which could be regarded as visual information of speed and direction were the important factors to drive safely. Especially for tile elderly, it is needed to enhance their ability of visual information processing that is to be decreased with aging. Therefore driving simulator to train and screen the poor driver should be studied.

• Korean Journal of Applied Biomechanics
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• v.15 no.2
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• pp.103-111
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• 2005

The purpose of this study was to analysis golf swing in accordance with each club using ground reaction force data. The subject of this study was current professional golf players in Korea. Golf clubs used for this study were driver, iron4, iron7, and pitching. The ground reaction force for left and right foot was collected by one Kistler and one Bertec force platforms. Also collected visual data by NC high speed camera to check the phase which was composed of address, top of backswing, impact and finish. Sampling rate was 600Hz both ground reaction forces data and visual data. The conclusion are as follows. 1. An aspect of change for ground reaction force was that the weight between the left foot and right foot were contrary to each other in general as the phase. 2. Without regard to the type of golf club, the ratio of necessary ground reaction forces for each phase in accordance with address, top of backswing, impact, and finish was comparatively identical. 3. According to the type of golf club, the tendency of Fy was not varied. In terms of Driver, at the moment of impact, the weight of foot-both right and left-was moved to the movement direction of golf because of the rotation force from swing.

• Journal of the Ergonomics Society of Korea
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• v.31 no.2
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• pp.371-377
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• 2012

Objective: The aim of this study is to investigate effect of driver's cognitive distraction on driver's physiological state and driving performance, and then to determine parameters appropriate for detecting the cognitive distraction. Background: Driver distraction is a major cause of traffic accidents and poses a serious threat to traffic safety due to ever increasing use of in-vehicle information systems and mobile phones during driving. Cognitive distraction, among four different types of distractions, prevents a driver from processing traffic information correctly and adapting to change in surround vehicle behavior in time. However, the cognitive distraction is more difficult to detect because it normally does not involve significant change in driver behavior. Method: A full-scale driving simulator was used to create virtual driving environment and situations. Participants in the experiment drove the driving simulator in three different conditions: attentive driving with no secondary task, driving and conducting secondary task of adding numbers, and driving and conducting secondary task of conversing with an experimenter. Parameters related with driver's physiological state and driving performance were measured and analyzed for their change. Results: The experiment results show that driver's cognitive distraction, induced by secondary task of addition and conversation during driving, increased driver's cognitive workload, and indeed brought change in driver's physiological state and degraded driving performance. Conclusion: The galvanic skin response, pupil size, steering reversal rate, and driver reaction time are shown to be statistically significant for detecting cognitive distraction. The appropriate combination of these parameters will be used to detect the cognitive distraction and estimate risk of traffic accidents in real-time for a driver distraction warning system.