• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.180-189
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• 2017

Some people who take a driver's license test retake it again because of license cancellation, but most of them take the test for the first time to drive the car. Driving a car is directly linked to life, and the initial correct driving habits are more important than anything else. In particular, it is very important to obtain a license by evaluating the correct driving ability based on objective and fair standards when learning the first driving, because many people acquire a driving license while entering the society for the first time. In this paper, we propose the S / W design and its main functions that can emit high quality drivers through efficient, fair and accurate automated scoring. Through this, it is proposed to improve the automatic grading driver's license system, to prevent traffic accidents, and to reduce traffic accidents through proper driving.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.214-227
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• 2021

The purpose of this study is to find the driving difficulty of automated vehicles in terms of road infrastructure operation. It was judged out of this study that the level of automated driving would be enhanced if the road situation recognition ability was advanced through the presentation of infrastructure information during the difficult driving situations. The difficulty evaluation index was divided into three stages, and a survey of experts and an AHP were conducted. The result of the AHP showed that the driving difficulty of the interrupted flow was much higher than that of the uninterrupted flow. The AHP results also showed that and the driving difficulty of unsignalized intersections and roundabouts under an interrupted flow was evaluated as the highest. The top six driving situations with high difficulty were also evaluated to occur under unsignalized intersections and roundabouts.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.641-652
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• 2021

Drivers have willing to do secondary tasks in situations deemed safe autonomous driving. I studied that positive notifications for secure areas could improve situation awareness and driving performance after TOR(Take over request) in autonomous driving. Comparing TOR alert only and monitoring alert conditions, participants in the positive notification condition showed higher situation awareness and driving performance. Also, in emotional assessment, the positive notification condition showed higher positive evaluation than other conditions. Due to Covid-19, I designed experiments separate online with driving videos in experiment 1 and offline using a driving simulator in experiment 2. This study has implications that presented a different perspective on autonomous driving notification design.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.566-576
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• 2018

The C-ITS requires the lane level positioning of the vehicle in the land transportation environment, and it is most effective to utilize the GNSS. In the precision positioning system based on satellite navigation, the evaluation of dynamic environment of lane level positioning performance should be accompanied and the evaluation system configuration should be preceded. In this paper, we selected performance indicators, assessment equipment, and reliability of reference equipment for evaluation of precision positioning user systems based on the GNSS. The performance evaluation system described above is applied to a real system, and the performance evaluation tool developed for the evaluation system is described. The numerical performance evaluation was carried out based on the data collected by carrying out the actual testbed driving. The performance evaluation by the actual driving trajectory and driving image comparison was performed to derive and analyse the evaluation results of the vehicle lane level positioning user system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.183-200
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• 2022

A variety of simulation approaches based on automated driving technologies have been proposed to develop traffic operations strategies to prevent traffic crashes and alleviate congestion. The maneuver of simulated autonomous vehicles (AVs) needs to be realistic and be effectively differentiated from the behavior of manually driven vehicles (MVs). However, the verification of simulated AV maneuvers is limited due to the difficulty in collecting actual AVs trajectory and interaction data with MVs. The purpose of this study is to develop a methodology to evaluate the suitability of AV maneuvers based on both driving and traffic simulation experiments. The proposed evaluation framework includes the requirements for the behavior of individual AVs and the traffic stream performance resulting from the interactions with surrounding vehicles. A driving simulation approach is adopted to evaluate the feasibility of maneuvering of individual AVs. Meanwhile, traffic simulations are used to evaluate whether the impact of AVs on the performance of traffic stream is reasonable. The outcome of this study is expected to be used as a fundamental for the design and evaluation of transportation systems using automated driving technologies.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.12
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• pp.469-481
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• 2016

Freight car accidents occur frequently and have a high mortality. In this reason, freight can insurance fee has been raised drastically. But speeding and overloading of trucks are still not decreased. We need to consider a measure about voluntary safe driving of truck drivers. We select UBI(Usage-Based insurance) as a measure for safe driving of truck drivers. UBI is a car insurance system and insurance fee is flexible. If vehicle drivers drive safely, insurance fee is discounted. The other way, if vehicle drivers drive dangerously, insurance fee is increased. In now, very high insurance fee for truck drivers, UBI is a effective way for leading a truck driver to safe driving. The most important thing in UBI is to evaluate truck driver rationally and accurately. In this paper, we select the reasons of truck accidents and develop driving evaluation model from multiple regression analysis and correlation analysis with accident reasons and truck accidents.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.491-498
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• 1997

This paper describes the arousal measurement and control system using fuzzy logic to prevent drowsy driving. Sugeno's method was used for fuzzy inference in this study. Arousal evaluation and control criteria were modified from result of Nz-IRI analysis depending on arousal sate. Membership function and rule base of fuzzy inference were determined from the modified arousal level criteria When lRl (Inter-SIR Interval) was shorter than 60sec, outputs of both methods were changed from small to big, but output of three step warning method was same level until the next warning range. Since output of fuzzy inference tracked well the change of subject's arousal level, problems of three step warning method could be overcome by fuzzy inference method Furthermore, the output of the fuzzy inference was highly correlated with Nz(r = 0.99). Therefore, the fuzzy inference method for evaluation and the control of arousal will be more effective at real driving situation than three step warning method.

• Journal of the Ergonomics Society of Korea
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• v.29 no.6
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• pp.831-841
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• 2010

Usability evaluation of physical products involves characterizing complex physical interactions between humans and products. Human models known as manikins have been widely utilized as usability evaluation tools for automobile interior package design. When combined with computer-aided design software programs, such manikins can be used to simulate driving postures and evaluate driver-interior fits early in the design process, and therefore, may greatly facilitate achieving high-quality design in a cost-efficient manner. The purpose of this study was to define a set of manikins for designing automobile interior packages for the South Korean male population. These manikins were conceptualized as "boundary" manikins, which represent individuals lacking in certain physical capacities or having usability-related issues (e.g., an individual with the 5th percentile forward reach capability, an individual with the 95th percentile shoulder width). Such boundary manikins can serve as an efficient tool for determining if an automobile interior design accommodates the majority of the population. The boundary manikins were selected from the large sample of Korean males whose anthropometric dimensions were described in the recent Size Korea anthropometric database. For each male in the database, his comfortable driving posture was represented using a kinematic body linkage model and various physical capacity measured and usability-related characteristics relevant to driver accommodation were evaluated. For each such measure, a boundary manikin was selected among the Korean males. The manikins defined in this study are expected to serve as tools for ergonomic design of automobile interior packages. The manikin selection method developed in this study was implemented as a generic software program useful for various product design applications.

• Korean Journal of Occupational Therapy
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• v.26 no.4
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• pp.127-143
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• 2018

Objective : The purpose of this study was to compare with the effects of driving simulator and Dynavision training after stroke through the test of cognitive ability and driving performance. Methods : Twenty-one stroke patients were randomly classified to the driving simulator training group (N=11) and Dynavision training group (N=10), and were carried out respectively training for 15 times. The driving performances was measured by the driving simulator test, and cognitive-perceptive abilities was measured by the DriveABLE Cognitive Assessment Tool, Trail Making Test-A, Trail Making Test-B and Mini Mental State Examination-K. Results : The driving simulator training group showed significant changes in all cognitive tests and most of driving performances. The Dynavision training group also showed significant changes in all cognitive tests except for Trail Making Test-A and some driving performances. The significant differences on both groups were found regarding the estimated degree of results on the on-road evaluation, the number of off road accidents and collisions. In addition, the causal influence of the two training methods on these variables was analyzed to be more than 20%. Conclusion : The driving simulator and Dynavision training were found to be effective intervention in the driving rehabilitation after stroke. In particular, it was confirmed that the driving simulator is an effective training to improve overall driving ability of stroke patients. In addition, the difference in training effect between the two training methods was found to be more than 20%.

• Journal of Auto-vehicle Safety Association
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• v.10 no.2
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• pp.29-35
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• 2018

This paper presents a quantitative evaluation method and result of moving vehicle perception using automotive radar. It is also important to analyze the accuracy of the perception algorithm quantitatively as well as to accurately percept nearby moving vehicles for safe and efficient autonomous driving. In this study, accuracy of the automotive radar-based perception algorithm which is developed based on interacting multiple model (IMM) has been verified via vehicle tests on real roads. In order to obtain experimental data for quantitative evaluation, Long Range Radar (LRR) has been mounted on the front of the ego vehicle and Short Range Radar (SRR) has been mounted on the rear side of both sides. RT-range has been installed on the ego vehicle and the target vehicle to simultaneously collect reference data on the states of the two vehicles. The experimental data is acquired in various relative positions and velocity, and the accuracy of the algorithm has been analyzed according to relative position and velocity. Quantitative analysis is conducted on relative position, relative heading angle, absolute velocity, and yaw rate of each vehicle.