• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.115-121
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• 2012

In spite of serious injuries caused by traffic accidents of car-pedestrian, the dispute is constantly occurring and economic losses and mental suffering is escalating since the cause of accidents is not scientifically identified. This study reviewed vehicle dynamics, driving dynamics, collision dynamics, traffic and road engineering for traffic accidents analysis based on traffic accidents related physically objective evidence and analysed the cause of accidents by getting results which applied vehicle initial collision velocity before collision, processing trajectory, collision stance, vehicle velocity before & after collision and parameter by using PC-Crash program. I found that skid mark and collision velocity of car-pedestrian had the error of 11.2%, 2,27% compared to theoretical values.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.295-302
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• 2004

On the field of speech processing the treatment of noise is still important problems for speech research. Especially, it has been noticed that the background noise causes remarkable reduction of speech recognition ratio. As the examples of the background noise, there are such various non-stationary noises existing in the real environment as driving noise of automobiles on the road or typing noise of printer. The treatment for these kinds of noises is not so simple as could be eliminated by the former Wiener filter, but needs more skillful techniques. In this paper as one of these trials, we show an algorithm which is a speech enhancement method using a model of mutual inhibition for noise reduction in speech which is contaminated by white noise or background noise mentioned above. It is confirmed that the proposed algorithm is effective for the speech degraded not only by white noise but also by colored noise, judging from the spectral distortion measurement.

• 전자공학회논문지 IE
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• v.46 no.1
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• pp.31-36
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• 2009

This study was to simulate it that the sending receiving vehicles run on the general national roads with the one-way two-lanes at 80[km/h] speed. This study was to select 280[m] radius of curvature based on the statistical data with high rate of traffic accidents, 140[m] length of direct roads considering the stopping stadia, 90[m] length of curve, and 8 points of curved roads at 11.25[m] intervals. As a result above, when the distance between the sending and receiving vehicles became more than 111[m], the propagation path of reflected wave by the adjacent vehicles became longer than the propagation path of reflected wave by the left/right reflectors because the number of repeated reflection increased. In this study, the repeated reflection for the propagation's reach to the receiving vehicles was about $1{\sim}2$[times] as it supposed it less than 111[m]. Accordingly, it found out that the propagation path of reflected wave received through the left/right reflectors was about $1{\sim}1.5[m]$ larger than the reflected wave produced by the adjacent vehicles regardless of lanes on which the sending and receiving vehicles were located.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.2
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• pp.183-189
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• 2010

A localization system for indoor robots is an important technology for robot navigation in a building. Our localization system imports the GPS system and consists of more than 3 satellite beacons and a receiver. Each beacon emits both an ultrasonic wave and radio frequency. The receiver in the robot computes the distance from it to the beacon by measuring the flying time difference between ultrasonic wave and radio frequency. It then computes its position with the distance information from more than 3 beacons whose positions are known. However, the distance information includes errors caused from the ultrasonic sensors; we found it to be limited to within one period of a wave (${\pm}2\;cm$ tolerance). This paper presents a method for predicting the maximum position error due to distance information errors by using Taylor expansion and singular value decomposition (SVD). The paper also proposes a measuring parameter such as sensitivity to represent the accuracy of the indoor robot localization system in determining the robot's position with regards to the distance error.

• Transactions of the KSME C: Technology and Education
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• v.2 no.1
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• pp.9-13
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• 2014

Nowadays, among several reasons for customers to choose their own cars, NVH performance plays much important role. The concern for the car interior noise is increasing recently, because electric cars and hybrid cars generate less engine noise which was the main noise of traditional cars. According to oversea references, high Lateral Dynamic Stiffness (LDS) of vehicle wheels is described to reduce Structure Bone Noise (SBN) which is being generated while driving cars. However availablet test standards and test results are not enough, in this study the interior noise has been measured after attaching a same tyre to several wheels which has different Lateral Dynamic Stiffness. The test has verified that the interior noise differs depending on Lateral Dynamic Stiffness of wheels. As to this, the reduction of the interior noise can be possible with the optimal design of the wheel.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.7 s.112
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• pp.704-711
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• 2006

Vibration test on MAST(multi axial simulation table) system has several advantage over one-axial vibration test that could simulate 6-DOF, 3-axial translation and 3-axial moment, at the same time. Since field vibration motion can be fully represented with 6-DOF, multi-axial vibration test on vehicle component is widely conducted in technical leading companies to make sure its fatigue performance in vibration environment. On the way to fulfill the process, editing technique of obtained field data is key issue to success a reliable vibration testing with MAST system. Since the original signals are not only too large to fulfill it directly, but all of the measured data is not guarantee its convergency on generating its driving files, editing technique of the original signals are highly required to make some events that should meet the equal fatigue damage on the target component In this paper, key technique on editing a field data feasible for MAST system is described based on energy method in vibration fatigue. To explain its technique explicitly, author first introduced a process on field data acquisition of two vehicle component and then, representing events are produced to keep up with the editing strategy about a energy method. In the final chapter, a time information regarding a vibration test on MAST system is derived from the energy data which is critical information to perform a vibration test.

• The Journal of the Acoustical Society of Korea
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• v.37 no.4
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• pp.256-261
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• 2018

There are three types of noise generated inside the vehicle: BSR (Buzz, Squeak, Rattle). In this paper, we propose a classifier that automatically classifies automotive BSR noise by using features extracted from deep convolutional neural networks. In the preprocessing process, the features of above three noises are represented as noise-map using STFT (Short-time Fourier Transform) algorithm. In order to cope with the problem that the position of the actual noise is unknown in the part of the generated noise map, the noise map is divided using the sliding window method. In this paper, internal parameter of the deep convolutional neural networks is visualized using the t-SNE (t-Stochastic Neighbor Embedding) algorithm, and the misclassified data is analyzed in a qualitative way. In order to analyze the classified data, the similarity of the noise type was quantified by SSIM (Structural Similarity Index) value, and it was found that the retractor tremble sound is most similar to the normal travel sound. The classifier of the proposed method compared with other classifiers of machine learning method recorded the highest classification accuracy (99.15 %).

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.1
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• pp.26-33
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• 2009

The directions of the road are divided into two, the right-hand side and left-hand side of the road, by the convention and specific native method in the world. This paper deals with the characteristics and behaviors of drivers who are accustomed to driving on right-hand side of the road, drive with a handle on the left-hand side, and comparing with left-hand side drivers. The driver's eye movements were measured by eye camera and questionnaires were used for measuring subjective evaluation such as driving mental workload. The experimental results indicated even if the experts who had much experience on right-hand side driving, they had lower driving skill than novice driver, accustomed to driving on left-hand side. In terms of mental workload, MCH rating scale and MNASA-TLX, the right-hand side drivers were in lower stress condition than the left-hand side drivers because of having much driving experience. However, they conducted a few mistakes by confusing the position of turn signal and windshield wiper because of their driving habit or traits and it lead to operation mistakes. These results can be applied effectively to develop the driving support information with changed environments.

• Journal of Korean Society of Transportation
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• v.18 no.6
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• pp.47-61
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• 2000

차량추종모형은 차선변경모형과 함께 미시적 시뮬레이션 모형의 핵심 모형으로서 정확한 차량추종모형의 적용은 시뮬레이션 모형 분석결과의 신뢰성에 영향을 미친다. 기존의 차량추종모형은 대부분 가속상황과 감속상황에 동일한 모형을 적용하거나 자극부문과 민감도 부분은 거의 동일한 형태를 취하고 있으며, 가상자료를 토대로 모형이 개발되었다. 본 연구의 목적은 첫째, 모형을 추정하기 위한 연구체계를 구성하고, 둘째, 이러한 연구체계를 이용하여 신호교차로 미시적 시뮬레이션에 직접 적용이 가능한 차량추종모형을 정립하는 데 있다. 본연구에서는 이를 위해서 신호교차로에서 미시적 실측자료를 수집하였으며, 수집된 자료에서 통계적 기법을 통해서 모형 추정에 적합한 자료를 구축하였다. 현장에서 실측된 이산적인 원시자료는 차량추종모형 추정에 직접 이용할 수 없다. 따라서, 이산적 원시자료를 모형추정에 적합한 자료로 구성하기 위하여 비선형 곡선적합 알고리즘을 이용하여 연속적인 궤적함수를 구성하였고, 이를 통해서 모형추정에 필요한 선두차량과 후행차량의 현재시점과 반응시간 이후 시점에서의 위치, 순간 가속도와 순간속도 등을 도출하였다. 본 연구에서는 차량추종상황을 가속상황, 감속상황, 출발상황, 그리고 정지상황으로 구분하여 차량추종모형을 구축하였다. 가속상황과 감속상황에 대해서는 실측자료를 이용하여 모형을 추정하였으며, 출발상황과 정지상황에 대해서는 추정된 가/감속상황의 모형을 바탕으로 출발상황과 정지상황에서의 차량행태를 설명할 수 있는 모형을 구축하였다 또한, 민감도와 자극부분을 새롭게 정의하여 각 상황별로 미시적 실측자료를 이용하여 모형을 추정하였다. 이렇게 추정된 모형들 중에서 통계적 기법과 실측치와의 비교를 통해서 가장 적합한 모형을 선택하였다. 선택된 모형은 통계적 검정, 가상자료 그리고 실측치와의 비교를 통해서 분석하였으며, 분석결과 구축모형의 적용성은 우수한 것으로 분석되었다.

• Journal of Korean Society of Transportation
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• v.30 no.5
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• pp.83-90
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• 2012

Driver ordinarily takes sudden braking when urgent situation is developed or when the vehicle is involved in an unexpected accident. Therefore, the most common trace at a traffic accident scene is skid mark. Currently, in investigating traffic accident, overspeed is determined by the length of skid mark. However, in order to identify accurate cause of accident, estimation of pre-braking speed which takes into account speed reduction during transient time should be considered as a requirement. In a recent study, several ways to estimate pre-braking speed were suggested, but none considered to differentiate the decelerating transient brake section and skidding section. This study analyzed trends of decelerating transient brake section and skidding section by real braking test.