• Korean Journal of Optics and Photonics
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• v.24 no.5
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• pp.231-236
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• 2013

We investigated the optical design of a smart headlamp capable of producing various beam patterns through only on/off modulation of light sources. This was implemented by forming a continuous matrix of beams from discontinuous beam patterns by means of a multi-array LED optical system. As one such optical system, the multi-array LED system is a convenient and economical device for implementing beam patterns with the simple on/off modulation of the light sources. A single optical assembly module can be made by combining a multiple-LED array, optical system module, and electronic control with no need for any additional mechanical components. The present optical system was designed to include a secondary lens and a projection lens mounted at the front of each LED in the array to realize accurate lighting patterns as well as the required luminosity at a distance of 25 m in the forward direction. Finally, we identified and analyzed the patterns implemented by the designed optical system that produced satisfactory performance of high beams and adaptive driving beams (ADB).

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.67-67
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• 2017

국내의 밭작물 재배에서는 부족한 인력과 시간을 단축하기 위한 농기계 사용이 필수가 되었다. 효율적인 농기계의 개발을 위해서는 농민들의 작업실태 분석이 반드시 선행되어야 한다. 본 연구에서는 감자 재배용 작업기 개발을 위해 전국의 감자 재배 농민을 대상으로 트랙터 작업기 사용실태 조사를 수행하였다. 조사대상은 강원도, 경상북도, 전라남도의 지역중 감자 생산량이 많은 곳을 분류하여 각 지역의 농업기계 대리점에서 추천한 농민을 대상으로 조사표에 의한 방문 면접 설문조사를 실시하였다. 분류된 지역은 강원도 홍천, 평창, 경상북도 고령, 김천, 전라남도 영광, 보성이다. 각 지역별 응답자수는 2명으로 진행하였다. 조사항목은 감자 재배시기, 보유하고 있는 작업기, 트랙터의 모델 및 보유대수, 작업기별 트랙터 주행단수 및 PTO 단수, 작업패턴 등이다. 조사결과, 공통적으로 감자품종 중 수미감자를 선호하는 것으로 조사되었고, 지역별로 시기상의 차이가 있지만 평균적으로 1월~5월과 8월~11월 사이에 감자 이모작을 실시하는 것으로 나타났다. 트랙터의 평균 보유대수는 2대였으며, 평균적으로 중형 트랙터 1대와 대형 트랙터 1대의 비율로 보유하고 있는 것으로 조사되었다. 보유하고 있는 작업기는 로타베이터, 수확기, 시비기, 방제기, 파종기 순으로 보유대수가 많았다. 작업기로 수행하는 밭작업으로는 경운정지, 비닐피복, 시비, 방제, 수확 등이 있었으며, 경운정지용 로터리 작업시 트랙터 주행단수와 PTO 단수는 트랙터의 경우 L2~L3단을 주로 사용하고, PTO의 경우 1단과 2단을 병행하여 사용하는 것으로 조사되었다. 로타베이터 작업패턴은 지역별로 차이를 보였으나, 평균적으로 밭의 모서리를 둘러서 작업하고 이후에 8자형식으로 이동하면서 두둑을 형성하는 것으로 나타났다. 이 작업패턴을 사용하는 이유는 후진을 하지않는 작업환경에서 가장 효율적이고 밭의 모서리에 흙이 모이지 않게하기 위함이라고 하였다.

• The Journal of Korean Institute of Information Technology
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• v.16 no.12
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• pp.75-83
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• 2018

Recently, autonomous vehicles have been actively studied. Pedestrian detection and recognition technology is important in autonomous vehicles. Pedestrian detection using CNN(Convolutional Neural Netwrok), which is mainly used recently, generally shows good performance, but there is a performance degradation depending on the environment of the image. In this paper, we propose a pedestrian detection system applying long-term memory structure of hippocampal neural network based on CNN network with LGP-FL (Local Gradient Pattern-Feature Layer) added. First, change the input image to a size of $227{\times}227$. Then, the feature is extracted through a total of 5 layers of convolution layer. In the process, LGP-FL adds the LGP feature pattern and stores the high-frequency pattern in the long-term memory. In the detection process, it is possible to detect the pedestrian more accurately by detecting using the LGP feature pattern information robust to brightness and color change. A comparison of the existing methods and the proposed method confirmed the increase of detection rate of about 1~4%.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.51-62
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• 2008

An innovative feature of this study is to propose a methodology for evaluating safety performance in real time based on vehicle trajectory data extracted from video images. The essence of evaluating safety performance is to capture unsafe car-following and lane-changing events generated by individual vehicles traveling within video surveillance area. The proposed methodology derived three indices including real-time safety index(RSI) based on the concept of safe stopping distance, time-to-collision(TTC), and the collision energy based on the conservation of momentum. It is believed that outcomes would be greatly utilized in developing a new generation of video images processing(VIP) based traffic detection systems capable of producing safety performance measurements. Relevant technical challenges for such detection systems are also discussed.

• Journal of the Korean Society for Railway
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• v.12 no.5
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• pp.678-686
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• 2009

A trial run of locally-developed tilting train has been in process on Chungbuk line since the test vehicle was first produced. For the system stabilization, interface verification among the systems including track, structure, catenary and signaling system, not to mention the rolling stock, is very crucial. Therefore, in this study, the dynamic rail force of the tilting (Hanvit 200), high-speed (KTX) and general (Mugunghwa) vehicle caused by driving in transition curve track was measured. And, it compared the tilting response with the other by using the measured rail force data in transition curve track, and then evaluated probability the range of load fluctuation for the variable dynamic vertical and lateral wheel load. As a result, a range of rail force by occurred a change of cant from the high-speed and general vehicle which had fixed bogie structure was distributed throughout small deviation. Otherwise, in case of the tilting train which was consisted of the pendulum bogie structure was distributed wide range about large deviation by changed of cant.

• The Journal of the Acoustical Society of Korea
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• v.19 no.5
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• pp.3-8
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• 2000

In this paper, we studied design and implementation of a robust speech recognition system in noisy car environment. The reference pattern used in the system is DMS(Dynamic Multi-Section). Two separate acoustic models, which are selected automatically depending on the noisy car environment for the speech in a car moving at below 80km/h and over 80km/h are proposed. PLP(Perceptual Linear Predictive) of order 13 is used for the feature vector and OSDP (One-Stage Dynamic Programming) is used for decoding. The system also has the function of editing the phone-book for voice dialing. The system yields a recognition rate of 89.75% for male speakers in SI (speaker independent) mode in a car running on a cemented express way at over 80km/h with a vocabulary of 33 words. The system also yields a recognition rate of 92.29% for male speakers in SI mode in a car running on a paved express way at over 80km/h.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.3
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• pp.349-360
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• 2024

The purpose of this study is to analyze the performance of the road network according to the penetration rate of autonomous vehicles (AV) of Level 4 or higher and the change in traffic volume. First, prior studies related to vehicle control variables of AV were reviewed, and future traffic demand in 2040, which is predicted to have a 50 % market share of AVs, was reflected in the simulation analysis. In addition, the change in traffic flow of continuous and intermittent flows was analyzed by increasing the AV market penetration rate and traffic volume of passenger cars, trucks, and buses by 25 % step by step from 0 to 100 %. As a result of the analysis, it was confirmed that the travel time increased as the traffic increased, and the pattern of decreasing the travel time due to the increase in the share of AVs, that is, the development of technology, can also be confirmed. Furthermore, it was also confirmed that the traffic speed showed a trend of increasing as the share of AVs increased. In this study, it was confirmed that the law of diminishing marginal rate of substitution (MRS) was satisfied by calculating the MRS according to the combination of traffic volume and speed while increasing the market penetration rate of AVs. Furthermore, it was confirmed that the convexity of the indifference curve was also satisfied in both intermittent and continuous traffic flow environments.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.25-31
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• 2013

The AVC System which has operated in Highways has two-piezo sensors. In this system the piezo sensors are installed on parally each other this configuration has a defect about diversion driving and sensor damage. In this reserch, 3-Sensor AVC algorithm has been proposed which is supported enhance accuracy of the vehicle classification rate compare with usual 2-Sensor systems. This algorithm is allowed to calculate wheel tread, wheel width. The third inclinded piezo sensor can detec twheel tread, wheel width using signal processing. 3-Sensor AVC has been installed in real highway and the outcome performance has been proof.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.236-241
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• 2015

This paper presents a study on transformable multiple quadruped robots by docking between robots and waist joints. This robot is able to go on a variety of angles because of mecanum wheels. It is also a hybrid design which allows robot use legs to overcome obstacles on complex terrains and wheels to move on flat ground. The robot is applied kinematics of mecanum wheels and walking, and its walking is based on specific patterns. Docking module is located in front and backside of robot, docking algorithm is suggested and fulfilled for docking between 2 robots. A waist joint is at the center of robot body for transformation and after docking and transformation, robot can activate new functions that carry something.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.505-510
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• 2000

Vehicle performances such as fuel consumption and catalyst-out emissions are affected by a driving pattern, which is defined as a driving cycle with the grade in this study. We developed an algorithm to recognize a current driving pattern by using a neural network. And this algorithm can be used in adapting the driving control strategy to the recognized driving pattern. First, we classified the general driving patterns into 6 representative driving patterns, which are composed of 3 urban driving patterns, 2 suburban driving patterns and 1 expressway driving pattern. A total of 24 parameters such as average cycle velocity, positive acceleration kinetic energy, relative duration spent at stop, average acceleration and average grade are chosen to characterize the driving patterns. Second, we used a neural network (especially the Hamming network) to decide which representative driving pattern is closest to the current driving pattern by comparing the inner products between them. And before calculating inner product, each element of the current and representative driving patterns is transformed into 1 and -1 array as to 4 levels. In the end, we simulated the driving pattern recognition algorithm in a temporary pattern composed of 6 representative driving patterns and, verified the reliable recognition performance.