• Journal of Korean Society of Transportation
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• v.25 no.4
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• pp.79-87
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• 2007

The interchanges of urban freeways have many problems with traffic operation due to high off-ramp flows and frequent congestion at adjacent intersections. The flow exiting from off-ramps is affected by the operational status and traffic volume conditions of the nearest signalized intersection. As a result, off-ramp flow cannot exit and the queue backs up the freeway mainline when queues from the signalized intersection form up to the junction of the off-ramp and street. The spacing between an off-ramp and an adjacent intersection is likely to determine the traffic conditions at the adjacent intersection. However, the current design guidelines do not consider such a factor. This study is to develop a model calculating the spacing between off-ramps and adjacent intersections considering the signal, traffic, and road conditions. The variables affecting the model in this study are effective green time (g/C), volume-capacity ratio (v/c), the number of lanes, and off-ramp volume. Various scenarios are designed to represent the effects of the variables and the road networks are constructed using VISSIM, which is a common traffic micro-simulation software package. The queue length is derived from VISSIM and this length is considered as the recommended spacing between the off-ramp and the adjacent intersection. Through the simulation analysis, regression models are developed to calculate the queue length reflecting the various conditions such as signals, traffic, and road configurations. The developed model can be used to create road design guidelines to determine the location of off-ramps in the planning stage.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2003.11a
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• pp.243-244
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• 2003

오존은 매우 불안정한 물질로서, 기타의 환경 대기 가스 분석법에서와 같이 해당 성분의 측정기를 표준 가스로 교정한 후 분석할 수 없다. 이러한 이유로, 환경 대기 중의 오존을 분석하는 일반 분석기의 교정을 목적으로, 본 연구실에서는, 국가 일차 오존 표준분광기(O$_3$-SRP)를 제작하여 운영하고 있다. 운영되고 있는 $O_3$-SRP의 측정 원리는 자외선 흡광 광도법이며, 농도값의 결정은 순수하게 Beer-Lambert 법칙에 따른다. Beer-Lambert 법칙에 따라서 오존 농도를 절대적으로 측정하기 위해서는 몰 흡광계수, 광로의 길이, 투과도, 온도 및 압력을 정확히 측정하여야 한다. (중략)

• 한국ITS학회:학술대회논문집
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• 2002.11a
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• pp.210-213
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• 2002

차량 대기열 측정에 관한 연구는 효과적인 교통 통제를 위해서 필수적인 요소이다. 이를 위해 본 논문에서는 영역기반 영상처리를 이용한 차량 대기열 분석에 관한 방법을 제안한다. 도로 영상에서 영역을 설정하고 각 영역에서의 차량 검출방법을 통하여 차량 대기열의 길이를 계산하였다. 이때 차량의 검출은 영역 처리를 이용하였고 대기열 측정은 검출된 차량의 최종단 위치를 파악하여 계산하였다. 이러한 방법은 차량 통행량 분석에 이용하여 능동적 교통 신호 체계에 응용될 수 있다.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.107-116
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• 2005

The information on travel time in providing the information of traffic to drivers is one of the most important data to control a traffic congestion efficiently. Especially, this information is the major element of route choice of drivers, and based on the premise that it has the high degree of confidence in real situation. This study developed a vehicle arrival time prediction algorithm called as "VAT-DV" for 6 corridors in total 6.1Km of "Nam-san area trffic information system" in order to give an information of congestion to drivers using VMS, ARS, and WEB. The spatial scope of this study is 2.5km~3km sections of each corridor, but there are various situations of traffic flow in a short period because they have signalized intersections in a departure point and an arrival point of each corridor, so they have almost characteristics of interrupted and uninterrupted traffic flow. The algorithm uses the information on a demand volume and a queue length. The demand volume is estimated from density of each points based on the Greenburg model, and the queue length is from the density and speed of each point. In order to settle the variation of the unit time, the result of this algorithm is strategically regulated by importing the AVI(Automatic Vehicle Identification), one of the number plate matching methods. In this study, the AVI travel time information is composed by Hybrid Model in order to use it as the basic parameter to make one travel time in a day using ILD to classify the characteristics of the traffic flow along the queue length. According to the result of this study, in congestion situation, this algorithm has about more than 84% degree of accuracy. Specially, the result of providing the information of "Nam-san area traffic information system" shows that 72.6% of drivers are available.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.240.1-240.1
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• 2014

대기압 플라즈마 제트 장치에 주입되는 기체의 유량 변화에 따른 방전 특성을 유체역학적으로 해석하였다. 장치에 주입되는 기체의 유량 변화는 레이놀즈수에 의한 유체 흐름의 상태 변화와 베르누이 정리에 의한 압력 변화를 동반한다. 유리관에 주입되는 기체의 레이놀즈수가 Re<2000이면 층류이며 Re>4000이면 난류, 2000

• Journal of Korean Society of Transportation
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• v.23 no.8 s.86
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• pp.181-191
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• 2005

This study developed an algorithm for real-time signal control based on the detection system that can collect sectional travel time. The signal control variable is maximum queue length per cycle and this variable has a sectional meaning. When a individual vehicle pass through the detector, we can gather the vehicle ID and the detected time. Therefor we can compute the travel time of an individual vehicle between consecutive detectors. This travel time informations were bisected including the delay and not. We can compute queue withdrawing time using this bisection and the max queue length is computed using the deterministic delay model. The objective function of the real-time signal control aims equalization of queue length for all direction. The distribution of the cycle is made by queue length ratios.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.54-62
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• 2018

As a part of realization of artificial intelligence signal(AI Signal), this study proposed an actuated signal algorithm based on vehicle queue length that estimates in real time by deep learning. In order to implement the algorithm, we built an API(COM Interface) to control the micro traffic simulator Vissim in the tensorflow that implements the deep learning model. In Vissim, when the link travel time and the traffic volume collected by signal cycle are transferred to the tensorflow, the vehicle queue length is estimated by the deep learning model. The signal time is calculated based on the vehicle queue length, and the simulation is performed by adjusting the signaling inside Vissim. The algorithm developed in this study is analyzed that the vehicle delay is reduced by about 5% compared to the current TOD mode. It is applied to only one intersection in the network and its effect is limited. Future study is proposed to expand the space such as corridor control or network control using this algorithm.

• 한국ITS학회:학술대회논문집
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• 2003.11a
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• pp.122-126
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• 2003

• 한국ITS학회:학술대회논문집
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• 2003.11a
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• pp.110-115
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• 2003

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.179-187
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• 2009

Currently, the signalized intersections in Korea are operated without providing an emergency vehicle preemption control strategy. Thus, it might threaten the safety of the pedestrians and drivers on highways when an emergency vehicle faces congested traffic conditions. The existing preemption control is activated when an emergency vehicle is detected along a path. This enables emergency vehicles to progress uninterrupted, but it also increases the delay of other vehicles. In this paper, a revised preemption control strategy considering queue length restrictions is proposed to make both a progressive movement of an emergency vehicle and reduce delay of other vehicles simultaneously. By applying the preemption control strategy through a simulation study, it was shown that delay of an emergency vehicle decreased to 44.3%-96.1% and speed increased to 8.8%-42.0% in all 9 cases as compared with a conventional signal control. The existing preemption control is superior for oversaturated conditions (v/c >1.0) or a link length less than 200m. However, the preemption control considering queue length constraints shows better performance than the existing preemption control when the v/c is less than 0.8 and a link length is longer than 500m.