• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.52-59
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• 2016

COSMOS system which was developed in Seoul for real-time signal control was designed to judge traffic condition for practicing signal operation. However, it occurs efficiency problem that stop line detection and queue length detection could not judge overflow saturation of street. For that reason, following research process GPS data of Seoul city's corporationowned taxi to calculate travel speed that excluded existing system of stop line detection and queue length detection. Also, "Research of calculating queue length by GPS data" which was progressed with following research expressed queue length. It is based on establishing algorithm of judging congestion situation. The algorithm was applied to a few areas where appeared congestion situation consistently to confirm real time traffic condition with established network. [Entrance of the National Sport Institute ${\rightarrow}$ Gangnam station Intersection, Yuksam station intersection ${\rightarrow}$ National Sport Institute.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.145-152
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• 2002

Real-time queueing information and/or predictive queue built-up information can be a good criterion in selecting travel options, such as routes, both for users, and for operators in operating transportation system. Provided properly, it will be a key information for reducing traffic congestion. Also, it helps drivers be able to select optimal roues and operators be able to manage the system effectively as a whole. To produce the predictive queue information, this paper proposes a predictive model for estimating and predicting queue lengths, mainly based on Kalman Filter. It has a structure of having state space model for predicting queue length which is set as observational variable. It has been applied for the Namsan first tunnel and the application results indicate that the model is quite reasonable in its efficacy and can be applicable for various ATIS system architecture. Some limitations and future research agenda have also been discussed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.3
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• pp.59-72
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• 2017

As the part of study which handles the measure to use the individual vehicle information of taxi GPS data on signal controls in order to overcome the limitation of Loop detector-based collecting methods of real-time signal control system, this paper conducted series of evaluations and improvements on link travel time, queue vehicle time estimates and traffic condition decision algorithm from the research introduced in 2016. considering the control group and the other, the link travel time has enhanced the travel time and the length of queue vehicle has enhanced the estimated model taking account of the traffic situation. It is analyzed that the accuracy of the average link travel time and the length of queue vehicle are respectably both approximately 95 % and 85%. The traffic condition decision algorithm reflected the improved travel speed and vehicle length. Smoothing was performed to determine the trend of the traffic situation and reduce the fluctuation of the data, and the algorithms have refined so as to reflect the pass period on overflow judgment criterion.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.1
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• pp.1-14
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• 2014

The expansion of the physical road in response to changes in social conditions and policy of the country has reached the limit. In order to alleviate congestion on the existing road to reconsider the effectiveness of this method should be asking. Currently, how to collect traffic information for management of the intersection is limited to point detection systems. Intelligent Transport Systems (ITS) was the traffic information collection system of point detection method such as through video and loop detector in the past. However, intelligent transportation systems of the next generation(C-ITS) has evolved rapidly in real time interval detection system of collecting various systems between the pedestrian, road, and car. Therefore, this study is designed to evaluate the development of an algorithm for queue length based real-time traffic signal control methodology. Four coordinates estimate on time-space diagram using the travel time each individual vehicle collected via the interval detector. Using the coordinate value estimated during the cycle for estimating the velocity of the shock wave the queue is created. Using the queue length is estimated, and determine the signal timing the total queue length is minimized at intersection. Therefore, in this study, it was confirmed that the calculation of the signal timing of the intersection queue is minimized.

• Journal of Korean Society of Transportation
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• v.12 no.2
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• pp.5-30
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• 1994

다이아몬드형 인터체인지는 고속도로와 노면가로가 교차할 경우 방향별 교통류를 처리하는데 보편적으로 사용하는 인터체인지이다. 인터체인지에 교통량의 부하가 과도해지 면 인터체인지내부의 교차로에서 발생한 대기차량이 종종 고속도로본선으로 역류하여 본선 의 교통소통에 문제를 야기하며 특히 고속도로의 안전에도 큰 위험요소가 된다. 본 논문은 과포화상태의 다이아몬드형 인터체인지의 교통신호제어를 다루며, 신호시간계획을 산출하는 동적 최적화모형(dynamic optimization model)을 제시한다. 최적화 모형은 지체도최소화를 목적함수로 하며, 함수계측법의 형태가 된다. 본 모형의 핵심은 신호제어에 따라 발생하는 대기차량길이를 모형화하여 대기차량길이가 정해진 상한치를 초과하지 않도록 하는 신호시 간계획을 산출하는데 있다. 제시된 동적모형은 다이아몬드형 인터체인지의 신호시간을 위하 여 널리 사용되는 PASSER III와 최적해를 상호 비교한다. TRAF-NETSIM을 통한 시뮬레이 션의 결과에 따르면 동적 모형이 우수한 결과를 보이며, 대기차량의 길이를 효과적으로 제 어하는 것으로 판명된다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5D
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• pp.663-669
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• 2011

In this study, the optimal length of left-turn lane in permissive left-turn signal system at the signalized intersection which has a left-turn bay is estimated. It is a simulation analysis using the queueing theory that estimate the length of left-turn lane. Traffic density conform to the standards of operating a permissive left-turn system of the Practical Manual Traffic Safety Facilities. And each of a left-turn arrival rate, a left-turn service rate, left-turn average queueing time, for green time average queueing vehicle, for red time average queueing vehicle and average queueing vehicle cycle is calculated. As a result of this study, we would learn how much the space should be secured at the signalized intersection which has a left-turn bay. The methodology using the queueing theory to work out the optimal length of waiting lane in the permissive left-turn signal system was presented.

• 재활복지
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• v.20 no.1
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• pp.171-188
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• 2016

The purpose of this study is to investigate effects of three conditions-words frequency, word length, and animacy-on the performance of naming in nonfluent aphasic patients. 15 nonfluent aphasic patients and 15 normal adults were participated in this study. The words consist only of concrete nouns and confrontational naming test was used. The test consisted of 40 questions and the condition of word were frequency(low-frequency/high-frequency), length(1 syllable/3 syllables) and animacy(animate/inanimate). The result of the study was as follows. First, naming was performed better with high-frequency words than with low-frequency words in both groups. Second, naming was performed better with 1 syllable words than with 3 syllable words in both groups. Third, naming performance depending on animacy did not show significant differences in both groups. These results indicate that compared to animacy of word, word frequency and length have bigger influence on the naming, and the difference by word frequency was more pronounced for nonfluent aphasic patients than for normal adults. The results of this study suggest that target word for the assessment and intervention of nonfluent aphasic patients, words frequency should be considered first in clinical setting.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.2
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• pp.34-44
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• 2007

Many urban cities deployed ITS technologies to improve the efficiency of traffic operation and management including a real-time franc control system (i.e., COSMOS). The system adopted loop detector system to collect traffic information such as volume, occupancy time, degree of saturation, and queue length. This paper investigated the applicability of detector information within COSMOS to represent the congestion level of the links. Initially, link travel times obtained from the field study were related with each of detector information. Results showed that queue length was highly correlated with link travel time, and direct link travel time estimation using the spot speed data produced high estimation error rates. From this analysis, a procedure was proposed to estimate congestion level of the links using both degree of saturation and queue length information.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.39-57
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• 2018

The purpose of this study was to construct an artificial intelligence model that learns and estimates the relationship between vehicle queue length and link travel time in urban areas. The vehicle queue length estimation model is modeled by three models. First of all, classify whether vehicle queue is a link overflow and estimate the vehicle queue length in the link overflow and non-overflow situations. Deep learning model is implemented as Tensorflow. All models are based DNN structure, and network structure which shows minimum error after learning and testing is selected by diversifying hidden layer and node number. The accuracy of the vehicle queue link overflow classification model was 98%, and the error of the vehicle queue estimation model in case of non-overflow and overflow situation was less than 15% and less than 5%, respectively. The average error per link was about 12%. Compared with the detecting data-based method, the error was reduced by about 39%.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.81-98
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• 2002

This paper documents the development of a bi-objective(minimizing delays and Queue lengths) cycle-free signal timing length model using Genetic Algorithm. The model was embodied using MATLAB. the language of technical computing. A special feature of this model is its ability to concurrently manage delays and queue lengths of turning movement concurrently. The model produces a cycle-free signal timing(cycles and green times) for each intersection on the cycle basis. Appropriate offsets could be also accomplished by applying cycle-free based signal timings for respective intersections. The model was applied to an example network which consists of four intersections. The result shows that the model produces superior signal timings to the existing signal timing model in terms of managing delays and queue lengths of turning movements.