• Journal of the Korean Society for Railway
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• v.18 no.2
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• pp.105-110
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• 2015

This paper presents a $4{\times}1$ beam-forming reader antenna system for a new type of RFID based train position detection technology. The required beamwidth of the reader antenna is analytically expressed for different train speeds. The proposed antenna system consists of four rectangular patch elements and two switching couplers which are designed, without any impedance matching networks, for two different antenna modes. The switching coupler is a rectangular quadrature coupler with Pin diodes connecting its center line and the ground plane. The beamwidth of the antenna when the diodes are off and on is $18^{\circ}$ and $39^{\circ}$, respectively. The proposed antenna system will be used for a real train test in the near future.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.1040-1046
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• 2005

지능형교통시스템(Intelligent Transportation System: ITS)의 기술발전에 따라 고속도로 상에도 각종 검지 센서가 설치되고 교통정보가 다양한 형태로 제공되고 있으며, 전자요금징수시스템(Electronic Toll Collection System: ETCS) 또한 시범운영단계를 마치고 모든 고속도로를 대상으로 확대적용을 준비 중에 있다. 본 논문에서는 ITS 관련시스템 중 고속도로를 대상으로 적용되는 전자요금징수시스템과 유고관리 시스템을 대상으로 수행되었던 시뮬레이션 사례를 소개하고, ITS 분야에서의 시뮬레이션 적용 필요성에 대해서 논의하고자 한다. 전자요금징수시스템을 대상으로 한 시뮬레이션의 경우 현재 시범운영중인 영업소를 대상으로 향후 다양한 요금지불수단 도입에 따른 효과적인 영업소 운영방안을 도출하는 것을 목적으로 개발되었으며, 운전자들의 영업소 차로선택모형 등에 대한 사전연구를 통하여 모델링에 반영하였다. 또한, 고속도로 유고관리시스템의 경우 사고 직후 사고영향에 대한 실시간 시뮬레이션을 수행하여 지체지속시간 및 지체영향구간을 예측하여, 향후 교통정보제공에 활용하는 것을 목적으로 개발되었다. 개발된 시뮬레이션 모델을 통하여 각종운영방안에 대한 평가를 수행하였으며, 실제 유고상황에서의 검지자료와의 비교를 통하여 성능평가를 수행하였다.

• Journal of Korean Society of Transportation
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• v.21 no.5
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• pp.83-95
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• 2003

This study aims to develop travel time estimation and prediction models on the freeway using measurements from vehicle detectors. In this study, we established a travel time estimation model using traffic volume which is a principle factor of traffic flow changes by reviewing existing travel time estimation techniques. As a result of goodness of fit test. in the normal traffic condition over 70km/h, RMSEP(Root Mean Square Error Proportion) from travel speed is lower than the proposed model, but the proposed model produce more reliable travel times than the other one in the congestion. Therefore in cases of congestion the model uses the method of calculating the delay time from excess link volumes from the in- and outflow and the vehicle speeds from detectors in the traffic situation at a speed of over 70km/h. We also conducted short term prediction of Kalman Filtering to forecast traffic condition and more accurate travel times using statistical model The results of evaluation showed that the lag time occurred between predicted travel time and estimated travel time but the RMSEP values of predicted travel time to observations are as 1ow as that of estimation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.68-77
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• 2013

This study suggested experimental study results of congestion detection method for intruding vehicle enforcement system. This congestion detection method is developed to determine optimal operation criteria of intruding vehicle enforcement system as detecting traffic congestion. In ITS sector, traffic management systems generally have used a sectional travel speed for congestion detection. However, image sensors have high error rate of congestion detection because of speed error. This study suggested comprehensive congestion detection criteria based on speed and occupancy rate using field studies. As field study results, the proposed intruding vehicle enforcement system using image sensor is capable of accurately detecting the traffic congestion using sectional speed of 20km/h and occupancy rate of 60% as congestion detection criteria.

• 한국공간정보시스템학회:학술대회논문집
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• 2007.06a
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• pp.177-182
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• 2007

최근 텔레매틱스 분야에서 GPS 수신기를 장착한 probe car를 통해 교통 정보를 수집하는 방법에 대한 연구가 활발히 진행되고 있다. 이 방법은 기존에 교통 정보를 수집하기 위해 활용되고 있던 고정식 검지기들에 비해 수집되는 정보가 높은 신뢰성을 가지고, 도로 환경에 민감하지 않으며, 낮은 유지비용으로 운용할 수 있다는 장점을 가지고 있다. 하지만, probe car는 자신의 위치 정보를 교통 정보 센터로 전송해 주어야 하기 때문에 프라이버시가 노출될 수 있고, 주차되어 있는 시간에는 통행 정보를 보내줄 수가 없다. 이런 이유로 대중 교통차량이나 상업용 차량이 주로 probe car로 활용되어지게 되는데, 그 수가 많지 않을뿐더러 운행 구간이 고르게 분포되지 않아 probe car가 지나지 않는 구간, 즉 교통 정보 누락 구간이 존재할 수 있는 문제점을 가지고 있다. 본 논문에서는 교통 정보 누락 구간의 처리를 위해 과거의 이력 정보로 대체하는 방법, 주변 도로의 구간 정보로 예측하는 방법, 회귀 분석을 통한 예측 방법 등을 기술하고 실제 probe car들로 수집된 서울시 강남대로 구간의 자료로 각 방법에 대한 실험을 실시하여 각각의 방법에 대한 결과를 비교 분석한다.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.147-152
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• 2015

Almost all existing inspection methods for catenary system have relied on dedicated track inspection cars. Two factors make it necessary to modify the conventional method: First, the climate has become increasingly similar to that of a subtropical area. In addition, high speed trains have been developed that can run as fast as 450Km/h. This paper presents a visual catenary inspection system structure that incorporates roadbed information for high-speed running environments. Conventional catenary inspection systems determined the degree of wearing only for the trolley wire. The facility inspection system presented in this paper on the other hand utilizes visual and sound data of inspection targets and adjusts inspection frequency and sensitivity depending on the geographic data.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.802-810
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• 2006

For a thorough train control, the precise train position detection is necessarily required. The widely used current way for train position detection is the one of using track circuits. The track circuit has a simple structure, and has a high level of reliability. However trains can be detected only on track circuits, which have to be installed on all ground sections, and much amount of cost for its installation and maintenance is needed. In addition, for the track circuit, only discontinuous position detection is possible because of the features of the closed circuit loop configuration. As the recent advances in telecommunication technologies and high-tech vehicle-based control equipments, for the train position detection, the method to detect positions directly from on trains is being studied. Vehicle-based position detection method is to estimate train positions, speed, timing data continuously, and to use them as the control information. In this paper, the features of GPS navigation and DR navigation are analyzed, and the navigation filters are designed by constructing vehicle-based train position detection method by combining GPS navigation and DR navigation for their complementary cooperation, and by using kalman filter. The position estimation performance of the proposed method is also confirmed by simulations.

• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.17-28
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• 2011

This study proposed a speed management strategy for the enhancement of traffic safety on freeways. A novel feature of the proposed strategy is to provide desirable speed information to individual vehicles. A microscopic traffic simulator, VISSIM, was used for the performance evaluation. Vehicle trajectory data were used to evaluate the various speed management scenarios including the different levels of proportions of heavy vehicles. The proposed speed management strategy would be a useful precursor for developing an effective traffic control and operations system to prevent traffic accidents on freeways.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.1-13
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• 2023

This study develops an optimal mobile-communication-based National Highway traffic volume estimation model using an ensemble-based machine learning algorithm. Based on information such as mobile communication data and VDS data, the LightGBM model was selected as the optimal model for estimating traffic volume. As a result of evaluating traffic volume estimation performance from 96 points where VDS was installed, MAPE was 8.49 (accuracy 91.51%). On the roads where VDS was not installed, traffic estimation accuracy was 92.6%.

• Journal of Korean Society of Transportation
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• v.26 no.2
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• pp.101-107
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• 2008

Traffic speed data may be missed due to detector malfunction or network problems. In this paper we have proposed effective methods to estimate the data which could not be collected through loop detectors. Our proposed algorithm has three steps. First step is to find the most similar neighbor data record by coefficient of correlation. Second step is to make some data records which is calculated by the 5 kinds of estimation methods. Third step is to compare the data records with history data record of observation link and thus the best method is selected. The proposed method is useful for estimating travel time.