• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.6
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• pp.127-132
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• 2008

Traffic intersection control is implemented by the data which is acquired to vechile loop detector. Traffic intersection control equation is Webster equation. which use passig and delayed vechile number. But webster equation is applied to the spot traffic intersection, it is not used to related traffic intersection network system. There is not the approprate remote traffic intersection control, even if there is, it is high cost local network system. Therefore low cost and expert traffic intersection control is realized by internet referencing next and distant intersection traffic information.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.15 no.2
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• pp.263-268
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• 1997

Software structure must be dynamic to support new geospatial information sources and their object-oriented implementation on the Web. JAVA is interactive, platform idependent and object-oriented language and meets all needs on Internet GSIS. This paper introduce JAVA based GIS program to manipulates various geographic data on Internet, communicating interactively and transfer real-time data between server and client. This and this program analysis roof detector in all part of Pusan area and indicates the traffic states, road surface conditions, weather information, shortest cut, and road names in JAVA client windows. Also this study shows various techniques in expression real time traffic informations.

• Proceedings of the KAIS Fall Conference
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• 2008.05a
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• pp.245-247
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• 2008

Traffic intersection conrol is implemented by the data which is acquired to vechile Loop detector. Traffic intersection control equation is Webster equation, which use passing and delayed vechile number. But webster equation is applied to the spot traffic intersection, it is not used to related traffic intersection network system. There is not the approprate remote traffic intersection control, even if there is, it is high cost local network system. Therefore low cost and expert traffic intersection control is realized by internet referencing next and distant intersection traffic information.

• 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.14 no.1
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• pp.135-154
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• 1996

This paper presents a heuristic algorithm for classifying vehicles using a single loop detector. The data used for the development of the algorithm are the frequency variation of a vehicle sensored from the circle-shaped loop detectors which are normal buried beneath the expressway. The pre-processing of data is required for the development of the algorithm that actually consists of two parts. One is both normalization of occupancy time and that with frequency variation, the other is finding of an adaptable number of sample size for each vehicle category and calculation of average value of normalized frequencies along with occupancy time that will be stored for comparison. Then, detected values are compared with those stored data to locate the most fitted pattern. After the normalization process, we developed some frameworks for comparison schemes. The fitted scales used were 10 and 15 frames in occupancy time(X-axis) and 10 and 15 frames in frequency variation (Y-axis). A combination of X-Y 10-15 frame turned out to be the most efficient scale of normalization producing 96 percent correct classification rate for six types of vehicle.

• Journal of Korean Society of Transportation
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• v.17 no.3
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• pp.97-116
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• 1999

The growing demand for the real time traffic information is bringing about the category and number of traffic collection mechanism in the era of ITS. There are, however, two problems in making data into information using various traffic data. First, the information making process of making data into the representative information, for each traffic collection mechanism, for the specified analysis periods is required. Second, the integration process of fusing each representative information into "the information" for each link out of each source is also required. That is, both data reduction and/or data to information process and information fusion are required. This article is focusing on the development of information fusing algorithm based on voting technique, fuzzy regression, and, Bayesian pooling technique for estimating the dynamic link travel time of networks. The proposed algorithm has been validated using the field experiment data out of GPS probes and detectors over the roadways and the estimated link travel time from the algorithm is proved to be more useful than the mere arithmetic mean from each traffic source.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.05a
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• pp.106-106
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• 2001

네트웍의 용량의 개념이 없는 미세한 교통혼잡 도구로서 Microscopic시뮬레이션 모형인 Paramics가 소개된다. 모형의 기본구조가 설명되고, 특히 응용사례로서 서울시 교통관리 시스템을 설치함에 있어서 대안의 평가에 따른 제반 결과의 척도를 이끌어 내는 절차가 소개되었고, 아울러 결과가 분석되어 제시되었다. 이는 미시적 교통 시뮬레이션을 위한 고성능의 소프트웨어로서 각 차량들은 상세한 속성들을 가지고, ITS와 운전자와의 인터페이스를 모델링 할 뿐만 아니라 정확한 교통류, 대중교통 시간, 혼잡정보를 시뮬레이션 할 수 있는 장점이 있는바 적용 분야로서 여기까지가 있으나 혼잡이 있는 도로 네트워크 및 일반도로 네트워크와 ITS 인프라의 존재상황에서 제반 모델링이 가능한바 이를 통한 도시고속도로 관리시스템의 효과를 분석하였다. 신호의 영향, 첨단신호제어, 램프 미터링, 루프 검지기, 다양한 속도 표지, VMS 정보전략 등의 기능을 소개하고 금번 서울시의 사례를 통한 모형의 장단점을 보고한다. 아울러 이 시뮬레이션 모형의 한계도 함께 지적되었다.

• Journal of Korean Society of Transportation
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• v.16 no.2
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• pp.177-195
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• 1998

지능형교통체계(ITS:Intellegent Transport System)의 구현을 위한 가장 중요한 요소중의 하나는 교통정보의 생성이다. 교통정보의 생성은 루프 검지기, 폐쇄회로(CCTV), probe 차량, 경찰, 통신원 등을 수집된 제보자료들을 분석 및 가공함으로써 이루어진다. 그러나 이들 수집원은 주어진 시간에 있어 모든 네트웍을 통해서 자료가 완전히 수집되어지는 것은 아니다. 즉, 특정 지역에 수집원이 몰려 있는 경우가 있는 반면, 전혀 수집되어지지 않는 지역이 발생할 수도 있다. 이러한 공간적인 불균형적 특성은 동시에 발생한 다량의 자료를 처리하는 기술과 자료가 수집되지 않은 지역에 대한 처리기술을 요하게 된다. 본 논문은 전술한 바와 같은 사항에 대하여 ITS의 진행 단계별로 드러날 수 있는 문제점을 검토하고, 자료통합에 대한 일반적인 개념을 우선 설명한다. 다음에 특정시각에 주어진 자료의 통합을 위해 퍼지선형회귀모형(fuzzy linear regression model)과 데이터 퓨전(data fusion)기법의 내용을 소개하고, 신뢰성있는 단일 교통정보생성을 위한 테이터 퓨전 알고리즘을 제시한다. 또한 제시된 알고리즘을 토대로 가상의 자료를 이용하여 적용가능 봉? 타진해 보았다. 제시되어진 알고리즘은 향후 교통정보 수집환경이 어느 정도 형성된다고 볼 때, 예측치와 실측자료간의 자료검증을 통하여 신뢰도를 가질 경우 보다 광범위하게 사용되어질 수 있을 것으로 판단된다.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.63-68
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• 2004

In this paper, we propose a method about the extraction of vehicle and tracking trajectory for moving vehicle tracking system in road. This system applied to the monitoring system of the traffic flow for ATMS(advanced traffic management system) of ITS(intelligent transport system). Also, this system can solve the problem of maintenance of loop sensor. And we detected vehicle using differential image analysis. Because of the road environment changes by real time. Therefore, the method to use background image is not suitable. And we used Kalman filter and innovation value and variable search area for vehicle tracking system. Previous method using fixed search area is sensitive to the moving trajectory and the speed of vehicle. Simulation results show that proposed method increases the possibility of traffic measurement more than fixed area traffic measurement system.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.181-190
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• 2022

In this paper, we use a LiDAR sensor and an image camera to detect a left-turning waiting vehicle in two ways, unlike the existing image-type or loop-type left-turn detection system, and a left-turn traffic signal corresponding to the waiting length of the left-turning lane. A system that can efficiently assign a system is introduced. For the LiDAR signal transmitted and received by the LiDAR sensor, the left-turn waiting vehicle is detected in real time, and the image by the video camera is analyzed in real time or at regular intervals, thereby reducing unnecessary computational processing and enabling real-time sensitive processing. As a result of performing a performance test for 5 hours every day for one week with an intersection simulation using an actual signal processor, a detection rate of 99.9%, which was improved by 3% to 5% compared to the existing method, was recorded. The advantage is that 99.9% of vehicles waiting to turn left are detected by the LiDAR sensor, and even if an intentional omission of detection occurs, an immediate response is possible through self-correction using the video, so the excessive waiting time of vehicles waiting to turn left is controlled by all lanes in the intersection. was able to guide the flow of traffic smoothly. In addition, when applied to an intersection in the outskirts of which left-turning vehicles are rare, service reliability and efficiency can be improved by reducing unnecessary signal costs.