• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1242-1243
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• 2011

차량 검지 시스템은 실시간으로 교통상황 자료를 수집하는 시스템으로, 관리대상 구간의 자료를 수집하여 시시각각 변하는 교통상황에 대한 효과적인 교통관리를 수행하도록 한다. 현재 차량 검지 시스템은 상당한 안정성과 정확성을 확보 하고 있기는 하나, 시스템 구성시 검지 시스템 자체의 구성에 드는 비용과 시간 보다는 센터와의 통신에 필요한 시스템 구축이나 전원 확보를 위한 전원선 공사등과 같은 주변 환경 요건 구축에 더욱 많은 비용과 시간이 드는 문제점이 있다. 이는 정보수집의 방식이 현재까지는 센터와 1:1 연결을 통한 정보교환에 의한 것이어서 전국단위의 N개 총신회선의 정보교환을 위해서는 1:N개의 통신회선이 필요하기 때문이다. 따라서 본 논문에서는 이러한 문제점 해결을 위한 레이더 차량 검지 시스템용 통합 프로토콜 제어기의 개발을 수행한다.

• Journal of Korean Society of Transportation
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• v.16 no.3
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• pp.101-111
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• 1998

현재 고속도로 교통관리시스템(FTMS)에 사용되고 있는 차량 검지기는 주로 루프 식 검지기가 이용되고 있으나, 유지관리에 많은 어려움이 있다. 본 연구에서는 이러한 문제 점을 갖고 있는 루프 검지기를 대체하기 위한 대체 검지기를 개발하는데 그 목적이 있다. 자기 검지기 신뢰도 평가는 현장 실험으로 이루어지며 비디오 촬영 및 루프 검지기, test car를 이용하여 교통량·속도·점유율의 기준자료를 마련하고 자기 검지기 자료와 비교·분석 및 통계적 검정을 실시하였다. 1차 실험과 2차 실험의 결과, 교통량과 속도는 실측자료와 유사했으나 점유율은 실측치와 다소 차이가 발생함을 보였다. 향후 점유율에 대한 보정이 이루어진다면 현재 사용중인 루프 검지기를 대체할 수 있을 것으로 기대된다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.4
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• pp.99-104
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• 2010

We introduce Internet TCP/IP control system to monitor the traffic volume on the traffic network system. To check the traffic volume on traffic road, we use the traffic detector system shppe of circle or diamond or rectangular. Nevertheless we use traffic detector, we will use internet addressin TCP/IP system. If we use TCP/IP control system, we acquire many good point, we achive high sircurity and low costness traffic monitoring system coming difficulty and high level position. But internet system is very easy and low cost direction. Traffic control system is very more depending on the high techinquesion and very complexity. Therefore we introducing TCP/IP internet addressing control system schemetic point.

• 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.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.23-29
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• 2014

The advanced traffic management system of intelligent transport systems automates the related traffic tasks such as vehicle speed, traffic volume and traffic incidents through the improved infrastructures like high definition cameras, high-performance radar sensors. For the safety of road users, especially, the automated incident detection and secondary accident prevention system is required. Normally, CCTV based image object detection and radar based object detection is used in this system. In this paper, we proposed the algorithm for real time highway incident detection system using multi surveillance cameras to mosaic video and track accurately the moving object that taken from different angles by background modeling. We confirmed through experiments that the video detection can supplement the short-range shaded area and the long-range detection limit of radar. In addition, the video detection has better classification features in daytime detection excluding the bad weather condition.

• Journal of The Korean Society For Urban Railway
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• v.6 no.4
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• pp.269-278
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• 2018

Railway obstacle detecion system has been introduced with high-speed railway in 2004 to prevent accidents by obstacles such as landslide, rockfall and things fallen from the gauntry over the railway. But existing system has some limitation for landslide or fallen obstacle over railway. Therefore, In this study, we suggest new advanced obstacle detection system introducing the OTDR, optical fiber fences and detection cameras. This system can detect depression degree by the force to the fences and video for the specific region as well as detection wire Off condition. We produce and functional tests for fiber fence and OTDR, which are the core parts of the development system, and results were obtained to demonstrate improved detection capabilities. Several functions also been tested to verify the advanced detection performance and got some satisfactory results. Further we will conduct environment tests and field test.

• 한국디지털정책학회:학술대회논문집
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• 2004.05a
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• pp.593-608
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• 2004

우리나라의 경우 교통정보수집용 검지기는 루프검지기가 주종을 있으며, 지금까지 한국에서 루프검지기를 대체할 수 있는 영상 및 초단파검지기와 같은 대체검지기에 대한 평가는 단속류 보디는 연속류 상황에 대한 평가로 제한되어 왔다. 한편 최근들어 점차 고속도로를 중심으로 영상검지기의 설치개소수가 급속히 증가하고 있는 추세이다. 이 영상검지기의 경우 연속 교통류 상황의 15 분 혹은 5 분 단위의 점유율, 교통량, 속도등의 교통변수 측정정확도는 검지시스템의 요구사항을 충족하는 것으로 나타났다. 본 연구에서는 한국의 장래 교통관리 첨단화에 요구되는 교통자료 수집수준을 시가지도로 및 고속도로를 중심으로 파악하고, 루프검지기의 대체 검지기로서 영상검지기에 대한 성능평가 및 분석을 실시하였다.

• Proceedings of the KSR Conference
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• 2005.05a
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• pp.1159-1164
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• 2005

현재 철도청이 운용중인 열차운행관리 시스템(Railway Traffic Management System, RTMS)은 서울, 대전, 부산, 순천 그리고 영주 등으로 총 5개 지역본부로 분산되어 있어 업무의 중복을 줄이고, 자동화(Automation)된 열차집중제어장치(Central Traffic Control, CTC)를 구축하기 위해 지역본부를 대전으로 통합하는 프로젝트를 진행중이다. 본 논문은 철도청 사령실 통합 신호설비 구축 프로젝트에 의거하여 열차 경합을 검지 또는 예측하고 운영자에게 최소의 시간 내에 최적의 해소 대책을 제시함을 목적으로 하는 열차 경합 검지 시스템을 구현하는 과정에서 작성되었다. 여기에서는 열차 경합 검지에 대한 개요와 검지 가능한 경합 종류에 대해 기술하고, 실제 구현된 알고리즘의 기본적인 내용, 프로세스의 구성도 및 시뮬레이션 결과를 설명하려고 한다.

• Journal of Korean Society of Transportation
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• v.23 no.5 s.83
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• pp.123-134
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• 2005

This research aims at developing a new method which can replace the existing method. known as the quality factor(Q factor) method by an L-R-C test for use in the performance test of inductive loop detectors(ILD) being installed and maintained. In this study, a sensor to detect a magnetic field in terms of frequency and intensity, a method to collect field data, the method of analysis, and the method of diagnosis were developed. An automatic diagnosis system which was developed to overcome those drawbacks has the following features : First, field data is collected automatically by a test vehicle equipped with magnetic field sensors that is running can be said to along the roadway and. thus, the new system completely overcome the roadway and, thus, the new system can be said to completely overcome the inefficiency of the existing method second, since the magnetic fold generated from the ILD is the final output of the whole system of ILD, the existing problem has been solved. third. since each of the detection area by height is collected by the magnetic sensors installed by height. a basic for the identification of the vehicle types to be detectable and the setting of adjustment factors has been made. For the automatic diagnosis system developed during in this study, a reliability test was carried out by comparing vehicle times of ILD installed ideally.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.543-552
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• 2008

ATIS(Advanced Traveler Information System) is the system to offer a real-time traffic information or traffic situation for the benefit of the client. One of traffic information collection methods for ATIS research is the method of image analysis. The method is divided into two : one is the method to set two loop detectors at the area and the other is the method detecting the vehicle through an image analysis. In this paper, we propose a real-time traffic information collection system to mix two methods. The system installs multiple virtual detection lines and traces the location of the vehicle. Use of multiple virtual detection lines supplements the defect of the method of loop detectors. And we drew a representative pixels in the detecting area and used it for image analysis. This is to solve the problem of time delay which increases as the image size increases. We gathered traffic images and experimented using the system and got 92.32% of detection accuracy.