• Journal of KIISE:Computing Practices and Letters
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• v.16 no.12
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• pp.1229-1233
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• 2010

In event-driven wireless sensor networks, network congestion occurs when event data, which have higher transmission rates than periodic sensing data, arc forwarded to bottleneck links. As the congestion continues, congestion collapse is triggered, so most of packets from source nodes are failed to transmit to a sink node. Rate control schemes can be a solution for preventing the congestion collapse problem. In this paper, a rate control scheme that each node controls child node's data rate based on congestion patterns is proposed. Experiments show that the proposed scheme effectively controls network congestion and successfully transmits more event data packets to a sink node than existing rate control schemes.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.15-16
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• 2023

해상교통관제 구역은 항만 시설을 사용하기 위한 입·출항 선박, 연안 해역을 이동하는 선박 등이 서로 복잡하게 운항하는 교통 패턴을 가지고 있다. 이를 안전하고 효과적으로 관리하기 위해 해상교통관제센터(VTS)에서는 선박을 실시간 모니터링하며 관제 업무를 수행하고 있지만, 교통 혼잡 상황에서는 업무 로드의 증가로 인해 관제 공백이 발생하기도 한다. 이에 교통 혼잡도 및 혼잡 구역을 예측한다면보다 효율적인 관제가 가능하지만 현재는 관제사의 경험에 전적으로 의존하고 있는 실정이다. 본 논문에서는 VTS 관점에서의 교통 혼잡을 정의하고, 과거 항적 데이터를 이용하여 항내 선박 교통 혼잡도 및 혼잡 구역을 예측하는 방법을 제안하였다. 또한, 실해역 데이터(대산항 VTS)를 적용하여 제안된 기술이 관제지원 도구로서 활용될 수 있는지 검토하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.1-17
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• 2022

Accurate analysis of the causes of metro rail traffic congestion provides a means of addressing issues arising from metro rail traffic congestion in metropolitan areas. Currently, congestion analysis based on counting, weight detection, CCTVs, and mobile Wi-Fi is limited by poor accuracies or because studies have been restricted to single routes and trains. In this study, a train congestion analysis model was used that includes the transfer and multi-path behavior of metro passengers and train operation plans for metropolitan urban railroads. Analysis accuracy was improved by considering traffic patterns in which passengers must wait for next trains due to overcrowding. The model updates train crowding levels every 10 minutes, provides information to potential passengers, and thus, is expected to increase the social benefits provided by the Seoul metropolitan subway

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.2
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• pp.100-109
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• 2022

Large-scale urban concentration of population and vehicles due to economic growth in Korea has been causing serious urban transport problems. Although the collection of congestion pricing has been evaluated as the most effective transportation policy to alleviate traffic demand, its effectiveness is very limited as it was just executed around congested points or along main arterial roads. This study derived dynamic congestion zones with the average travel speed of 206 traffic analysis zones in Busan Metropolitan City to propose a dynamic congestion pricing collection system by employing Space-Time Cube Analysis and Emerging Hot Spot Analysis. As a result, dynamic hot spots were formed from 7h to 24h and particularly, traffic congestion was severely deteriorated from 18h to 20h around Seomyeon and Gwangbok-dong. Therefore, it is expected that the effect of dynamic congestion pricing will be maximized in managing traffic demand in the city center.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2A
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• pp.95-104
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• 2012

Pattern recognition using ensemble classifiers is composed of strong classifier which consists of many weak classifiers. In this paper, we used feature extraction to organize strong classifier using static camera sequence. The strong classifier is made of weak classifiers which considers environmental factors. So the strong classifier overcomes environmental effect. Proposed method uses binary foreground image by frame difference method and the boosting is used to train crowdedness model and recognize crowdedness using features. Combination of weak classifiers makes strong ensemble classifier. The classifier could make use of potential features from the environment such as shadow and reflection. We tested the proposed system with road sequence and subway platform sequence which are included in "AVSS 2007" sequence. The result shows good accuracy and efficiency on complex environment.

• Journal of Navigation and Port Research
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• v.47 no.4
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• pp.212-219
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• 2023

Vessel Traffic Service (VTS) area presents a complex traffic pattern due to ships entering or leaving the port to utilize port facilities, as well as ships passing through the coastal area. To ensure safe and efficient management of maritime traffic, VTS operators continuously monitor and control vessels in real time. However, during periods of high traffic congestion, the workload of VTS operators increases, which can result in delayed or inadequate VTS services. Therefore, it would be beneficial to predict traffic congestion and congested areas to enable more efficient traffic control. Currently, such prediction relies on the experience of VTS operators. In this paper, we defined vessel traffic congestion from the perspective of a VTS operator. We proposed a method to generate traffic networks using historical navigational data and predict traffic congestion and congested areas. Experiments were performed to compare prediction results with real maritime data (Daesan port VTS) and examine whether the proposed method could support VTS operators.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.206-207
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• 2010

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.341-344
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• 2006

유고란 도로상에서 교통량의 주기적인 집중에 의한 혼잡과는 구별되는 개념으로 교통사고, 도로보수 그리고 자연재해와 같은 비 반복적인 정체의 상황을 일컫는다. 이러한 유고는 막대한 통행시간이 추가로 발생하고 연료소모, 환경피해 등의 문제가 발생하므로 이러한 교통손실을 최소화하기 위하여 자동유고감지 알고리즘의 개발이 필수적이다. 이를 위하여 현재 다양한 검지기에서 수집된 교통 데이터를 바탕으로 유고를 감지하는 연구가 많이 진행되고 있다. 본 논문에서는 각종 유고 상황을 인지하여 제2의 사고를 예방할 수 있는 효율적인 유고감지 알고리즘을 개발하기 위하여 퍼지논리와 패턴을 함께 사용하였다. 먼저 퍼지논리와 패턴에 사용되는 데이터는 루프 검지기에서 5분 마다 수집된 교통정보(교통량, 점유율, 속도)를 이용하였다. 교통정보를 이용하여 구축된 요일 및 시간대별 패턴과 함께 퍼지논리를 이용하여 도출된 유고 소속도를 가지고 유고를 감지하였다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.09a
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• pp.406-414
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• 1995

자재절단문제를 일반적인 알고리즘을 사용하여 해결하였을 경우 패턴이 형 성되었을 때 계속되는 패턴에서 부품들이 연속하여 절단되 나오지 않게 된 다. 이와같이 부품이 연속되어 나오지 않는 경우를 부품이 단락 (discontinuity)되어진다고 이야기 한다. 이럴 경우 각 부품들은 원하는 주문 량만큼 절단되어 나올 때까지 생산라인에서 대기하고 있어야 한다. 따라서 생산라인에서는 절단된 모든 부품들을 임시적으로 적재해 놓아야 하므로 공 종소요가 증가하게 되고 절단공정이 혼잡해 지게 된다. 이를 볼때 절단되어 나오는 부품들이 계속되는 패턴에서 연속적으로 절단되어지게 하는 것이 중 요하다. 이와같이 부품들이 단락되어지지 않고 연속적으로 생산되면 공정소 요를 줄일수 있게 될 뿐 아니라 생산성의 향상을 기할수 있게 될 것이다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.7
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• pp.1312-1318
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• 2006

One of the common services of telematics is the car navigation that finds the shortest path from source to target. Until now, some routing algorithms of the car navigation do not consider the real-time traffic information and use the static shortest path algorithm. In this paper, we prosed the method to predict the traffic flow in the future. This prediction combines two methods. The former is an accumulated speed pattern, which means the analysis results for all past speeds of each road by classfying the same day and the same time inteval. The latter is the Kalman filter. We predicted the traffic flows of each segment by combining the two methods. By experiment, we showed our algorithm gave better precise predicition than only using accumulated speed pattern that is used commonly. The result can be applied to the car navigation to support a dynamic shortest path. In addition, it can give users the travel information to avoid the traffic congestion areas.