• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권8호
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• pp.2473-2489
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• 2022

Urban development has brought about the increasing saturation of urban traffic demand, and traffic congestion has become the primary problem in transportation. Roads are in a state of waiting in line or even congestion, which seriously affects people's enthusiasm and efficiency of travel. This paper mainly studies the discrete domain path planning method based on the flow data. Taking the traffic flow data based on the highway network structure as the research object, this paper uses the deep learning theory technology to complete the path weight determination process, optimizes the path planning algorithm, realizes the vehicle path planning application for the expressway, and carries on the deployment operation in the highway company. The path topology is constructed to transform the actual road information into abstract space that the machine can understand. An appropriate data structure is used for storage, and a path topology based on the modeling background of expressway is constructed to realize the mutual mapping between the two. Experiments show that the proposed method can further reduce the interpolation error, and the interpolation error in the case of random missing is smaller than that in the other two missing modes. In order to improve the real-time performance of vehicle path planning, the association features are selected, the path weights are calculated comprehensively, and the traditional path planning algorithm structure is optimized. It is of great significance for the sustainable development of cities.

• 한국컴퓨터정보학회논문지
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• 제29권1호
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• pp.195-209
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• 2024

1990년대 개발되어 현재의 모습을 갖춘 교통신호제어기는 최근 도로 이용자의 교통안전 향상 및 자율협력주행 등을 목적으로 설치되는 다양한 장치들에 대한 전원공급 문제와 다양한 통신방식, 계층화된 블랙박스 구조 등으로 인해 유연성과 확장성에 한계를 가지고 있다. 이에 본 논문에서는 이더넷전원장치(PoE : Power over Ethernet) 기술을 통해 직류(DC) 전원 사용과 전원공급 문제를 해결하고, 메시지 브로커(Message Broker) 기술을 통해 중앙화된 데이터 기반 제어를 함으로써 빠르게 변화하는 미래 교통환경에 대응이 가능한 교통안전시설 통합관제시스템을 설계하였다. 또한 시계열 데이터를 기반으로 동작하는 교통안전시설 장치를 위한 데이터 기반 실시간 제어 방안을 구현하고 검증하였다.

• 한국멀티미디어학회논문지
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• 제22권12호
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• pp.1438-1446
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• 2019

Recently, the number of mobile users as well as high-speed Internet user has been increasing rapidly. Moreover, traffic is growing fast as services that provide real-time content such as Youtube and Netflix become popular. The problem of traffic control in real-time content services is important because many people use cell phones to receive real-time content. In this regard, the field of CCN is currently being studied. We studied the mobility of nodes among CCN research fields. Node mobility can be divided into three categories : consumer mobility, intermediate node, and provide mobility. In this paper, we propose Mobility Node Support(MD-INS) to support the intermediate-node mobility in CCN real-time services. Experimental results show that the proposed scheme shows better performance than CCN in terms of service disconnection time and packet loss.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.94-97
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• 1999

In this paper, a new real-time neural network connection admission controller is proposed. The proposed controller measures traffic flows, cell loss rate and cell delay periodically each classes. The Neural network learns the relation between those measured information and service quality by real-time. Also the proposed controller uses the DWRR multiplexer with buffer dedicated to every traffic source in order to measure the delay that cells experience in buffer. Experimental result shows that the proposed method can control effectively heterogeneous traffic sources with diverse QoS requirement.

• 인터넷정보학회논문지
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• 제11권4호
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• pp.1-10
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• 2010

현재 융합 산업과 유비쿼터스 기술이 고도화되면서 U-City, 스마트폰과 같은 다양한 인프라 및 장치에서 고부하를 요구하는 네트워크 컨텐츠를 지원하고 있다. 이에 따라 멀티미디어 데이터와 같은 전통적인 고부하 컨텐츠의 실시간 참조가 급증하여 네트워크 부하에 따른 멀티미디어 재생 품질이 급격히 하락할 것으로 예상된다. 본 논문에서는 서로 다른 재생 성능을 가지는 다양한 클라이언트 매체가 요청하는 스트림 전송량을 시간 중심의 컨텐츠 선호도와 매체 선호도를 통합한 TP(Top Performance) 계수에 따라 MMS(Multimedia Streaming Server)의 가용 트래픽을 차등 할당하여 멀티미디어 재생 품질을 향상시키는 MPP(Media Preference for Presentation) 기반의 트래픽 할당 기법을 개선하였다. 통합된 TP 계수를 실시간 트래픽 할당스케듈러에 적용하고, 시뮬레이션 실험을 통해 멀티미디어 재생 스트림이 서버의 가용 트래픽 이내에서 할당되고 있음을 확인하였다. 그리고 MPP 기반의 실시간 스케듈링 알고리즘을 시간 중심형 영상 컨텐츠와 매체 선호도의 가중치를 이용하여 통합한 TP 계수를 이용하여 개선하였고, 실험을 통해 트래픽을 요청하는 3개의 클라이언트에 대해 3.91%, 4개의 클라이언트에 대해 3.88%의 가용 트래픽 손실률을 줄였다.

• 국제초고층학회논문집
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• 제3권2호
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• pp.155-165
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• 2014

This study measured and compared the variation of ventilation rate and fan energy consumption according to various control strategies after installing wireless sensor-based pilot ventilation system in order to verify the applicability of demand-controlled ventilation (DCV) strategy that was efficient ventilation control strategy for underground parking lot. The underground parking lot pilot ventilation system controlled the ventilation rate by directly or indirectly tracking the traffic load in real-time after sensing data, using vehicle detection sensors and carbon monoxide (CO) and carbon dioxide ($CO_2$) sensor. The ventilation system has operated for 9 hours per a day. It responded real-time data every 10 minutes, providing ventilation rate in conformance with the input traffic load or contaminant level at that time. A ventilation rate of pilot ventilation system can be controlled at 8 levels. The reason is that a ventilation unit consists of 8 high-speed nozzle jet fans. This study proposed vehicle detection sensor based demand-controlled ventilation (VDS-DCV) strategy that would accurately trace direct traffic load and CO sensor based demand-controlled ventilation (CO-DCV) strategy that would indirectly estimate traffic load through the concentration of contaminants. In order to apply DCV strategy based on real-time traffic load, the minimum required ventilation rate per a single vehicle was applied. It was derived through the design ventilation rate and total parking capacity in the underground parking lot. This is because current ventilation standard established per unit floor area or unit volume of the space made it difficult to apply DCV strategy according to the real-time variation of traffic load. According to the results in this study, two DCV strategies in the underground parking lot are considered to be a good alternative approach that satisfies both energy saving and healthy indoor environment in comparison with the conventional control strategies.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2017년도 춘계학술대회
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• pp.722-723
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• 2017

본 연구에서는 커넥티드 자동차(Connected Car, ConnCar)의 주행 효율 향상을 위한 교통신호 제어에 초점을 맞추고 있다. 이를 위한 세부 연구 범위는 다음과 같다. i) ConnCar 간의 상황 정보 공유, ii) 게임이론 기반의 협상을 통한 의사결정

• 대한설비관리학회지
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• 제23권4호
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• pp.21-27
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• 2018

This paper proposed the real-time monitoring methodology of a traffic signal controller. The proposed methodology is based on the simulation technology, and it is necessary to construct a simulation model imitating the behavior of a traffic signal controller. By executing the simulation model, we can obtain the 'nominal system trajectory' of the traffic signal controller. On the other hand, an IoT(Internet of Things)-based monitoring device is implemented in a traffic signal controller. Through the monitoring device, it is possible to obtain the 'actual system trajectory'. By comparing the nominal system trajectory and the actual system trajectory, we can estimate the degree of deterioration of a traffic signal controller.

• 자동차안전학회지
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• 제14권4호
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• pp.6-15
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• 2022

In this study, a traffic light recognition algorithm was implemented and validated for low-speed special purpose vehicles in an urban environment. Real-time image data using a camera and YOLO algorithm were applied. Two methods were presented to increase the accuracy of the traffic light recognition algorithm, and it was confirmed that the second method had the higher accuracy according to the traffic light type. In addition, it was confirmed that the optimal YOLO algorithm was YOLO v5m, which has over 98% mAP values and higher efficiency. In the future, it is thought that the traffic light recognition algorithm can be used as a dual system to secure the platform safety in the traffic information error of C-ITS.

• ETRI Journal
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• 제26권5호
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• pp.391-396
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• 2004

In this paper, we propose a packet scheduling discipline called packet loss fair scheduling, in which the packet loss of each user from different real-time traffic is fairly distributed according to the quality of service requirements. We consider an orthogonal frequency division multiple access (OFDMA) system. The basic frame structure of the system is for the downlink in a cellular packet network, where the time axis is divided into a finite number of slots within a frame, and the frequency axis is segmented into subchannels that consist of multiple subcarriers. In addition, to compensate for fast and slow channel variation, we employ a link adaptation technique such as adaptive modulation and coding. From the simulation results, our proposed packet scheduling scheme can support QoS differentiations while guaranteeing short-term fairness as well as long-term fairness for various real-time traffic.