• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.570-577
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• 2011

In this paper, Policy-based QoS in 3GPP service network management techniques are not applied to the DiffServ technology is applied to the first interpretation. The next PBNM and DiffServ associated technologies by applying QoS performance improvement is verified. In this case that PBNM and DiffServ technology is applied, the amount of voice traffic reduced about 1 msec while best-effort traffic occurs 75 percent of the output link capacity. Also, video traffic which is the same as data traffic showed a decreased $0\sim10^{-4}$ packet loss rate than the case that DiffServ technology is applied. We apply the appropriate policy PBNM and DiffServ QoS mechanisms of the existing set of policies is not affected, just by using the appropriate 3GPP Service QoS level to suit the network operation, management can do that was found. This analytical method based on the University of California at Berkeley through NS-2 DiffServ technology into existing systems and next-generation networks mandated PBNM and DiffServ technology is applied to performance evaluation for the case.

• Journal of Information Processing Systems
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• v.12 no.2
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• pp.183-195
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• 2016

This paper presents a complete method for vehicle detection and tracking in a fixed setting based on computer vision. Vehicle detection is performed based on Scale Invariant Feature Transform (SIFT) feature matching. With SIFT feature detection and matching, the geometrical relations between the two images is estimated. Then, the previous image is aligned with the current image so that moving vehicles can be detected by analyzing the difference image of the two aligned images. Vehicle tracking is also performed based on SIFT feature matching. For the decreasing of time consumption and maintaining higher tracking accuracy, the detected candidate vehicle in the current image is matched with the vehicle sample in the tracking sample set, which contains all of the detected vehicles in previous images. Most remarkably, the management of vehicle entries and exits is realized based on SIFT feature matching with an efficient update mechanism of the tracking sample set. This entire method is proposed for highway traffic environment where there are no non-automotive vehicles or pedestrians, as these would interfere with the results.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.18-26
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• 2012

As the performance of the next-generation broadband wireless networks is dramatically enhanced, various services (i.e., education, video conferencing, online games, etc.) have been provided to users through a smart mobile platform. Since those services are usually provided by using the centralized architecture, it is difficult for a lot of users to provide the scalable communication service with regard to traffic management. To solve these problems, we have proposed an architecture of P2P-based group communication management scheme using smart mobile device. More specifically, we design the group management protocol and algorithm for the group member management and the traffic management. By using these methods, the mobile multimedia streaming service can be provided with scalability. In order to verify the performance of the proposed scheme, we have mathematically analyzed the performance in terms of the average transmission delay and bandwidth utilization.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.744-748
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• 2003

Developing an interactive satellite multi­media system, such as a digital video broadcasting (DVB) return channel via satellite (RCS) system, is gaining popularity over the world To accommodate the increasing traffic demand we are motivated to investigate an alternative for improving return channel utilization We develop an efficient method for optimal packet scheduling in an interactive satellite multimedia system using hybrid CDMA/TDMA channels. We formulate the timeslot-code assignment problem as a binary integer programming (BIP) problem, where the throughput maximization is the objective, and decompose this BIP problem into two sub-problems for the purpose of solution efficiency. With this decomposition, we promote the computational efficiency in finding the optimal solution of the original BIP problem Since 2001, ETRI has been involved in a development project where we have successfully completed an initial system integration test on broadband mobile Internet access via Ku-band channels using the proposed resource allocation algorithm.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.208-221
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• 2020

The objective of this study is to estimate and analyze the traffic density of continuous flow using the trajectory of individual vehicles and the headway of sample probe vehicles-front vehicles obtained from ADAS (Advanced Driver Assitance System) installed in sample probe vehicles. In the past, traffic density of continuous traffic flow was mainly estimated by processing data such as traffic volume, speed, and share collected from Vehicle Detection System, or by counting the number of vehicles directly using video information such as CCTV. This method showed the limitation of spatial limitations in estimating traffic density, and low reliability of estimation in the event of traffic congestion. To overcome the limitations of prior research, In this study, individual vehicle trajectory data and vehicle headway information collected from ADAS are used to detect the space on the road and to estimate the spatiotemporal traffic density using the Generalized Density formula. As a result, an analysis of the accuracy of the traffic density estimates according to the sampling rate of ADAS vehicles showed that the expected sampling rate of 30% was approximately 90% consistent with the actual traffic density. This study contribute to efficient traffic operation management by estimating reliable traffic density in road situations where ADAS and autonomous vehicles are mixed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5D
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• pp.611-617
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• 2009

With advanced technologies applied to transportation, realtime traffic information has been necessary for not only drivers but also agencies. In normal, traffic conditions have been represented to three levels according to congestion: "free", "slow", and "jammed". Those categories and criteria are set up for traffic management even though traffic information is provided for drivers. This study examines how drivers feel current congestion levels and delves into traffic categories and criteria which they recognize. To collect data for drivers' recognition, a survey of freeway travellers is conducted answering the question about traffic flow speed from video image on a freeway section. In the result of the survey, the surveyee preferred a 4-level traffic condition including "delayed" to 3-level traffic condition. As its criteria, 20 km/h, 50 km/h, and 75 km/h were obtained. These results are expected to contribute to building more appropriate traffic information for drivers and providing an operational guideline for Traffic Monitering Centers.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.5
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• pp.11-20
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• 2014

Due to the importance of vehicle detector which plays an essential role in generating real-life traffic information, maintaining detector data quality is preeminent in advanced traffic management and information systems (ATMIS). To this end, agencies periodically conduct performance tests on detectors. Detector evaluation is generally performed by comparing baseline data with corresponding detector data. Here, two important things need to be addressed; one is errors (or uncertainties) included in baseline data and the other is the confidence interval concept to represent evaluation results of sample data to corresponding ones of population. To resolve these problems, a new detector evaluation scheme is introduced and the scheme is applied to individual level detector evaluations of loop, video image, and radar detectors. The purpose of individual level evaluation is to eliminate the balancing (or cancelling-out) effects of over- and under-counts. As a consequence, the proposed scheme is proven to be effectively applied to real-world detector evaluations.

• The Journal of the Korea Contents Association
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• v.6 no.3
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• pp.1-11
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• 2006

With the improvement of information telecommunication technology, the various service in broadband integrated services digital networks have a wide range of delay, delay jitter and cell loss probability requirements according to traffic specification. Therefore, the design of appropriate control schemes that can satisfy the cell loss, delay requirements with various traffic specification for B-ISDN is an extremely important challenging problem. In this paper, we propose a priority control scheme using a window counter and a cell counter per each type of class. In the proposed priority control scheme, for satisfying required service quality, we performed the priority control scheme using the delay/loss factors obtained by comparing window counter with cell counter. The performance of proposed control scheme is estimated by computer simulation. In the results of simulation, we verified that the proposed method satisfied per class requirements as the results showed that cell loss probability has a order of video, data, voice and delay time has a order of video, voice and data.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.4
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• pp.95-103
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• 2009

Global interests for construction of 3 dimensional spatial information has risen due to development of measurement sensors and data processing technologies. In spite of criticism for the violation of personal privacy, CCTV cameras equipped in outdoor public space of urban area are used as a fundamental sensor for traffic management, crime prevention or hazard monitoring. For safety guarantee in urban environment and disaster prevention, a surveillance system integrating pre-constructed 3 dimensional spatial information with CCTV data or video sequence is needed for monitoring and observing emergent situation interactively in real time. In this study, we proposed applicability of the prototype system for web visualization based on X3D, an international standard of real time web visualization, by integrating 3 dimensional spatial information with video sequence.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.353-361
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• 2020

Due to the rapid urbanization, various traffic problems such as traffic jams during commute and regular traffic jams are occurring. In order to solve these traffic problems, it is necessary to quickly and accurately estimate and analyze traffic volume. ITS (Intelligent Transportation System) is a system that performs optimal traffic management by utilizing the latest ICT (Information and Communications Technology) technologies, and research has been conducted to analyze fast and accurate traffic volume through various techniques. In this study, we proposed a deep learning-based vehicle detection method using UAV (Unmanned Aerial Vehicle) video for real-time traffic analysis with high accuracy. The UAV was used to photograph orthogonal videos necessary for training and verification at intersections where various vehicles pass and trained vehicles by classifying them into sedan, truck, and bus. The experiment on UAV dataset was carried out using YOLOv3 (You Only Look Once V3), a deep learning-based object detection technique, and the experiments achieved the overall object detection rate of 90.21%, precision of 95.10% and the recall of 85.79%.