• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2483-2503
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• 2016

Traffic congestion is a severe problem in many modern cities around the world. Real-time and accurate traffic congestion identification can provide the advanced traffic management systems with a reliable basis to take measurements. The most used data sources for traffic congestion are loop detector, GPS data, and video surveillance. Video based traffic monitoring systems have gained much attention due to their enormous advantages, such as low cost, flexibility to redesign the system and providing a rich information source for human understanding. In general, most existing video based systems for monitoring road traffic rely on stationary cameras and multiple vehicle tracking method. However, most commonly used multiple vehicle tracking methods are lack of effective track initiation schemes. Based on the motion of the vehicle usually obeys constant velocity model, a novel vehicle recognition method is proposed. The state of recognized vehicle is sent to the GM-PHD filter as birth target. In this way, we relieve the insensitive of GM-PHD filter for new entering vehicle. Combining with the advanced vehicle detection and data association techniques, this multiple vehicle tracking method is used to identify traffic congestion. It can be implemented in real-time with high accuracy and robustness. The advantages of our proposed method are validated on four real traffic data.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.85-95
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• 2009

Congestion on expressways is increasing in spite of continuous road construction. In enlargement of expressway capacity to lessen congestion, a long period is needed and in the case of traffic congestion, it would be impossible to avoid long periods of traffic congestion. So, it is necessary to cope with traffic congestion through continuous traffic condition monitoring, analysis of the causes of congestion and the development of alternatives before traffic conditions worsen. A congestion index that can express traffic operating conditions measurably is needed to monitor those conditions. Thus, in this research, a new congestion index, the Traffic Condition Index (TCI), is developed. TCI is able to evaluate roads that have different grades (or design speeds) and to judge traffic condition as good, fair and poor (congested). In addition, TCI has merits in that it can strengthen the function of existing Freeway Traffic Management Systems (FTMS) and can be applied to congestion management easily: TCI calculates congestion intensity and severity using data obtained from existing FTMS. In order to validate TCI, it was applied to the Kyungbu Expressway and the Seohaean Expressway. As a result, TCI shows a good performance in the aspect of applicability and ability of presentation of traffic conditions compared with travel speed and Travel Time Index (TTI).

• International Journal of Highway Engineering
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• v.10 no.3
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• pp.119-128
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• 2008

On the many highways, severe traffic congestions happen chronically and make traffic problems like reduction of mobility because of rapid increase of vehicles though road construction has been last. In order to solve these traffic problems, it is needed to find the trend and the symptom of traffic congestion and to analyze the cause of congestion and the(spatial) range affected by congestion. To develop the traffic condition monitoring index prior to doing all those things is most important. With this reason, many countries including U.S. had been developed the congestion criteria and indices. In this paper, applicability and characteristics of existing traffic congestion indices were considered and the direction for development of a new traffic condition index was suggested to achieve an effective traffic management.

• International Journal of Highway Engineering
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• v.18 no.3
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• pp.11-19
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• 2016

PURPOSES : This study supports the evidence that it is possible to rehabilitate a damaged pavement with a lane closure specifically based on the Gimcheon~Sunsan project. METHODS : The prediction results from the simulation programs were compared with field monitoring, which focused on traffic management planning, congestion (length, time, and passing speed), bypass, and user cost, among others. RESULTS : The research results showed that lane closure application and pavement repair of the aged pavement in Korea were possible, even though the prediction results were minimally different from the field monitoring. The road agency contributes to service life extension of the rehabilitated pavement using this method. CONCLUSIONS : A marginal effect caused by the lane closure was observed on travelling users or vehicles, and the user cost of pavement repair decreased. Therefore, introducing the repair method or rehabilitation in Korea is possible. Information dissemination through various media was properly done to execute the project well. Moreover, the construction area traffic utilized nearby alternative roads. Therefore, improving the repaired pavemen's service life while ensuring that the pavement management agency can provide a road with comfortable user riding quality was possible.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.2
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• pp.196-205
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• 2000

As the number of cars is suddenly increasing, the number of cars on road exceeds the capacity of the road. In order to disperse the stream of traffic, there are many approaches for calculating the degree of congestion using traffic monitoring camera, and analyzing the velocity or the number of moving objects. Since those methods use background image, it is necessary to prepare the proper background image. In this paper, we proposed the algorithm to calculate the degree of congestion without background image. We perform DCT to the road image to obtain the edge information of cars, and then use it for calculating the degree of congestion.

• Transportation Technology and Policy
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• v.10 no.4
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• pp.39-47
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• 2013

• Journal of Communications and Networks
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• v.18 no.3
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• pp.513-522
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• 2016

We propose a mechanism for monitoring load in quality of service (QoS)-enabled wireless networks and show how it can be used for network management as well as for dynamic pricing. Mobile network traffic, especially video, has grown exponentially over the last few years and it is anticipated that this trend will continue into the future. Driving factors include the availability of new affordable, smart devices, such as smart-phones and tablets, together with the expectation of high quality user experience for video as one would obtain at home. Although new technologies such as long term evolution (LTE) are expected to help satisfy this demand, the fact is that several other mechanisms will be needed to manage overload and congestion in the network. Therefore, the efficient management of the expected huge data traffic demands is critical if operators are to maintain acceptable service quality while making a profit. In the current work, we address this issue by first investigating how the network load can be accurately monitored and then we show how this load metric can then be used to provide creative pricing plans. In addition, we describe its applications to features like traffic offloading and user satisfaction tracking.

• Journal of Korea Multimedia Society
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• v.14 no.7
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• pp.933-939
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• 2011

Recent heavy rains have caused natural disasters such as flooding and landslides nationwide. Because of flooding occurrence in most of the roads, traffic congestion and isolation caused many loss especially at rush hour. Constant monitoring and analysis of past disaster history data are needed to prevent disasters on areas prone to floods and disaster risk areas. If we managed to obtain traffic volume, speed, phase around intersection using disaster history data when disasters occurred, we can analyse traffic congestion, change of disaster scale and rainfall. In this study, We select a target district to develop by using a route from Dae-nam intersection in Busan Namgu Daeyoeon-dong, over Gwangan large bridge up until Haeundae Olympic intersection, We developed a system which searches disaster history information, traffic volume using disaster history data based on user selection of the road.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.72-84
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• 2017

Together with the Big Data of the 4th Industrial Revolution, the traffic information system has been changed to an section detection system by the point detection system. With DTG(Digital Tachograph) data based on Global Navigation Satellite System, the properties of raw data and data according to processing step were examined. We identified the vehicle trajectory, the link travel time of individual vehicle, and the link average travel time which are generated according to the processing step. In this paper, we proposed a application method for traffic management as characteristics of processing data. We selected the historical data considering the data management status of the center and the availability at the present time. We proposed a method to generate the Travel Time Index with historical link average travel time which can be collected all the time with wide range. We propose a method to monitor the traffic congestion using the Travel Time Index, and analyze the case of intersections when the traffic operation method changed. At the same time, the current situation which makes it difficult to fully utilize DTG data are suggested as limitations.

• The KIPS Transactions:PartC
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• v.9C no.4
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• pp.489-496
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• 2002

This study proposes a new polling algorithm allowing dynamic change in polling period based on line utilization prediction. Polling is the most important function in network monitoring, but excessive polling data causes rather serious congestion conditions of network when network is In congestion. Therefore, existing multiple polling algorithms decided network congestion or load of agent with previously performed polling Round Trip Time or line utilization, chanced polling period, and controlled polling traffic. But, this algorithm is to change the polling period based on the previous polling and does not reflect network conditions in the current time to be polled. A algorithm proposed in this study is to predict whether polling traffic exceeds threshold of line utilization on polling path based on the past data and to change the polling period with the prediction. In this study, utilization of each line configuring network was predicted with AR model and violation of threshold was presented in probability. In addition, suitability was evaluated by applying the proposed dynamic polling algorithm based on line utilization prediction to the actual network, reasonable level of threshold for line utilization and the violation probability of threshold were decided by experiment. Performance of this algorithm was maximized with these processes.