• Journal of the Korean Society of Industry Convergence
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• v.4 no.1
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• pp.41-49
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• 2001

This study developed signal optimization algorithm by analyzing vehicle arrival patterns. The major principle of signal optimization is dissipate all queueing vehicle in 1cycle and assign delay time uniformly for all approaches. For this, this study used optimal green time and surplus green time. Optimal green time calculated by estimated traffic volume from vehicle arrival model. Surplus green time defined as the gap of optimal green time and queue dissipated time. And alternative cycle has minimum surplus green time was selected as the optimal cycle. Finally, total delay and average delay per vehicle can be calculated by using queueing theory.

• Industrial Engineering and Management Systems
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• v.9 no.4
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• pp.294-302
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• 2010

There is a trend toward the world's manufacturing sites moving to East Asia. After manufacture, these products are transported to the advanced nations for their consumption demands. Among such advanced nations, the U.S.A. has the largest demand, and then Japan and European countries follow. It should be noted that the infrastructures of the Asian districts used for the production sites are rather limited, and the volume of products transported from these districts of Asia to the U.S.A is becoming tremendously large. This situation is causing very serious traffic problems. New products are required to be transported swiftly by air. Once the consumption and market demands are stable however, the products should be sent rather slowly, but in larger amounts. However, the airports of China are quite restricted in capacity, while the transportation volume is becoming large. As a result, transportation cost and the time required for transportation are increasing. Now, a third method is appearing. This is the so-called Sea and Air transportation. The cost and time in transit of this mode take mean positions between Air and Ocean services. At present there exists no well-thought-out strategy for how to allocate these three methods of transportation. This paper is an attempt to theoretically describe this mechanism and to discover the optimal way to allocate the three modes. For this purpose, several mathematical properties of value and cost of the products are defined, and on this basis a simulation of the transportation is established.

• Journal of the Korean Institute of Navigation
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• v.15 no.2
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• pp.39-47
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• 1991

As per the rapid development of world economics the marine traffic volume was increased accordingly and caused frequent disasters in human lives and natural environment in the consequence of accidents. As the result of the above they started to establish Vessel Traffic System(VTS) and separation scheme in waterway from 1960' to prevent the marin traffic accident but the problem of safety at sea appears now as neither fully defined nor sufficiently analysed. At the present, the dominant factor in establishing the strategy of marine traffic has been safety of navigation concerning only with the ship, but the risk of society derives almost wholly from the nature of cargo. To measure the degree of danger for each ship there is suggested concept of safety factor numbers denoting the level of latent danger in connection with ship and her cargo. In this paper, where the strategy of VTS is put on controlling density of safety factor for control area. it suggested algorithms how to assign the vessels and also to get optimal sequence of vessels located to a sector in the sense of minimizing the passage delay. For the formulation of problem, min max and 0-1 programming methods are applied and developed heuristic algorithm is presented with numerical example to improve the efficiency of calculation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.7A
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• pp.757-767
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• 2008

Start Ongoing next generation networks are expected to be deployed over current existing networks, in the form of overlayed heterogeneous networks, in particular, in hot spot areas. Therefore, it will be necessary to develop an interworking technique such as load balancing, to achieve increased overall resource utilization in the various heterogeneous networks. In this paper, we present a new load balancing mechanism termed 'soft' load balancing where the IP(Internet Protocol) traffic of a user is divided into sub-traffic, each of which flows into a different access network. The terminology of soft load balancing involves the use of both load sharing and handover techniques. Through a numerical analysis, we obtain an optimal LBR (Load Balancing Ratio) for determining the volume of traffic delivered to each network over an overlayed multi-cell environment. Using the optimal LBR, a more reliable channel transmission can be achieved by reducing the outage probability efficiently for a given user traffic.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.34-39
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• 2001

The median barrier is one of the roadside hardware to prevent severe human and property damage from highway traffic accidents. The foreign standard of concrete median barrier was introduced and implemented without modification fitting to domestic vehicle and highway condition. In a car accident, median barrier doesn't protect vehicle effectively, especially for heavy vehicle such as bus and heavy truck. The purpose of this study is to develop the optimal performance design of concrete median barrier using the design of experiment with crash simulation analysis which is done by Pam-Crash that is one of the commercial crash simulation software. As a result of this study, an optimal design of concrete median barrier is obtained considering von Mises stress, volume and COG acceleration of truck.

• International Journal of Highway Engineering
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• v.12 no.2
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• pp.43-49
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• 2010

This study deals with the traffic accident of the Cheongju arterial link sections. The purpose of the study is to develop the traffic accident model. In pursuing the above, this study gives particular attentions to developing the ZAM(zero-altered model) model using the accident data of arterial roads devided by 322 small link sections. The main results analyzed by ZIP(zero inflated Poisson model) and ZINB(zero inflated negative binomial model) which are the methods of ZAM, are as follows. First, the evaluation of various developed models by the Vuong statistic and t statistic for overdispersion parameter ${\alpha}$ shows that ZINB is analyzed to be optimal among Poisson, NB, ZIP(zero-inflated Poisson) and ZINB regression models. Second, ZINB is evaluated to be statistically significant in view of t, ${\rho}$ and ${\rho}^2$ (0.63) values compared to other models. Finally, the accident factors of ZINB models are developed to be the traffic volume(ADT), number of entry/exit and length of median. The traffic volume(ADT) and the number of entry/exit are evaluated to be the '+' factors and the length of median to be '-' factor of the accident.

• Journal of the Korean Institute of Navigation
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• v.19 no.1
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• pp.33-48
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• 1995

In the process of containerization, the problem of regional maldistribution of container management plan arises seriously due to several factors like a number of unbalances of containers between loading and discharging ports. This study focus on the minimizing cost. This study is composed of two models which in effective management decision making show decision of the number of containers and transfer of empty containers. One is decision of the number of containers which carriers should possess by appropriate forecasting and the other is effective management decision making which includes the transfer of empty containers on calling ports. This study has suggested as follows, First, the Time Series analysis method, especially the "Exponential Smooting with Trend Adjustment" was used to forecast the trade volumes for the designated traffic route. Second, the Time Series analysis method in deciding the optimal number of owned container at the unbalances trade situation between East Bound and West Bound service, most important variables were found such as total traffic volume, the calling interval at a port, the number of days of voyage and the length of stay on shore of container for the optimal number of owned container. Third, effective management decision making model, which makes it possible to analyze the impacts of change in important matters such as lease and positioning policy, and actually influence decision making.on making.

• Journal of Korean Port Research
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• v.9 no.2
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• pp.39-49
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• 1995

Recently, the traffic volume has been greatly increased partly because of high growth rate of domestic and world economy, and partly because of increased transhipment demand resulting from the destruction of Kobe port by earthqwake early this year. So, container facilities in Pusan Port are under serious congestion. The congestion costs in connection with container traffic in Pusan Port is estimated to be 29.3 billion won in 1994. In 1995 the situation is still worsening. PECT has continued to grow annually by 35% in cargo handling exceeding more than 31% of the total container volumes handled in Korea. The BOR of container berths in PECT in 1994 is 75% reflecting extreme congestion in container traffic. The reason for such serious congestion in PECT is the shortage of container handling facilities in comparison with ever-increasing cargo traffic. In order to solve the provisional problem, the shortage of handling capacity, a model developed to optimize the operation of PECT is described and demonstrated. The model minimizes total port costs, including the costs of dock labour, facilities and equipment, ship, containers, and cargo. The object of this study is, through the model results, mainly to determine the optimal combination of berths and cranes under various circumstances and to show that total costs per ship or unit of cargo served can be reduced by increasing the number of cranes per berth and berth utilization above present levels. Eventually, the results obtained with this model in PECT suggest that increase to 3 in the number of cranes per existing berth could reduce the need for major investments in berths and even reduce operating costs.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.167-176
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• 2009

Several travel demand management schemes have been used for controlling overloaded traffics on urban area. To maximize efficiency of the travel management, traffic manager has to set target level that we try to arrive in advance, and then to find optimal variable to attain this goal. In this regard, this paper presents two travel demand management models, expressed by mathematical program, and also presents their solution algorithms. The first is to find optimal travel demand for origin-destination (OD) pair, based on average travel time between the OD pair, and the second is based on the ratio of volume over capacity on congested area. An example is given to test the models.

• 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%.