• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.3
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• pp.285-291
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• 2014

This study applied regression analysis to evaluate the impact of hourly average congestion calculated by bumper model in the congested area of each passage of each port on the peak time congestion, to suggest the model formula that can predict the peak time congestion. This study conducted regression analysis of hourly average congestion and peak time congestion based on the AIS survey study of 20 ports in Korea. As a result of analysis, it was found that the hourly average congestion has a significant impact on the peak time congestion and the prediction model formula was derived. This formula($C_p=4.457C_a+29.202$) can be used to calculate the peak time congestion based on the predicted hourly average congestion.

• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.5
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• pp.483-490
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• 2013

In this study, we analyzed AIS measured data for ten days by selecting the four main ports with many ships arriving in the national ports. The peak time congestion of the main ports, calculated by survey research, was about 3.8-5.7 times higher than the hourly average congestion. This is very different from the results of the advanced research, evaluating the marine traffic congestion of the Ulsan main port based on the existing Port-MIS statistical data, which showed a peak time congestion of about 1.7 times higher than the hourly average. This identifies the problem of distorting the traffic characteristics of the current passage. Therefore, in order to evaluate marine traffic congestion, it would be more appropriate to calculate it based on survey research, rather than Port-MIS statistical data.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.1
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• pp.1-8
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• 2017

In this study, a congestion assessment was conducted to verify seasonal differences in congestion for major coastal traffic routes and fairways in major ports with GICOMS Data for 7 days without issuing a special weather report. As a result, a maximum of 11 % and 82 % are shown, with an average of 3.5 % and a 30 % seasonal difference for hourly average congestion and peak time congestion. Therefore, seasonal differences for the target area should be taken into consideration to perform further congestion assessments, particularly for maritime traffic safety assessments, and keen attention should be given to setting up safety measures against congestion.

• Journal of Korean Society of Transportation
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• v.33 no.2
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• pp.214-222
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• 2015

Jeju International Airport has become the most delayed airport in Korea, due to increased demand in air passengers and unexpected local weather condition. Observing the demands continuously grow for a decade, the airport is expected to be saturated in the near future. As a part of effort to prepare effective and timely measure for this expected situation, airport planners seeks the annual runway capacity, i.e., the appropriate number of flight operations in a given year with tolerable delay. In practice, the FAA formula is frequently adopted for the capacity estimation. The method, however, has intrinsic issues: 1) the hourly capacity imbedded in the formula is not clearly defined and thus the estimated value is vulnerable to be subjective judgement, and 2) the formula doesn't consider aircraft delay resulted from runway congestion. In this paper, we explain a novel method for estimating the daily runway capacity and then converting to the annual capacity taking into account the aircraft delay. In this paper, average delay of aircraft was measured using microscopic air traffic simulation model. Daily capacity of the runways were analyzed based on the simulation outputs and the method to assess the yearly capacity is introduced. Using a microscopic simulation model named TAAM, we measure the average aircraft delay at various levels of flight demand, and then estimate the practical daily runway capacity. The estimated daily and annual runway capacities of Jeju airport are about 460 operations a day which is equal to 169,000 operations year. The paper discusses how to verify the simulation model, and also suggests potential enhancement of the method.