• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.4
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• pp.381-388
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• 2018

This study proposes marine traffic volume estimation method considering ship speed, a factor excluded from the existing method. Ten days of GICOMS marine traffic data from Pyeongtaek and Dangjin ports was applied to this study. As a result, converted traffic volume with the proposed estimation method showed an increase of 4.41 (${\pm}0.99$) times or decrease of 0.59 (${\pm}0.04$) at most, compared with the existing estimation method. Average marine traffic congestion for each time applying the proposed estimation method showed an increase of 1.43 (${\pm}0.10$) compared with the existing estimation method. The maximum marine traffic congestion for each time was 1.62 (${\pm}0.34$) times higher compared with the existing estimation method. Marine traffic peak time, defined as the highest point of marine traffic congestion, was evaluated to be different from that of the existing method because of distribution of vessel speed. In conclusion, considering ship speed is necessary when estimating marine traffic volume to produce a practical estimate of marine traffic capacity.

• Journal of Navigation and Port Research
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• v.32 no.7
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• pp.521-527
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• 2008

The Istanbul Strait is one of the important waterways in the world. And its southern entrance has a highly congested local traffic. Till now there are several studies regarding how the Istanbul Strait is dangerous to navigate and how those dangers can be mitigated. But there is no study regarding local traffic which is posing great collision risk. In a certain traffic area, marine traffic safety assessment parameters are traffic volume, frequency of collision avoidance maneuver, traffic density, traffic flow and potential encounter, In this paper local traffic volume, traffic flow and potential encounter number of local traffic vessels and possibility of collision are investigated in order to find degree of danger at the southern entrance of the Istanbul Strait. Finally by utilizing those, risky areas are determined for southern entrance of the Istanbul Strait. Results have been compared to a previous study regarding risk analysis at congested areas of the Istanbul Strait (Aydogdu, 2006) and consistency of the results were presented.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.2
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• pp.186-192
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• 2014

In this paper, we analysed vessel traffic volume and patterns of traffic flow for ships using areas where included wind farm site and adjacent waters of Daejeong Offshore Wind Farm, and estimated traffic volume by classified navigational routes according to suggestion of rational routeing measures on the basis of classified patterns after installation of offshore wind facilities. Also, we assessed vessel traffic safety for each designed routeing measures on the basis of estimated traffic volume and proposed requisite countermeasures for the safe navigation of ships. With a result of analysing patterns of traffic flow, the current traffic flow was classified by 8 patterns and the annual traffic volume was predicted to 8,975 ships. On the basis of these, expected the vessel traffic volume according to designed four routeing mesaures after installation of wind farm. As result of assessing vessel traffic safety by using powered-vessel collision model of SSPA on the basis of the estimated traffic volume, the value of collision probability was less than safe criteria $10^{-4}$. Thereby we made sure usability of the designed routeing measures for the safe navigation of ships.

• Journal of the Korean Society of Marine Environment & Safety
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• v.10 no.2 s.21
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• pp.29-34
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• 2004

The marine traffic congestion has increased due to the expansion of vessel traffic volume in Korean coastal waterway these days. Heavy traffic could bring serious marine casualties which cause the loss of human lives, properties and marine pollution in coastal area. In this paper, the probability analysis of marine casualties in Korean coast. To achieve this aim, clears up the cause of accident and examines closely the mutual relations among marine casualties, weather condition, and marine traffic volume. These casualties are classified into several patterns or the point of view of ship's size, ship's type and ship's age and its characteristics of each pattern are described In detail.

• Proceedings of KOSOMES biannual meeting
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• 2017.04a
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• pp.78-78
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• 2017

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.06a
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• pp.515-517
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• 2013

We carried out the maritime safety audit for Sandal Water Bridge constructed between Geje-Do and Sandal-Do in 2015. To study as to whether can be secured the marine traffic safety for this area, this research investigated and performed the marine accident, marine traffic volume, the marine traffic flow simulation and shiphandling simulation. It is considered to be required the quantitative guidelines for maritime safety audit including audit target area and formal audit object etc.

• Proceedings of KOSOMES biannual meeting
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• 2004.05b
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• pp.13-18
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• 2004

The marine traffic congestion has increased due to the expansion of vessel traffic volume in Korean coastal waterway these days. Heavy traffic could bring serious marine casualties which cause the loss of human lives, properties and marine pollution in coastal area. In this paper. the probability analysis of marine casualties in Korean coastal To achieve this aim, clears up the cause of accident and examines closely the mutual relations among marine casualties, weather condition, and marine traffic volume. These casualties are classified into several pattens or the point of view of ship‘s size, ship’s type and ship‘s age and its characteristics of each patten are described in detail.

• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.6
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• pp.612-620
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• 2013

In this study, time series analysis was tried, which is widely applied to demand forecast of diverse fields such as finance, economy, trade, and so on, different from previous regression analysis. Future marine traffic volume was forecasted on the basis of data of the number of ships entering Incheon port from January 1996 to June 2013, through courses of stationarity verification, model identification, coefficient estimation, and diagnostic checking. As a result of prediction January 2014 to December 2015, February has less traffic volume than other months, but January has more traffic volume than other months. Also, it was found out that Incheon port was more proper to ARIMA model than exponential smoothing method and there was a difference of monthly traffic volume according to seasons. The study has a meaning in that future traffic volume was forecasted per month with time series model. Also, it is judged that forecast of future marine traffic volume through time series model will be the more suitable model than prediction of marine traffic volume with previous regression analysis.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.1
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• pp.33-41
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• 2014

Unlike the existing regression analysis, this study anticipated future marine traffic volume using time series analysis and artificial neural network model. Especially, it tried to anticipate future marine traffic volume by applying predictive value through time series analysis on artificial neural network model as an additional input variable. This study used monthly observed values of Incheon port from 1996 to 2013. In order for the verification of the forecasting of the model, value for 2013 is anticipated from the built model with observed values from 1996 to 2012 and a proper model is decided by comparing with the actual observed values. Marine traffic volume of Incheon port showed more traffic than average for May and November by 5.9 % and 4.5 % respectably, and January and August showed less traffic than average by 8.6 % and 4.7 % in 2015. Thus, it is found that Incheon port has difference in monthly traffic volume according to the season. This study can be utilized as a basis to reflect the characteristics of traffic according to the season when investigating marine traffic field observation.

• Journal of Navigation and Port Research
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• v.31 no.5 s.121
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• pp.353-359
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• 2007

Effective plan and operation managements can be established in advance if the traffic volume of container ship will be forecasted in the trend for container port's cargo volume to increase. At the viewpoint for marine traffic the number of incoming and outgoing container ship can be presumed in the long run and organised rational plan to deal the demand of marine traffic on the basis. Therefore, the paper estimated the future traffic volume of incoming and outgoing container ship for Busan, Gwangyang, and Incheon port on a forecasting data basis of container volume suggested in the national ports base plan. The trends of volume per ship on container were estimated with ARIMA models and seasonal index was computed. Thus the traffic volume of container ship in the future was estimated computing with volume per ship in 2011,2015, and 2020 respectively.