• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.5
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• pp.527-534
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• 2019

Several types of mathematical analysis methods are used for port waterway risk assessment based on marine traffic volume. In Korea, a marine traffic congestion model that standardizes the size of the vessels passing through the port waterway is applied to evaluate the risk of the waterway. For example, when marine traffic congestion is high, risk situations such as collisions are likely to occur. However, a scientific review is required to determine if there is a correlation between high density of maritime traffic and a high risk of waterway incidents. In this study, IWRAP Mk2(IALA official recommendation evaluation model) and a marine traffic congestion model were used to analyze the correlation between port waterway risk and marine traffic congestion in the same area. As a result, the linear function of R2 was calculated as 0.943 and it was determined to be significant. The Pearson correlation coefficient was calculated as 0.971, indicating a strong positive correlation. It was confirmed that the port waterway risk and the marine traffic congestion have a strong correlation due to the influence of the common input variables of each model. It is expected that these results will be used in the development of advanced models for the prediction of port waterway risk assessment.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.1370-1376
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• 2008

The structure of railroad or subway is that low fare transportation system of the large traffic volume. Like this structure is subjected to the cyclic load of moving vehicle. Consequently the result of the settlement analysis or plastic deformation prediction of railroad bed could be used as an important factor in safety of the railroad. The results of cyclic triaxial test were used in the numerical analysis of power model which Li and Selig(1994) developed. The soil samples were obtained from the construction site of railroad. Cyclic triaxial test was conducted with the variation of the magnitude of cyclic load and soil types. The large magnitude of plastic deformation in the railroad bed is caused of structure failure of the railroad.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10c
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• pp.499-501
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• 2001

무선 채널 상태는 같은 셀 안의 사용자의 수 또는 사용자의 움직이는 속도 등과 같은 많은 변수들로 인해 급격히 변화한다. 따라서 무선 채널의 효율적 관리는 무선 통신에 있어서 가장 중요한 고려사항이다. 효율적인 무선 채널 관리를 위해서는 정량적인 근거를 제시해 주는 기준인 트래픽 양 측정방안이 요구된다. 현재 3GPP의 UMTS문서에서 제시하고 있는 정량적인 근거는 오직 RLC 대회에 있는 양만을 참조한다. 이 경우 일정한 레이트(rate)론 유지하는 음성형 서비스(conversational service)에는 적당할 수 있지만 멀티미디어와 같이 레이트가 일정하지 않은 서데스에 대해서는 이후에 전송될 데이터에 대한 정확한 트래픽 양 측정이 불가능하다. 따라서 본 논문에서는 토큰 버켓 모델을 이용하여 이후에 들어올 데이터 양에 대하여 보다 정확한 트래픽 양을 예측할 수 있는 메커니즘을 제안한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.1
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• pp.73-80
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• 2018

In motorway traffic flow control, the conventional way based on real-time response has been changed into advanced way based on proactive response. Future traffic conditions over multiple time intervals are crucial input data for advanced motorway traffic flow control. It is necessary to overcome the uncertainty of the future state in order for forecasting multiple-period traffic volumes, as the number of uncertainty concurrently increase when the forecasting horizon expands. In this vein, multi-interval forecasting of traffic volumes requires a viable approach to conquer future uncertainties successfully. In this paper, a forecasting model is proposed which effectively addresses the uncertainties of future state based on the behaviors of temporal evolution of traffic volume states that intrinsically exits in the big past data. The model selects the past states from the big past data based on the state evolution of current traffic volumes, and then the selected past states are employed for estimating future states. The model was also designed to be suitable for data management systems in practice. Test results demonstrated that the model can effectively overcome the uncertainties over multiple time periods and can generate very reliable predictions in term of prediction accuracy. Hence, it is indicated that the model can be mounted and utilized on advanced data management systems.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.183-193
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• 2019

This study developed a shockwave detection and prediction of their extinction point method based on continuous wavelet transform using trajectory data from probe vehicles equipped with automotive sensors.. To analyze the effectiveness of the proposed method, this paper proposed two measures which are a distance error between the extinction points of the predictor and an time-location error of the extinction points. The proposed concept was proved using the micro simulation based experiment with three exogenous variables of traffic volume, lane-close duration, market penetration of probe vehicles. The analysis results show that the proposed method is capable of detecting the traffic shockwaves as well as predicting their extinction point, and also that the accuracy of the proposed method is highly dependent on the rate of the probe vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.203-213
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• 2021

A vehicle crash occurs due to various factors such as the geometry of the road section, traffic, and driver characteristics. A safety performance function has been used in many studies to estimate the relationship between vehicle crash and road factors statistically. And depends on the purpose of the analysis, various characteristic variables have been used. And various characteristic variables have been used in the studies depending on the purpose of analysis. The existing domestic studies generally reflect the average characteristics of the sections by quantifying the traffic volume in macro aggregate units such as the ADT, but this has a limitation that it cannot reflect the real-time changing traffic characteristics. Therefore, the need for research on effective aggregation units that can flexibly reflect the characteristics of the traffic environment arises. In this paper, we develop a safety performance function that can reflect the traffic characteristics in detail with an aggregate unit for one hour in addition to the daily model used in the previous studies. As part of the present study, we also perform a comparison and evaluation between models. The safety performance function for daily and hourly units is developed using a negative binomial regression model with the number of accidents as a dependent variable. In addition, the optimal negative binomial regression model for each of the hourly and daily models was selected, and their prediction performances were compared. The model and evaluation results presented in this paper can be used to determine the risk factors for accidents in the highway section considering the dynamic characteristics. In addition, the model and evaluation results can also be used as the basis for evaluating the availability and transferability of the hourly model.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.95-106
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• 2005

Road accidents are considered as the result of a complex interplay between road, vehicle, environments, and human factors. Little study, however, has been carried out on the attributes of human factor compared to the road geometric conditions and traffic conditions. The previous researches focused on mainly both traffic and geometric conditions on specific location. Therefore, it's hard to explain phenomenon of the high traffic accident rates where road and traffic conditions are good. Because of these reasons, accident analysis has contributed on geometric improvement and has not contributed on traffic management such as selection of attention section, driver napping alert, etc. The freeway incident management is also associated with reliable prediction of incident occurrences on freeway sections. This paper presents a method for estimating the effect of trip length on freeway accident rate. A PAR (Potential Accident Ratio), the new concept of accident analysis, considering TLFDs (Trip Length Frequency Distributions) is suggested in this paper. This approach can help to strengthen freeway management and to reduce the likelihood of accidents.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.4
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• pp.417-428
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• 2021

Since future maintenance cost estimation of infrastructure involves uncertainty, it is important to make use of a failure prediction model. However, it is difficult for local governments to develop accurate failure prediction models applicable to infrastructure due to a lack of budget and expertise. Therefore, this study estimated the life expectancy of asphalt road pavement of national highways using the Bayesian Markov Mixture Hazard model. In addition, in order to accurately estimate life expectancy, environmental variables such as traffic volume, ESAL (Equivalent Single Axle Loads), SNP (Structural Number of Pavement), meteorological conditions, and de-icing material usage were applied to retain reliability of the estimation results. As a result, life expectancy was estimated from at least 13.09 to 19.61 years by region. By using this approach, it is expected that it will be possible to estimate future maintenance cost considering local failure characteristics.

• Journal of Korea Port Economic Association
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• v.25 no.2
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• pp.73-94
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• 2009

In this paper the benefit was forecasted for traffic safety facilities to be constructed along the inland waterway between Phnom Penh and Chong Kneas(Siem Reap) port in Cambodia. First of all, the number of cruise ships passengers and cargo volumes were predicted. Second, the traffic volume of the cruise ships and cargo ships were calculated according to the prediction. Last, the safety benefit of traffic safety facilities was forecasted with the traffic after surveying the waterway accidents. The other benefit was also presented by converting the effect of relieving the emotional burden of navigators into currency value. Accordingly the entire benefit was estimated to be $14,990, $20,950 and $28,540 for pessimistic, moderate and optimistic prospects, in 2011. And then the entire benefits are calculated as $28,320, $63,060 and $95,230 for each prospect in the final estimation year 2020.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.19-28
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• 2009

In case of land development projects constructed, to solve induced transportation volume needs analysis of traffic demand. Trip-generation of land development projects is exactly predicted by using traffic instigating-basic-unit in each facility of land developments. But in case of a phase of trip-distribution, because a range of destinations is very enormous and it needs enormous data to reflect all of its characters, whenever trip-distribution is predicted, the method which assumes the rate of trip-distribution is same both before completion of land development projects and after is often used. But because there is no exact criterion, the method suggested above is also affected by subjective opinion. Accordingly, this study look over using trip-distribution of specific areas's DB and suggests a size of zone to predict a distribution of land development projects exactly. Also production - constrained gravity model which uses the gap between a distribution of suggested ranges and induced land development project is suggested for more exact prediction of trip-distribution. Besides accuracy of prediction is scrutinized by using Mean Squared Error.