• KDI Journal of Economic Policy
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• v.35 no.4
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• pp.31-61
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• 2013

The purpose of this study is to calculate the economic value of transport demand forecasting risks in the road PPP project. Under the assumption that volatility of the road PPP project value occurs only in regard with uncertainty of traffic volume forecasting, this study calculates the economic value of the traffic forecasting risks in the case of the road PPP project. To that end, forecasted traffic volume is assumed to be a stochastic variable and to follow the Geometric Brownian motion as time passes. In particular, this study attempts to differentiate itself from existing studies that simply use an arbitrary assumption by presenting the application of different traffic volume growth volatility and the rates before and after the ramp-up period. Analysis of the case projects reveals that the risk premium related to traffic volume forecast of the project turns out as 7.39~8.30%, without considering option value-such as minimum revenue guarantee-while the project value volatility caused by transport demand forecasting risks is 17.11%. As the discount rate grows higher, the project value volatility tends to decrease and volatility in project value is always suggested to be larger than that in transport volume influenced by leverage effect due to fixed expenditure. The market value of transport demand forecasting risk-calculated using the project value volatility and risk premium-is analyzed to be between 0.42~0.50, implying that a 1% increase or decrease in the transport amount volatility would lead to a 0.42~0.50% increase or decrease in risk premium of the project.

• Journal of Korean Society of Transportation
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• v.34 no.5
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• pp.421-436
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• 2016

Public-Private-Partnerships tend to be committed high project development cost and recover the cost through future revenue during the operation period. In general, long-term concession can bring on more revenue to private investors, but short-term concession less revenue due to the short recovering opportunities. The concession period is usually determined by government in advance or by the private sectors's proposal although it is a very crucial factor for the PPPs. Accurate traffic forecasting should be most important in planing and evaluating the operation period in that the forecasted traffic determines the project revenue with user fees in PPPs. In this regards, governments and the private investors are required to consider the traffic forecast risk when determining concession period. This study proposed a model for the optimal concession period in the PPPs transportation projects. Monte Carlo simulation was performed to find out the optimal concession period while traffic forecast uncertainty is considered as a project risk under the expected return of the private sector. The simulation results showed that the optimal concession periods are 17 years and 21 years at 5.5% and 7% discount level, respectively. This study result can be applied for the private investors and/or any other concerned decision makers for PPPs projects to set up a more resonable concession period.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.30-44
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• 2020

The application of PPLT is difficult to analyze and judge only from the effects of the delay time. In this study, the application of PPLT was proposed using not only the delay time of PLT and PPLT due to the change in traffic volume and the number of opposite straight lanes but also the traffic volume of passing a left turn and the number of conflict risks as indicators. According to the analysis, the more left-turn traffic than capacity and the less opposite-straight volume, the greater the PPLT effect. On the other hand, if the left-turn traffic is below capacity, the delay time will be reduced partially, but the overall passing left turn volume will not increase, and the conflict risk will increase. In addition, the conflict risk increases in the third lane or higher. Moreover, the difference of passing left-turn volume between PLT and PPLT showed a pattern similar to the delay time difference, and the PPLT coverage was wider than the difference in delay time and was associated more with the conflict risk numbers. Therefore, it would be reasonable to use passing left-turn traffic primarily, consider the delay time below the left-turn capacity, and consider the conflicting risk numbers simultaneously at or above the opposite straight three lanes.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.10a
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• pp.137-139
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• 2014

우리나라 항만을 입출항하는 선박은 연간 390,245척(2013년)이며, 연안해역을 통항하는 선박은 우리나라 남해안이 세계에서도 통항척수가 많은 해역이다. 이러한 연안 해역에서 거리별 통항교통량 분포 및 해양사고 분포를 통하여 연안해역 거리별 위험도를 파악하여 교통량 분산 등을 유도하여 해상교통 안전을 향상시키는데 목적이 있다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.11a
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• pp.271-272
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• 2018

부산항 신항은 현재 21개의 선석 규모에서 2030년까지 총 40선석까지 확대할 계획을 갖고 있다. 항만의 확대에 따라 선박 통항량 증가가 예상되며, 이를 대비해 해상교통관제도 해상교통량을 기반으로 집중관제구역을 설정할 필요가 있다. 본 연구는 부산항 신항을 대상으로 해상교통위험도 모델을 이용해 위험구역을 정량화하고 집중적으로 관제가 필요한 구역을 도출하는 것을 목적으로 한다.

• Journal of Korean Society of Transportation
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• v.17 no.2
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• pp.29-40
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• 1999

복잡한 현대 문명 생활을 영위하는 가운데 각종 위험물질이 날마다 생산되어 운반되어지고 있다. 이러한 위험물질이 운반되는 과정에서 위험물사고발생은 불가피하다. 위험물사고는 발생확률은 낮지만 일단 사고발생시 인명, 환경, 재산피해가 심각하기 때문에 가능한 한 피해를 최소화하기 위한 대책이 필요하다. 본 연구에서는 공로수송에 있어 위험물질운송에 따른 경로별 위험도 분석을 위한 모형을 개발하고, 본 모형에 기초하여 계산된 링크별 위험도를 낮추기 위한 대책을 제시하였다. 각 링크별 위험도를 계산하기 위해서는 링크별 교통량, 사고 데이타 및 위험물질별 사고시 피해영향규모 등을 결정해야 하는 바, 이러한 작업은 사실상 수작업으로 불가능하다. 이를 자동적으로 수행하는 방안으로 지리정보시스템을 활용하였다 또한, 여러 가지 위험물질별 위험도 분석에서 위험물사고 저감대책, 위험물사고시 피해최소화 대책 등 일련의 작업을 하나의 시스템에서 이루어지도록 하는 의사결정지원시스템 형태의 위험물수송관리시스템으로 개발하였다. 최종적으로는 위험물질 중 대부분을 차지하는 석유.화학물질을 가장 많이 다루는 지역인 울산지역을 시범지역으로 선정하여 본 연구에서 제시한 모형을 적용해 보았다.

• Journal of Korean Society of Transportation
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• v.17 no.3
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• pp.117-130
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• 1999

Earthquakes damage roadway bridges and structures, resulting in significant impacts on transportation system Performance and regional economy. Seismic risk analysis (SRA) procedures establish retrofit priorities for vulnerable highway bridges. SRA procedures use average daily traffic volumes to determine the relative importance of a bridge. This research develops a cost-effective transportation network analysis (TAN) procedure for evaluating numerous traffic flow analyses in terms of the additional system cost due to failure. An important feature of the TNA Procedure is the use of an associative memory (AM) approach in the artificial intelligence held. A simple seven-zone network is developed and used to evaluate the TNA procedure. A subset of link failure system states is randomly selected to simulate synthetic post-earthquake network flows. The performance of different AM model is evaluated. Results from numerous link-failure scenarios demonstrate the applicability of the AM models to traffic flow estimation.

• Journal of Korean Society of Transportation
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• v.31 no.1
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• pp.57-64
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• 2013

Recently, bicycle accidents have increased with the ever-increasing number of cyclists. Bicycle accidents occurred frequently in intersections, and the perpendicular collision between a right-turning car and a crossing bicycle was the most prevalent accident type. In particular, the collision was caused by motorists' carelessness. In other words, the accident-involved motorists did not pay sufficient attention to a bicycle crossing behind them. Another cause was a cyclist's higher speed than pedestrians. This paper evaluated the potential risk of the collision between right-turning cars and crossing bicycles based on simulation experiments, with motorists' speed and carelessness focused on. Consequently, it was found that to reduce the potential risk of the collisions a motorist should slow down and pay more attention to the rear sight by turning his/her head.

• 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.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.75-83
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• 2022

Korea, which has the highest pedestrian fatality rate among OECD countries, is making efforts to improve the safe walking environment by enacting laws focusing on pedestrian. Spatial clustering was conducted with scan statistics after examining the social network data related to traffic accidents for children and seniors. The word cloud was used to examine people's recognition Campaigns for children and literature survey for seniors were in main concern. Naedang and Yongsan are the regions with the highest relative risk of weak pedestrian for children and seniors. On the contrary, Bongmu and Beomeo are the lowest relative risk region. Naedang-dong and Yongsan-dong of Daegu Metropolitan City were identified as vulnerable areas for pedestrian safety due to the high risk of pedestrian accidents for children and the elderly. This means that the scan statistics are effective in searching for traffic accident risk areas.