• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.3
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• pp.298-305
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• 2019

The demand for the revitalization of marine tourism in Busan North Port is increasing due to changes in functions such as an increase in harbor traffic volume and the expansion of marine leisure space in Busan. As a result, Busan City plans to set a phased alleviation target for prohibition of cruise ship operations, and to lift the prohibition of excursion ship operations in North Port following the cancellation of the prohibition of excursion ship operations in South Port in 2017. The purpose of this study is to evaluate the risk of excursion ship operations in Busan North Port by applying the marine traffic assessment index and to examine the possibility of excursion ship operations. For this purpose, port status, marine accidents, and traffic flow of Busan North Port were investigated. In addition, marine traffic assessment indexes, such as traffic congestion, risk based on an ES Model, and IWRAP MkII, a maritime risk assessment tool, were used to assess the risk and possibility of excursion ship operations in Busan North Port. This study can be used as basic data for analyzing the risk factors that may occur when excursion ships are operated in Busan North Port and to define how excursion ships should operate, with related safety measures.

• Journal of Digital Convergence
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• v.16 no.10
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• pp.213-222
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• 2018

This study was conducted to derive the traffic accident risk index through the recognition of the elderly driver's driving pattern to reduce the traffic accident rate of elderly drivers and to reflect them in the renewal and return policy of driver's license accordingly. First, the traffic accident risk index is defined by analyzing the behavioral characteristics of older drivers to derive the major factors that lead to traffic accidents. Second, we present a method to measure the traffic accident risk index from the driving pattern of the elderly through the smart-phone, the camera and the distance sensor attached to the car. Finally, we derive three thresholds by computer simulation and determine the accident risk from the measured traffic accident risk index as four steps and suggest ways to ensure safe driving of older drivers. It is required to objectively assess the driving ability of an aged driver in accordance with the proposed method, and to induce the driver to reset the driver's license renewal cycle and voluntarily return the driver's license to minimize social costs due to increased traffic accidents.

• Journal of Navigation and Port Research
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• v.42 no.2
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• pp.97-106
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• 2018

Despite the development of safety measures and improvements in preventive systems technologies, maritime traffic accidents that involve ships carrying hazardous and noxious substances (HNS) continuously occur owing to increased amount of HNS goods transported and the growing number of HNS fleet. To prevent maritime traffic accidents involving ships carrying HNS, this study proposes an intuitive route risk assessment technique using risk contours that can be visually and quantitatively analyzed. The proposed technique offers continuous information based on quantified values. It determines and structures route risk factors classified as absolute danger, absolute factors, and influential factors within the assessment area. The route risk is assessed in accordance with the proposed algorithmic procedures by means of contour maps overlaid on electronic charts for visualization. To verify the effectiveness of the proposed route risk assessment technique, experimental case studies under various conditions were conducted to compare results obtained by the proposed technique to actual route plans used by five representative companies operating the model ship carrying HNS. This technique is beneficial not only for assessing the route risk of ships carrying HNS, but also for identifying better route options such as recommended routes and enhancing navigation safety. Furthermore, this technique can be used to develop optimized route plans for current maritime conditions in addition to future autonomous navigation application.

• Korean Journal of Culture and Social Issue
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• v.8 no.1
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• pp.61-77
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• 2002

This study focuses on drivers' risk perception & construct in risk scene. The measures used were the scores of hazard perception, namely the subjects' evaluation of the degree of risk through the 'Q-sorting' with 30 drivers. The subjects were divided into 3 groups according to their evaluating score, Z-score, road users' hazard(type 1), environmental hazard(type 2), situational hazard(type 3). And ten constructs derived from Q-sorting were compared through 'consensus item analysis'. It suggest that there are different in constructs for risk perception. Then those results are discussed in terms of theoretical and practical implication of traffic safety including accidents analysis and drivers' education.

• Journal of Korean Society of Transportation
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• v.14 no.2
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• pp.119-136
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• 1996

The evaluation of risk level or possibility of traffic accidents is a fundamental task in reducing the dangers associated with current transportation system. However, due to the lack of data and basic researches for identifying such factors, evaluations so far have been undertaken by only the experts who can use their judgements well in this regard. Here comes the motivation this thesis to evaluate such risk level more or less in an automatic manner. The purpose of this thesis is to test the fuzzy-logic theory in evaluating the risk level of traffic accidents. In modeling the process of expert's logical inference of risk level determination, only the geometric features have been considered for the simplicity of the modeling. They are the visibility of road surface, horizontal alignment, vertical grade, diverging point, and the location of pedestrain crossing. At the same time, among some inference methods, fuzzy composition inference method has been employed as a back-bone inference mechanism. In calibration, the proposed model used four sites' data. After that, using calibrated model, six sites' risk levels have been identified. The results of the six sites' outcomes were quite similar to those of real world other than some errors caused by the enforcement of the model's output. But it seems that this kind of errors can be overcome in the future if some other factors such as driver characteristics, traffic environment, and traffic control conditions have been considered. Futhermore, the application of site's specific time series data would produce better results.

• 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 Convergence for Information Technology
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• v.11 no.7
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• pp.14-20
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• 2021

Most accidents caused by road icing in winter lead to major accidents. Because it is difficult for the driver to detect the road icing in advance. In this work, we study how to accurately detect road traffic emerging risk using AutoML and CNN's ensemble model that use both structured and unstructured data. We train CNN-based road traffic emerging risk classification model using images that are unstructured data and AutoML-based road traffic emerging risk classification model using weather data that is structured data, respectively. After that the ensemble model is designed to complement the CNN-based classification model by inputting probability values derived from of each models. Through this, improves road traffic emerging risk classification performance and alerts drivers more accurately and quickly to enable safe driving.

• Journal of Navigation and Port Research
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• v.41 no.3
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• pp.93-102
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• 2017

When VTSOs (Vessel Traffic Service Operator) determine the degree of collision risk for two vessels, they consider comprehensive information about each vessel's course, speed, DCPA, TCPA, and encountering situation. In this study, we proposed a utility function based on the risk attitudes of VTSOs toward the Risk Index (RI). The RI was calculated using the risk of encounter, the risk of approach, and the risk of time for two vessels in order to predict each ship's collision risk from the VTS viewpoint. We obtained each coefficient of the RI and the risk attitude through a survey of collision risks among VTSOs of Korea. In order to verify whether the proposed utility is reasonable, we validated by applying the degree of collision risk to some historical cases of accidents in Busan port along with the Ship of ES value($ES_S$) of ES(Environmental Stress) model.

• Ocean Systems Engineering
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• v.12 no.3
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• pp.267-284
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• 2022

A subsea pipeline designed across active shipping lane prones to failure against external interferences such as anchorage activities, hence risk assessment is essential. It requires quantifying the geometric probability derived from ship traffic distribution based on Automatic Identification System (AIS) data. The actual probability density function from historical vessel traffic data is ideal, as for rapid assessment, conceptual study, when the AIS data is scarce or when the local vessels traffic are not utilised with AIS. Recommended practices suggest the probability distribution is assumed as a single peak Gaussian. This study compares several fitted Gaussian distributions and Monte Carlo simulation based on actual ship traffic data in main ship direction in an active shipping lane across a subsea pipeline. The results shows that a Gaussian distribution with five peaks is required to represent the ship traffic data, providing an error of 0.23%, while a single peak Gaussian distribution and the Monte Carlo simulation with one hundred million realisation provide an error of 1.32% and 0.79% respectively. Thus, it can be concluded that the multi-peak Gaussian distribution can represent the actual ship traffic distribution in the main direction, but it is less representative for ship traffic distribution in other direction. The geometric probability is utilised in a quantitative risk assessment (QRA) for subsea pipeline against vessel anchor dropping and dragging and vessel sinking.

• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.95-102
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• 2011

This paper presents a Driving Risk Model (DRM) based on driving speed choices using an Ordered Response Probit (ORP) model. The DRM is conceptualized based on the relation between speed deviation and the occurrence of crashes found by Solomon. The impacts of various driving risk factors are revealed by applying the DRM to evaluate the effectiveness of In-Vehicle Traffic Warning Information (IVTWI) in expressway driving. Regarding driving risk, the results show that: (1) the risk is lower among male drivers, those with more driving experience and those with less accident history, (2) the risk is higher when driving takes place on wet road surface, in the afternoon, and under conditions of low traffic volume, and (3) the risk is also higher on both downgraded and long curve sections. Additionally, the results provide evidence that provision of IVTWI can decrease the driving risk. The proposed DRM provides a solution for assessing the traffic safety impacts of countermeasures on roadways when there is a shortage of traffic accidents data.