• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.553-560
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• 2010

This study examined the factors influencing the number of enforcement cases on traffic signal violation. The study collected enforcement data on traffic signal violation by multi-functional unmanned cameras across the Daegu metropolitan area, and analyzed the data to determine correlations among various factors including physical dimensions and engineering characteristics of the roadway as to how they would influence the number of violations. The resulting analysis provided a general model that assesses applicability for multi-functional unmanned cameras, and further shed helpful insights on efficient utilization of such traffic signal enforcement equipments in terms of installation thresholds and location. By identifying violation-prone features and characteristics and subsequent enforcement considerations, this research also supports safety efforts in reducing the number of traffic accidents as well.

• Journal of Navigation and Port Research
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• v.33 no.8
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• pp.519-524
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• 2009

Although it is expected to provide fundamental data for advanced VTS system by analyzing traffic accidents in VTS area, there is no quantitative analysis to find it.. In this research, it is examined and analyzed marine casualties records(1999-2004), data of Port-MIS and data of each VTS center. The results of this research are as below. 1) It is necessary to reduce traffic accident and to improve VTS operating system. 2) It is discovered for statistical discrepancy between vessels controlled by VTS and vessels not controlled by VTS in accident cause, visibility, perception distance and cause of late perception in collision accidents 3) It is necessary for VTS assistance to be positive and to made in ample time consecutively. 4) As the result of traffic accident prediction model, it is necessary to develop a system improving VTS operators' ability to identify dangerous ships.

• Journal of Korean Society of Transportation
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• v.18 no.5
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• pp.7-16
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• 2000

This paper is focused on verifying time-space repetition of the highway accident and finding the their causes and deterrents. We classify all months into several seasonal groups, develop the model for each seasonal group and analyze the results of these models for Joong-bu highway. The existence of seasonal effect is verified by the analysis or self-organizing map and the accident indices. Agglomerative hierarchical cluster analysis which is used to decide the seasonal groups in accordance with accident patterns, winter group, spring-fall group. and summer group. The accident features of winter group are that the accident rate is high but the severity rate is low. while those of summer group are that the accident rate is low but the severity rate is high. Also, the regression model which is developed to identify the accident Pattern or each seasonal group represents that the season-related factors, such as the amount of rainfall, the amount of snowfall, days of rainfall, days of snowfall etc. are strongly related to the accident pattern of evert seasonal group and among these factors the traffic volume, amount of rainfall. the amount of snowfall and days of freezing importantly affect the local accident Pattern. So, seasonal effect should be considered to the identification of high-risk road section. the development of descriptive and Predictive accident model, the resource allocation model of accident in order to make safety management plan efficient.

• International Journal of Highway Engineering
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• v.13 no.3
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• pp.157-165
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• 2011

With respect to the trend of highway traffic accident, highway accident is in decline, whileas, the fatality is on an increasing trend. Thus, many efforts to decrease highway traffic accidents and improve the safety, are required. In particular, in case of highway, the management standard by grade for accident black spot is designated. Thus, investing the effect factors by grade for highway traffic accident is required in detail. Thus, in this study, the factors affecting the traffic accidents among the environmental factors based on the graded data for the accident black spot in the applicable section targeting the Seoul-Pusan Express Highway, were reviewed; accident forecasting model which would analyze the characteristics of the accidents for determining the accident grade, was developed. As a result of establishing a model by using Quantification Theory of Type II, considering the characteristics of the dependent and independent variables based on the geometric structure, 'the fixed variable' among the variables relating to the accident, for the variables influencing over the accident grade, 'the type of vans, a chassis and people', 'the trailers, special vehicles and chassis people' and 'the negligence of watching and cloudy weather' were analyzed as common factors, in case of 'horizontal alignment', 'longitudinal slope' and, 'barricade' respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.54-63
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• 2023

Pedestrian traffic needs to be accurately quantified to predict effectively pedestrian traffic accidents, however, pedestrian traffic is more difficult to measure than vehicle traffic. In this study, we suggest the time-and cost-effective application of mobile closed-circuit television (CCTV) using a smartphone as an alternative that can collect and analyze real-time data with little. In the present investigation, the pedestrian-vehicle conflict that can develop into an accident was defined as the pedestrian accident exposure. After installing mobile CCTV in 40 sections of Dongseong-ro, Daegu, the pedestrian accident exposure was estimated through negative binomial regression analysis using the collected data. The results of the analysis showed statistically significant changes in the pedestrian accident exposure variables. Based on the present results, a pedestrian accident exposure estimation model was developed which can be used in sections where pedestrian accidents may occur.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.319-320
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• 2022

해무는 해면에 인접한 층에서 수증기가 응결하여 대기 중에 부유하는 현상으로 기상학적으로 수평 가시거리가 1km이하 일때로 정의되며 해무로 인해 항공기 이착륙 지연, 교통사고, 운항 통제, 인명 피해 등 사회적, 경제적 피해를 유발하고 있다. 본 연구에서는 기존의 해무 발생, 탐지, 예측과 관련한 연구를 비교 분석하여 향후 연구개발의 방향을 제시하고자 한다. 해무 발생, 예측과 관련하여 연구개발이 진행되어 왔으나 해무의 특성상 규칙성이 약하고 고정적인 측정법이나 이를 다루기 위한 네트워크가 부족하여 예측하기가 어렵다. 특히, 국내에서는 국립해양조사원과 기상청에서 해무 탐지 및 예측에 관한 연구개발 및 서비스가 진행되고 있으나 현업화가 이루어지지 않거나 특정지점에 대한 정보만 제공되고 있는 한계가 있다. 따라서, CCTV영상, 인공위성 영상, 시정계, 기상자료, 수치모형을 통해 수집된 정보를 통합하여 예측할 수 있는 인공지능기반의 해무 탐지 및 예측 기술개발이 진행되어야 할 것이다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.237-240
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• 2023

본 논문은 철도 건널목(교차로)에서 발생하는 차량, 보행자 및 야생 동물 사고 등의 상황에서 발생하는 위험 요소를 설정하고 철도 건널목(교차로)의 운행상황을 확인할 수 있도록 모형 철도 주변에 유형별 센서들을 설치하고 데이터를 인지하여 시스템에 저장하고, 유효한 데이터 분석을 통해 Orange3 머신러닝 기법을 적용한다. 철도 건널목에 관련된 이미지 중 위험인자로서 차량, 보행자 및 야생동물등의 객체를 감지하고 데이터를 수집하여 활용한다. 또한 이러한 데이터들은 이용자 상황에 맞는 철도 데이터 운영 시스템으로 적용할 수 있도록 위험 예측 시스템을 제안한다.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.173-184
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• 2008

Development of an accident estimation model based on accident data can be made after accident occurrences. However, the taking of historical accident data is not easy, and there have been differences between real accident data and police-reported accident data. Also, another difficult shortcoming is that historical traffic accident data better consider driver behavior or intersection characteristics. A new method needs to be developed that can predict accident occurrences for traffic safety improvement in black spots. Traffic conflict decision techniques can acquire and analyze data in time and space, requiring less data collection through investigation. However, there are shortcomings: as existing traffic conflict techniques do not operate automatically, the analyst's opinion could easily affect the study results. Also, existing methods do not consider the severity of traffic conflicts. In this study, the authors presented traffic conflict decision criteria which consider conflict severity, including opposing left turn traffic conflict and cross traffic conflict decision criteria. In order to test these criteria, the authors acquired three signalized intersection images (two intersections in Sungnam city and one intersection in Paju) and analyzed the acquired images using image processing techniques based on individual vehicle tracking technology. Within the analyzed images, level 1 conflicts occurred 343 times over three intersections. Some of these traffic conflicts resulted in level 3 conflict situations. Level 3 traffic conflicts occurred 25 times. From the study results, the authors found that traffic conflict decision techniques can be an alternative to evaluate traffic safety in black spots.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.79-88
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• 2019

This study analyzes the influential factors and patterns associated with death from aircraft accidents and incidents using data mining techniques. To this end, we used two datasets for aircraft accidents and incidents, one from the National Transportation Safety Board (NTSB) and the other from the Federal Aviation Administration (FAA). We developed our prediction models using the decision tree classifier to predict death from aircraft accidents or aircraft incidents and thereby derive the main cause factors and patterns that can cause death based on these prediction models. In the NTSB data, deaths occurred frequently when the aircraft was destroyed or people were performing dangerous missions or maneuver. In the FAA data, deaths were mainly caused by pilots who were less skilled or less qualified when their aircraft were partially destroyed. Several death-related patterns were also found for parachute jumping and aircraft ascending and descending phases. Using the derived patterns, we proposed helpful strategies to prevent death from the aircraft accidents or incidents.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.583-595
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• 2014

Currently, Korean transportation policies are aiming for increase of safety and environment-friendly and efficient operation, by avoiding construction and expansion of roads, and upgrading road alignments and facilities. This is revealed by that there have been 22 road expansion projects (30%) and 50 road improvement projects (70%) under the 3rd Five-Year Plan for National Highways ('11~'15), while there were 53 road expansion projects (71%) and 22 road improvement projects (29%) under the 2nd Five-Year Plan for National Highways. For more effective road improvement projects, there is a need of choosing projects after an objective and scientific safety assessment of each road, and assessing safety improvement depending on projects. This study is intended to develop a model for this road safety analysis and assessment. The major objective of this study is creating a road safety analysis and assessment model appropriate for Korean society, based on the HSM (Highway Safety Manual) of the U.S. In order to build up data for model development, the sections thought to have identical geometrical structure factors in 5 lines, Cheonbuk province, were divided as homogeneous sections, and representative values of geometric structures, facilities, traffic volume, climate conditions and land usage were collected from the 1,452 sections divided. In order to build up data for model development, the sections thought to have identical geometrical structure factors in 5 lines, Cheonbuk province, were divided as homogeneous sections, and representative values of geometric structures, facilities, traffic volume, climate conditions and land usage were collected from the 1,452 sections divided. The collected data was processed correlation analysis of each road element was implemented to see which factor had a big effect on traffic accidents. On the basis of these results, then, an accident model was established as a negative binomial regression model.Using the developed model, an Crash Modification Factor (CMF) which determines accident frequency changes depending on safety performance function (SPF) predicting the number of accident occurrence through traffic volume and road section expansion, road geometric structure and traffic properties, was extracted.