• Proceedings of the KGS Conference
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• 2004.05a
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• pp.102-102
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• 2004

많은 데이터들이 데이터베이스로 구축되면서, 데이터로부터 의미 있는 정보나 지식을 도출하기 위한 새로운 분석법이 제기 되었는데, 그 중 하나가 데이터 마이닝이다. 데이터 마이닝은 급격하게 증가하는 데이터들을 보다 효과적으로 분석하여 유용하고 의미 있는 정보나 지식을 찾기 위해 수행하는 데이터 분석 방법이다. 하지만 이러한 방법이 공간데이터에 적용될 때는 공간 데이터의 특수성으로 인해 그 효과를 기대하기가 어렵다. (중략)

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.97-111
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• 2009

Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a signal intersection and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, we intend to present a technology capable of overcoming problems in which advanced existing technologies exhibited limitations in handling real-time due to large data capacity such as object separation of vehicles and tracking, which pose difficulties due to environmental diversities and changes at a signal intersection with complex traffic situations, as pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian complex model analytical method which has been considered the best among well-known environmental obstacle reduction methods. To prove that the technology developed by this research has performance advantage over existing automatic traffic accident recording systems, a test was performed by entering image data from an actually operating crossroad online in real-time. The test results were compared with the performance of other existing technologies.

• Journal of the KSME
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• v.35 no.8
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• pp.691-697
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• 1995

인체 머리부분의 충격력이 가했을 때 어떠한 상해가 발생할 것인가에 대하여 수치해석적인 접 근을 시도하였다. 복잡한 생체구조의 단순화, 비선형적인 재료 특성으로 인하여 해석 결과는 정 량적인 정확성보다 정성적인 경향성에 보다 큰 의미가 있다고 할 수 있으며, 앞으로 개선할 여 지가 많다고 할 수 있다. 또 의학적인 부분에 관한 기초지식이 필요하기 때문에 의학계의 조건 또는 의학계와의 공동 연구가 요망된다고 하겠다. 해석 결돠의 검증은 과거에는 주로 사체 및 동물 심험에 의하여 행해졌으나 현재에는 사체 실함이 금지되어 있고, 동물(원숭이, 개, 돼지 등 )을 이용한 실험도 동물 보호단체의 반발로 여의치 않은 형편이다. 현재는 교통사고 등에서의 사체 부검 및 사고 상황의 역추적에 의해 생체 실함을 대신할 데이터가 마련되고 있으나, 정확한 사고 상황을 파악하는 것 자체가 또한 어려운 작업이다. 그래서 각 나라에서 일부분씩 가지고 있는 생체에 대한 데이터를 모아 전세계적인 데이터 베이스를 만들어 공유하려는 작업이 진행 되고 있다. 이렇게 실험이 불가능하거나 어려운 상황하에서는 수치 시뮬레이션이 주요한 해석 수단이 될 수 있을 것이라 생각된다.

• Journal of Korean Society of Transportation
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• v.26 no.2
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• pp.17-24
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• 2008

Traffic accident forecasting model has been developed steadily to understand factors affecting traffic accidents and to reduce them. In Korea, the length of highways is over 3,000km, and it is within the top ten in the world. However, the number of accidents-per-one kilometer highway is higher than any other countries. The rapid increase of travel demand and transportation infrastructures since 1980's may influence on the high rates of traffic accident. Accident severity is one of the important indices as well as the rate of accident and factors such as road geometric conditions, driver characteristics and type of vehicles may be related to traffic accident severity. However, since all these factors are interacted complicatedly, the interactions are not easily identified. A structural equations model is adopted to capture the complex relationships among variables. In the model estimation, we use 2,880 accident data on highways in Korea. The SEM with several factors mentioned above as endogenous and exogenous variables shows that they have complex and strong relationships.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.119-130
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• 2009

The aim of this study is to analyze the effects of DVR(Driving Video Recorder) operation on decreasing the number of traffic accidents, the cost of traffic accident claim, and the behavioral change in drivers' driving. The data for this research are obtained from taxi drivers in Busan. For this, Structural Equation Model and two-way ANOVA are employed for empirical analysis. Overall results of this study show that the number of traffic accidents of 4 taxi corporations in Busan has decreased by average 32.7 percent after using DVRs. In addition, as to the cost of taxi accident claims, it is expected that the DVR operation has a considerable effect on economic benefits of taxi corporations. Moreover, this study could make clear the difference in behaviors between DVR users and non-users, and discriminate the positive and negative impacts of the DVR operation on the drivers' driving behavior. The study quantitatively examined the indirect impact of 'attitude', 'subject norm' and 'behavioral control' factors on planned 'behavior', and the direct impact of 'behavioral control' factor on the planned 'behavior'. This study suggests that they should add the video recoding function of DVRs when operation recorder(blackbox for the car) is obligatorily set up on cars for business by traffic security law.

• 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 the Korean Association of Geographic Information Studies
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• v.13 no.2
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• pp.41-53
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• 2010

Traffic safety assessment is often accomplished by analyzing the number of crashes occurring in some geographic space over certain specific time duration. In this paper, we introduce a procedure that can efficiently analyze spatial and temporal changes in traffic crashes before-and-after implementation of a certain traffic controlling measure. For the analysis, crash frequency data before-and-after closing a major highway around St. Louis in Missouri was collected through Transportation Management System(TMS) database that is maintained by Missouri Department of Transportation (MoDOT). In order to identify any spatial and temporal pattern in crashes, each crash is pinpointed on a map using the dynamic segmentation in GIS. Then, the identified pattern is statistically confirmed using an analysis of variance table. The advantage of this approach is to easily assess spatial and temporal trend of crashes that are not readily attainable otherwise. The results from this study can possibly be applied in enhancing the highway safety assessment procedure. This paper also makes several suggestions for future development of a comprehensive transportation data system in Korea which is similar to MoDOT's TMS database.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.597-598
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• 2018

Recently, the future traffic system is mainly aiming traffic safety by collecting, managing and providing traffic information using traffic system. But In this paper, we propose traffic safety using traffic safety mark which is currently utilized transportation infrastructure. The vehicle receives the sensed data with the traffic safety sign as a host, and carries out communication between the vehicles or the infrastructure. By using the information of sensing data, various information can be obtained. In addition to the construction section, traffic accidents can also be utilized. Therefore, this paper is designed to simplify the frame of sensing data and contribute to traffic safety through continuous research.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.61-68
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• 2024

Despite the continuous efforts to mitigate pedestrian accidents at crosswalks, the problem persist. Vulnerable groups, including the elderly and disabled individuals are at a risk of being involved in traffic incidents. This paper proposes the implementation of object detection algorithm using the YOLO v5 model specifically for pedestrians using assistive devices like wheelchairs and crutches. For this research, data was collected and utilized through image crawling, Roboflow, and Mobility Aids datasets, which comprise of wheelchair users, crutch users, and pedestrians. Data augmentation techniques were applied to improve the model's generalization performance. Additionally, ensemble techniques were utilized to mitigate type 2 errors, resulting in 96% recall rate. This demonstrates that employing ensemble methods with a single YOLO model to target transportation-disadvantaged individuals can yield accurate detection performance without overlooking crucial objects.

• Journal of Navigation and Port Research
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• v.34 no.10
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• pp.727-733
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• 2010

An estimation algorithm of collision risk among multiple ships has been developed in order to reduce human error and prevent collision accidents. The algorithm is designed to calculate the collision risk among ships based on Fuzzy theory by using AIS data as traffic information. In this paper, to validate the algorithm, the AIS data of actual collision accident, which occurred between a product carrier and a cargo carrier in Busan harbor in 2009 are collected. The replay simulation is carried out on the actual AIS data and the collision risk is calculated in real time. In this paper, the features of the estimation algorithm of collision risk and the results of replay simulation based on AIS data of actual collision accident are discussed.