• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.91-105
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• 2024

Car accidents occur as a result of collisions between vehicles, leading to both vehicle damage and personal and material losses. This study developed a vehicle accident detection model based on 2,550 image frames extracted from car accident videos uploaded to YouTube, captured by CCTV. To preprocess the data, bounding boxes were annotated using roboflow.com, and the dataset was augmented by flipping images at various angles. The You Only Look Once version 8 (YOLOv8) model was employed for training, achieving an average accuracy of 0.954 in accident detection. The proposed model holds practical significance by facilitating prompt alarm transmission in emergency situations. Furthermore, it contributes to the research on developing an effective and efficient mechanism for vehicle accident detection, which can be utilized on devices like smartphones. Future research aims to refine the detection capabilities by integrating additional data including sound.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.3
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• pp.68-83
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• 2019

The number of pedestrian traffic accident fatalities is three times the number of car accidents in South Korea. Serious accidents are caused especially at intersections when the vehicle turns to their right. Various pedestrian collision warning services have been developed, but they are insufficient to prevent dangerous pedestrians. In this study, P2CWS is developed to warn approaching vehicles based on the pedestrians' characteristics. In order to evaluate the performance of the service, actual pedestrian data were collected at the intersection of Daejeon, and comparative analysis was carried out according to pedestrian characteristics. As a result, the performance analysis showed a higher accordance when the characteristics of the pedestrian is considered. Accordingly, we can conclude that identifying pedestrian characteristics in predicting the pedestrian crossing is important.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.285-287
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• 2012

근래 정부에서는 차량용 블랙박스의 필요성과 효율성을 인식해 모든 차량에 블랙박스(EDR, Event Data Recorder)를 의무적으로 장착하게 하고, 이를 통해 차량의 운행 정보와 상황을 모니터 및 관리를 할 수 있도록 정부 시책을 신설하고 이를 추진하고 있는 중이다. 특히 차량사고 발생시 이를 시뮬레이션하고 분석할 수 있는 자료가 매우 부족하다. 교통사고의 시뮬레이션 사고 차량의 운행정보뿐만 아니라 주변 운행환경 및 운행여건, 다른 차량의 간섭 등 매우 많은 정보가 필요하기 때문이다. 이에 본 논문에서는 블랙박스 간 Ad-hoc network을 이용해 차량의 정보를 공유 할 수 있는 시스템을 제안하고자 한다. 즉, 차량에서 돌발상황이 발생했을 때 발생 차량의 블랙박스 의 정보와 주변 운행하고 있는 차량에 장착되어 있는 블랙박스의 정보를 Ad-hoc network를 통해 사고 발생차량으로 수집, 이를 저장하고 추후사고에 대한 시뮬레이션 에서 이 데이터들을 통해 돌발상황 당시의 주변 차량 흐름과 다른 차량간의 간섭 및 돌발상황 유발 같은 현상을 조금 더 정확하게 시뮬레이션 함으로서 돌발상황에 대한 분석 및 판단에 도움을 줄 것이라 생각한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3D
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• pp.303-311
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• 2010

There have been various forms of systems such as a digital speedometer or a black box etc. to meet the social requirement for reducing traffic accidents and safe driving. However that systems are based on after-accident vehicle data, there is limit to prevent the accident before. So in our previous research, by storing, analyzing the Vehicle-dynamic information coming from driver's behavior, we are developing the decision-device which could provide driver with Alerting-Information in real-time to enhance the driver's safety drive. but the performance valuation is not yet executed. Finally, this study developed positional recognition system by using the DGPS for pre-developed risky driving decision device. The result of test analyzed with the same that the aggregated vehicle dynamics data in DGPS and dangerous risky driving decision device. If the performance of risky driving decision device is verified by precisely positional recognition system, the risky driving management of vehicle would be effected.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.236-238
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• 2022

According to the current Road Traffic Act, the 2020 amendment bill is currently in effect as a system that designates vehicle types for each lane for the purpose of securing road use efficiency and traffic safety. When comparing the number of traffic accident fatalities per 10,000 vehicles in Germany and Korea, the number of traffic accident deaths in Germany is significantly lower than in Korea. The representative case of the German autobahn, which did not impose a speed limit, suggests that Korea's speeding laws are not the only answer to reducing the accident rate. The designated lane system, which is observed in accordance with the keep right principle of the Autobahn Expressway, plays a major role in reducing traffic accidents. Based on this fact, we propose a traffic enforcement system to crack down on vehicles violating the designated lane system and improve the compliance rate. We develop a designated lane enforcement system that recognizes vehicle types using Yolo5, a deep learning object recognition model, recognizes license plates and lanes using OpenCV, and stores the extracted data in the server to determine whether or not laws are violated.Accordingly, it is expected that there will be an effect of reducing the traffic accident rate through the improvement of driver's awareness and compliance rate.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.141-155
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• 2017

As the use of SNS becomes more active, many people are posting their thoughts about specific events in their SNS in the form of text. As a result, SNS is used in various fields such as finance and distribution to conduct service satisfaction surveys and consumer monitoring. However, in the transportation area, there are not enough cases to utilize unstructured data analysis such as emotional analysis. In this study, we developed an emotional analysis methodology that can be used in transportation by using highway VOC data, which is atypical data collected by Korea Expressway Corporation. The developed methodology consists of morpheme analysis, emotional dictionary construction, and emotional discrimination of the collected unstructured data. The developed methodology was verified using highway related tweet data. As a result of the analysis, it can be guessed that many information and information about the construction and the accident were related to the highway during the analysis period. Also, it seems that users complain about the delay caused by construction and accident.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.761-767
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• 2012

Maritime traffic assessment is important to understand the characteristics of maritime traffic and to prevent maritime accidents. The maritime traffic assessment can be calculated from the ship trajectory data observed by using AIS(Automatic Identification System). This paper developes a maritime traffic assessment tool using ship's position and speed, course, time data from ships navigating waterways. The results are represented in terms of the number of traffic quantity and traffic distribution, speed distribution, geometric collision candidates. The developed tool will contributes to advance maritime traffic safety by VTS(Vessel Traffic Services).

• 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.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.267-268
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• 2022

Jeju coastal waters are limited to high-risk areas due to the passage of international cruise ships, passenger ships, with a large number of people and fishing boats, or to the jeju port and the jeju civilian-military combined port and near by seas, so a VTS system will be established along jeju and seogwipo coast. There is no accurate standard for determining the number of people required by the maritime traffic control center. Therefore, this study calculated the required operating personnel for control seats on the coast of jeju and seogwipo by using VTS big data to efficiently calculate the workload of maritime traffic control. It is judged that this study can be used basic data for research that sets the standard for calculating the control workload.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.3
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• pp.27-35
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• 2002

A knowledge-based image retrieval technique is image searching methods using some features from the queried image. The materials in this study are automobile head lamps. The input data is composed of characters and images which have various pattern. The numbers, special symbols, and general letters are under the category of the character. The image informations are made up of the distribution of pixel data, statistical analysis, and state of pattern which are useful for the knowledge data. In this paper, we implemented a retrieval system for the scientific crime detection at traffic accident using the proposed multi knowledge-based image retrieval technique. The values for the multi knowledge-based image features were extracted from color and gray scale each. With this 22 features, we improved the retrieval efficiency about the color information and pattern information. Visual basic, crystal report and MS access DB were used for this application. We anticipate the efficient scientific detection for the traffic accident and the tracking of suspicious vehicle.