• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.391-394
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• 2006

본 연구에서 영상 패턴인식 기술을 이용하여 교차로에서 발생하는 교통사고의 전과정을 동영상으로 기록하고 취득된 사고 자료를 교통관리센터에 전송하여 필요한 조치를 바로 취할 수 있도록 하는 시스템을 제시하였다. 제안된 기술에 따라 개발된 교통사고 자동기록장치가 서울시 교통사고 다발 교차로에 설치되어 운영 및 성능평가 중이다. 동 장치에서 수집된 교통사고 동영상 자료는 교통사고 조사신뢰도를 높이고 교통안전 개선에 크게 기여할 것이다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2015.11a
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• pp.197-198
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• 2015

우리나라의 자동차 역사는 주요 선진국에 비해 60년 정도 짧지만 자동차와 일어나는 교통사고의 발생률이나 심각도를 고려한다면 교통사고를 줄이기 위한 여러 가지 원인을 분석해 보는 것이 중요하다. 본 연구는 방송프로그램에 방송한 차량용 영상기록장치(VDR) 제보영상을 통해 다양한 교통사고의 원인을 수집하여 운전자의 행태를 분석하여 교통사고를 발생을 감소 시킬 수 있는 방안을 제시하는 연구목적이다. 방송된 차량용 영상 전체 1,262건에 대해 운전자 행태 분석을 실시하여 DB를 구축하고 이를 교통사고 분석 시스템 TAAS 통계를 비교 분석 결과 전체 1,262건 중 노면상태가 건조 할 때가 1,153건, 기상상태가 맑을 때 1,176건, 주야별 운전시 주간이 1,0,13건으로 높게 분석되었다. 또한 사고유형으로는 차대차 860건이 68.1%로 높게 분석 되었다. 따라서 운전에 장애가 되는 요소가 없는 경우 운전자 개인이 과속과 전방주시 태만이 발생할 가능성이 높으므로 운전자들에 대한 교육을 통해 의식개혁이 필요하다.

• Review of KIISC
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• v.24 no.2
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• pp.35-41
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• 2014

자동차 산업 인프라의 발달로 자동차 사용 인구는 지속적으로 증가하고 있으며, 이에 따른 자동차 사고도 매년 증가하고 있다. 자동차 사고는 개인 및 사회의 비용손실과 즉결되므로 많은 운전자들이 자동차용 블랙박스(사고영상기록장치)를 구입하여 장착하고 있다. 이런 자동차용 블랙박스는 교통사고 시점의 영상을 저장 재생 하므로 정확한 사고원인을 규명하는데 활용되고 교통사고를 예방하는 효과가 있다. 그러나 그 이면에 자동차용 블랙박스는 자동차가 운행될 때 마다 영상을 촬영하고 저장되기 때문에 의도되지 않은 개인의 사생활이 노출 될 수 있으며 또한 저장된 사고영상 데이터를 의도적으로 조작하여 교통사고의 원인규명을 방해하는 문제가 발생 하기도 한다. 본 연구에서는 이러한 문제를 해결하기 위한 국내 관련 동향을 알아보고 보안기술을 적용 할 수 있는 방안을 제시하고자 한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.6
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• pp.1321-1328
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• 2015

The automobiles in Korea have approximately 60 years of history and this is relatively short compared to advanced countries. However, considering the traffic accident rate or severity related to automobiles, various efforts are required to reduce traffic accidents. Various problems caused by traffic accidents are not only related to individual damages but also have become social problems. In order to resolve this, it is important to analyze the cause of traffic accidents. This study aims to suggest methods to reduce traffic accidents by analyzing driving behavior, which is one of the reasons for a number of traffic accidents that were collected through traffic accident videos reported using DVRs (Driving Video Recorder) and were aired to the public via a SBS TV program for the past two years and four months. In particular, unlike other existing studies that aim at analyzing the causes of traffic accidents simply using data, this study constructed a database by analyzing every single DVR that stores the situation before and after the accident using relatively high-resolution video information to provide practical plans to reduce traffic accidents through statistical analysis.

• 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 Information Science Society Conference
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• 2005.11b
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• pp.76-78
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• 2005

본 교통사고 동영상 DB 설계의 연구 목적은 교통사고 자동기록장치에서 수집되는 교통사고 동영상 자료를 효율적으로 활용하기 위한 교통사고 동영상 DB 구축 방안에 관한 연구이며, 이를 위해 ISO/IEC 11179 표준인 MDR을 이용한 교통사고 동영상 DB 논리 모델을 제안하는 데 있다. 본 논문에서 제안하는 DB구조를 통해 실시간 대용량 교통사고 동영상 데이터에 대한 데이터의 생성, 관리 및 검색 성능을 향상시킬 수 있을 뿐만 아니라, MDR 표준 개념 적용으로 상호 이질적인 DB 간의 상호운용성(interoperability)이 증대된다.

• Journal of Korean Society of Transportation
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• v.30 no.2
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• pp.127-136
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• 2012

Multi-car rear-end collision accidents have three categories: sequential collision from the rear which is commonly referred to as chain reaction collision, sequential collision from the front, and mixed-order collision. This paper suggests several effective methods of reconstruction analysis for multi-car rear-end collision accidents. First, by incorporating the traditional empirical method which uses vehicle damage caused by brake dive and passenger injuries, with results of theoretical analysis made within mechanics of rigid body, it is made possible for the method to be put to immediate practical use. A methodology to precisely analyze multi-car rear-end collision accidents was suggested using a simulation program simultaneously with a video event data recorder which is starting to be widely used in domestic vehicles. To go beyond the simple intuitive analysis of the video event data recorder, the simulation analysis based on the results of video analysis was executed to acquire various information, so that the causes and responsibility could be clearly stated.

• 한국ITS학회:학술대회논문집
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• v.2006 no.10
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• pp.113-117
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• 2006

• 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 Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.132-142
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• 2014

In this paper, we propose a traffic lights detection method using visual attention and spot-lights detection. To detect traffic lights in city streets at day and night time, the proposed method is used the structural form of a traffic lights such as colors, intensity, shape, textures. In general, traffic lights are installed at a position to increase the visibility of the drivers. The proposed method detects the candidate traffic lights regions using the top-down visual saliency model and spot-lights detect models. The visual saliency and spot-lights regions are positions of its difference from the neighboring locations in multiple features and multiple scales. For detecting traffic lights, by not using a color thresholding method, the proposed method can be applied to urban environments of variety changes in illumination and night times.