• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.940-942
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• 2023

교통사고 통계에 따르면 비보호 구역 내 도로에서 발생하는 교통사고 발생률이 일반 도로보다 30% 높은 수준임이 밝혀졌다. 기존 첨단 운전자 지원 시스템(ADAS: Advanced Driver Assistance Systems)은 다양한 사고 시나리오가 존재하는 비보호 구역에 적용하기에는 한계가 있다. 본 논문은 이러한 문제에 대응하기 위해 기존 ADAS 기능을 확장하여 예측과 판단이 어려운 비보호 구역에서 AI 분석을 통해 운전자에게 주행 가능 여부를 시각적으로 제공하는 시스템을 개발하고자 한다. 이 시스템은 운전자에게 경고와 지원을 제공함으로써 비보호 구역 내 교통사고를 예방할 수 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.504-506
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• 2012

운전자 지원 시스템(ADAS)은 최근 지능형 자동차 분야에서 중요한 이슈로 손꼽히는 기술 중 하나이다. 이 중에서 실시간 표지판 인식 기술은 운전자 지원 시스템의 하나로 운전자의 안전과 직결될 수 있어 높은 정확성과 실시간성이 요구된다. 그동안 표지판 인식 분야는 색상과 현상을 기반으로 연구가 진행되어왔으나, 교통 표지판은 국가별로 그 특징과 형태가 각기 상이하여 적용하는데 한계가 있다. 본 논문에서는 한국의 속도제한 표지판을 실시간으로 검출하고 인식하기 위하여, 1) 영상에서 색상 특징을 이용하여 후보 영역을 검출하고, 2) 형상 정보를 분석하여 표지판의 형태를 검증하고, 3) 검출된 후보영역의 내부문자(숫자)를 분할하고 인식하는 시스템을 제안한다.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.257-265
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• 2006

다양한 정보기기들의 복합화 형태로 진화하는 차세대 텔레매틱스 시스템에서는 운전자의 안정성 확보와 workload 감소가 중요한 이슈로 대두되어 Interface의 단순화, GUI Interaction의 극복 등의 대한 문제해결이 중요시 되고 있다. 이를 위해 본 연구에서는 사용자의 mental model를 고려한 운전자의 자유로운 navigation을 지원할 eyes-free 기술인 haptic interface를 지원하는 모델 개발을 목표로 기존 haptic interface를 지원하는 기기들의 문제점을 도출하고 차세대 텔레매틱스 시스템의 분석을 통해 기능적 요구사항을 정의하였다. 이를 기반으로 사용자에게 haptic interface를 통한 interaction을 제공함으로써 차세대 텔레매틱스 시스템을 지원하는 conceptual model을 개발하였다. 또한 haptic device design시에 고려되는 평가지표들을 선별하여 평가지표의 계층적 구조도를 작성한 후 AHP평가 모델을 개발하여 haptic device design 시의 중요 고려사항을 도출하고 중요도를 산정하여 초기 design 단계에서의 prototype에 대한 객관적이고 정량적인 평가를 제공하였다.

• ICROS
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• v.18 no.2
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• pp.21-29
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• 2012

최근 자동차 연구개발에 있어 내연기관을 대체하는 친환경 자동차기술과 더불어 무인자동차, 자율주행기술이 많은 부분에서 시도되고 실현되어가고 있다. 지능형 자동차라는 개념에서 적용되었던 운전자안전보조시스템, 편의지원과 사고경감 시스템 등이 하나로 통합되어 무인자동차 기술로 발전하고 있다. 또 차량에 고가의 센서를 장착하여 주변환경이나 운전자를 모니터링하는 방식에서 IT 융합기술을 이용한 네트워크기술 (V2I, V2V, V2N & V2X)을 접목시키는 방안을 통하여 개개의 차량은 물론 교통체계의 전체적인 변화를 추구하고 있다. 이러한 첨단차량기술은 새로운 교통문화(차량공유시스템, 군집주행)의 개발과 또다른 교통체계의 연구로 확장되어가고 있다.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.760-767
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• 2018

Advanced driver assistance system(ADAS) is a major technique in the intelligent vehicle field. The techniques for ADAS can be separated in two classes, i.e., methods that directly control the movement of vehicle and that indirectly provide convenience to driver. In this paper, we propose a novel system that gives a visual assistance to driver by translating a night road image to a day road image. We use the black box images capturing the front road view of vehicle as inputs. The black box images are cropped into three parts and simultaneously translated into day images by the proposed image translation module. Then, the translated images are recollected to original size. The experimental result shows that the proposed method generates realistic images and outperforms the conventional algorithms.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.55-62
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• 2015

In this paper, we proposed the method that enabling warning through real-time analysis of dangerous driving behavior, improving driving habits and safe driving using the digital tachograph. Most of traffic accidents and green drive are closely related of driving habits. These wrong driving habits need to be improved by the real-time analysis, warning and automated method of driving habits. We confirmed the proposed that the method will help support eco-driving, safe driving through real-time analysis of driving behavior and warning through the method implementation and experiment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.3
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• pp.65-77
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• 2013

Recent advanced sensors and communication technologies have been widely applied to advanced safety vehicle (ASV) for reducing traffic accident and injury severity. To apply the advanced safety vehicle technologies, it is important to quantify the safety benefits, which is a fundamental for justifying application. This study proposed a methodology for quantifying the effectiveness of the advanced driver assistant system (ADAS), and applied the methodology to lane departure warning system (LDWS) and automatic emergency braking system (AEBS) which are typical advanced driver assistant systems. When the proposed methodology is applied to 2008-2010 gyeonggi-province crash data, LDWS would reduce about 10~14% of relevant crashes such as head-on, run-off-the road, rollover and fixed-object collisions on the road. In addition, AEBS could potentially prevent about 50% of total rear-end crashes. The outcomes of this study support decision making for developing not only vehicular technology but also relevant safety policies.

• Journal of the korean Society of Automotive Engineers
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• v.25 no.4
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• pp.47-48
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• 2003

• Convergence Security Journal
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• v.12 no.6
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• pp.31-37
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• 2012

Today, the core technology of an automobile is becoming to IT-based convergence system technology. To cope with many kinds of situations and provide the convenience for drivers, various IT technologies are being integrated into automobile system. In this paper, we propose an convergence system, which is called Augmented Driving System (ADS), to provide high safety and convenience of drivers based on image information processing. From imaging sensor, the image data is acquisited and processed to give distance from the front car, lane, and traffic sign panel by the proposed methods. Also, a converged interface technology with camera for gesture recognition and microphone for speech recognition is provided. Based on this kind of system technology, car accident will be decreased although drivers could not recognize the dangerous situations, since the system can recognize situation or user context to give attention to the front view. Through the experiments, the proposed methods achieved over 90% of recognition in terms of traffic sign detection, lane detection, and distance measure from the front car.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.96-108
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• 2017

The current collision warning and avoidance system(CWAS) is one of the representative Advanced Driver Assistance Systems (ADAS) that significantly contributes to improve the safety performance of a vehicle and mitigate the severity of an accident. However, current CWAS mainly have focused on preventing a forward collision in an uninterrupted flow, and the prevention performance near intersections and other various types of accident scenarios are not extensively studied. In this paper, the safety performance of Vision-Sensor (VS) and Radar-Sensor(RS) - based collision warning systems are evaluated near an intersection area with the data from Naturalistic Driving Study(NDS) of Second Strategic Highway Research Program(SHRP2). Based on the VS and RS data, we newly derived sixteen vehicle-to-vehicle accident scenarios near an intersection. Then, we evaluated the detection performance of VS and RS within the derived scenarios. The results showed that VS and RS can prevent an accident in limited situations due to their restrained field-of-view. With an accident prevention rate of 0.7, VS and RS can prevent an accident in five and four scenarios, respectively. For an efficient accident prevention, a different system that can detect vehicles'movement with longer range than VS and RS is required as well as an algorithm that can predict the future movement of other vehicles. In order to further improve the safety performance of CWAS near intersection areas, a communication-based collision warning system such as integration algorithm of data from infrastructure and in-vehicle sensor shall be developed.