• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.788-790
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• 2022

최근 자동차 패러다임이 스마트카의 개념으로 급격히 변화하면서 생체신호를, 기반으로 감정을 인식하는 기술은 졸음에 의한 각종 사고들을 예방하는데 적극 사용되고 있다. 자동차의 안전 시스템의 경우 운전자 주의 경고 기능을 이미 탑재하고 있으므로, 운전자 표정을 인식해 적절한 서비스를 제공하여 자동차의 엔터테인먼트 분야인 인포테이먼트 기술을 더욱 폭넓게 활용할 수 있다.

• Journal of the Institute of Convergence Signal Processing
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• v.17 no.2
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• pp.77-82
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• 2016

The purpose of this paper is to develop the algorithm of human arousal inducing interface using steady-state visual evoked potential(SSVEP) and its verification through experiments. In order to develop the model, computer-based SSVEP program simulation is preliminary performed. From the results of the simulation, stimulus pattern is decided to checkerboard and SSVEP frequency range is set into beta wave (13~30Hz). After the experiment on proving the effect of SSVEP flashing stimulation while driving by installing it at the location of people mostly falling asleep in the highway, the result confirms that both during the night and the day, after SSVEP flashing stimulation, a wave Beta immediately increases and the subjects keep high stimulation for the 5 minute maintaining stage.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2009.05a
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• pp.190-195
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• 2009

자동차 이용자 수가 증가 할수록 자동차 사고로 인한 피해도 많이 늘어나고 있다. 이러한 자동차 사고를 사전에 예방하기 위해서는 운전자의 상태 및 현재 차량 상태를 파악하여 사고를 미리 방지함으로서 운전자의 안전을 보조할 수 있는 시스템이 필요하다. 본 연구에서는 안전운전을 보조하기 위하여 졸음운전 여부 감지 시스템, 후진시 후방 안전거리를 감지하는 시스템, 쾌적한 운전 환경을 위한 실내 환경 측정 시스템, 주차 시 생길 수 있는 사고에 대한 감시시스템을 센서와 MCU등을 이용한 임베디드 시스템을 구현 하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1540-1543
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• 2013

최근 자동차 관련 연구 분야 중 안전사고 예방에 대한 관심이 높아짐에 따라 안전지능형 기술들의 연구가 활발히 이루어지고 있다. 졸음운전과 같이 운전자의 의지와 상관없는 무의식적인 차선 이탈은 중앙선 침범으로 이어져 대형 사고를 유발할 가능성이 크다. 이와 같은 요인들은 의식적인 상황에서의 차량의 통제를 방해하고 결국 예기치 않은 차선 이탈로 연결될 수 있다. 따라서 본 논문에서는 차선 이탈 여부를 미리 판단하여 주행차선을 이탈하기 전에 운전자게에 알려줌으로써 운전자의 안전을 향상 시켜주며 자동차 안전사고 예방기술에 관련하여 차선검출과 차선이탈경고시스템 알고리즘을 설계하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.754-761
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• 2008

As the automobile industry and technologies are developed, driver's tend to more concern about service matters than mechanical matters. For this reason, interests about recognition of human knowledge and emotion to make safe and convenient driving environment for driver are increasing more and more. recognition of human knowledge and emotion are emotion engineering technology which has been studied since the late 1980s to provide people with human-friendly services. Emotion engineering technology analyzes people's emotion through their faces, voices and gestures, so if we use this technology for automobile, we can supply drivels with various kinds of service for each driver's situation and help them drive safely. Furthermore, we can prevent accidents which are caused by careless driving or dozing off while driving by recognizing driver's gestures. the purpose of this paper is to develop a system which can recognize states of driver's emotion and attention for safe driving. First of all, we detect a signals of driver's emotion by using bio-motion signals, sleepiness and attention, and then we build several types of databases. by analyzing this databases, we find some special features about drivers' emotion, sleepiness and attention, and fuse the results through Multi-Modal method so that it is possible to develop the system.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.845-847
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• 2022

교통사고의 원인 중 90%는 졸음운전과 같은 운전자의 부주의 때문에 발생하고 있다. 정부에서도 사고로 인한 인명피해 심각성을 인지하고 2019년부터 전방충돌방지 시스템과 차선이탈 경고 장치 등 ADAS(Advanced Driver Assistance Systems)를 의무적으로 적용하도록 규제를 강화하는 추세이다. 충돌사고를 예방하기 위해 본 논문에서는 영상처리를 기반으로 하여 객체 검출, 차간거리 측정, 후미등 검출, 차선 검출 기능을 적용하여 위험한 상황을 감지하고 운전자에게 경고 알림을 제공하는 System을 개발한다. 더 나아가 다양한 모빌리티 서비스에 이를 활용할 수 있는 방안을 제공한다.

• Journal of IKEEE
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• v.18 no.3
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• pp.368-375
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• 2014

Brain computer interface(BCI) technology has been continuously developed due to the continuous development of interface technology and the promotion of brain wave research. In this paper, we propose a driving habit management system by adopting BCI to transportation. The proposed system consists of the electroencephalogram(EEG) measuring unit, the EEG analysis unit, the memory section for storing the state information of drivers, the speed controller unit and the alarming section for generating warnings. Our proposed system can reduce the drowsy driving, improve the driving habits of users and help to prevent traffic accidents.

• International Journal of Highway Engineering
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• v.11 no.1
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• pp.177-186
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• 2009

Rumble strip was introduced in highway pavement for driver's safety in Korea on 2000. With proving its effectiveness, total length of highway with rumble strip has increased. This research team suggested a modified form of the existing rumble strip, which was placed on new concrete pavement during construction. The modified construction equipment was applied on test section at PyungTeak-Eumsung highway with some performance experiments. Through the equation of stopping sight distance proposed AASHTO, the modified form is safer than the existing one due to 0.65m of extra width. The indoor noise test showed that the modified form $3.5{\sim}9dB(A)$ noisier than the main pavement, which wasn't applied by rumble method. Therefore, it was one of alternatives to prevent sleeping. The modified form made the frequency effected on man's eye. There were no differences of the noise and vibration between modified form and existing one. However, that driver who participated on operating test on that section felt that the former was safer than the latter. It can be concluded that modified form can be applied to the new concrete pavement, that will decrease traffic accident.

• Journal of Korean Society of Transportation
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• v.30 no.2
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• pp.43-52
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• 2012

A lane departure warning system (LDWS) is an effective technology-based countermeasure for preventing traffic crashes as it provides warning information to drivers. Understanding the characteristics of perception and satisfaction levels on LDWS is fundamental for deriving better performance and functionality enhancements of the system. The purpose of this study is to evaluate the user satisfaction of LDWS. A survey to collect user perception and user preference data was conducted. Both cross-tabulation analysis and binary logistic regression technique were adopted to identify the factors affecting user satisfaction for LDWS. The results revealed that the accuracy and timeliness of warning information was significant for evaluating the effectiveness of LDWS. In particular, the warning accuracy at a curve segment on the road was the most dominant factor affecting user satisfaction. The outcome of this study would be valuable in evaluating and designing LDWS functionalities.