• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.1
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• pp.77-86
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• 2016

Drivers can receive diverse types of traffic information through a number of methods. However, there are not enough information services considering human factors. In this study, as a basic research on human factors of the drivers, characteristic analysis on drivers' mean glance (fixation) durations with different running speeds on the expressway was performed under diverse running environments. To control variables other than running speeds, running environments were categorized into 4 types: 'daytime running without preceding vehicles', 'daytime running with preceding vehicles', 'nighttime running without preceding vehicles', and 'nighttime running with preceding vehicles'. Furthermore, ANOVA Test was used to divide speed groups. As a result of performing a multiple comparison to compare differences in glance behavior per each group, the road item and the preceding vehicles item showed an increase in mean glance durations as the speed increased, while the front view showed a decrease in mean glance durations. It was confirmed that the road sign showed no statistically significant difference in glance durations as the speed varied.

• Science of Emotion and Sensibility
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• v.17 no.3
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• pp.117-128
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• 2014

As the main cause of car accidents is driver distraction, HUD utilization is important to boost drivers' front-observing. Recently, As HUD includes a variety of contents products have appeared on market, the possibility increases cognitive load while driving. The purpose of this study is that currently being used HUD contents how much affect drivers while driving. To investigate about it, the experiment is examined cognitive aspect with utilization aspect of different gender and illuminance environment. The study provides, in accordance with the internal and external illuminance, the visibility make a difference. The gap between the internal and external illuminance is higher, the visibility is better. Also, this study confirms that HUD's awareness of contents depends on driving information. Drivers concentrate more on higher related driving contents than lower ones.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.25-35
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• 2017

This study aimed to analyze a driver's night visibility, according to the installation of a lighting system for driving an agricultural machine during the night time. For the night visibility analysis, a luminance measurement test on the lighting system and a gaze duration measurement test through eye movement measurement devices were carried out. In the luminance measurement test, the increase of luminance was confirmed as relative distance from an agricultural machine was closer and the conditions of the lighting equivalence are improved. Also the gaze duration measurement test, total gaze duration from an agricultural machine increased, as the conditions of the lighting equivalence are improved. In addition, it was identified that the difference in average gaze duration from an agricultural machine was statistically significant as the agricultural machine was driven in high speed. In conclusion, when the lighting system is installed on an agricultural machine, a driver's night visibility from the agricultural machine improves, which is expected to be enormously helpful to the prevention of agricultural machine accidents.

• Science of Emotion and Sensibility
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• v.16 no.2
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• pp.195-206
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• 2013

The main causes of traffic accidents while driving a car is of the driver's visual distraction. In this study, the color sensitivity of the information projected on the windshield were evaluated for HUD (Head Up Display) system which helps the driver's eyes on the road while driving. The driving Information were projected $9^{\circ}$ downward from front sight $0^{\circ}$ under lab's fluorescent lights, LED floorlights and the TV had having 25 [lux] illumination when driving at night environment and 100,000 [lux] of daylight environment. Munsell color hue of the basic five colors (R, Y, G, B, P) and the color of traffic lights YR, W were the color of the seven characters, each character were outlined by White, Gray except for W. Total of 19 experimental stimuli was shown in the environment of day and night driving for asking visibility information of color, fatigue, preferences, and evaluate the degree of interference. The results came out that the bright Y and G color is visibility significantly for daylight. Second, with the outline of the text, the color of the outline works as a background for luminance contrast effects and affects visibility. Third, without the outline, the glass in front of the vehicle acts as the background and the luminance contrast of characters achieve greater brightness and visibility. The luminance contrast between the stimuli and background should be considered for increasing color visibility for driving information which is an important factor for HUD commercialization.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.329-332
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• 2015

야간에 자동차를 운행할 때 검정색 차량 같은 어두운 색상의 자동차는 운전자가 인지를 못하는 경우가 많고 안개가 짙게 낀 상황도 운전자의 시야가 좁아져 교통사고율이 급격하게 증가한다. 도로교통공단의 자료에 의하면 최근 5년(2009~2013) 동안 가해자의 안전거리 미확보로 인한 교통사고는 매년 감소하는 것으로 나타나지만, 안전운전 의무 불이행 다음으로 두 번째로 높은 사고 건수를 기록하고 있다. 이는 아직도 운전자의 시인성 저하에 대한 방안이 부족하기 때문이다. 시인성 저하를 위한 대책으로 BMW, AUDI, Benz 회사에서 적외선 카메라를 이용한 나이트 비젼이 있으나 거리감지기능이 없어 디스플레이를 계속 주시하면서 운행하여야 하므로 시야가 좁아져 다른 위험이 발생할 수 있다. 현재 시중에 제공되고 있는 적외선 나이트 비젼 카메라를 이용하였을 때 일반 시야보다 약 4배 정도의 거리를 인식할 수 있었고, 이러한 나이트 비젼의 장점을 활용하여 전면 차량과의 안전거리를 확보하는 시스템을 제안한다. 본 논문에서는 제시하는 시스템은 시인성이 떨어지는 환경을 가정하여 설계하였고 나이트 비젼 카메라를 이용해 디스플레이로 출력하여 육안으로 구분할 수 없는 물체도 인지할 수 있어 헤드라이트를 켜고 운행할 때보다 안전한 운행을 할 수 있을 것으로 보인다. 하지만 디스플레이를 지속적으로 주시하며 운행할 경우 거리 감각이 떨어져 근접해 오는 물체와의 충돌 사고를 막기 힘들 것으로 보인다. 따라서 이러한 단점을 보안하기 위해 영상 데이터를 활용하여 앞 차량의 유무를 파악하고 차량이 있을 때 안전거리를 디스플레이에 표시함으로 앞 차량과의 거리를 유지하여 사고를 예방하여 안전 운행이 가능하도록 설계하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.3
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• pp.175-181
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• 2017

In this paper, we describe a design and development of car HUD(Head-Up-Display) navigation system using a Raspberry Pi. Car drivers can't concentrate on driving due to the use of various electronic devices, especially the car navigation systems installed in the cars. Therefore, car accident caused by not concentrating on the driving views is one of the most common accident types. In order to prevent the problems, HUD technology is used to help the driver to secure front views, thereby to minimize the traffic accidents caused by neglecting forward views. In this research, we propose the design and development techniques of a HUD navigation system using Raspberry Pi, and we believe that the commerical use of HUD navigation will grately reduce the risk of many car accidents.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.12
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• pp.123-129
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• 2014

In accordance with the development of various convergence devices, cameras are being used in many types of the systems such as security system, driver assistance device and so on, and a lot of people are exposed to these system. Therefore the system should be able to recognize the human behavior and support some useful functions with the information that is obtained from detected human behavior. In this paper we use a machine learning approach based on 2D image and propose the human behavior pattern recognition methods. The proposed methods can provide valuable information to support some useful function to user based on the recognized human behavior. First proposed one is "phone call behavior" recognition. If a camera of the black box, which is focused on driver in a car, recognize phone call pose, it can give a warning to driver for safe driving. The second one is "looking ahead" recognition for driving safety where we propose the decision rule and method to decide whether the driver is looking ahead or not. This paper also shows usefulness of proposed recognition methods with some experiment results in real time.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.836-839
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• 2012

본 논문에서는 운전자의 안전을 보장하기 위해 영상 처리 기술을 기반으로 도로 정보를 검출해 운전자에게 알려주고, 버튼을 직접 손으로 눌러야 하는 물리적 인터페이스를 대체할 차세대 인터페이스 기술을 제안한다. 제안된 기술은 카메라 한대에서 입력 받은 영상 정보를 제안된 알고리즘을 통해 앞차와의 거리, 차선, 교통 표지판을 검출하고 차량 내부를 주시하는 카메라와 운전자의 음성을 인식할 마이크를 기반으로 음성인식과 동작 인식이 결합된 인터페이스를 제공한다. 본 논문에서 개발된 기술을 통해 설제 테스트를 실시해 본 결과 표지판인식, 차선검출, 앞차와의 거리 검출 등의 인식률이 약 90% 이상이었으며, 이러한 기술적 요소들은 운전자가 인지하지 못하는 상황 등에서도 적절한 정보를 운전자에게 제공해 줌으로써 교통사고 확률을 크게 낮출 수 있을 것으로 기대된다.

• Electronics and Telecommunications Trends
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• v.30 no.5
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• pp.11-21
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• 2015

최근 IT기술과 산업 간 융합이 활발한 가운데 자동차에도 각종 첨단 IT기술이 접목되면서 운전자의 안전과 편의성이 향상된 스마트카(smart car)가 속속 개발되고 있다. 가까운 미래에 스마트카의 도움으로 운전자가 전방주시 의무에서 자유롭게 될 수 있게 되면, 운행 중에 언제 어디서나 모바일 인터넷을 통한 정보접근이 가능하도록 지원하는 컴퓨팅 환경인 자동차 사물인터넷(Internet of Vehicles, Automotive IoT)이 중요하게 대두될 것으로 전망된다. 자동차 사물인터넷의 개념이 아직은 명확히 잡혀있지 않지만, 대체로 모바일 연결성(mobile connectivity)을 중심으로, 교통안전 혼잡해소뿐만 아니라 다양한 사용자 맞춤형 서비스 산업을 창출할 수 있는 컴퓨팅 환경을 의미한다. 즉, 운전자와 자동차, 자동차와 주변환경 및 교통인프라, 그리고 일상생활의 모든 요소가 자동차를 매개로 해서 유기적으로 연결되는 컴퓨팅 환경을 의미하며, 가까운 미래에 이런 컴퓨팅 환경을 지원하는 자동차가 상용화될 것으로 전망된다. 본고에서는 이러한 전망을 반영하여 자동차 사물인터넷 환경의 스마트카에 적용될 주요 기술과 서비스를 분석하고, 스마트카와 자율주행의 핵심기술인 인포테인먼트 플랫폼의 주요 동항 및 이슈를 살펴보고자 한다.