• Journal of Nutrition and Health
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• v.41 no.8
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• pp.851-859
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• 2008

To promote the adoption of healthier eating patterns, this study was aimed to develop and evaluate alternative front of pack nutrition signposting concepts. Based on previous research, we developed two signposting concepts, Multiple Traffic Light (MTL) and Multiple Traffic Light with % Daily Value (MTL-%DV). The signposts featured three key nutrients, total sugar, saturated fat, and sodium. Actual food packaging with no front of pack signposting (NoSP) was included in the evaluation to act as a benchmark against which to compare the performance of the different signposting options. Using an interviewer administered method, we assessed the degree of understanding and time to interpret on a total of 534 subjects (194 elementary, 108 middle, and 103 high schoolers, 128 adults). In the individual product evaluations, MTL (87.0%) obtained the highest level of correct responses, followed by MTL-%DV (83.1%) and NoSP (52.2%). Except for signposting concepts, age, gender and living area were not associated with the degree of correct responses in multivariate analyses. When used to compare products with different colors of nutrient contents, correct responses were more than 90% for MTL-%DV (91.5%) and MTL (90.3%). The middle and high schoolers revealed the lower likelihood of correct response compared to the other two groups. In case of comparing products with same colors of nutrient contents, the proportion of correct responses was the highest in NoSP (90%), followed by MTL%DV (77.4%) and MTL (48.5%). In terms of time to interpret, MTL-%DV and MTL performed better than NoSP in the individual product evaluation and the comparison of two products with different colors of nutrient contents. NoSP performed the best in the comparison of two products with same colors of nutrient contents. A majority of the participants preferred MTL-%DV (78%) most and thought it the most useful in helping them make healthier food choices. Based on these findings, MTL-%DV was considered to most closely meet the objectives of the initiatives.

• Transportation Technology and Policy
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• v.7 no.2
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• pp.71-78
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• 2010

• Proceedings of the Korea Multimedia Society Conference
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• 2001.11a
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• pp.827-832
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• 2001

기존 신호등 체계의 문제점을 보완하기 위해 센서를 이용하여 각 차로에 진행하려고 하는 차량을 감지하고, 대기 차량이 없을 경우 다음방향으로 신호를 주어 소통에 효율성을 높였으며 특히 GAL소자 하나로 설계함으로써 개발비용을 줄이도록 하였다.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.470-473
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• 2002

기존 차량 트래픽 시스템 관련 연구들은 신호등체계 보다 차선변경을 중요시하고, 차량의 목적지 없이 랜덤으로 주행함으로 사실성이 저하된다. 본 논문에서는 차량 트래픽의 사실성을 높이기 위해 신호등체계를 도입하고 출발지와 목적지 등을 부여한다. 또한 출발지점과 목적지점의 차량 트래픽률을 제어하고, 출발지점에서 목적지점까지의 최적경로를 찾아 주행하는 방법에 대해 설계하고 구현한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.200-203
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• 2016

최근 자율주행자동차에 대한 관심이 증가함에 따라 교통 상황을 인식하는 방법에 대한 연구도 활발하게 진행되고 있다. 특히 교통신호등의 인식은 치명적인 결과를 야기하는 교통사고와 밀접하게 연관된다는 점에서 중요성이 더욱 부각되고 있다. 본 논문에서는 컴퓨터 비전 시스템을 기반으로 한 교통신호등 인식 방법을 제안한다. 차선, 표지판 등과는 다르게 교통신호등은 빛을 발하는 특징이 있으며 그 모양과 형태 또한 규격화 되어 있다. 이러한 특징 중 색상과 형태 특징을 이용하여 두 단계의 추출과정을 거쳐 교통신호등을 인식한다. 먼저 HSV 색 공간에서 적색, 녹색, 주황색의 빛을 발하는 영역을 찾아낸 뒤, 신호의 원형 특징을 이용해 가로, 세로 사이즈와 크기로 신호의 후보를 추출한다. 다음, 신호등의 검은 박스 영역을 찾기 위해 추출한 신호 후보군의 주변부가 검정색인지를 확인한다. 최종적으로 신호등의 박스 부분을 검출하여 신호를 발하는 위치를 기반으로 신호를 인식한다. 실험결과 많은 계산량을 요구하는 기계학습을 사용하지 않고도 실시간 처리와 높은 인식률로 교통 신호를 인식할 수 있음을 확인하였다.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.472-478
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• 2017

In this paper, we deals with optimizing traffic signal timing in grid networks by using a network topology design method. Optimizing traffic signal timing includes minimizing delay time delay between departure and destination by interlocking straight traffic signal in the minimum spanning tree(MST). On the assumption that users of network abide by the paths provided in this paper, this paper shows optimizing traffic signal timing in grid networks. the paths provided in this paper is gathered by using Dijkstra algorithm used in computer networks. The results indicate minimizing delay time of passing through the grid network and interlocking traffic signal in the grid network.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1709-1712
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• 2013

교통 신호등은 운전자 혹은 보행자들의 뚜렷한 시인성 확보를 위해 가능한 주위 배경과 구분되는 색상, 모양, 질감 등으로 구성하여 설치되어 있는 특징을 가지고 있다. 결국 기존 교통 신호등 검출 연구들에서는 대부분 교통 신호등의 색상과 모양을 기반으로 한 검출 연구가 주류를 이루고 있는 것이 사실이다. 하지만, 외부 날씨, 복잡한 시내, 다른 물체와의 겹침 등의 문제로 인해 색상 및 모양 기반의 교통 신호등, motion blur, 검출 오류가 증가 되고 있다. 따라서 본 연구에서는 입력 영상에서 색상정보를 배제하고 motion blur나 밝기 변화에 덜 민감하고 먼 거리에서도 뛰어난 시인성을 가진 spot light 검출을 통해 입력 영상에서 가장 밝은 교통표지판 후보 영역들을 검출한다. 그리고 교통 신호등의 특징인 가능한 원형을 유지하고 있으며 원형 외부 색상과 내부 색상이 현저하게 두드러지는 영역을 maximally stable extremal regions (MSER) 알고리즘을 사용하여 입력 영상에서 후보 영역을 선택한다. 마지막으로, 검출된 영역들에서 교통 신호등 영역을 검출하기 위해 템플릿 매칭 방법을 적용한다. 제안한 방법을 도로 상에서 실험한 결과, 평균 94% 이상의 검출율을 제시하였고, 특히 야간 시간대에 검출율이 비교적 높게 제시되었다.

• Journal of KIISE
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• v.42 no.10
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• pp.1231-1238
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• 2015

Traffic light rules are one among the most common and important safety rules as the directly correlate with the safety of pedestrians. Consequently, an algorithm is required to cause an automated (or semi-automated) vehicle to observe traffic light signals. We present a novel, artificial potential function to guide an automated vehicle through traffic lights. Our function consists of three potential function components representing the three traffic light colors: green, yellow, and red. The traffic light potential function smoothly changes an artificial potential field using the elapsed time for the current light and light conversion. Our traffic light potential function is combined with other potential functions to guide vehicles' movement and constructs the final artificial potential field. Using various simulations, we found or method successfully guided the vehicle to observe traffic lights while behaving like human-controlled cars.

• Journal of Korean Society of Transportation
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• v.25 no.3
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• pp.19-28
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• 2007

Korea's national highways, which emphasize a high level of mobility, serve primarily intercity travel and are used as a detour for freeways. However. at the present. the highways do not have consistent geometric features or other characteristics: for example. some highways have full access control and others have uncontrolled access. Generally, geometric and traffic conditions affect Pronouncedly travel speeds in the highway sections. This study focused on the effect of signalized intersection relative factors on the speeds: signalized intersection densities, signal phases, and volume levels. The study shows that signalized intersection density was the strongest variable affecting the travel speeds: the speeds held fairly constant over intersection densities below 0.3 intersections/km, decreased sharply through intersection density of 0.7 intersections/km. and appeared constant at the lowest level over intersection densities above 0.7 intersections/km. The results also indicate that the effect of signal and traffic volume levels on the speeds was similar to that of the signalized intersection density.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.717-719
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• 2015

The research and development of the unmanned vehicle is being carried out actively in domestic and foreign countries. The research is being carried out to provide various services so that the weakness of system such as conventional 2D-based navigation systems can be supplemented and the driving can be safer. This paper suggests the method that enables real-time video processing in more efficient way by realizing the location detection and signal recognition technique of traffic signals in video. In order to overcome the limit of conventional methods that have a difficulty in analyzing the signal as it is sensitive to brightness change, the proposed method realizes the program that grasps the depth data in front of the vehicle using video processing, analyzes the signal by detecting traffic signal and estimates color components of traffic signal in front and the distance between traffic signal and the vehicle.