• 대한공간정보학회지
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• 제20권2호
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• pp.31-37
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• 2012

도로의 확장 및 신규 도로의 설치로 인하여 도로교통시설물의 변경 및 신규설치는 매년 꾸준히 증가하고 있다. 또한, 자동차 및 운전자의 증가와 함께 교통안전을 위한 도로 및 교통안전표지는 지속적인 증설과 관리가 요구된다. 도로 시설물 중 교통안전표지판을 신속하게 갱신하기 위하여 본 연구에서는 교통안전표지판에 대하여 자동인식기능을 개발하고 위치정확도를 분석하여 수치지형도의 도로시설물 효율적 갱신방안 제시를 목적으로 하였다. 이를 위하여 좌표측정을 위한 전방위 카메라 표정요소 산출, GPS/IMU/DMI 통합시스템 구축 및 영상처리기법을 적용하여 수치지형도의 도로시설물 DB의 효율적 갱신방법을 제시하였다.

• 대한토목학회논문집
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• 제38권4호
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• pp.587-593
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• 2018

현재 널리 사용되고 있는 도로교통소음 예측프로그램들은 국외 예측모형을 바탕으로 제작된 것이 대부분이다. 이에 본 연구에서는 국내 도로교통환경에 적합한지를 알아보기 위해 국외 예측모형에 대한 검증을 수행하였다. 또한, 예측모형마다 도로교통소음 발생에 대한 영향요인이 다르기 때문에 주요 요인들에 대한 분석 및 고찰을 선행하였다. 본 연구에서는 도로교통소음 예측 시 사용되고 있는 영향인자와 기존 예측모형에 대하여 고찰하고, 교통환경 및 도로기하구조를 고려하여 주행차량의 발생 소음에 영향을 미치는 영향인자와의 관계를 다중회귀분석을 통한 예측모형으로 도출하였다. 나아가 기존의 도로교통소음 예측모형(국립환경과학원(NIER), 독일의 RLS-90)과 도출된 도로교통소음 예측모형의 실측값을 적용하여 비교 검증 결과, 오차의 절대값 합은 NIER, RLS-90, 모형값 순으로 나타났다. 따라서 본 모형식이 향후 도로교통소음 예측 모델링에 대한 연구의 참고자료로 활용할 수 있는 기틀을 제공하고자 한다.

• 대한인간공학회지
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• 제21권3호
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• pp.25-34
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• 2002

The road sign in dynamic traffic system is an important element which affects on human cognitive performance on driving. Web-based vision system simulator was developed to examine the cognition time of the road sign in dynamic environment. This experiment the cognition time of the road sign in dynamic environment. This experiment was designed in with-subject design with two factors: vehicle speed and the amount of information of the traffic sign. It measured the cognition time of the road sign through two evaluation methods: the subjective test with vision system simulator and computational cognitive model. In these two evaluations of human cognitive performance under the dynamic traffic environment, it demonstrated that subject's cognition time was affected by both the amount of information of traffic sign and driving speed.

• 한국안전학회지
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• 제25권6호
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• pp.186-196
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• 2010

It has been well known that traffic accidents occur under combined functional contributions of drivers, vehicles and road facilities, and that evaluation of safety levels for a specific road section or point is generally much complicated. Additionally, most of traffic accidents occur randomly implicating it is necessary to be evaluated in terms of probability theory. Thus, the evaluation model which reflects various characteristics and probabilistic distributions of traffic accidents has been necessary. The present paper provides a reliability based model with variables of probabilistic operating speeds and design speeds together which have been individually explaining associated characteristics in traffic accidents. Consequently, the model made it possible for speed management and road improvement projects to be evaluated in a common index. Application studies were performed in three cases. Through the studies, couples of facts were identified that the model successfully considered the probabilistic operating speeds and design speeds together and that then, the model evaluated road safety alternatives relatively which are complicatedly characterized and differently located.

• 한국컴퓨터정보학회논문지
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• 제14권10호
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• pp.259-270
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• 2009

본 연구의 목적은 통합도로교통 서비스 체계 구현을 위한 교통정보센터를 구축하는데 있다. 이러한 목적을 달성하기 위하여 기존의 교통정보센터 기능과 운영현황을 분석하고, 통합도로교통정보 서비스를 제공하는 교통정보센터를 개발함으로서 안전지향형 통합도로교통정보센터의 구현사례를 소개한다. 지능형교통체계는 안전지향의 통합도로교통정보 서비스 제공을 통한 교통안전체계를 구현할 뿐 만 아니라 전방의 홍수, 폭설 낙석, 도로유실 붕괴 등과 같은 자연재해 및 긴급상황 발생시 관련 정보를 시의 적절하게 제공함으로써 운전자의 안전한 도로운행을 지원하게 된다. 따라서 통합도로교통정보 서비스체계의 교통정보센터는 국민들에게 편리하게 사용할 수 있는 대국민 교통정보 서비스 제공으로 이용자 친화형 교통관리체계와 통합도로교통정보센터 기능을 실현하는데 일조할 것이다.

• 융합정보논문지
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• 제11권7호
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• pp.14-20
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• 2021

겨울철 도로 결빙으로 인한 사고는 대부분 큰 사고로 이어진다. 이는 운전자가 도로의 결빙을 사전에 자각하기 어렵기 때문이다. 본 연구에서는 AutoML과 CNN의 앙상블 모델을 이용하여 도로교통 이머징 리스크를 정확하게 탐지하는 방법을 연구한다. 비정형 데이터인 이미지를 이용한 CNN 이미지 특징 추출 기반 도로교통 이머징 리스크 분류 모델과 정형 데이터인 기상 데이터를 이용한 AutoML 기반 도로교통 이머징 리스크 분류 모델을 각각 학습시킨다. 그 후 모델들에서 도출된 확률값을 입력하여 CNN 기반 분류 모델을 보완하도록 앙상블 모델을 설계한다. 이를 통해 도로교통 이머징 리스크 분류 성능을 향상하고 더 정확하고 빠르게 운전자에게 경고하여 안전한 주행이 가능하도록 한다.

• 한국안전학회지
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• 제28권6호
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• pp.84-89
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• 2013

The main causes of traffic accidents can be classified by 3 factors - human error, vehicle deficiency and road environmental problem and most accidents occurs not only 1 factor but combination of 2 or 3-factors. Among these factors, road environmental factor is the most important factor due to influence the behavior of cars and road users and road environmental factor affects 30% of total accidents approximately. The 5 years traffic accidents data analyzed to verify the accidents severity on Korea National Highways. In order to analyze the severity, Ordered Probit Model was used. As a independent variables of this model the number of lane, neighbor road environments, sight distance, vertical grade, lane width, shoulder width and traffic volume were used and as a dependent variables the minor injuries, serious injuries and fatalities were used. Research results shows that sight distance and lane width are identified as significant factors for the traffic accident severity and lesser sight distance and lane width shows greater traffic accident severity.

• 한국도로학회논문집
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• 제17권3호
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• pp.59-68
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• 2015

PURPOSES : This study suggests the application of glow line marking technology for reducing traffic accidents at nighttime. METHODS : In this study, using a statistical analysis, we analyzed the characteristics of traffic accidents occurring at nighttime. Next, the strength, weakness, opportunity, and threat (SWOT) factors were derived based on a current-status analysis of glow line marking technology and road environments. An SO strategy, ST strategy, WO strategy, and WT strategy were established in accordance with the four SWOT factors. RESULTS : This study suggests that the following strategies should be promoted to apply glow line marking technology to a road environment: 1) an activation strategy for the technological development of glow line markings for a new paradigm in reducing traffic accidents, 2) a benefit enhancement strategy applying glow line marking technology in places where nighttime traffic accidents frequently occur, 3) a strategy for the expansion of glow line marking by replacing streetlights, and 4) a strategy for enhancing road applications through the development of various line marking methods in consideration of both performance and costs. CONCLUSIONS : The application of glow line markings in a road environment can contribute to a reduction of traffic accidents at nighttime, and aid energy savings from the replacement of streetlights.

• 대한안전경영과학회지
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• 제13권1호
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• pp.127-131
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• 2011

Even if there are no causing factors such as car crash and road works, traffic congestion come from traffic growth on the road. In this case, estimation of traffic flow helps find the solution of traffic congestion problem. In this paper, we present a optimization model which used on traffic equilibrium problem and studied the problem of inverting shortest path sets for complex traffic system. And we also develop pivotal decomposition algorithm for reliability function of complex traffic system. Several examples are illustrated.

• 상하수도학회지
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• 제23권5호
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• pp.631-636
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• 2009

This study has its intention to investigate the water quality of non-point source which is runoff from roads. We have classified and selected twelve sites as city road, industrial road, national road and mountain road by considering their traffic volume and surroundings. Water quality was analyzed based on BOD, COD, SS, T-N and T-P and the concentrations were measured by sampling after rainfall with the interval of 10 minutes, 20 minutes, and 30 minutes. BOD was the highest in city road with 57.6 mg/L and the lowest in mountain road with 45.0 mg/L. For COD, the highest concentration in industrial road was 146.5 mg/L and the lowest was in mountain road with 98.0 mg/L. The run off concentration of SS was up to maximum 630.0 mg/L (average 280.4 mg/L) which was remarkable compared to other types of road. It showed its lowest concentration in national road with 76.0 mg/L. T-N and T-P were the highest in industrial road and the lowest in mountain road. We found out that the runoff concentration was high with large amount of traffic volume and it seemed to be high in city road and industrial road where they were largely affected by their surroundings. Relatively, national road and mountain road seemed to show low concentration as they have less traffic volume and less affected by their surroundings.