• 한국도로학회논문집
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• 제13권4호
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• pp.221-229
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• 2011

도로 설계는 자연 지형에 순응하도록 선형을 결정함으로써 경제적이며 환경적인 피해가 최소화되는 도로 건설이 이루어지도록 할 필요가 있다. 현 도로설계기준은 지형을 평지와 산지로만 구분하고 있으나 국토의 25.8%가 구릉지이며 미국이나 호주 등 선진국의 경우도 지형을 평지, 구릉지, 산지로 세분화하여 자연 지형에 최대한 부합되는 설계를 유도하고 있음을 감안 시 구릉지를 포함한 세분화된 기준이 필요하다. 본 연구는 원지반의 기복량을 지표로 세 가지 독립된 지형간의 구분 기준을 정량적으로 제시하였다. 세분화된 지형 정의를 전제로 지형을 구분할 수 있는 방안에 대한 개념적 틀을 세우고 이를 도로설계 사례분석 등을 토대로 검토하였다. 연구 결론으로, 평지는 설계 단위구간(1km) 내 지반고 최고점과 최저점의 차이가 40m 미만, 구릉지는 40~60m 이내, 산지는 60m를 초과하는 것으로 제안하였다.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제4권11호
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• pp.521-528
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• 2015

도로주행 영상에서의 객체 검출에 관한 기존의 연구들은 날씨 및 조명 상태에 따른 객체 검출의 어려움 때문에 대부분 맑은 날씨의 영상을 대상으로 연구가 진행되었다. 본 논문에서는 도로주행 영상의 다양한 날씨 및 조명 상태를 먼저 판단하고, 이를 기반으로 도로 이정표에 대한 색상모델을 설정하여 이정표 객체를 찾는 방법을 제안한다. 제안한 방법은 5종류의 도로 이미지 특징을 이용하여 맑음, 흐림, 비, 야간, 역광으로 날씨 및 조명 상태를 먼저 분류하고, 각각의 상태에서 대상 이정표 색상의 픽셀값의 범위를 추출하여 GMM(Gaussian Mixture Model)을 생성하고 이를 객체 추출에 사용한다. 날씨 및 조명이 다양하게 변하는 도로주행 영상에 제안한 방법을 적용하여 이정표 영역이 안정적으로 찾아지는 것을 확인할 수 있었다.

• 한국군사과학기술학회지
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• 제13권5호
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• pp.894-902
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• 2010

This paper presents a vision-based robust off-road terrain classification method against environmental variation. As a supervised classification algorithm, we applied a neural network classifier using wavelet features extracted from wavelet transform of an image. In order to get over an effect of overall image feature variation, we adopted environment sensors and gathered the training parameters database according to environmental conditions. The robust terrain classification algorithm against environmental variation was implemented by choosing an optimal parameter using environmental information. The proposed algorithm was embedded on a processor board under the VxWorks real-time operating system. The processor board is containing four 1GHz 7448 PowerPC CPUs. In order to implement an optimal software architecture on which a distributed parallel processing is possible, we measured and analyzed the data delivery time between the CPUs. And the performance of the present algorithm was verified, comparing classification results using the real off-road images acquired under various environmental conditions in conformity with applied classifiers and features. Experiments show the robustness of the classification results on any environmental condition.

• Journal of Information Processing Systems
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• 제2권1호
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• pp.52-57
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• 2006

One of the important functions of an Intelligent Transportation System (ITS) is to classify vehicle types using a vision system. We propose a method using machine-learning algorithms for this classification problem with 3-D object model fitting. It is also necessary to detect road lanes from a fixed traffic surveillance camera in preparation for model fitting. We apply a background mask and line analysis algorithm based on statistical measures to Hough Transform (HT) in order to remove noise and false positive road lanes. The results show that this method is quite efficient in terms of quality.

• 한국도로학회논문집
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• 제16권6호
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• pp.181-189
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• 2014

PURPOSES : Ambiguous decision on whether rural or urban area for road design can increase the construction cost and restrict the land use of surrounding area. However, administrative classification on rural and urban area is not directly related to road design because of this classification is not based on the engineering viewpoint, so method which can explain the road design context is required. METHODS : Method which enables to identify the area for road design is suggested based on the deceleration expected to be experienced by drivers who use the road section concerned. Deceleration rate corresponding to the area such as rural or urban suggested in Road Design Guideline is used as the criteria to identify the area by comparing this value with the estimated deceleration rate at the road section concerned. Speed profile method is utilized to derive the deceleration rate, and speed estimation way for reflecting both road geometry and intersection is suggested using stopping sight distance concept. RESULTS : The procedure of the method application is suggested, and the design example utilizing the method is provided. CONCLUSIONS : The method is expected to be used to identify the area for road design with engineering viewpoint, and design consistency among the roads with similar driving environment can be made.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 춘계학술대회논문집
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• pp.872-876
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• 2007

Road traffic noise map is effective method to save cost and time for environmental noise assessment. Generally, noise is calculated by using theoretical equation of noise prediction, and the calculated result can be influenced by various input factors. Especially, domestic vehicle classification method for traffic flow and heavy vehicle percentage is different from that of foreign countries. Thus, this can cause effect on the noise prediction results. In this study, noise prediction results by using domestic vehicle classification method are compared with those by foreign methods.

• 한국소음진동공학회논문집
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• 제22권2호
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• pp.193-197
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• 2012

Road traffic noise map is effective method to save cost and time for environmental noise assessment. Generally, noise is calculated by using theoretical equation of noise prediction, and the calculated result can be influenced by various input factors. Especially, domestic vehicle classification method for traffic flow and heavy vehicle percentage is different from that of foreign countries. Thus, this can cause effect on the noise prediction results. In this study, noise prediction results by using domestic vehicle classification method are compared with those by foreign methods.

• 한국도로학회논문집
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• 제17권2호
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• pp.143-150
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• 2015

PURPOSES : The authors set out to estimate the related carbon emissions, energy use, and costs of the national freeways and highways in Korea. To achieve this goal, a macro-level methodology for estimating those amounts by road type, road structure type, and road life cycle was developed. METHODS : The carbon emissions, energy use, and costs associated with roads vary according to the road type, road structure type, and road life cycle. Therefore, in this study, the road type, road structure type, and road life cycle were classified into two or three categories based on criteria determined by the authors. The unit amounts of carbon emissions and energy use per unit road length by classification were estimated using data gathered from actual road samples. The unit amounts of cost per unit road length by classification were acquired from the standard cost values provided in the 2013 road business manual. The total carbon emissions, energy use, and cost of the national freeways and highways were calculated by multiplying the road length by the corresponding unit amounts. RESULTS: The total carbon emissions, energy use, and costs associated with the national freeways and highways in Korea were estimated by applying the estimated unit amounts and the developed method. CONCLUSIONS: The developed method can be employed in the road planning and design stage when decision makers need to consider the impact of road construction from an environmental and economic point of view.

• 대한산업공학회지
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• 제26권4호
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• pp.354-362
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• 2000

Increasing amount of road tragic in 90's has drawn much attention in Korea due to its influence on safety problems. Various types of data analyses are done in order to analyze the relationship between the severity of road traffic accident and driving conditions based on traffic accident records. Accurate results of such accident data analysis can provide crucial information for road accident prevention policy. In this paper, we apply several data fusion, ensemble and clustering algorithms in an effort to increase the accuracy of individual classifiers for the accident severity. An empirical study results indicated that clustering works best for road traffic accident classification in Korea.

• 한국도로학회:학술대회논문집
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• 한국도로학회 2005년도 학술발표회 논문집
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• pp.401-406
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• 2005