• 한국도로학회지:도로
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• v.6 no.2 s.20
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• pp.40-46
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• 2004

• Journal of Broadcast Engineering
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• v.21 no.4
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• pp.609-620
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• 2016

Recently, there are active studies on a forward collision warning system to prevent the accidents and improve convenience of drivers. For collision evasion, the vehicle detection system is required. In general, existing learning-based vehicle detection methods use the entire appearance of the vehicles from rear-view images, so that each vehicle types should be learned separately since they have distinct rear-view appearance regarding the types. To overcome such shortcoming, we learn Haar-like features from the lower part of the vehicles which contain tail lights to detect vehicles leveraging the fact that the lower part is consistent regardless of vehicle types. As a verification procedure, we detect tail lights to distinguish actual vehicles and non-vehicles. If candidates are too small to detect the tail lights, we use HOG(Histogram Of Gradient) feature and SVM(Support Vector Machine) classifier to reduce false alarms. The proposed forward vehicle detection method shows accuracy of 95% even in the complicated images with many buildings by the road, regardless of vehicle types.

• Proceedings of the KSR Conference
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• 2003.05a
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• pp.151-158
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• 2003

현재 각 도시철도 운영기관이 사용하고 있는 부품코드체계는 구 정부물품 분류체계 11자리를 수요한 코드체계로의 군, 급의 2단계 분류로 구성되어 있어, 분류단계의 제약이 존재할 뿐만 아니라 분류체계의 구조적 문제로 군, 급, 품명의 빈번한 통합, 삭제에 따른 코드 관리의 어려움이 존재하고 있다. 또한, 사용자가 원하는 물품을 해당 분류체계로 찾아가기 위한 그룹별 탐색과 통계적 분석이 불가능한 실정이다. 이러한 분류체계의 문제점과 향후 차종의 노후화로 발생될 관리품목의 증가로 업무능률 저하가 예상되기 때문에 새로운 체계의 표준화된 부품코드체계가 절실히 필요한 실정이다. 본 논문은 산업 발전에 따르는 확장성과 세분화에 대한 분류구조의 탄력성을 가지고 객관적으로 분류 추가 및 변경이 가능하도록 하고, 정부 및 국제기관 표준권고안과 호환성을 가질 수 있는 표준 부품코드체계를 제정하기 위한 연구결과이다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.345-346
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• 2018

차종 별 교통량 자료는 도로의 유지관리나 분석 등의 행정 처리 업무에 필요한 기본 자료임과 동시에 각종 연구에 활용된다. 본 시스템은 그 일환으로서 화물차나 일반차량을 구분하여 특정 도로의 화물차 비율이나 교통량을 파악하는데 활용할 수 있다. 머신 러닝 알고리즘 중에서 높은 성능을 보이는 Support Vector Machine (SVM) 알고리즘을 이용하여 도로 위의 일반차량과 화물차를 구분하였다. 우선, 화물차와 일반차량의 차이를 구분하고자 각각의 영상에 대해 Histogram of Oriented Gradients (HOG) 기반 특징점을 추출하고 이에 따라 1 차원 벡터로 표현된 데이터를 SVM 으로 분류하여 구분한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.1-17
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• 2021

Identifying the exact train and the type of train boarded by passengers is practically cumbersome. Previous studies identified the trains boarded by each passenger by matching the Automated Fare Collection (AFC) data and the train schedule diagram. However, this approach has been shown to be inefficient as the exact train boarded by a considerable number of passengers cannot be accurately determined. In this study, we demonstrate that the AFC data - diagram matching technique could not estimate 28% of the train type selected by passengers using the Seoul Metro line no.9. To obtain more accurate results, this paper developed a two-step method for estimating the train type boarded by passengers by applying the AFC data - diagram matching method followed by a mixture distribution analysis. As a result of the analysis, we derived reasonable express train use/non-use passenger classification points based on 298 origin-destination pairs that satisfied the verification criteria of this study.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2017.11a
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• pp.245-246
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• 2017

현재 고령자는 65세 이상으로 정해져 있고 고령 운전자 사고에 관련된 연구들은 65세를 기준으로 일반 운전자와 고령 운전자를 구분한다. 하지만 실질적으로 교통약자로 분류되어야 하는 신체 능력을 가진 고령 운전자를 구분하는 연구는 부족한 실정이다. 분석결과 차종별 주요 사고특성에 대해 70세 이상의 경우 사고 발생에 미치는 영향력이 높아지는 것으로 나타났으며, 70~80세 구간에서 사고 발생 빈도가 상대적으로 낮았던 승용차에 대해서도 주요사고특성을 분석한 결과 75~84세 구간에서 사고 발생에 대한 영향력이 높아지는 것이 나타났다. 이는 고령화가 진행되고 평균 수명이 늘어나 고령자 구간 폭도 증가하기 때문에, 고령자 내에서도 특성이 나뉘게 되고 본 연구를 통해 연령군집별로 사고 발생에 대한 영향력이 달라지는 것을 확인하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.66-69
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• 2007

차량의 종류(차종)에 관한 정보는 ITS(지능형 교통시스템) 및 각종 교통 관련 분야에서 각종 교통 분석 및 지표로 활용될 수 있는 기초 정보이며 교통제어나 차량에 연관된 범죄 등에서 자동차의 인식에 관한 연구의 중요성 때문에 이에 관련된 연구는 오래 전부터 수행되어왔다. 본 논문에서는 차량의 크기를 바탕의 이륜, 소형, 중형, 대형 등 4종으로 차량을 분류 하였다. 차량영역 획득 과정에서 발생하는 잡음 및 조명변화 등 환경적 요인을 극복하고자 윤곽선정보와 배경차분법을 이용해 획득된 차영상 정보의 합영상을 획득하였다. 실험영상으로는 실제 교통관제 시스템에서 획득된 영상을 사용하였으며 실험결과 90%이상의 인식률을 보였다.

• International Journal of Highway Engineering
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• v.11 no.4
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• pp.69-78
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• 2009

Korea has achieved significant economic growth with building the Gyeongbu Expressway. As the number of new road construction projects has decreased, it becomes more important to maintain optimal status of the current road networks. One of the best ways to accomplish it is weight enforcement as active control measure of traffic load. This study is to develop High-speed Weigh-in-motion System in order to enhance efficiency of weight enforcement, and to analyze patterns of overloaded trucks on highways through the system. Furthermore, it is to review possibilities of developing overweight control system with application of the HS-WIM system. The HS-WIM system developed by this study consists of two sets of an axle load sensor, a loop sensor and a wandering sensor on each lane. A wandering sensor detects whether a travelling vehicle is off the lane or not with the function of checking the location of tire imprint. The sensor of the WIM system has better function of classifying types of vehicles than other existing systems by detecting wheel distance and tire type such as single or dual tire. As a result, its measurement errors regarding 12 types of vehicle classification are very low, which is an advantage of the sensor. The verification tests of the system under all conditions showed that the mean measurement errors of axle weight and gross axle weight were within 15 percent and 7 percent respectively. According to the WIM rate standard of the COST-323, the WIM system of this study is ranked at B(10). It means the system is appropriate for the purpose of design, maintenance and valuation of road infrastructure. The WIM system in testing a 5-axle cargo truck, the most frequently overloaded vehicle among 12 types of vehicles, is ranked at A(5) which means the system is available to control overloaded vehicles. In this case, the measurement errors of axle load and gross axle load were within 8 percent and 5 percent respectively. Weight analysis of all types of vehicles on highways showed that the most frequently overloaded vehicles were type 5, 6, 7 and 12 among 12 vehicle types. As a result, it is necessary to use more effective overweight enforcement system for vehicles which are seriously overloaded due to their lift axles. Traffic volume data depending upon vehicle types is basic information for road design and construction, maintenance, analysis of traffic flow, road policies as well as research.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.1
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• pp.66-76
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• 2016

Determination of type of a vehicle is being used in various areas such as collecting tolls, collecting statistical traffic data and traffic prognosis. Because most of the vehicle type classification systems depend on vehicle length indirectly or directly, highly reliable automatic vehicle length measurement system is crucial for them. This study makes use of a pencil beam laser rangemeter and devises a mechanical device which rotates the laser rangemeter. The implemented system measures the range between a point and the laser rangemeter then indicates it as a spherical coordinate. We obtain several silhouettes of cross section of the vehicle, the rate of change of the silhouettes, signs of the rates then squares the rates to apply cell averaging constant false alarm rate (CA-CFAR) technique to find out where the border is between the vehicle and the background. Using the border and trigonometry, we calculated the length of the vehicle and confirmed that the calculated vehicle length is about 94% of actual length.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11b
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• pp.208-211
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• 2005

This paper describes the development process of steering system for reduce idle vibration through the data level of frequency and sensitivity. High stiffness and light weight vehicle is a major target in the refinement of passenger cars to meet customers' contradictable requirements between NVH performance and fuel economy. The target frequency of the steering system is set by benchmarking of a competitive vehicle and the vibration mode map is used to separate steering column modes from resonance of body structure and engine idle rpm. This paper descirbes the analysis approach process for high stiffness of steering system and the design guideline is suggested about steering column and support system by using mother car at initial design stage. We used a patent map in order to analyze accurately a technical trend and suggested the design process using dynamic damper of steering system considering sensitivity. And we established techniques of analysis on steering system and evaluated the level of accuracy of analysis through correlating the test and analysis results. It makes possible to design the good NVH performance vehicle at initial design stage and save vehicles to be used in tests. These improvements can lead to shortening the time needed to develop better vehicles.