• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.5
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• pp.47-52
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• 2011

Vehicle classification data are considerably used in the almost all fields of transportation planning and engineering. Highway agencies use a large number of vehicle classification schemes. Vehicles on the national highway are classified by 12-Category classification system, using number of axles, distances between axles, vehicle length, overhang, and other factors. In the case of using existing axle-sensor-based classification counters (that is, 12-category classification system), two-axle vehicles(Class 1 to 4) can be erroneously classified because a passenger vehicle becomes larger and similar with class 3 and 4. In this reason, this study proposes the vehicle classification scheme based on using vehicle height profiles obtained by a laser sensors. Also, the accuracy of the proposed method are tested through a field study.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.1D
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• pp.45-51
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• 2010

Traffic volume is essential data for traffic control or maintenance and rehabilitation planning. The volume especially with respect to the type of vehicles can facilitate to those road operations. In this research, a method for vehicle classification was developed using skewed sensors which can generate traffic signatures. In order to characterize vehicle types, the method investigates whether the second axle of each vehicle consists of dual tires. The presence of dual tire is determined by the discriminate function obtained from discriminant analysis. The validation using 1,878 vehicles recorded from a highway using a CCTV camera indicated significantly accurate results: 96.92% for class 1, 82.91% for class 3 and 79.13% for class 4.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.1
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• pp.153-159
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• 2012

Driver's view has blind spot of automobile surroundings due to physical components of automobile architecture. Obstacles on blind spot are the cause of car destruction and car accidents. Cars which produced in recent have obstacle detection sensors and rear view cameras which provide information of obstacles on the blind sopt, and have also AVM(Around View Monitoring) which provides automobile surroundings for driver's safe driving. During a low-speed travel while parking or moving in a narrow street, a driver get help for safe driving by taking information of automobile surroundings using the above-mentioned devices. In this paper, we present a design and implementation of a 4-sided monitoring (4SM) system, which helps a driver see an integrated view of a vehicle's perimeter at a glance, using a car PC connected to four cameras installed on the front, rear, left, and right sides.

• Journal of the korean Society of Automotive Engineers
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• v.16 no.4
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• pp.6-22
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• 1994

본 연구에서는 각각의 대체에너지 차량과 기타 저공해과제(촉매기술 등)에서 구체적인 재료의 역할을 알아본다. 1. 메타놀 차량. 2. 전기자동차. 3. 천연가스 차량. 4. 촉매기술. 5. 저공해 차량의 여러 고려사항.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.461-467
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• 2006

To detect individual vehicular speed, double loop detection technique has been widely used. This paper investigates four methodologies to measure individual speed using only a single loop sensor in a traveling lane. Two methods developed earlier include estimating the speed by means of (Case 1) the slop of inductance wave form generated by the sensor and (Case 2) the average vehicle lengths. Two other methods are newly developed through this study, which are estimations by measuring (Case 3) the mean of wheelbases using the sensor installed traversal to the traveling lane and (Case 4) the mean of wheel tracks by the sensor installed diagonally to the traveling lane. These four methodologies were field-tested and their accuracy of speed output was compared statistically. This study used Equality Coefficient and Mean Absolute Percentage Error for the assessment. It was found that the method (Case 1) was best accurate, followed by method (Case 4), (Case 2), and (Case 3).

• Computational Structural Engineering
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• v.10 no.4
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• pp.12-21
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• 1997

차량충돌에 대하여 운전자의 안전확보를 위하여 새로 개발한 철재 중앙분리대에 대한 안전성 분석을 위하여 인체모형을 탑재한 실물차량 충돌실험을 실시하였다. 인체모형의 두부와 흉부, 대퇴부 및 차량의 무게중심점에서 가속도와 충격하중을 계측하여 철재 중앙분리대 방호울타리에 차량충돌시 운전자의 안전성을 검증한 결과 다음과 같은 결론을 도출하였다. 1) 철재 중앙분리대 방호울타리는 콘크리트 중앙분리대 방호울타리에 비해 운전자의 신체 상해치와 차량파괴 등에 있어서 뛰어난 충격흡수성능을 보여주었다. 2) 철재 중앙분리대 방호울타리는 콘크리트 중앙분리대 방호울타리의 경우 빈번히 발생하는 차량전복과 같은 2차사고의 유발 가능성이 전혀 없는 구조적 안정성을 보여주었다. 3) 경량의 차량충돌에 대하여 자체 탄성영역내에서 충격을 흡수하여 유지보수 측면에서 유리함을 나타냈다. 4) 충돌 수 충돌차량에 대한 차량유도성능이 뛰어났으며, 차량의 충돌후 이탈각도는 충돌각도의 60% 이내로 나타났다. 5) 철재 중앙분리대 방호울타리로부터 분리된 파편이 거의 없어 도로소통에 지장을 초래하지 않는다.

• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.81-93
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• 2022

Recently, there have been many studies on object recognition around the vehicle and recognition of traffic signs and traffic lights in autonomous driving. In particular, such the recognition of traffic lights is one of the core technologies in autonomous driving. Therefore, many studies for such the recognition of traffic lights have been performed, the studies based on various deep learning models have increased significantly in recent. In addition, as a high-quality AI training data set for voice, vision, and autonomous driving is released on AIHub, it makes it possible to develop a recognition model for traffic lights suitable for the domestic environment using the data set. In this study, we developed a recognition model for traffic lights that can be used in Korea using the AIHub's training data set. In particular, in order to improve the recognition performance, we used various models of YOLOv4 and YOLOv5, and performed our recognition experiments by defining various classes for the training data. In conclusion, we could see that YOLOv5 shows better performance in the recognition than YOLOv4 and could confirm the reason from the architecture comparison of the two models.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.1
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• pp.53-65
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• 2012

Recently wireless intra-vehicle communication has received a great interest from the automotive industry and ultra wideband (UWB) technology is considered as one of the potential candidate for this system. Many research works have been done on the measurement and modeling of intra-vehicle communication channel. However, very little work has been reported for the performance analysis of various PHY layer methods under the intra-vehicle communication environment. This paper is to study IEEE 802.15.4a standard in intra-vehicle channel and to evaluate its performance. Channel model in chassis and engine compartment is considered for evaluation. Through simulation BER performance of system with different receiver structures is analyzed.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.1303-1306
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• 2005

최근 차량에 설치된 단말기를 통해 길안내 서비스, 교통정보 서비스 등 다양한 정보를 제공하는 텔레매틱스 서비스가 활발하게 연구되고 있다. 하지만 현재 대다수의 텔레매틱스 서비스는 최대 15m의 공간 오차를 가진 GPS 기술을 이용하기 때문에 차량의 정확한 위치정보를 파악하기는 힘들다. 따라서 본 연구에서는 무선 센서 노드를 이용해 GPS보다 정확한 차량의 위치정보와 속도를 감지해 교차로에서 발생할 수 있는 차량 충돌을 예측하고 충돌 위험 정보를 교차로에 근접한 자동차에게 알려주는 텔레매틱스 교통안전시스템을 구성하고 노드 간 통신 프로토콜로서 IEEE 802.15.4[1]를 채택한 후 고정 라우팅 방식으로 차량정보를 베이스 스테이션까지 보내어 교차로 주변차량 전체에 브로드캐스트하는 방식을 취하도록 한다. 빠르게 이동하는 차량의 특성상 교차로 차량 충돌 방지 서비스 구현에 있어서 높은 실시간성과 신뢰성을 갖춘 프로토콜이 요구된다. 따라서 본 차량 충돌 예측을 위한 교통안전시스템의 신뢰성과 실시간성을 평가하기 위하여 Network Simulator 2 (NS/2)[2]를 이용하여 시뮬레이션 한다.

• Journal of the korean Society of Automotive Engineers
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• v.4 no.1
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• pp.5-19
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• 1982

차량에 있어서 제동장치가 차지하는 중요도는 다른 부품에 비하여 매우 크다고 말할 수 있겠다. 그래서 차량 brake system을 적용하는데 있어서 가장 기초가 되는 수식 및 일반사항을 설명 함으로써 차량과 brake 관계를 넓게 이해하고 가장 적합한 제동장치의 설계에 도움을 주려는 데 본 기술의 목적이 있다. 우선 차량제원에 맞는 brake 성능에 관하여 생각하여 보자. 2개의 차 축을 갖고 있는 차량에서 제동할 경우 전 후 차축(front axle, rear axle)의 동하중(dynamic weight)은 정지상태 때의 하중과는 달라지게 된다. 그러므로 brake 성능은 이 동하중의 분배에 좌우되는 것이다.