• 한국콘텐츠학회논문지
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• 제7권2호
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• pp.30-39
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• 2007

본 연구는 고안전도 차량의 자율주행을 위해 필수적인 장애물 차량 탐지를 위한 시스템 개발에 관한 것이다. 먼저 칼만필터를 이용해 차량에 부착된 CCD 카메라에 의해서 획득한 전방 영상으로부터 주행차선의 경계를 탐지한다. 그리고 탐지된 경계의 회귀분석을 통해 차선을 인식한다. 다음으로 주행 방향을 인식하기 위해 탐지된 차선내의 도로 굴곡 파라미터를 오류 역전파 알고리즘의 입력값으로 사용한다. 마지막으로 전방과 측방에 탐지영역을 설정함으로써 탐지영역으로 들어오는 장애물 차량을 탐지할 수 있다. 제안한 방법으로 실험한 결과 주행방향 인식과 장애물 차량의 인식 모두 90% 이상의 높은 정확도를 보였다.

• 한국전기전자재료학회논문지
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• 제28권8호
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• pp.544-549
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• 2015

Since LEDs (light emitting diodes) have many advantages as a light source in vehicle headlamp, such as good reliability, energy and space saving, and flexible headlamp design. On the other hand, the dependence of its performance and life on temperature have great influence on its practical use. In this study, design and fabrication of heat sink for vehicle LED headlamp were performed using thermally-conductive plastics. This study focused on the effective heat sink structure with limited space in the vehicle LED headlamp. We designed two different prototype of heat sink by thermal simulation using SolidWorks program, which had excellent temperature characteristics. The two different prototype of heat sink were fabricated by injection molding with thermally-conductive plastics. The results showed that LED $T_j$ (junction temperature) of sample B (model 1) and sample C (model 1, 2) was below then $165^{\circ}C$ when applying the thermally-conductive plastics in heat sink of vehicle LED headlamp.

• 한국ITS학회 논문지
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• 제1권1호
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• pp.70-78
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• 2002

치관 국제적으로 전방차량을 따라 순항하거나 전방 장애물을 인식해 경고를 주는 등 교통 및 도로 상황에 대응하여 운전자에게 안전운전을 지원하는 기능을 갖춘 첨단안전차량(Advanced Safety Vehicle: ASV)이 개발되어 시판되고 있다. 국제표준기구(ISO) ITS기술위원회(TC2O4)의 도로/차량 경고 및 제어시스템(Vehicle/Roadway Warning and Control System) 분야(WGl4)에서는 ASV의 각종 기능과 관련한 국제표준을 제정하기 위한 작업이 활발히 진행되고 있다. 또한 각 국가들은 ASV 핵심기능들을 대상으로 그 나라의 도로 및 교통 환경 하에서 실차 주행시험을 통해 기능의 안전도 및 적합성을 평가하는 연구개발을 진행하고 있다 우리나라에서도 건설교통부 ITS 연구개발사업을 통해 ASV 핵심 기능의 하나인 감응식순항제어(Adaptive Cruise Control: ACC)에 대한 국내의 주행 적합성을 평가하기 위한 종합 시험평가 프로그램이 개발 제시되었다. 본 논문에서는 진행중인 국제표준을 근거로 국내의 도로/교통조건에 따른 차량주행 시나리오를 통해 개발된 ACC 종합시험평가 프로그램을 소개하고 이에 따라 실시된 시험결과를 분석한다 이를 통해 결과적으로 ACC의 곽내 주행을 위한 안전기준의 필요성을 제시한다.

• 자동차안전학회지
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• 제10권4호
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• pp.33-39
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• 2018

Recently, the automobile industry has developed ADAS (Advanced Driver Assistance System) to prevent traffic accidents and reduce driver's driving burden. Among the ADAS, the LKAS (Lane Keeping Assistance System) is a support system for the convenience and safety of the driver, and the main function is to maintain the driving lane of the vehicle. LKAS is a system that uses radar sensor and camera sensor to collect information about the position of the vehicle in the lane and to support keeping the lane through control if necessary. In many countries, LKAS has already been commercialized and the convenience and safety of drivers have been improved. The international LKAS evaluation test procedure is being developed and discussed by standardization committees such as the ISO (International Organization for Standardization) and the Euro NCAP (New Car Assessment Program). In Korean, the LKAS test method is specified in the KNCAP (Korean New Car Assessment Program), but the evaluation method is not defined. Therefore, the LKAS test procedure that meets international standards and is suitable for domestic road environment is necessary. In this paper, development of LKAS test evaluation scenarios that meets international standards and considering domestic road environment, and the formula that can evaluate the result value after control as the relative distance of lane and the front wheel are suggested. And a comparative analysis was conducted to verify the validity of the suggested scenario and formula. The test evaluation was conducted using the vehicle equipped with the LKAS.

• 융합신호처리학회논문지
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• 제22권2호
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• pp.85-90
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• 2021

운전자의 안전 운전을 위한 첨단 운전자 보조시스템(ADAS; Advanced Driver Assistance System)은 자율주행 자동차에서 중요한 연구 분야 가운데 하나이다. 특히, 이전에 자동차에 부착된 영상센서를 기반으로 한 ADAS 소프트웨어는 구축 비용이 저렴하고 그 활용도가 우수하다. 본 논문에서는 선행차의 주행 상황을 인지할 수 있는 선행 차량 후미등(Tail-Lamp)의 정지등(Break-Lamp) 영역을 검출하는 알고리즘을 제안한다. 제안하는 방법은 주행 영상으로부터 객체 추적에 우수한 성능을 보이고 있는 YOLO 기술을 이용하여 자동차 객체를 추출하고, 추출된 자동차 관심 영역의 HSV 영상을 이용하여 정지등의 밝기 변화 영역을 검출한다. 그 다음 검출된 각 정지등 후보 고립영역을 라벨링하여 후보 영역들 간의 모양 대칭성을 인지하는 선택적 주의집중 모델(Selective Attention Model)을 적용하여 정지등 영역을 검출한다. 제안한 알고리즘의 성능 평가를 위하여 다양한 주행 영상에 적용하여 실험한 결과 ADAS에 적용 가능한 성공적인 검출 결과를 보였다.

• 대한임베디드공학회논문지
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• 제12권2호
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• pp.113-120
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• 2017

In this paper, we present a night-time vehicle detection method using CNN (Convolutional Neural Network) classification. The camera based night-time vehicle detection plays an important role on various advanced driver assistance systems (ADAS) such as automatic head-lamp control system. The method consists mainly of thresholding, labeling and classification steps. The classification step is implemented by existing CIFAR-10 model CNN. Through the simulations tested on real road video, we show that CNN classification is a good alternative for night-time vehicle detection.

• Journal of Advanced Marine Engineering and Technology
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• 제25권1호
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• pp.124-130
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• 2001

This paper presents a methodology on automation of a trailer type vehicle which consists of two parts: a tractor and a trailer. Backward moving and parking control is very important to automate this type of vehicle. It is difficult to control the motion such a trailer vehicle whose dynamics in non-holonomic. Therefore, in this paper, the modeling and parameter estimation of the system using a RCGA(real-coded genetic algorithm) is proposed and a backward path tracking control algorithm is then obtained. The simulation results verify the effectiveness of the proposed method.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 추계학술대회
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• pp.696-701
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• 2004

A vehicle cruise control algorithm using an Interacting Multiple Model (IMM)-based Multi-Target Tracking (MTT) method has been presented in this paper. The vehicle cruise control algorithm consists of three parts; track estimator using IMM-Probabilistic Data Association Filter (PDAF), a primary target vehicle determination algorithm and a single-target adaptive cruise control algorithm. Three motion models; uniform motion, lane-change motion and acceleration motion, have been adopted to distinguish large lateral motions from longitudinal motions. The models have been validated using simulated and experimental data. The improvement in the state estimation performance when using three models is verified in target tracking simulations. The performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. These simulations show system response that is more realistic and reflective of actual human driving behavior.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.511-514
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• 2005

This paper propose an advanced control strategy to improve vehicle handling and directional stability by integrating Active Front Steering(AFS) with Electronic Stability Program(ESP) . The effect of the integrated control system on the vehicle handling characteristics and directional stability is studied through a close loop computer simulation of and eight degree of freedom nonlinear vehicle model and driver model. Simulation results confirm the effectiveness of the proposed control system and the overall improvements in vehicle handling and directional stability

• 대한산업공학회지
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• 제30권4호
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• pp.346-354
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• 2004

Most industrial logistic systems have focused on carrying products from manufacturers or distribution centers to customers. In recent years, they are faced with the problem of integrating reverse flows into their transportation systems. In this paper, we address the vehicle routing problems with mixed delivery and pick-up(VRPMDP). Mixed operation of delivery and pick-up during a vehicle tour requires rearrangement of the goods on board. The VRPMDP considers the reshuffling time of goods at customers, hard time windows, and split operation of delivery and pick-up. We construct a mixed integer mathematical model and propose a new genetic algorithm named GAMP for VRPMDP. Computational experiments on various types of test problems are performed to evaluate GAMP against the modified Dethloff's algorithm. The results show that GAMP reduces the total vehicle operation time by 5.9% on average, but takes about six times longer computation time.