• 한국지능시스템학회논문지
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• 제21권4호
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• pp.430-435
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• 2011

본 논문에서는 상대위치인식과 자계기반 안내를 결합한 무인주행 차량의 주행기법을 제안한다. 자계기반 주행은 이동하는 경로에 자계가 항상 계측되면 안정적인 자율주행이 가능하다. 하지만 외부요인으로 인해 자계가 검출되지 않으면 예측 불가능한 상황이 발생하는 단점이 있다. 따라서 상대위치인식을 이용한 무인주행을 통해 자계가 검출되지 않는 구간을 극복하는 방법을 제안하였다. 제안한 방법의 유용함을 검증하기 위하여 차량을 개발하고 자계기반 주행 실험하였다. 또한 자계가 없는 구간에서의 상대항법을 이용한 무인주행 실험을 실시하고 결과를 분석하여 문제점 극복의 가능성을 확인하였다.

• 센서학회지
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• 제24권3호
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• pp.175-180
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• 2015

Worldwide, studies on intelligent vehicles for the convenience of drivers have been actively conducted as the number of cars has increased. However, vehicle convenience enabled by buttons lowers the concentration on driving and hence poses as a huge threat to the safety of the driver. The use of one of the convenient features, impaired driving auxiliary equipment, is limited because of its complex usage, and this device also hinders the front view of the driver. This paper proposes a vehicle-control device for controlling the convenient features as well as changes in speed and direction using gestures and motions of the driver. This device consists of an ultrasonic sensor for recognizing movement, an arduino for accepting signal control functions and servo and DC motors apply to various vehicle parts. Firstly, the vehicle-control device was designed using a 3D CAD program known as Solid-works based on the size of the steering wheel. Then, through simulations, a suitable length for minimizing the absorbent between ultrasonic sensors was confirmed using a program known as COMSOL Multiphysics. Finally, simulation results were verified through experiments, and the optimal size of the device was identified through the number of errors.

• 한국지능시스템학회논문지
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• 제18권6호
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• pp.775-780
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• 2008

본 논문에서는 자계표식을 이용한 로봇형 차량의 무인주행기술을 제안한다. 자계표식을 이용한 주행시스템에서 가장 중요한 것은 자계도로상의 자석의 위치예측이다. 자석의 위치를 예측하기 위하여 자석과 센서의 상관관계를 해석하고 도로에 매설된 자석의 위치를 검출하기 위한 배열형 자계표식 위치인식센서를 제안한다. 또한 스텝모터를 이용한 조향제어장치를 개발하고 자동모드 및 수동모드 운전이 가능토록 한다. 무인주행 실험을 위해 자계도로를 설치하고, 제작된 로봇형 차량의 실험을 통해 실용성을 입증한다.

• 한국분무공학회지
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• 제23권4호
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• pp.221-226
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• 2018

Despite the increasingly stringent automotive emissions regulations, the impact of vehicle emissions on air pollution remains large. In addition, since the issue of emission of more exhaust gas than the exhaust gas measured in the test room when the vehicle passing the exhaust gas regulation standard is run on the actual road, many countries studied and introduced gas regulations about Real Driving Emission using Portable Emission Measurement System. At present, Korea regulations restrict the number of NOx and PN in diesel vehicles. In the case of gasoline vehicles, there is no regulation on emission gas, but there is a problem of continuing automobile exhaust gas problems and a large amount of gasoline GDI vehicle's PN emission. So research and interest are increasing due to this problem. In this study, characteristics of exhaust gas depending on changes of ambient temperature were analyzed among various factors affecting exhaust gas measurement of gasoline vehicles. As a result, at the low temperature test, the lower the ambient temperature, the more the exhaust gas was emitted. At ordinary temperature test, no specific tendency was observed due to changes of ambient temperature.

• 자동차안전학회지
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• 제13권1호
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• pp.14-25
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• 2021

This paper presents a RLS based adaptive sliding mode observer (A-SMO) for unknown fault reconstruction in longitudinal autonomous driving. Securing the functional safety of autonomous vehicles from unexpected faults of sensors is essential for avoidance of fatal accidents. Because the magnitude and type of the faults cannot be known exactly, the RLS based A-SMO for unknown acceleration fault reconstruction has been designed with relationship function in this study. It is assumed that longitudinal acceleration of preceding vehicle can be obtained by using the V2V (Vehicle to Vehicle) communication. The kinematic model that represents relative relation between subject and preceding vehicles has been used for fault reconstruction. In order to reconstruct fault signal in acceleration, the magnitude of the injection term has been adjusted by adaptation rule designed based on MIT rule. The proposed A-SMO in this study was developed in Matlab/Simulink environment. Performance evaluation has been conducted using the commercial software (CarMaker) with car-following scenario and evaluation results show that maximum reconstruction error ratios exist within range of ±10%.

• 한국산업정보학회논문지
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• 제28권4호
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• pp.35-43
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• 2023

차세대 전기자동차에서는 전비 향상 및 주행 성능 개선을 위하여 각 휠에 의해 직접적으로 토크를 제어하는 인 휠 모터 시스템에 대한 연구가 진행되고 있다. 이에 따라 본 논문에서는 전기자동차 구동용 인 휠 모터에 적용되는 토크 벡터링 시스템에서 각 휠에 가해지는 토크를 분배하는 알고리즘에 대한 연구를 수행하였다. 차량의 주행 및 조향에 따른 실제 차량 특성 파라미터를 적용한 차량 모델을 구현하기 위해 MATLAB Simulink 환경에서 시뮬레이션을 진행하였으며 제안된 알고리즘에 따라 토크 분배가 이뤄지는 것을 확인하였다.

• 한국자동차공학회논문집
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• 제19권1호
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• pp.73-81
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• 2011

The performance of emission factor has been validated by comparison with on-road test data. Emission factor, which is a function of vehicle speed, has been acquired based on chassis dynamometer test with NIER driving pattern. Portable Emission Measurement System, PEMS has measured on-road emission. Test vehicle was operated on defined test routes under different driving conditions, and made ten trips along its route. Emission factors properly simulate on-road test result, although there is some drawback to consider variety of driving condition on real world. Vehicle specific power and acceleration have been used to explain the distributed on-road result within same vehicle speed range. The trend in carbon dioxide and nitrogen oxide emission with respect to specific power and acceleration is clear. It has been found that specific power is a good explanatory variable for microscopic analysis for modal test result. Acceleration is good for microscopic as well as macroscopic analysis.

• 한국ITS학회 논문지
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• 제16권4호
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• pp.107-121
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• 2017

본 연구에서는 군집주행환경에서 비자율차의 행태분석을 위해 영상기반의 조사를 통해 피실험자의 인적특성과 군집주행 인지여부를 조사하고, 주행 시뮬레이션 실험을 통해 비자율차의 차량거동을 수집했다. 또한, 주행 시뮬레이션 실험 후 NASA-TLX 설문조사를 통해 작업부하점수를 조사했다. 영상기반 인지특성 조사 결과 피실험자 대부분이 군집주행 중인 차량들을 인지하고 군집 차량군으로 인해 부담감을 느끼는 것으로 나타났다. 군집주행환경에서의 평균속도가 비군집주행환경일 때보다 낮게 나타났고, 평균속도의 표준편차는 군집주행환경일 때 더 높게 나타났다. 인적특성과 작업부하점수를 연계분석한 작업부하평가 결과 군집, 비군집주행환경 시 인적특성별로 작업부하점수가 통계적으로 유의한 차이가 나타나는 결과들을 확인했다. 인적특성과 차량거동을 연계분석한 차량거동평가 결과에서도 군집, 비군집주행환경 시 통계적으로 유의한 차이가 나타나는 결과들을 확인했다. 본 연구의 결과를 고령운전자, 여성 등 고위험군 운전자의 안전성 증대, 비자율차 운전자에게 주변 군집주행차량에 대한 정보 제공 방안 모색 등의 비자율차 운전자를 위한 교통관리전략을 수립하는데 활용할 수 있을 것이라 판단된다.

• 한국군사과학기술학회지
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• 제10권3호
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• pp.139-147
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• 2007

In military transportation, the use of wide trailer for transporting the large and heavy weight equipments such as tank, armoured vehicle, and mobile gunnery is quite common. So, the vulnerability of causing traffic accidents for these wide military trailer to bump or collide with another car in adjacent lane is very high due to its broad width in excess of its own lane's width. Also, the possibility of these strayed accidents can be increased especially by the careless driver. In this paper, the recognition system of lane and vehicle headway direction is developed to detect the possible collision and warn the driver to prevent the fatal accident. In the system development, Kalman filtering is used first to extract the border of driving lane from the video images supplied by the CCD camera attached to the vehicle and the driving lane detection is completed with regression analysis. Next, the vehicle headway direction is recognized by using neural network scheme with the extracted parameters of the detected driving lane feature. The practical experiments for the developed system are also carried out in the real traffic road of Seoul city area and the results show us the more than 90% accuracy in recognizing the driving lane and vehicle headway direction.

• 드라이브 ㆍ 컨트롤
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• 제12권3호
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• pp.18-24
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• 2015

The plug-in hybrid electric vehicle has a high fuel economy and can be driven long distances. Its different modes include the electric vehicle, hybrid electric vehicle, and only engine operating mode. A power management strategy is important to determine which mode should be selected. The strategy makes the vehicle more efficient using appropriate power sources for driving. However, the strategy usually needs a driving speed profile which is future driving cycle. If the profile is known, the strategy easily determines which mode is driven efficiently. However, it is difficult to estimate the speed profile for a real system. To address this problem, this paper proposes a new power distribution strategy using a neural network. The average speed and driving range are used as input parameters to train the neural network system. The strategy determines a limit for the use of the battery and the desired power is distributed between the engine and the motor simultaneously. Its fuel economy can increase by improving the basic strategy.