• 제어로봇시스템학회논문지
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• 제19권11호
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• pp.998-1003
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• 2013

This study proposes an adaptive control algorithm for lateral motion of a UGV (Unmanned Ground Vehicle) using an NN (Neural Networks). The lateral motion of the UGV can be corrupted with various uncertainties such as side slip. In order to compensate the performance degradation of the UGV under various uncertainties, an NN-based adaptive control is designed by utilizing a virtual control concept. Since both the drift and input gain terms are uncertain, the proposed method adapts the whole terms related to the difference between the nominal and real systems. To avoid a singularity problem with the adaptive control, the affine property of the UGV dynamic model is utilized and the overall closed-loop stability is analyzed rigorously. Finally, numerical simulations using Carsim are performed to validate the effectiveness of the proposed scheme.

• 한국정밀공학회지
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• 제30권10호
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• pp.1051-1059
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• 2013

In general, lateral ride comfort of railway vehicle is mainly influenced by a secondary suspension placed between the bogie and carbody. Higher operating speeds of train results in increased vibration of carbody, which has a negative impact related to the ride comfort. To solve this problem, researches to replace the conventional passive suspension with (semi)active technology in the secondary suspension of a railway vehicle have been carried out. The semi-active suspension using the magneto-rheological damper is relatively simpler system and has advantage in maintenance compared to the hydraulic type semi-active damper. This study was performed to reduce lateral vibration acceleration of carbody related to ride comfort of railway vehicles with a semi-active suspension system. The numerical analysis was conducted by replacing passive lateral damper with semi-active MR damper, and robust control with the MR damper was applied to the 1/5 scaled railway vehicle model.

• 대한임베디드공학회논문지
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• 제4권4호
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• pp.180-189
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• 2009

Currently, most automobile companies are interested in research on intelligent autonomous vehicle. They are mainly focused on driver's intelligent assistant and driver replacement. In order to develop an autonomous vehicle, lateral and longitudinal control is necessary. This paper presents a lateral and longitudinal control system for autonomous vehicle that has only mono-vision camera. For lane detection, we present a new lane detection algorithm using clothoid parabolic road model. The proposed algorithm in compared with three other methods such as virtual line method, gradient method and hough transform method, in terms of lane detection ratio. For adaptive control, we apply a vanishing point estimation to fuzzy control. In order to improve handling and stability of the vehicle, the modeling errors between steering angle and predicted vanishing point are controlled to be minimized. So, we established a fuzzy rule of membership functions of inputs (vanishing point and differential vanishing point) and output (steering angle). For simulation, we developed 1/8 size robot (equipped with mono-vision system) of the actual vehicle and tested it in the athletics track of 400 meter. Through the test, we prove that our proposed method outperforms 98 % in terms of detection rate in normal condition. Compared with virtual line method, gradient method and hough transform method, our method also has good performance in the case of clear, fog and rain weather.

• 자동차안전학회지
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• 제14권4호
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• pp.53-59
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• 2022

This paper describes an integrated control of torque vectoring and rear wheel steering using model predictive control. The control objective is to minimize the yaw rate and body side slip angle errors with chattering alleviation. The proposed model predictive controller is devised using a linear parameter-varying (LPV) vehicle model with real time estimation of the varying model parameters. The proposed controller has been investigated via computer simulations. In the simulation results, the performance of the proposed controller has been compared with uncontrolled cases. The simulation results show that the proposed algorithm can improve the lateral stability and handling performance.

• 대한기계학회논문집A
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• 제41권7호
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• pp.591-597
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• 2017

이 논문은 횡방향 안정성 및 조향성능 개선을 위한 차량 통합운동제어시스템(IDCB)의 개발에 관한 것이다. IDCB의 개발을 위하여 8자유도의 차량 모델 및 비선형 관측기를 설계하였다. 퍼지 로직 제어 방법 및 슬라이딩 모드 제어 방법을 이용하여 전륜 및 후륜의 제동압력을 독립적으로 제어하여 차량의 요 속도 및 횡방향 미끄러짐 각이 목표값을 추종하도록 하였다. 결과를 살펴보면 비선형 관측기는 만족할 만한 수준의 관측 결과를 보여주었다. 개발된 IDBC는 다양한 노면 조건 및 운전 조건에서 요속도 및 횡방향 미끄러짐 각이 목표값을 잘 추종하도록 하여 차량의 횡방향 안정성 및 조향성을 개선시키는 것을 확인할 수 있다.

• 대한기계학회논문집A
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• 제30권10호
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• pp.1276-1283
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• 2006

This study proposes two ESP systems which are designed to enhance the lateral stability of a vehicle. A BESP uses an inner rear wheel braking pressure controller, while a EBESP employs an inner rear wheel and front outer wheel braking pressure controller. The performances of the BESP and EBESP are evaluated for various road conditions and steering inputs. They reduce the slip angle and eliminate variation in the lateral acceleration, which increase the controllability and stability of the vehicle. However EBESP enhances the lateral stability and comfort. A driver model is also developed to control the steer angle input. It shows good performances because the vehicle tracks the desired lane very well.

• 제어로봇시스템학회논문지
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• 제18권11호
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• pp.1065-1071
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• 2012

In this paper, we proposed a method for vehicle monitoring with trajectory reconstruction. For safety, it is important to monitor the driving habit of driver. Every year, many accidents occur due to the reckless driving of the driver. Continuous monitoring of the status of commercial vehicles is needed for safety through the entire path from start point to the destination. To monitor the reckless driving, we try to monitor the trajectory of the vehicle by using vehicle's lateral acceleration data. Compared with steering angle and lateral acceleration, these resemble each other. So, we find the relationship of steering angle and acceleration, and find the global direction of vehicle. We find the position of non-GPS section with EKF (External Kalman Filter) and reconstruct the whole trajectory during vehicle driving.

• 한국항행학회논문지
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• 제11권4호
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• pp.359-370
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• 2007

무인 자동차 시스템에 있어 차선추적과 물체회피 기술은 중요한 핵심기술 이다. 본 논문에서는 차량제어와 모델링, 센서 실험을 통하여 차선추적 및 물체회피 방법을 제안하고자 한다. 첫 번째 물체회피는 가/감속을 위한 종 방향 제어와 조향제어에 의한 횡 방향 제어 두 개의 부분으로 구성되어 진다. 각각의 시스템은 무인자동차의 제어를 위하여 차량의 위치, 주변환경 인식, 상황에 따른 빠른 처리를 요구한다. 차량의 제어 전략이 작동되는 동안 도로에서의 물체인식과 회피는 차량의 속도에 달려 있다. 두 번째 영상시스템을 통한 차선추석방법을 설명한다. 이 또한 두 부분으로 구성된다. 첫 번째 횡/종 제어를 위한 로도 모델이 포함된다. 두 번째 차선추적방법, 영상처리 알고리즘, 필터링 방법 및 영상처리 방법을 다룰 것이다. 마지막으로 본 논문에서는 실차실험을 통한 차선추적 및 물체회피 차량제어 및 모델링 방법을 제안한다.

• 대한의용생체공학회:의공학회지
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• 제38권1호
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• pp.32-42
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• 2017

The aim of this study was to evaluate driving performance of Healthy and disabled groups (with or without driver's license) to control steering wheel by using steering assistive devices in the driving simulator. The persons with partial loss of use of all four limbs have problems in operation of the motor vehicle because of functional loss to operate steering wheel. Therefore, if steering assistive devices for grasping the steering wheel are used to control the vehicle on the road in persons with disabilities, the disabled persons can improve mobility in their community life by driving a motor vehicle safely. Ten healthy subjects (with or w/o driver's license) and ten subjects with physical disabilities (with or w/o driver's license) were involved in this study to evaluate driving performance to operate steering wheel by using four types of steering assistive devices (Single-pin, V-grip, Palm-grip, Tri-pin) in driving simulator. STISim Drive 3 software was used to test the steering performance in four scenarios: straight road at low and high speed of vehicle (40 km/h and 80 km/h), curved road at low and high speed of vehicle (40 km/h and 80 km/h). This study used two-way ANOVA in order to compare the effects of two factors (type of steering assistive device and subject group) in the three dependent variables of driving performance (the lateral position of vehicle, standard deviation of lateral position representing the variation of the left and right movement of the vehicle and the number of line crossing). The mean values of the three dependent variables (lateral position, standard deviation of lateral position, the number of line crossing) of steering performance were statistically significantly smaller for the healthy or disabled groups with driver's license than the other groups without driver's license on the curved road at high speed of vehicle compared to low speed of vehicle.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.687-690
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• 2000

Lately, many studies have been progressed for the protection human's lives and property as holding in check accidents happened by human's carelessness or mistakes. One part of these is the development of an autonomouse vehicle. General control method of vision-based autonomous vehicle system is to determine the navigation direction by analyzing lane images from a camera, and to navigate using proper control algorithm. In this paper, characteristic points are abstracted from lane images using lane recognition algorithm with sobel operator. And then the vehicle is controlled using two proposed auto-steering algorithms. Two steering control algorithms are introduced in this paper. First method is to use the geometric relation of a camera. After transforming from an image coordinate to a vehicle coordinate, a steering angle is calculated using Ackermann angle. Second one is using a neural network algorithm. It doesn't need to use the geometric relation of a camera and is easy to apply a steering algorithm. In addition, It is a nearest algorithm for the driving style of human driver. Proposed controller is a multilayer neural network using Levenberg-Marquardt backpropagation learning algorithm which was estimated much better than other methods, i.e. Conjugate Gradient or Gradient Decent ones.