• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.5
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• pp.165-172
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• 2000

The VDC(Vehicle Dynamic Control) is a control system whose target is to improve stability of a vehicle under lateral motion. A lateral vehicle motion, especially on a slippery road, can lead to a hazardous situation, and the situation can even worsen by the driver`s inappropriate response. In this paper, two VDC systems, a fuzzy-based controller and an LQR-based controller have been developed. The controllers take as input the yaw rate and the sideslip angle of either body or rear wheel, and they yield the direct yaw moment signal by which the vehicle can gain stability during cornering. Simulations have been conducted to evaluate the performance of the control system. The results indicated that the controllers can successfully improve vehicle stability under potentially dangerous driving conditions.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.2_2
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• pp.359-370
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• 2023

For a vehicle to follow a reference path accurately, its position must be estimated accurately and reliably. In this paper, we propose a lateral control algorithm for autonomous navigation of a vehicle via USAT(Ultrasonic Satellite System), which is an absolute position measurement system using an ultrasonic wave and INS(Inertial Navigation System) integration. In order to estimate the vehicle's parameters, a J-turn test is used. And the autonomous navigation performances of proposed lateral control algorithm and validity of proposed lateral control algorithm are verified and evaluated by simulation and experiments.

• Journal of Auto-vehicle Safety Association
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• v.15 no.3
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• pp.17-26
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• 2023

This paper presents extended state feedback control based on impulse response for lane change of autonomous driving vehicle. The triple characteristic root of path tracking system and longitudinal velocity determine feedback gains. We suggest a resemblance of impulse response curve of the system and lane change trajectory of the vehicle. The root affects the duration of lane change and lateral acceleration. The effect of limited lateral acceleration and saturation of steering angle will be analyzed and discussed. Finally, simulation results will show the trajectory of lane change based on impulse response under limitation of lateral acceleration.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.713-719
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• 2012

This paper is concerned with the dynamic modeling for the hardware-in-the-loop simulation of lateral vibrations of a railway vehicle. The resulting dynamic model is a nine degree-of-freedom model which can describe the lateral, roll and yaw motions of the car body and two bogies. It is assumed that the external disturbances come from wheel motions. In order to test the efficacy of the model, the linear quadratic regulator and the sky-hook control algorithm were designed and applied to the model. The simulation results show that both control algorithms are effective in suppressing the vibrations of railway vehicles.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.7
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• pp.634-641
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• 2012

This paper is concerned with the dynamic modeling for the hardware-in-the-loop simulation of lateral vibrations of a railway vehicle. The resulting dynamic model is a nine degree-of-freedom model which can describe the lateral, roll and yaw motions of the car body and two bogies. It is assumed that the external disturbances come from wheel motions. In order to test the efficacy of the model, the linear quadratic regulator and the sky-hook control algorithm were designed and applied to the model. The simulation results show that both control algorithms are effective in suppressing the vibrations of railway vehicles.

• International Journal of Automotive Technology
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• v.3 no.2
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• pp.71-78
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• 2002

A new control method far vision-based autonomous vehicle is proposed to determine navigation direction by analyzing lane information from a camera and to navigate a vehicle. In this paper, characteristic featured data points are extracted from lane images using a lane recognition algorithm. Then the vehicle is controlled using new Levenberg-Marquardt neural network algorithm. To verify the usefulness of the algorithm, another algorithm, which utilizes the geometric relation of a camera and vehicle, is introduced. The second one involves transformation from an image coordinate to a vehicle coordinate, then steering is determined from Ackermann angle. The steering scheme using Ackermann angle is heavily depends on the correct geometric data of a vehicle and a camera. Meanwhile, the proposed neural network algorithm does not need geometric relations and it depends on the driving style of human driver. The proposed method is superior than other referenced neural network algorithms such as conjugate gradient method or gradient decent one in autonomous lateral control .

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.6 s.165
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• pp.931-942
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• 1999

This paper develops a 3 DOF vehicle model which includes lateral, roll and yaw motion to study a 4WS vehicle. The model is used for the simulation of a 4WS vehicle behavior, and to derive a control algorithm for rear wheel steering. This paper uses a feedforward plus feedback control scheme to compute a rear wheel steering angle. The feedforward control scheme for computing the first rear wheel steering angle uses a gain which is acquired by multiplying a proper value on a gain to maintain a zero sideslip angle. The feedback control scheme for computing the second rear wheel steering angle uses fuzzy logic and model following control scheme. A linear 2 DOF model is used as a reference model for model following control, and is derived from the developed 3 DOF model by neglecting sprung mass roll motion. A reference state variable is yaw rate, and is computed using the linear 2 DOF model. J-turn and lane change maneuver simulation are performed to show the effectiveness of the developed control scheme. The simulation results show that the 4WS vehicle with the developed control scheme has much better performance in yaw rate, lateral acceleration, roll angle, and sideslip angle than the 2WS vehicle. Also, the results show that the performance of the developed control is close to the one of an optimal control which assumes all states are perfect.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.6
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• pp.213-221
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• 2003

This paper describes a method of lane tracking by means of a vision system which includes vehicle control and modeling. Lane tracking is considered one of the important technologies in an unmanned vehicle and mobile robot system. The current position and condition of the vehicle are calculated from an image processing method by a CCD camera. We deal with lane tracking as follows. First, vehicle control is included in the road model, and lateral and longitudinal controls. Second, the image processing method deals with the lane detection method, image processing algerian, and filtering method. Finally, this paper proposes a correct method for lane detection through a vehicle test by wireless data communication.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.899-910
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• 2013

This paper presents a novel lateral stability control system for electric vehicle based on sideslip angle estimation through Kalman filter using the integration of a single antenna GPS receiver and yaw rate sensor. Using multi-rate measurements including yaw rate and course angle, time-varying parameters disappear from the measurement equation of the proposed Kalman filter. Accurate sideslip angle estimation is achieved by treating the combination of model uncertainties and external disturbances as extended states. Active front steering and direct yaw moment are integrated to manipulate sideslip angle and yaw rate of the vehicle. Instead of decoupling control design method, a new control scheme, "two-input two-output controller", is proposed. The extended states are utilized for disturbance rejection that improves the robustness of lateral stability control system. The effectiveness of the proposed methods is verified by computer simulations and experiments.

• Journal of Mechanical Science and Technology
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• v.16 no.10
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• pp.1253-1263
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• 2002

The control system design and modeling of an unmanned vehicle by means of a new concept for better performance through a tole-operation system is suggested by sensor fusion. But, the control of a real vehicle is very difficult, because the system identification of the vehicle is hard to find the unknown factors and the disturbances of the experimental environment. For the longitudinal and lateral controls, the traction system and steering system models are set up and a tuning method to find the gain of the controller by experiments is presented. In this research, mechanical and electronic parts are implemented to operate the unmanned vehicle and data reconstruction method of information about the environment data coming from several sensors is presented by data plot for the vehicle navigation. This paper focuses on the integration of tole-operated unmanned vehicle. This vehicle mainly controlled lateral and longitudinal directions with actuators for controlling vehicle movement and sensors for the closed-loop controlled system.