• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.5
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• pp.206-213
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• 2002

This paper proposes a vehicle trajectory prediction method for application to vehicle-to-vehicle distance control. This method is based on 2-dimensional kinematics and a Kalman filter has been used to estimate acceleration of the object vehicle. The simulation results using the proposed control method show that the relative distance characteristics can be improved via the trajectory prediction method compared to the customary vehicle stop and go cruise control systems which makes the vehicle remain at a safe distance from a preceding vehicle according to the driver's preference, automatically slow down and come to a full stop behind a preceding vehicle.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.408-412
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• 2003

Obstacle avoidance algorithm is very important on an unmanned vehicle. Therefore, in this research, we propose a algorithm of obstacle avoidance and we can prove through vehicle test and sensor experiments. Obstacle avoidance must be divided into two parts: the first part includes the longitudinal control for acceleration and deceleration and the second part is the lateral control for steering control. Each system is used for unmanned vehicle control, which notes its location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control strategy of the vehicle can detect obstacles and perform obstacle avoidance on the road, which involves vehicle velocity. In this paper, we propose a method for vehicle control, modeling, and obstacle avoidance, which are confirmed through vehicle tests.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.257-257
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• 2000

The objective of this research is to monitor and control the vehicle motion in order to remove out the existing safety risk based upon the human-machine cooperative vehicle control. A predictive control method is proposed to control the steering wheel of the vehicle to keep the lane. Desired angle of the steering wheel to control the vehicle motion could be calculated based upon vehicle dynamics, current and estimated pose of the vehicle every sample steps. The vehicle pose and the road curvature were calculated by geometrically fusing sensor data from camera image, tachometer and steering wheel encoder though the Perception Net, where not only the state variables, but also the corresponding uncertainties were propagated in forward and backward direction in such a way to satisfy the given constraint condition, maintain consistency, reduce the uncertainties, and guarantee robustness. A series of experiments was conducted to evaluate the control performance, in which a car Like robot was utilized to quit unwanted safety problem. As the results, the robot was keeping very well a given lane with arbitrary shape at moderate speed.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.6
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• pp.295-301
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• 2001

In this paper, an impedance control using a serial chain of spring-damper system is proposed for a vehicle platoon. For safety of the vehicle platoon, it is required to regulated the distance between each vehicle at a preassigned value even in case of vehicle model error, or moise in the measurement signal. Since the spring-damper system is physically stable and widely used to represent the interaction with the uncertain environments, it is appropriate to the longitudinal control of the vehicle platoon. By considering the nonholonomic characteristics of the vehicle motion, the lateral control and the longitudinal control of the vehicle paltoon are unified in the proposed algorithm. Computer simulation is carried out to verify the robustness against the uncertainties such as the vehicle model error and the measurement noise.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.5
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• pp.183-192
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• 2003

Obstacle detection and avoidance are considered as one of the key technologies on an unmanned vehicle system. In this paper, we propose a method of obstacle detection and avoidance and it is composed of vehicle control, modeling, and sensor experiments. Obstacle detection and avoidance consist of two parts: one is longitudinal control system for acceleration and deceleration and the other is lateral control system for steering control. Each system is used for unmanned vehicle control, which notes its location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control system of the vehicle can detect obstacles and perform obstacle avoidance on the road, which involves vehicle velocity. In this paper, we propose a method for vehicle control, modeling, and obstacle avoidance, which are evaluated through road tests.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.4
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• pp.173-179
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• 2003

In this paper, a real-time multibody vehicle dynamics and control model has been developed for a virtual reality intelligent vehicle simulator. The simulator consists of low PCs for a virtual reality visualization system, vehicle dynamics and control analysis system a control loading system, and a network monitoring system. Virtual environment is created by 3D Studio Max graphic tool and OpenGVS real-time rendering library. A real-time vehicle dynamics and control model consists of a control module based on the sliding mode control for adaptive cruise control and a real-time multibody vehicle dynamics module based on the subsystem synthesis method. To verify the real-time capability of the model, cut-in, cut-out simulations have been carried out.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.4
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• pp.130-140
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• 2000

In this paper the reference model following control(RMFC) scheme through the optimal control theory is investigated for the independent rear wheel steering(IRWS) vehicle. RMFC vehicle follows the dynamic performance of a virtual vehicle as a reference model deisgned in the controller. Linear vehicle model of two degres-of-freedom is used to derive control scheme which is applied to full vehicle for evaluating handling performances. And 4WS vehicle through RMFC is compared to the conventional 2WS vehicle and 4WS vehicle in the J-turn test. The RMFC logic is also extended to IRWS vehicle, IRWS with RMFC shows not only the excellent handling performance but salso some advantages in terms of the directional stability and responsiveness from the simulation results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.7
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• pp.1401-1407
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• 2002

This paper represents an investigation of the vehicle-to-vehicle distance control system using Hardware-in-the-Loop Simulation(HiLS). Control logic is primarily developed and tested with a specially equipped test vehicle. Establishment of an efficient and low cost development tool is a very important issue, and test vehicle approach is costly and time consuming. HiLS method is useful in the investigation of driver assistance and active safety systems. The HiLS system consists of a stepper motor for throttle control, a hydraulic brake system with an electronic vacuum booster, an electronic controller unit, a data logging computer which are used to save vehicle states and signals of actuator through a CAN and a simulation computer using mathematical vehicle model. Adaptation of a CAN instead of RS-232 Serial Interface for communication is a trend in the automotive industry. Since this environment is the same as a test vehicle, a control logic verified in laboratory can be easily transferred to a test vehicle.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.3
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• pp.123-129
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• 2002

This paper proposes a vehicle trajectory prediction method far application to vehicle-to-vehicle distance control. This method is based on 2-dimensional kinematics and a Kalman filter has been used to estimate acceleration of the object vehicle. The simulation results using the proposed control method show that the relative distance characteristics can be improved via the trajectory prediction method compared to the customary intelligent cruise control algorithm.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.5
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• pp.115-121
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• 2001

A driving load estimation method for intelligent cruise control(ICC) vehicles has been proposed in this paper. Vehicle driving load is one of the most important factors of perturbations in vehicle control and can affect the control performance critically. The effect of the control with driving load estimation on vehicle-to-vehicle distance control has been presented and investigated via computer simulations and vehicle tests. The results show that vehicle-driving-load-adaptive control can provide an ICC system with a good acceleration tracking performance. In addition, the results show that driving load estimation can compensate not only the variation of driving load but also the modeling errors.