Chang Mook Kang

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In this paper, we deal with comparative evaluation of dynamic and kinematic vehicle models for autonomous driving control systems. Comparative lane coefficients estimation performance of each model is evaluated according to the tire slip angle. Each estimation makes use of clothoidal road constraints, respectively. We observe that the kinematic model is(More)
Predictive virtual lane has been known that it can cope with up to several sampling period camera failure providing improved lateral control performance of lane keeping system. In this paper, we propose an improved lane estimation scheme using a vehicle kinematic lateral motion model and clothoidal road constraints to resolve a longer failure than that(More)
In this paper, we propose a new adaptive side slip observer using a simple combined vehicle dynamics. Though there are many ways to estimate the side slip angle, some problems still exist in the popular estimation techniques based on the kinematic model, the dynamic model, and the combined kinematic-dynamic model. Therefore we propose the adaptive side slip(More)
In this paper, we consider on-road vehicle localization with the global positioning system (GPS) under long term failure of a vision sensor. When the output of vision sensor is not available due to its malfunction and/or environmental conditions, it is necessary for the lateral control system to maintain its stability before the driver takes over control(More)
In this paper, we propose kinematic vehicle lateral motion model based lane keeping system considering look-ahead distance. The state-space model based on the kinematic vehicle lateral motion model is derived and we design the lane keeping system(LKS) based on the kinematic model. The kinematic model based LKS is robust against unknown vehicle parameters(More)
In this paper, we are interested in the situation of the ego vehicle tracking the previous vehicle's GPS waypoint on highway. Even if waypoints are irregular, in order to improve the tracking performance and steering performance of the GPS waypoint tracking, curve fitting and model predictive control have been applied. The improvement of the performance of(More)
In this paper, we propose a flatness based controller which tracks the desired angle of an electric power steering system with augmented observer and a state feedback controller. Unlike the torque-overlayed backstepping method in a lane-keeping system, using the known nominal model parameters results in better tracking performance then the previous method.(More)
It is known that the kinematic model based motion control is robust against unknown vehicle parameters variation. Recently we reported that lane keeping system (LKS) with look-ahead distance using the kinematic vehicle lateral motion model is feasible and its performance is compatible with a dynamic vehicle lateral motion model using look-ahead distance(More)
In this paper, we propose a new autonomous braking system based on deep reinforcement learning. The proposed autonomous braking system automatically decides whether to apply the brake at each time step when confronting the risk of collision using the information on the obstacle obtained by the sensors. The problem of designing brake control is formulated as(More)