Chang Mook Kang

Comparative evaluation of dynamic and kinematic vehicle models

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 robust against unknown vehicle parameters tire-road condition or cornering stiffness for autonomous driving systems under lane keeping situation. The reliability of each model was validated via not only computational simulation results but also experimental results with a test vehicle.

Lane estimation using a vehicle kinematic lateral motion model under clothoidal road constraints

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 considered in the previous study. The lane estimation system gives virtual lane information to the lateral control system. The developed algorithm was validated via computational simulation results with CarSim and MATLAB/Simulink, and experimental results with a test vehicle equipped with an AutoBox from dSPACE.

Adaptive side slip angle observer using simple combined vehicle dynamics

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 observer. A combined model of linearized roll motion and lateral vehicle dynamics was used to involve the roll motion in the second-order lateral vehicle dynamics. Furthermore, a time delay was also applied to the combined model, reflecting the reaction time between the steering angle and the side slip angle. We designed an H∞ discrete-time slip angle observer using linear matrix inequality to reduce the infinite norm between a set of disturbance inputs and the estimation error. The performance of the proposed method was validated via simulations and experiments.

On-Road Vehicle Localization with GPS under Long Term Failure of a Vision Sensor

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 authority. We propose how to estimate lane coefficients with GPS data and the latest normal lane coefficients in the presence of failure. This lane estimation method enables the lane keeping system to keep its stability. The developed algorithm was validated via computational simulation results with CarSim and MATLAB/Simulink. We also included experimental results with a test vehicle equipped with an AutoBox from dSPACE.

Torque Overlay Based Robust Steering Wheel Angle Control for Lateral Control Using Backstepping Design

Abstract We propose a torque overlay based robust steering wheel angle control of electric power steering (EPS) for lateral control using backstepping design. The main contribution of this paper is that the proposed method is designed based on torque overlay and that the global uniform ultimate boundedness of the steering wheel angle tracking error is guaranteed using only steering wheel angle feedback with external disturbances. The key idea is to make the EPS dynamics be simplified. Then, the external disturbances, system function, and input gain uncertainty are regarded as a disturbance. An augmented observer is designed to estimate the full state and the disturbance. A nonlinear damping controller is developed via backstepping to suppress a position tracking error using input-to-state stability property. The proposed method uses only steering wheel angle feedback and nominal value of the input gain. The proposed method is simple to implement in real-time control and robust to the parameter uncertainties and the external disturbances. Since the proposed method is designed based on torque overlay as add-on type, it can be integrated with the conventional EPS system facilitating drivers intervention.

Slip Angle Estimation: Development and Experimental Evaluation

Abstract This paper develops a slip angle estimation method using measurements of lateral acceleration and yaw rate. A unique model for slip angle estimation is developed by combining velocity kinematics, yaw dynamics, and lateral translational dynamics, so as to avoid sensor drift and parameter variation effect. The model is used in designing a state estimator to estimate slip angle, which compensates slip angle prediction error using the measurements of lateral acceleration and yaw rate. Experimental performance verification of the proposed slip angle estimation scheme is presented.

A comparative study of lane keeping system: Dynamic and kinematic models with look-ahead distance

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 variation. Furthermore, to consider look-ahead distance in the kinematic vehicle lateral motion model, we designed output measurement matrix using clothoidal constraints. Hence, we can control the vehicle at look-ahead distance like human driver. Control performance of each model was validated via computational simulation results with CarSim and MAT-LAB/Simulink, and experimental results with electric power steering system equipped with an Autobox from dSPACE.

Vehicle trajectory prediction for adaptive cruise control

In this paper, we propose a new vehicle trajectory prediction algorithm for adaptive cruise control (ACC). When vehicle trajectory prediction is not precise enough, it is possible for a neighboring vehicle to be detected as a target. Thus, we propose a new method using both yaw rate and curvature rate to precisely predict vehicle trajectory and to resolve an undesirable case in ACC system. The proposed method was validated via CarSim and MATLAB/Simulink. Also, we validated the proposed method via experimental results with a test vehicle on highway system for the practicality.

GPS waypoint fitting and tracking using model predictive control

In this paper, we are interested in the situation of the ego vehicle tracking the previous vehicles 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 the waypoint tracking was validated via computational experimental results.

On-Road Path Generation and Control for Waypoints Tracking

This article addresses path generation and predictive control for waypoints tracking. By considering irregularity of waypoints given by the leading vehicle, the waypoints-following vehicle is made to track a clothoid path that assures safe and comfortable driving while keeping track of the waypoints in the least squares sense. In the generation of such a clothoid path, the path generation scheme utilized the clothoidal constraint and weighted least squares curve fitting. Predictive control is applied to improve path tracking performance over horizon, with constraints on steering and its rate being considered for safe and comfortable steering. A computational experiment, utilizing a set of leading vehicle generated waypoints on a highway, is conducted to demonstrate utility of the path generation and predictive control scheme.