Optimal Vehicle Stability Control with Driver Input and Bounded Uncertainties
Tamaddoni, Seyed Hossein
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For decades vehicle control has been extensively studied to investigate and improve vehicle stability and performance. Such controllers are designed to improve driving safety while the driver is still in control of the vehicle. It is known that human drivers are capable to learn and adapt to their built-in vehicle controller in order to improve their control actions based on their past driving experiences with the same vehicle controller. Although the learning curve varies for different human drivers, it results in a more constructive cooperation between the human driver and the computer-based vehicle controller, leading to globally optimal vehicle stability. The main intent of this research is to develop a novel cooperative interaction model between the human driver and vehicle controller in order to obtain globally optimal vehicle steering and lateral control. Considering the vehicle driver-controller interactions as a common two-player game problem where both players attempt to improve their payoffs, i.e., minimize their objective functions, the Game Theory approach is applied to obtain the optimal driver's steering inputs and controller's corrective yaw moment. Extending this interaction model to include more realistic scenarios, the model is discretized and a road preview model is added to account for the driver's preview-time characteristic. Also, a robust interaction model is developed to stabilize the vehicle performance while taking bounded uncertainty effects in driver's steering behavior into consideration using the Integral Sliding Mode control methodology. For evaluation purposes, a nonlinear vehicle dynamics model is developed that captures nonlinear tire characteristics and includes driver steering controllability and vehicle speed control systems such as cruise control, differential braking, and anti-lock braking systems. A graphical user interface (GUI) is developed in MATLAB to ease the use of the vehicle model and hopefully encourage its widespread application in the future. Simulation results indicate that the proposed cooperative interaction model, which is the end-product of human driver's and vehicle controller's mutual understanding of each other's objective and performance quality, results in more optimal and stable vehicle performance in lateral and yaw motions compared to the existing LQR controllers that tend to independently optimize the driver and vehicle controller inputs.
- Doctoral Dissertations