Motion control of an autonomous vehicle at driving limits

• Main Author: Luo, Jixin
• Other Authors: Lyu Chen
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2021
• Subjects: Engineering::Mechanical engineering
• Online Access: https://hdl.handle.net/10356/150473
• Institution: Nanyang Technological University

This report explored the driving limit of the autonomous vehicle using MPC control to trace the reference trajectory. The first objective is to develop a MPC controller. The kinematic model of vehicle was established, and state-space equations were derived from the kinematic model. The state-space equation was non-linear and linearized by Taylor expansion at the reference points. Forward-Euler method was adopted to discretize the model, so that the predictive model could be built. The predictive model was able to predict the state of the vehicle within predict domain, with a given current input and state. Therefore, the error to the refence states can be found with the predictive model. The optimization was defined as by verifying the control value, the error to the reference was minimized with constraints. The optimization problem was solved by MATLAB quadprog() solver, where the constraints come from the geometry restrictions of the vehicle. The results were time series of input, and the input for the current time was passed to the vehicle model to update the vehicle states. With the MPC controller, the simulations were conducted with Simulink, under 2 driving limit scenarios: lane-changing and sharp cornering. The model simulates the motion control of the vehicle with different longitudinal velocities and friction coefficients of the road. The optimal velocity and curvature of the vehicle under designed MPC controller was found by adopting bisection method with trial and error.