Model predictive tracking controller for a high fidelity vehicle dynamics model

This paper considers the problem of tracking a reference trajectory for an autonomous vehicle. A model predictive control (MPC) approach is used to solve the tracking control problem. The control constraints on steering wheel angle and drive torque are incorporated in the control law. A nonlinear vehicle model inclusive of rolling motions is developed and is subsequently linearized for different operating regimes. The proposed controller uses a linear time varying state space representation of the nonlinear vehicle model. In addition to this a high fidelity multi-body dynamics model of the vehicle is developed in CarSim which emulates real vehicle characteristics. A co-simulation study is performed and the proposed method is evaluated by computational simulations. The controller is able to track the longitudinal and lateral positions, velocities and yaw rate references at different operating speeds. The results show the effectiveness of our approach for obstacle avoidance scenario on a two lane one way road.