This Project deals with the longitudinal and lateral control of an automotive vehicle within the framework of fully automated guidance. The automotive vehicle is a complicated system with nonlinear longitudinal and lateral coupled dynamics. As a result, automated guidance must be performed in conjunction with longitudinal and lateral control. In this lab, we examine a model predictive control-based automated steering technique. To deal with the longitudinal speed tracking problem, a longitudinal control technique is also proposed. Finally, a unified longitudinal and lateral control strategy helps to improve the combined control performance. This whole control strategy is tested through simulations showing the effectiveness of the present approach for a path tracking task using the Pure Pursuit algorithm.
๐ด The Included PDF contains the full details of the dynamic model used, the design of controllers and their assesment and performance analysis for different situations/conditions.
- run Init.m to initialize the simulink model
- run the simulink simulation
- run Init.m again to display the simulated trajectory with respect to the reference trajectory and re-initialize the simulink models
- Full_control_with_fixed_reference_velocity : used to test the controller for a constant reference linear velocity
- Full_control_with_variable_reference_velocity : using a piecewise reference velocity depending on the shape of the track
- -MPC : the standalone MPC controller for later control
- The complete control scheme :
- The performance of the controller evaluated for a path tracking task using the PurevPursuit algorithm for a constant reference velocity of 50km/h, dry, smooth road:
- The performance of the controller evaluated for a path tracking task using the PurevPursuit algorithm for a constant reference velocity of 90km/h, dry, smooth road:
- Solving the problem by using adaptive ( variable/piecewise ) reference velocity: