Design and Implementation of a Strategy for Path Tracking on Autonomous Heavy-Duty Vehicles

Abstract: In this thesis, a combined feedforward and feedback controller for improved path tracking on autonomous heavy-duty vehicles is designed and implemented. The steering wheel is controlled in order to follow a reference curvature, computed by a higher-level MPC, responsible for minimizing the distance to a planned path. The steering dynamics, from steering wheel via wheel angles, to a measurable vehicle curvature, is modeled, and a conversion from desired curvature gain to input angle to the steering wheel is derived. Tests with an autonomous Scania R580 show that the desired curvature can be followed with satisfactory small error, both in a designed slalom path and on a more generic test track. By utilizing future curvature values computed by the MPC, a non-causal feedforward controller can reduce the delay from input to the steering wheel to a measured response in curvature, by almost two thirds, compared to the currently implemented solution. Compared to an open-loop control design, tests in simulation show that a feedback controller can reduce errors in curvature gain. However, with the identified steering dynamics and the improved conversion from steering wheel angle to curvature, no further improvement in the curvature gain was seen when implementing the feedback controller in the test vehicle. Care must also be taken not to introduce instability in the system when the feedback controller is implemented in series with a high-level MPC.