  To study the effects of uncertainty in autonomous motion planning and
control, an 8-DOF model of a tractor-semitrailer is implemented and analyzed.
The implications of uncertainties in the model are then quantified and
presented using sensitivity analysis and closed-loop simulations. The analysis
reveals that the significance of various model parameters varies depending on
the specific scenario under investigation. By using sampling-based closed-loop
predictions, uncertainty bounds on state variable trajectories are determined.
Our findings suggest the potential for the inclusion of our method within a
robust predictive controller or as a driver-assistance system for rollover or
lane departure warnings.
