  For the autonomous operation of articulated vehicles at distribution centers,
accurate positioning of the vehicle is of the utmost importance. Automation of
these vehicle poses several challenges, e.g. large swept path, asymmetric
steering response, large slide slip angles of non-steered trailer axles and
trailer instability while reversing. Therefore, a validated vehicle model is
required that accurately and efficiently predicts the states of the vehicle.
Unlike forward driving, open-loop validation methods can not be used for
reverse driving of articulated vehicles due to their unstable dynamics. This
paper proposes an approach to stabilize the unstable pole of the system and
compares three vehicle models (kinematic, non-linear single track and multibody
dynamics model) against real-world test data obtained from low-speed
experiments at a distribution center. It is concluded that single track
non-linear model has a better performance in comparison to other models for
large articulation angles and reverse driving maneuvers.
