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The design of reliable path-following controllers is a key ingredient forsuccessful deployment of self-driving vehicles. This controller-design problemis especially challenging for a general 2-trailer with a car-like tractor dueto the vehicle's structurally unstable joint-angle kinematics in backwardmotion and the car-like tractor's curvature limitations which can cause thevehicle segments to fold and enter a jackknife state. Furthermore, advancedsensors with a limited field of view have been proposed to solve thejoint-angle estimation problem online, which introduce additional restrictionson which vehicle states that can be reliably estimated. To incorporate theserestrictions at the level of control, a model predictive path-followingcontroller is proposed. By taking the vehicle's physical and sensinglimitations into account, it is shown in real-world experiments that theperformance of the proposed path-following controller in terms of suppressingdisturbances and recovering from non-trivial initial states is significantlyimproved compared to a previously proposed solution where the constraints havebeen neglected.

On sensing-aware model predictive path-following control for a reversing general 2-trailer with a car-like tractor