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Designing a local planner to control tractor-trailer vehicles in forward andbackward maneuvering is a challenging control problem in the research communityof autonomous driving systems. Considering a critical situation in thestability of tractor-trailer systems, a practical and novel approach ispresented to design a non-linear MPC(NMPC) local planner for tractor-trailerautonomous vehicles in both forward and backward maneuvering. The tractorvelocity and steering angle are considered to be control variables. Theproposed NMPC local planner is designed to handle jackknife situations,avoiding multiple static obstacles, and path following in both forward andbackward maneuvering. The challenges mentioned above are converted into aconstrained problem that can be handled simultaneously by the proposed NMPClocal planner. The direct multiple shooting approach is used to convert theoptimal control problem(OCP) into a non-linear programming problem(NLP) thatIPOPT solvers can solve in CasADi. The controller performance is evaluatedthrough different backup and forward maneuvering scenarios in the Gazebosimulation environment in real-time. It achieves asymptotic stability inavoiding static obstacles and accurate tracking performance while respectingpath constraints. Finally, the proposed NMPC local planner is integrated withan open-source autonomous driving software stack called AutowareAi.

A Non-linear MPC Local Planner for Tractor-Trailer Vehicles in Forward and Backward Maneuvering