Optimization problems for trajectory planning in autonomous vehicle racing are characterized by their nonlinearity and nonconvexity. Instead of solving these optimization problems, usually a convex approximation is solved instead to achieve high update rate. We present real-time-capable model predictive control (MPC) planner based on nonlinear single-track Pacejka’s magic tire formula racing. A...

Connected Automated Vehicles (CAVs) have the potential to improve traffic operations when they cooperatively maneuver in merging sections. State-of-the-art approaches cooperative either build on heuristics solutions or prohibit mainline CAVs change lane multilane highways. This paper proposes a hierarchical control approach that ensures collision-free and traffic-efficient through interaction o...

This paper deals with planning in the presence of constraints and preferences as proposed for the 5 International Planning Competition. State trajectory constraints are translated into LTL formulae and are compiled into Büchi automata in PDDL format. Preference constraints are compiled into numerical fluents. Values of these fluents are changed by grounded operator effects upon violation. We pr...