Global Motion Planning for Multi-Trailer Vehicles in Partially Structured Environments

Abstract This paper presents a collision-free motion planning method for truck-trailer vehicles that integrates road networks to enable efficient exploration of large partially structured environments. It is used for autonomous maneuvering that often requires sophisticated solution strategies. Complex environments imply combinatorial search problems, which can be solved by global path planners that divide the task into multiple smaller trajectory planning steps and a graph search on a higher abstraction layer. Existing lattice-based approaches assume an unstructured environment, whereas realistic company sites usually contain isolated road networks and maneuvering spaces in a hybrid manner. Hence, in this paper, maneuvering and the use of a road network are treated at the same hierarchical level and are embedded in the global lattice planner. When the underlying graph search establishes a connection to the road network, all reachable sections of the network are explored and integrated into the graph search simultaneously. Due to the structural properties of roads, higher traveling velocities are possible and collision avoidance in presence of other moving vehicles is simplified significantly. Thus, safety, efficiency and the subjective motion quality are increased when a road network is used. Therefore an augmented graph definition is derived, as well as an adapted heuristic that preserves the optimality guarantees of lattice planners. Further expansion types are presented to improve the exploration of straight segments and to incorporate dedicated direction changes for improved executability.