An incremental strategy for tractor-trailer vehicle global trajectory optimization in the presence of obstacles

Trajectory planning is a critical aspect in driving an autonomous tractor-trailer vehicle. This study considers trajectory planning as a minimal-time optimal control problem that incorporates the kinematics, mechanical/physical constraints, environmental requirements and an optimization criterion. This formulation benefits in the ability to directly handle time-dependent requirements. A gradient-based numerical solver is adopted to tackle the formulated optimal control problem. An incremental strategy is proposed to enhance the global optimization ability of that solver and to help find satisfactory solutions in challenging cases. Specifically, when an optimal solution is found, we doubt whether that is merely a local optimum and then still expect to make evolution; when optimal solutions are not easy to obtain, we expect at least one feasible solution first, which is taken as a preliminary guess to assist the subsequent optimization process. Both procedures proceed alternatively until no progress can be made any further. Some intricate simulation results are well beyond manual operation ability. Moreover, our overall proposal, as a unified and open framework, can deal with a wide variety of user-specified requirements.

I. Introduction

A tractor-trailer system consists of a towing engine (i.e., a tractor) and several articulated trailers that carry commercial cargo. Compared with a rigid-body vehicle of the same length, a tractor-trailer vehicle turns around with a smaller radius and thus is more agile. This merit has given rise to the wide applications of tractor-trailer systems particularly in sinuous or cluttered scenarios [1]. Buses, trams, trains, trucks and even the robotic floor cleaner are all real-world examples of a tractor-trailer system.