Hierarchical motion control strategies for handling interactions of automated vehicles
Balázs Németh, Péter Gáspár
Abstract
The paper proposes motion control strategies for automated road vehicles to handle interactions among vehicles. The control strategies are built in a hierarchical structure, which contains a high-level learning-based control, a low-level robust control and an optimization-based supervisor. The purposes of the control strategies are to guarantee collision-free motion of the vehicles, and moreover to improve economy and traveling time performance levels. In the paper two configurations of the hierarchical structure are proposed, which are based on the centralized and independent design for automated vehicle motion. The paper presents the comparison of the two configurations through simulation examples. Moreover, the operation of the independent configuration on a small-scaled indoor test vehicle platform is also presented.