A Hierarchical Control Framework for Drift Maneuvering of Autonomous Vehicles

Maneuvering an autonomous vehicle under drift condition is critical to the safety of autonomous vehicles when there is a sudden loss of traction due to external conditions such as rain or snow, which is a challenging control problem due to the presence of significant sideslip and nearly full saturation of the tires. In this paper, we focus on the control of drift maneuvers of autonomous vehicle to track circular paths with either fixed or moving centers, subject to change in the tire-ground interaction. In order to achieve the above tasks, we propose a hierarchical control architecture which decouples the curvature and center control of the trajectory. In particular, an outer control loop is proposed to stabilize the center by tuning the target curvature, and an inner control loop tracks the curvature using a feedforward/feedback controller enhanced by an
$\mathcal{L}_{1}$
adaptive component. The hierarchical architecture is flexible because the inner loop is task-agnostic and adaptive to changes in tire-ground interaction, which allows the outer loop to be designed independent of low-level dynamics, opening up the possibility of incorporating sophisticated planning algorithms. We implement our control strategy on a simulation platform as well as on a 1/10 scale RC car, and both the simulation and experiment results illustrate the effectiveness of our strategy in achieving the above described set of drift maneuvering tasks.