  Inertia drift is an aggressive transitional driving maneuver, which is
challenging due to the high nonlinearity of the system and the stringent
requirement on control and planning performance. This paper presents a solution
for the consecutive inertia drift of an autonomous RC car based on
primitive-based planning and data-driven control. The planner generates complex
paths via the concatenation of path segments called primitives, and the
controller eases the burden on feedback by interpolating between multiple real
trajectories with different initial conditions into one near-feasible reference
trajectory. The proposed strategy is capable of drifting through various paths
containing consecutive turns, which is validated in both simulation and
reality.
