  In this paper, we address the problem of motion planning and control at the
limits of handling, under locally varying traction conditions. We propose a
novel solution method where traction variations over the prediction horizon are
represented by time-varying tire force constraints, derived from a predictive
friction estimate. A constrained finite time optimal control problem is solved
in a receding horizon fashion, imposing these time-varying constraints.
Furthermore, our method features an integrated sampling augmentation procedure
that addresses the problems of infeasibility and sensitivity to local minima
that arise at abrupt constraint alterations, e.g., due to sudden friction
changes.
  We validate the proposed algorithm on a Volvo FH16 heavy-duty vehicle, in a
range of critical scenarios. Experimental results indicate that traction
adaptive motion planning and control improves the vehicle's capacity to avoid
accidents, both when adapting to low local traction, by ensuring dynamic
feasibility of the planned motion, and when adapting to high local traction, by
realizing high traction utilization.
