  This paper presents a trajectory planner for autonomous driving based on a
Nonlinear Model Predictive Control (NMPC) algorithm that accounts for Pacejka's
nonlinear lateral tyre dynamics as well as for zero speed conditions through a
novel slip angles calculation. In the NMPC framework, road boundaries and
obstacles (both static and moving) are taken into account thanks to soft and
hard constraints implementation. The numerical solution of the NMPC problem is
carried out using ACADO toolkit coupled with the quadratic programming solver
qpOASES. The effectiveness of the proposed NMPC trajectory planner has been
tested using CarMaker multibody models. Time analysis results provided by the
simulations shown, state that the proposed algorithm can be implemented on the
real-time control framework of an autonomous vehicle under the assumption of
data coming from an upstream estimation block.
