NMPC trajectory planner for urban autonomous driving

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