On Low Complexity Predictive Approaches to Control of Autonomous Vehicles.

In this chapter we present low complexity predictive approaches to the control of autonomous vehicles. A general hierarchical architecture for fully autonomous vehicle guidance systems is presented together with a review of two control design paradigms. Our review emphasizes the trade off between performance and computational complexity at different control levels of the architecture. In particular, experimental results are presented, showing that if the controller at the lower level is properly designed, then it can handle system nonlinearities and model uncertainties even if those are not taken into account at the higher level. [ABSTRACT FROM AUTHOR]