%B European Control Conference (ECC), 2013
%A Mario Zanon
%A J. V. Frasch
%A Moritz Diehl
%D 2013
%L eprints4043
%X Real-time autonomous driving requires a precise knowledge of the state and the ground parameters, especially in dangerous situations. In this paper, an accurate yet computationally efficient nonlinear multi-body vehicle model is developed, featuring a detailed Pacejka tire model, and a Moving Horizon Estimation (MHE) scheme is formulated. To meet the real-time requirements, an efficient algorithm based on the Real Time Iteration (RTI) scheme for the Direct Multiple Shooting method is exported through automatic C code generation. The exported plain C-code is tailored to the model dynamics, resulting in computation times in the range of a few milliseconds. In addition to state estimates, MHE provides friction coefficient estimates, allowing the controller to adapt to varying road conditions. Simulation results from an obstacle avoidance scenario on a low friction road are presented.
%K collision avoidance;friction;iterative methods;mobile robots;motion control;nonlinear control systems;road safety;road vehicles;state estimation;tyres;MHE scheme;Pacejka tire model;RTI scheme;automatic C code generation;dangerous situations;direct multiple shooting method;friction coefficient estimation;friction road;ground parameters;model dynamics;nonlinear moving horizon estimation;nonlinear multibody vehicle model;obstacle avoidance;real time iteration scheme;real-time autonomous driving;road conditions;state estimates;Computational modeling;Friction;Load modeling;Tires;Vehicle dynamics;Vehicles;Wheels;Moving Horizon Estimation;autonomous driving;code generation;road friction estimation
%I IEEE
%P 4130-4135
%C Zurich, Switzerland
%T Nonlinear Moving Horizon Estimation for combined state and friction coefficient estimation in autonomous driving