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Nonlinear Moving Horizon Estimation for combined state and friction coefficient estimation in autonomous driving

Zanon, Mario and Frasch, J. V. and Diehl, Moritz Nonlinear Moving Horizon Estimation for combined state and friction coefficient estimation in autonomous driving. In: European Control Conference (ECC), July 17-19, 2013, Zurich, Switzerland pp. 4130-4135. ISBN 978-3-033-03962-9. (2013)

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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.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: 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
Subjects: T Technology > T Technology (General)
Research Area: Computer Science and Applications
Depositing User: Mario Zanon
Date Deposited: 12 Mar 2018 09:13
Last Modified: 12 Mar 2018 09:13
URI: http://eprints.imtlucca.it/id/eprint/4043

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