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.

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

Zanon M;
2013-01-01

Abstract

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.
2013
978-3-033-03962-9
autonomous driving; code generation ; Moving Horizon Estimation; road friction estimation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11771/7085
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