eprintid: 4043
rev_number: 9
eprint_status: archive
userid: 87
dir: disk0/00/00/40/43
datestamp: 2018-03-12 09:13:16
lastmod: 2018-03-12 09:13:16
status_changed: 2018-03-12 09:13:16
type: conference_item
metadata_visibility: show
creators_name: Zanon, Mario
creators_name: Frasch, J. V.
creators_name: Diehl, Moritz
creators_id: mario.zanon@imtlucca.it
creators_id: 
creators_id: 
title: Nonlinear Moving Horizon Estimation for combined state and friction coefficient estimation in autonomous driving
ispublished: pub
subjects: T1
divisions: CSA
full_text_status: restricted
pres_type: paper
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
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.
date: 2013-07
date_type: published
publisher: IEEE
pagerange: 4130-4135
event_title: European Control Conference (ECC)
event_location: Zurich, Switzerland
event_dates: July 17-19, 2013
event_type: conference
refereed: TRUE
isbn: 978-3-033-03962-9
book_title: European Control Conference (ECC), 2013
official_url: http://ieeexplore.ieee.org/document/6669832/
citation:   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)  
document_url: http://eprints.imtlucca.it/4043/1/06669832.pdf