A Predictive Controller for Autonomous Vehicle Path Tracking

This paper presents a model predictive controller (MPC) structure for solving the path-tracking problem of terrestrial autonomous vehicles. To achieve the desired performance during high-speed driving, the controller architecture considers both the kinematic and the dynamic control in a cascade stru...

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Bibliographic Details
Published inIEEE transactions on intelligent transportation systems Vol. 10; no. 1; pp. 92 - 102
Main Authors Raffo, G.V., Gomes, G.K., Normey-Rico, J.E., Kelber, C.R., Becker, L.B.
Format Journal Article
LanguageEnglish
Published Piscataway, NJ IEEE 01.03.2009
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Summary:This paper presents a model predictive controller (MPC) structure for solving the path-tracking problem of terrestrial autonomous vehicles. To achieve the desired performance during high-speed driving, the controller architecture considers both the kinematic and the dynamic control in a cascade structure. Our study contains a comparative study between two kinematic linear predictive control strategies: The first strategy is based on the successive linearization concept, and the other strategy combines a local reference frame with an approaching path strategy. Our goal is to search for the strategy that best comprises the performance and hardware-cost criteria. For the dynamic controller, a decentralized predictive controller based on a linearized model of the vehicle is used. Practical experiments obtained using an autonomous ldquoMini-Bajardquo vehicle equipped with an embedded computing system are presented. These results confirm that the proposed MPC structure is the solution that better matches the target criteria.
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ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2008.2011697