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Cited by 342

The DOI matches its Crossref record.

A Predictive Controller for Autonomous Vehicle Path Tracking

Raffo, G.V., Gomes, G.K., Normey-Rico, J.E., Kelber, C.R., Becker, L.B.·2009·IEEE Transactions on Intelligent Transportation Systems

Abstract

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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Metadata

Authors
Raffo, G. V., Gomes, G. K., Normey-Rico, J. E., Kelber, C. R., & Becker, L. B.
Venue
IEEE Transactions on Intelligent Transportation Systems
Published
2009-03
Volume
10
Issue
1
Pages
92-102
ISSN
  • 1524-9050 (ISSN-L)
  • 1558-0016
OpenAlex
W2172117433
Cited by
342
References
0
FWCI
19.21
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A Predictive Controller for Autonomous Vehicle Path Tracking. https://app.cochat.ai/papers/10.1109/tits.2008.2011697
The paper
Raffo, G. V., Gomes, G. K., Normey-Rico, J. E., Kelber, C. R., & Becker, L. B. (2009). A Predictive Controller for Autonomous Vehicle Path Tracking. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/tits.2008.2011697

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.