A predictive controller for autonomous vehicle path tracking

  • Authors:

  • Guilherme V. Raffo;Guilherme K. Gomes;Julio E. Normey-Rico;Christian R. Kelber;Leandro B. Becker

  • Affiliations:

  • Department of Systems Engineering and Automation, University of Seville, Seville, Spain and Department of Automation and Systems Engineering, Federal University of Santa Catarina;Department of Tax Credit Services, Automatic Data Processing, Inc., Porto Alegre, Brazil and Department of Automation and Systems Engineering, Federal University of Santa Catarina;Department of Automation and Systems Engineering, Federal University of Santa Catarina, Florianópolis, Brazil;Department of Advanced Engineering, DHB Componentes Automotivos S.A., Porto Alegre, Brazil;Department of Automation and Systems Engineering, Federal University of Santa Catarina, Florianópolis, Brazil

  • Venue:
  • IEEE Transactions on Intelligent Transportation Systems
  • Year:
  • 2009

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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 "Mini-Baja" 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.