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Optimization and Engineering

, 10:439 | Cite as

Generating locally optimal trajectories for an automatically driven car

  • Matthias Gerdts
  • Simon Karrenberg
  • Bernhard Müller-Beßler
  • Gregor Stock
Article

Abstract

The test-drive of an automobile along a given test-course can be modeled by formulating a suitable optimal control problem. However, if the length of the course is very long or if it has a very complicated structure, the numerical solution of the optimal control problem becomes very difficult. Therefore a moving horizon technique is employed, which splits the optimal control problem into a sequence of local optimal control problems that are combined by suitable continuity conditions. This approach yields a reference trajectory. A controller and differential GPS are integrated in a real-world car and allows a reference trajectory to be followed in real-time. A benefit of this approach is the very high accuracy obtained in reproducing the reference trajectory. Hence, it can be used for testing different setups of cars under the same conditions while excluding the comparatively large influence of a real-world driver. In this article, we will focus on a method for generating the reference trajectory and report our experiences with this algorithm. The method allows an locally optimal solution to be computed for various handling courses in a robust way.

Keywords

Optimal control Automatic test-driving Direct discretization method Moving horizon 

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Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Matthias Gerdts
    • 1
  • Simon Karrenberg
    • 2
  • Bernhard Müller-Beßler
    • 2
  • Gregor Stock
    • 2
  1. 1.School of MathematicsUniversity of BirminghamBirminghamUK
  2. 2.Volkswagen AGKonzernforschungWolfsburgGermany

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