An Inverse Optimal Control Approach for Trajectory Prediction of Autonomous Race Cars

Rudolf Reiter, Florian Messerer, Markus Schratter, Daniel Watzenig, Moritz Diehl

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

Abstract

This paper proposes an optimization-based approach to predict trajectories of autonomous race cars. We assume that the observed trajectory is the result of an optimization problem that trades off path progress against acceleration and jerk smoothness, and which is restricted by constraints. The algorithm predicts a trajectory by solving a parameterized nonlinear program (NLP) which contains path progress and smoothness in cost terms. By observing the actual motion of a vehicle, the parameters of prediction are updated by means of solving an inverse optimal control problem that contains the parameters of the predicting NLP as optimization variables. The algorithm therefore learns to predict the observed vehicle trajectory in a least-squares relation to measurement data and to the presumed structure of the predicting NLP. This work contributes with an algorithm that allows for accurate and interpretable predictions with sparse data. The algorithm is implemented on embedded hardware in an autonomous real-world race car that is competing in the challenge Roborace and analyzed with respect to recorded data.

Original languageEnglish
Title of host publication2022 European Control Conference, ECC 2022
PublisherInstitute of Electrical and Electronics Engineers
Pages146-153
Number of pages8
ISBN (Electronic)9783907144077
DOIs
Publication statusPublished - 2022
Event20th European Control Conference: ECC22 - London, Hybrider Event, United Kingdom
Duration: 12 Jul 202215 Jul 2022
https://ecc22.euca-ecc.org/

Conference

Conference20th European Control Conference
Abbreviated titleECC 2022
Country/TerritoryUnited Kingdom
CityLondon, Hybrider Event
Period12/07/2215/07/22
Internet address

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems and Management
  • Control and Systems Engineering
  • Control and Optimization
  • Modelling and Simulation

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