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Control Barrier Functions and Input-to-State Safety With Application to Automated Vehicles

  • Anil Alan
  • , Andrew J. Taylor
  • , Chaozhe R. He
  • , Aaron D. Ames
  • , Gabor Orosz
  • University of Michigan, Ann Arbor
  • California Institute of Technology

Research output: Contribution to journalArticlepeer-review

116 Scopus citations

Abstract

Balancing safety and performance is one of the predominant challenges in modern control system design. Moreover, it is crucial to robustly ensure safety without inducing unnecessary conservativeness that degrades performance. In this work, we present a constructive approach for safety-critical control synthesis via control barrier functions (CBFs). By filtering a hand-designed controller via a CBF, we are able to attain performant behavior while providing rigorous guarantees of safety. In the face of disturbances, robust safety and performance are simultaneously achieved through the notion of input-to-state safety (ISSf). We take a tutorial approach by developing the CBF-design methodology in parallel with an inverted pendulum example, making the challenges and sensitivities in the design process concrete. To establish the capability of the proposed approach, we consider the practical setting of safety-critical design via CBFs for a connected automated vehicle (CAV) in the form of a class-8 truck without a trailer. Through experimentation, we see the impact of unmodeled disturbances in the truck's actuation system on the safety guarantees provided by CBFs. We characterize these disturbances and using ISSf, produce a robust controller that achieves safety without conceding performance. We evaluate our design both in simulation, and for the first time on an automotive system, experimentally.

Original languageEnglish
Pages (from-to)2744-2759
Number of pages16
JournalIEEE Transactions on Control Systems Technology
Volume31
Issue number6
DOIs
StatePublished - Nov 1 2023

Keywords

  • Connected automated vehicles (CAVs)
  • control barrier functions (CBFs)
  • input-to-state safety (ISSf)
  • robust safety-critical control

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