Formalizing and evaluating requirements of perception systems for automated vehicles using spatio-temporal perception logic

Mohammad Hekmatnejad, Bardh Hoxha, Jyotirmoy V. Deshmukh, Yezhou Yang, Georgios Fainekos

Research output: Contribution to journalArticlepeer-review

Abstract

Automated vehicles (AV) heavily depend on robust perception systems. Current methods for evaluating vision systems focus mainly on frame-by-frame performance. Such evaluation methods appear to be inadequate in assessing the performance of a perception subsystem when used within an AV. In this paper, we present a logic—referred to as Spatio-Temporal Perception Logic (STPL)—which utilizes both spatial and temporal modalities. STPL enables reasoning over perception data using spatial and temporal operators. One major advantage of STPL is that it facilitates basic sanity checks on the functional performance of the perception system, even without ground truth data in some cases. We identify a fragment of STPL which is efficiently monitorable offline in polynomial time. Finally, we present a range of specifications for AV perception systems to highlight the types of requirements that can be expressed and analyzed through offline monitoring with STPL.

Original languageEnglish (US)
Pages (from-to)203-238
Number of pages36
JournalInternational Journal of Robotics Research
Volume43
Issue number2
DOIs
StatePublished - Feb 2024

Keywords

  • Programming environment
  • recognition
  • sensing and perception computer vision
  • simulation, interfaces and virtual reality
  • visual tracking

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Mechanical Engineering
  • Electrical and Electronic Engineering
  • Artificial Intelligence
  • Applied Mathematics

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