Evaluating perception systems for autonomous vehicles using quality temporal logic

Adel Dokhanchi, Heni Ben Amor, Jyotirmoy V. Deshmukh, Georgios Fainekos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

For reliable situation awareness in autonomous vehicle applications, we need to develop robust and reliable image processing and machine learning algorithms. Currently, there is no general framework for reasoning about the performance of perception systems. This paper introduces Timed Quality Temporal Logic (TQTL) as a formal language for monitoring and testing the performance of object detection and situation awareness algorithms for autonomous vehicle applications. We demonstrate that it is possible to describe interesting properties as TQTL formulas and detect cases where the properties are violated.

Original languageEnglish (US)
Title of host publicationRuntime Verification- 18th International Conference, RV 2018, Proceedings
EditorsChristian Colombo, Martin Leucker
PublisherSpringer Verlag
Pages409-416
Number of pages8
ISBN (Print)9783030037680
DOIs
StatePublished - 2019
Event18th International Conference on Runtime Verification, RV 2018 - Limassol, Cyprus
Duration: Nov 10 2018Nov 13 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11237
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Runtime Verification, RV 2018
CountryCyprus
CityLimassol
Period11/10/1811/13/18

Keywords

  • Autonomous vehicles Perception
  • Image processing
  • Machine Learning
  • Monitoring
  • Temporal logic

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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