@inproceedings{20761baa5b364933b19b6513e5f82143,
title = "Evaluating perception systems for autonomous vehicles using quality temporal logic",
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.",
keywords = "Autonomous vehicles Perception, Image processing, Machine Learning, Monitoring, Temporal logic",
author = "Adel Dokhanchi and Amor, {Heni Ben} and Deshmukh, {Jyotirmoy V.} and Georgios Fainekos",
note = "Funding Information: Acknowledgements. This work was partially supported by the NSF I/UCRC Center for Embedded Systems and by NSF grants 1350420, 1361926 and 1446730. Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2018.; 18th International Conference on Runtime Verification, RV 2018 ; Conference date: 10-11-2018 Through 13-11-2018",
year = "2019",
doi = "10.1007/978-3-030-03769-7_23",
language = "English (US)",
isbn = "9783030037680",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "409--416",
editor = "Christian Colombo and Martin Leucker",
booktitle = "Runtime Verification- 18th International Conference, RV 2018, Proceedings",
}