Systematic Situation Coverage versus Random Situation Coverage for Safety Testing in an Autonomous Car Simulation

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

Abstract

Autonomous vehicles (AV) have the potential to improve road transport, but faults in the autonomous driving software can result in serious accidents. To assess the safety of AV driving software, we need to consider the wide variety and diversity of situations that it may encounter. Explicit situation coverage has previously been presented, but its usefulness has received a little empirical scrutiny. In this study, we evaluate a situation coverage based safety testing approach by comparing the performance of random and situation coverage-based test generation in terms of its ability to detect seeded faults in our ego AV at a road intersection under diverse environmental conditions. Our results suggest that this implementation of situation coverage, at least, does not provide an advantage over random generation.
Original languageEnglish
Title of host publicationLADC 2023: 12th Latin-American Symposium on Dependable and Secure Computing
PublisherACM
Pages208-213
Number of pages6
DOIs
Publication statusPublished - 20 Oct 2023
EventLADC 2023: 12th Latin-American Symposium on Dependable and Secure Computing - La Paz, Bolivia, Plurinational State of
Duration: 16 Oct 202320 Oct 2023

Conference

ConferenceLADC 2023: 12th Latin-American Symposium on Dependable and Secure Computing
Country/TerritoryBolivia, Plurinational State of
CityLa Paz
Period16/10/2320/10/23

Bibliographical note

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