Analysing Experimental Results Obtained when Applying Search-based Testing to Verify Automated Driving Functions

Florian Kluck, Franz Wotawa, Gerhard Neubauer, Jianbo Tao, Mihai Nica

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

Abstract

Assuring safety in case of automated and autonomous driving is of uttermost importance requiring exhaustive search for critical scenarios allowing to reveal faults in current implementations. Different approaches like search-based testing have been already used to come up with test cases that allow to detect situations where the automated or autonomous driving function reacts in an unwanted way. In this paper, we contribute to the corresponding research and provide an in-depth analysis of results obtained using search-based testing applied to two different automatic emergency braking systems. We primarily focus on answering the question regarding the number of parameters required to find crashes. An answer to this question has implications for practice as well as for other testing techniques like combinatorial testing, where there is a need to identify the combinatorial strength in advance for assuring the detection of faults. Our analysis revealed important parameters of tests and we observed that interactions of at least 4 parameters are required to obtain critical scenarios of a high probability.

Original languageEnglish
Title of host publicationProceedings - 2021 8th International Conference on Dependable Systems and Their Applications, DSA 2021
PublisherInstitute of Electrical and Electronics Engineers
Pages213-219
Number of pages7
ISBN (Electronic)9781665443913
DOIs
Publication statusPublished - 2021
Event8th International Conference on Dependable Systems and Their Applications: DSA 2021 - Virtuell, China
Duration: 11 Sep 202112 Sep 2021

Conference

Conference8th International Conference on Dependable Systems and Their Applications
Abbreviated titleDSA 2021
Country/TerritoryChina
CityVirtuell
Period11/09/2112/09/21

Keywords

  • ADAS testing
  • search-based testing
  • test automation
  • VV of ADAS

ASJC Scopus subject areas

  • Software
  • Safety, Risk, Reliability and Quality
  • Artificial Intelligence
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'Analysing Experimental Results Obtained when Applying Search-based Testing to Verify Automated Driving Functions'. Together they form a unique fingerprint.

Cite this