Coverage based testing for V&V and Safety Assurance of Self-driving Autonomous Vehicle : A Systematic Literature Review

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


Self-driving Autonomous Vehicles (SAVs) are gaining more interest each passing day by the industry as well as the general public. Tech and automobile companies are investing huge amounts of capital in research and development of SAVs to make sure they have a head start in the SAV market in the future. One of the major hurdles in the way of SAVs making it to the public roads is the lack of confidence of public in the safety aspect of SAVs. In order to assure safety and provide confidence to the public in the safety of SAVs, researchers around the world have used coverage-based testing for Verification and Validation (V&V) and safety assurance of SAVs. The objective of this paper is to investigate the coverage criteria proposed and coverage maximizing techniques used by researchers in the last decade up till now, to assure safety of SAVs. We conduct a Systematic Literature Review (SLR) for this investigation in our paper. We present a classification of existing research based on the coverage criteria used. Several research gaps and research directions are also provided in this SLR to enable further research in this domain. This paper provides a body of knowledge in the domain of safety assurance of SAVs. We believe the results of this SLR will be helpful in the progression of V&V and safety assurance of SAVs.
Original languageEnglish
Title of host publicationThe Second IEEE International Conference On Artificial Intelligence Testing
Publication statusPublished - 23 Aug 2020
EventThe Second IEEE International Conference On Artificial Intelligence Testing - Keble College, Oxford, United Kingdom
Duration: 13 Apr 202016 Apr 2020


ConferenceThe Second IEEE International Conference On Artificial Intelligence Testing
Abbreviated titleAITest 2020
Country/TerritoryUnited Kingdom

Bibliographical note

© This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.

Cite this