mlsanityData to 7 Oct 2026

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

arXiv 2103.04364 ↗First posted 7 Mar 2021cs.AI cs.RO cs.SEcited by 8

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Abstract (arXiv)

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.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 8 of its 43 references that are in the map. First posted on arXiv 7 Mar 2021.

Builds on

8 of 43 references.

References · 8

  1. 2016Game-Theoretic Modeling of Driver and Vehicle Interactions for Verification and Validation of Autonomous Vehicle Control Systemscited by 24
  2. 2019Testing Scenario Library Generation for Connected and Automated Vehicles, Part I: Methodologycited by 24
  3. 2019A Systematic Literature Review about the impact of Artificial Intelligence on Autonomous Vehicle Safetycited by 10
  4. 2019Testing Scenario Library Generation for Connected and Automated Vehicles, Part II: Case Studiescited by 10
  5. 2016A Corroborative Approach to Verification and Validation of Human--Robot Teamscited by 6
  6. 2016Intelligent Agent-Based Stimulation for Testing Robotic Software in Human-Robot Interactionscited by 4
  7. 2016Model-based Test Generation for Robotic Software: Automata versus Belief-Desire-Intention Agentscited by 2
  8. 2015Systematic and Realistic Testing in Simulation of Control Code for Robots in Collaborative Human-Robot Interactionscited by 1

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Cited by year

Citing papers per year: 2021: 2; 2022: 0; 2023: 2; 2024: 1; 2025: 3.

8 papers.