mlsanityData to 7 Oct 2026

ViSTA: a Framework for Virtual Scenario-based Testing of Autonomous Vehicles

arXiv 2109.02529 ↗First posted 6 Sep 2021cs.AI cs.ROcited by 6

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Abstract (arXiv)

In this paper, we present ViSTA, a framework for Virtual Scenario-based Testing of Autonomous Vehicles (AV), developed as part of the 2021 IEEE Autonomous Test Driving AI Test Challenge. Scenario-based virtual testing aims to construct specific challenges posed for the AV to overcome, albeit in virtual test environments that may not necessarily resemble the real world. This approach is aimed at identifying specific issues that arise safety concerns before an actual deployment of the AV on the road. In this paper, we describe a comprehensive test case generation approach that facilitates the design of special-purpose scenarios with meaningful parameters to form test cases, both in automated and manual ways, leveraging the strength and weaknesses of either. Furthermore, we describe how to automate the execution of test cases, and analyze the performance of the AV under these test cases.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 6 of its 20 references that are in the map. First posted on arXiv 6 Sep 2021.

Builds on

6 of 20 references.

References · 6

  1. 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
  2. 2016OpenAI Gymcited by 1,684
  3. 2016Playing for Data: Ground Truth from Computer Gamescited by 816
  4. 2018Unity: A General Platform for Intelligent Agentscited by 232
  5. 2020LGSVL Simulator: A High Fidelity Simulator for Autonomous Drivingcited by 119
  6. 2021Pylot: A Modular Platform for Exploring Latency-Accuracy Tradeoffs in Autonomous Vehiclescited by 33

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Cited by year

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

6 papers.