ViSTA: a Framework for Virtual Scenario-based Testing of Autonomous Vehicles
Andrea Piazzoni, Jim Cherian, Mohamed Azhar, Jing Yew Yap, James Lee, Wei Shung, Roshan Vijay

TL;DR
ViSTA is a comprehensive framework for virtual scenario-based testing of autonomous vehicles, enabling automated and manual test case generation, execution, and performance analysis to identify safety issues before real-world deployment.
Contribution
This paper introduces ViSTA, a novel framework that integrates scenario generation, automation, and analysis for AV testing in virtual environments.
Findings
Effective scenario generation with meaningful parameters
Automated execution of test cases
Performance analysis of AVs under various scenarios
Abstract
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.
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