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.
翻译:在本文中,我们介绍ViSTA,这是作为2021年IEEE自动测试驱动AI测试挑战的一部分而开发的一个基于虚拟情景的自治车辆测试框架,基于情景的虚拟测试旨在构建AV所要克服的具体挑战,尽管在不一定与真实世界相类似的虚拟测试环境中;这一方法旨在查明在将AV实际部署到路上之前产生的安全关切的具体问题;在本文中,我们描述了一种全面的测试案例生成方法,该方法有助于设计具有有意义的参数的特殊目的情景,以自动和人工方式形成测试案例,从而形成测试案例,同时利用其中之一的力量和弱点。此外,我们描述了如何自动实施测试案例,并分析在这些测试案例下AV的性能。