测试自动驾驶汽车的31个挑战:采访来自行业和研究领域的专家

Felix Beringhoff, Joel Greenyer, Christian Roesener, Matthias Tichy
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引用次数: 5

摘要

整个汽车行业的共识是,自动驾驶系统和自动驾驶汽车对质量保证,特别是测试的执行方式提出了挑战。然而,缺乏最新的实证研究来证实这一担忧。我们采访了几位来自行业和研究领域的专家,系统地确定了方法和工具方面的挑战和改进机会。我们在本文中报告了我们在基于场景和模拟的测试、测试自动化和测试执行领域中确定的31个挑战。许多专家提出的一个反复出现的挑战是,如何将需要测试的条件转换为可执行的场景模型。这不仅仅是一个编写场景脚本的问题,而且还考虑到在测试中的车辆可能试图逃避期望的测试条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Thirty-One Challenges in Testing Automated Vehicles: Interviews with Experts from Industry and Research
There is consensus across the automotive industry that Automated Driving Systems and automated vehicles challenge the way how quality assurance and, particularly, testing must be performed. However, there is a lack of up-to-date empirical studies that substantiate this concern. We conducted interviews with several experts from industry and research to systematically identify challenges as well as improvement opportunities in methods and tools. We report in this paper on 31 challenges that we identified in the areas of scenario- and simulation-based testing, test automation, and test execution. One recurrent challenge expressed by many experts is the problem how to translate a desired condition to be tested into an executable scenario model. This is not alone a question of scripting the scenario, but also of considering a vehicle under test that might try to evade the desired test condition.
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