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A Test Scenario Automatic Generation Strategy for Intelligent Driving Systems

机译:智能驾驶系统的测试场景自动生成策略

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摘要

In this paper, a methodology of automatic generation of test scenarios for intelligent driving systems is proposed, which is based on the combination of the test matrix (TM) and combinatorial testing (CT) methods together. With a hierarchical model of influence factors, an evaluation index for scenario complexity is designed. Then an improved CT algorithm is proposed to make a balance between test efficiency, condition coverage, and scenario complexity. This method can ensure the required combinational coverage and at the same time increase the overall complexity of generated scenarios, which is not considered by CT. Furthermore, the way to find the best compromise between efficiency and complexity and the bound of scenario number has been analyzed theoretically. To validate the effectiveness, it has been applied in the hardware-in-the-loop (HIL) test of a lane departure warning system (LDW). The results show that the proposed method can ensure required coverage with a significantly improved scenario complexity, and the generated test scenario can find system defects more efficiently.
机译:本文提出了一种智能驾驶系统自动生成测试场景的方法,该方法基于测试矩阵(TM)和组合测试(CT)方法的结合。利用影响因素的分层模型,设计了情景复杂度的评估指标。然后提出一种改进的CT算法,以在测试效率,条件覆盖率和场景复杂性之间取得平衡。这种方法可以确保所需的组合覆盖范围,同时增加了生成方案的总体复杂度,而CT对此并未考虑。此外,从理论上分析了在效率和复杂性以及方案编号范围之间找到最佳折衷方案的方法。为了验证有效性,已将其应用于车道偏离预警系统(LDW)的在环硬件(HIL)测试中。结果表明,所提出的方法可以确保所需的覆盖范围,并显着提高了方案的复杂性,并且生成的测试方案可以更有效地发现系统缺陷。

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