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Automatic Generation Method of Test Scenario for ADAS Based on Complexity

机译:基于复杂性的ADAS测试场景的自动生成方法

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ADAS must be tested thoroughly before they can be deployed for series production. Comparing with road and field test, bench test has been widely used owing to its advantages of less labor costs, more controllable scenarios, etc. However, there is no satisfied systematic approach to generate high-efficiency and full-coverage test scenarios automatically because of its integration of human, vehicle and traffic. Most of the test scenarios generated by the existing methods are either too simple or too few to be able to achieve full coverage of requirements. Besides, the cost is high when the ET method is used. To solve the aforementioned problems, an automatic test scenario generation method based on complexity for bench test is presented in this paper. Firstly, considering the fact that the device is easier to malfunction under complex cases, an index measuring the complexity of test case is proposed by using the method of AHP. Based on the existing combinatorial test case generation algorithm, the proposed complexity index is used to evaluate the effectiveness and guide to generate test cases that are more effective. Furthermore, to improve the test efficiency, a clustering method is introduced to combine the discrete test cases into continuous scenarios. The effectiveness of the proposed method has been validated by applying to LDW. The results show that: (a) A more complex case is easier to find the faults of a system; (b) The generated scenarios can achieve full coverage of the specified N-wise combination; (c) The scenarios generated by the proposed method can detect the system malfunctions more efficiently with a more compact test suite.
机译:必须在部署串联生产之前彻底测试ADA。与道路和现场测试相比,由于其劳动力成本较低,更可控的情景等的优点而广泛使用台式试验。然而,没有满足的系统方法,因为它的融合人类,车辆和交通。现有方法产生的大多数测试场景都太简单或太少,无法实现需求的全面覆盖。此外,使用ET方法时,成本很高。为了解决上述问题,本文提出了一种基于台式试验复杂性的自动测试场景生成方法。首先,考虑到在复杂的情况下设备更容易出现故障,通过使用AHP的方法提出了测量测试用例复杂性的指标。基于现有的组合测试案例生成算法,所提出的复杂性指数用于评估生成更有效的测试用例的有效性和指导。此外,为了提高测试效率,引入了聚类方法以将离散的测试用例组合成连续场景。通过申请LDW验证了所提出的方法的有效性。结果表明:(a)更复杂的案例更容易找到系统的故障; (b)所产生的方案可以完全覆盖指定的N-WISE组合; (c)所提出的方法产生的场景可以更具紧凑的测试套件更有效地检测系统故障。

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