闭环ACAS Xu神经网络验证

Sanaz Sheikhi, Stanley Bak
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引用次数: 2

摘要

基准建议:神经网络控制系统(NNCS)在自动驾驶中起着至关重要的作用。然而,验证它们的正确性是一个巨大的挑战。在本文中,我们考虑了ACAS Xu的神经网络压缩,这是一种常用的开环神经网络验证基准。ACAS Xu是一种空对空避碰系统,用于无人驾驶飞机发出水平转弯通知,以避免与入侵飞机相撞。我们提出了特定的性质和不同的系统假设,以使用该系统作为闭环nnc基准。我们给出了基于随机生成的测试用例的属性的实验结果,并提供了仿真代码。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Closed-Loop ACAS Xu Neural Network Verification
Benchmark Proposal: Neural Network Control Systems (NNCS) play critical roles in autonomy. However, verifying their correctness is a substantial challenge. In this paper, we consider the neural network compression of ACAS Xu, a popular benchmark usually considered for open-loop neural network verification. ACAS Xu is an air-to-air collision avoidance system for unmanned aircraft issuing horizontal turn advisories to avoid collision with an intruder aircraft. We propose specific properties and different system assumptions to use this system as a closed-loop NNCS benchmark. We present experimental results for our properties based on randomly generated test cases and provide simulation code.
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CiteScore
1.60
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