一句话：面向 DNN 驱动的自动驾驶汽车，提出/介绍 DeepTest，以支持其测试与部署前的可靠性验证。
随着深度神经网络（DNN）的进展，使用摄像头、LiDAR 等传感器的 DNN 驱动自动驾驶汽车已能在无人工干预下行驶。Tesla、GM、Ford、BMW、Waymo/Google 等主要厂商均在研发和测试不同类型的自动驾驶车辆；加州、得州、纽约州等美国多州也通过新立法，加速自动驾驶汽车在公共道路上的测试与部署。论文标题为 DeepTest，表明工作聚焦此类 DNN 驱动自动驾驶系统的测试。但所给摘要仅提供上述背景，未给出具体方法、关键技术或实验评估结果，因此无法进一步概括其测试策略与有效性证据。
Recent advances in Deep Neural Networks (DNNs) have led to the development of DNN-driven autonomous cars that, using sensors like camera, LiDAR, etc., can drive without any human intervention. Most major manufacturers including Tesla, GM, Ford, BMW, and Waymo/Google are working on building and testing different types of autonomous vehicles. The lawmakers of several US states including California, Texas, and New York have passed new legislation to fast-track the process of testing and deployment of autonomous vehicles on their roads.