The disclosure provides automotive CAN decoding using supervised machine learning. Techniques for identifying certain signals sent over the CAN bus between components of a vehicle are provided herein. Specifically, certain testing maneuvers designed to engage the component of interest are provided to a technician for performing on the vehicle. The messages can be captured from the CAN bus and analyzed, using supervised machine learning algorithms, to isolate the message ids and the byte numbers so that the values of the component of interest may be observed for determining performance metrics. Once identified, these performance metrics may be used to compare with other vehicles or improve the design and performance of the vehicle.
本公开提供“使用监督机器学习的汽车CAN解码”。本文提供了用于识别在车辆部件之间通过CAN总线发送的某些信号的技术。具体地,被设计为接合感兴趣部件的某些测试操纵被提供给技术人员以在车辆上执行。可以从所述CAN总线捕获消息并使用监督机器学习算法分析消息,以隔离消息id和字节号,使得可以观察所述感兴趣部件的值以确定性能度量。一旦被识别,这些性能度量即可以用于与其他车辆进行比较或改进所述车辆的设计和性能。
AUTOMOTIVE CAN DECODING USING SUPERVISED MACHINE LEARNING
使用监督机器学习的汽车CAN解码
2021-08-03
Patent
Electronic Resource
Chinese
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