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DETECTING AND DIAGNOSING ANOMALOUS DRIVING BEHAVIOR USING DRIVING BEHAVIOR MODELS

机译:使用行车行为模型检测和诊断异常行车行为

摘要

Embodiments and examples are disclosed for intelligent vehicle diagnostics using driving behavior modeling and monitoring. For one example, a data processing system for a vehicle includes a plurality of sensors and a vehicle control unit (VCU). The VCU may sample the output from each of the plurality of sensors and assemble a dataset which may be transmitted to a cloud computing center. The cloud computing center may apply statistical machine learning algorithms to the dataset and training data to develop a model of a user's expected driving behavior. The cloud computing center may transmit the model to the vehicle, wherein the VCU may utilize the model to monitor the user's driving behavior. In response to detecting driving behavior that is anomalous to the expected driving behavior, the VCU may diagnose the cause of the anomalous behavior and take one or more preventative actions based on the diagnosis.
机译:公开了用于使用驾驶行为建模和监视的智能车辆诊断的实施例和示例。例如,一种用于车辆的数据处理系统,包括多个传感器和车辆控制单元(VCU)。 VCU可以采样来自多个传感器中的每个传感器的输出并且组装可以被发送到云计算中心的数据集。云计算中心可以将统计机器学习算法应用于数据集和训练数据,以开发用户的预期驾驶行为的模型。云计算中心可以将模型发送到车辆,其中,VCU可以利用模型来监视用户的驾驶行为。响应于检测到与预期驾驶行为异常的驾驶行为,VCU可以诊断异常行为的原因,并基于该诊断采取一种或多种预防措施。

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