Embodiments and examples are disclosed for intelligent vehicle diagnostics using driving behavior modeling and monitoring. For one example, a data processing system (100) for a vehicle (102) includes a plurality of sensors (103a-n) and a vehicle control unit (VCU) (106). The VCU (106) may sample the output from each of the plurality of sensors (103a-n) (405) and assemble a dataset which may be transmitted to a cloud computing center (104) (410). The cloud computing center (104) may apply statistical machine learning algorithms to the dataset and training data to generate a model of a user's expected driving behavior. The vehicle (102) may receive the generated model from cloud computing system (104) via network (124)(415), wherein the VCU (106) may utilize the model to monitor the user's driving behavior (420). In response to detecting driving behavior that is anomalous to the expected driving behavior (425), the VCU (106) may diagnose the cause of the anomalous behavior (430) and take one or more preventative actions based on the diagnosis (435).
DETECTING AND DIAGNOSING ANOMALOUS DRIVING BEHAVIOR USING DRIVING BEHAVIOR MODELS