CPC G07C 5/085 (2013.01) [B60W 50/0205 (2013.01); B60W 50/035 (2013.01); B60W 50/038 (2013.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06N 3/088 (2013.01); G07C 5/008 (2013.01); G07C 5/0808 (2013.01); B60W 2710/06 (2013.01); B60W 2710/18 (2013.01)] | 13 Claims |
1. A method for vehicle fault detection, comprising:
collecting operational data from a plurality of sensors in a vehicle, the plurality of sensors being associated with a plurality of vehicle sub-systems;
concatenating data features from the operational data with a sensor correlation graph that includes indications of correlations between groups of related sub-systems;
processing the concatenated data with a neural network to generate a fault score, which represents a similarity to fault state training scenarios, and an anomaly score, which represents a dissimilarity to normal state training scenarios;
determining that the fault score is above a fault score threshold and that the anomaly score is above an anomaly score threshold to detect a fault; and
performing a corrective action responsive the fault, based on a sub-system associated with the fault, selected from the group consisting of changing an operational status of one or more of the plurality of vehicle sub-systems, changing the setting of a device in the vehicle, stopping an engine of the vehicle, applying brakes of the vehicle, and changing operational properties of the engine, transmission or brakes of the vehicle to compensate for adverse conditions.
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