Abstract: Methods and systems are provided for selectively inhibiting a stop-start controller of a vehicle based on a predicted anxiety of a driver of the vehicle on a road segment that includes one or more road attributes associated with increased levels of anxiety. In one example, selectively inhibiting a stop-start controller of a vehicle based on a predicted anxiety of a driver of the vehicle includes determining a driver classification for a driver operating the vehicle; predicting an anxiety level of the driver at an upcoming traffic condition, based on the driver classification; and selectively inhibiting an upcoming engine idle-stop event based on the predicted anxiety level of the driver.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to determine a predicted classification related to a road segment; upon a vehicle including the computer traveling over the road segment, determine an actual classification related to the road segment; in response to the actual classification failing to match the predicted classification, transmit a notification to a server remote from the vehicle; and upon receiving an instruction responsive to the notification, transmit vehicle data related to the road segment to the server.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to generate an operation parameter histogram for each of a plurality of vehicle operation parameters, operate a test vehicle according to the operation parameter histograms, input each operation parameter histogram and a plurality of test vehicle environment data to a machine learning program, output from the machine learning program a classification for each operation parameter histogram from the machine learning program, input the classifications to a predictive damage model of a three-dimensional schematic of a vehicle component, and adjust one of a size or a shape of the three-dimensional schematic based the output of the predictive damage model. The operation parameter histograms are based on collected data about operation of a plurality of vehicles. Each operation parameter histogram includes an array of elements.

Abstract: Vehicle environment data about operation of a plurality of vehicles and vehicle component data for a vehicle component is input into a machine learning program to obtain a transfer function that correlates vehicle environment data to vehicle component data within a specified range of vehicle component parameters. A first event is identified by determining that a datum in the vehicle component data is outside the specified range. A predictive damage model of a vehicle component is updated based on the first event. A virtual parameter of a component model is adjusted based on output from the predictive damage model.

Abstract: Methods and systems are provided for selectively inhibiting a stop-start controller of a vehicle based on a predicted anxiety of a driver of the vehicle on a road segment that includes one or more road attributes associated with increased levels of anxiety. In one example, selectively inhibiting a stop-start controller of a vehicle based on a predicted anxiety of a driver of the vehicle includes determining a driver classification for a driver operating the vehicle; predicting an anxiety level of the driver at an upcoming traffic condition, based on the driver classification; and selectively inhibiting an upcoming engine idle-stop event based on the predicted anxiety level of the driver.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to generate an operation parameter histogram for each of a plurality of vehicle operation parameters, operate a test vehicle according to the operation parameter histograms, input each operation parameter histogram and a plurality of test vehicle environment data to a machine learning program, output from the machine learning program a classification for each operation parameter histogram from the machine learning program, input the classifications to a predictive damage model of a three-dimensional schematic of a vehicle component, and adjust one of a size or a shape of the three-dimensional schematic based the output of the predictive damage model. The operation parameter histograms are based on collected data about operation of a plurality of vehicles. Each operation parameter histogram includes an array of elements.