Method and System for Adjusting Vehicle Settings
First Claim
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1. A method for adjusting settings in a vehicle, comprising the steps of training and operating,wherein the training further comprises:
- constructing input vectors from sensor data acquired from vehicle subsystems, wherein each input vector defines a context;
constructing, for each input vector, a corresponding output vector from adjustable settings recorded in a current context;
accumulating, in a memory, a training database including pairs of the input vectors and the output vectors;
learning a predictive model from the training database, wherein the predictive model predicts the corresponding output vector from the input vector; and
wherein, the operating further comprises;
constructing the input vectors from sensor data acquired from vehicle subsystems that defines the contexts;
predicting a most likely output vector using the predictive model; and
adjusting the settings according to the most likely output vector, wherein the method is performed in a processor.
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Abstract
Settings in a vehicle are adjusted by first learning a predictive model of output vectors that correspond to input vectors of sensor data acquired from vehicle subsystems during training. Each input vector defines a known context associated with the vehicle. During later operation of the vehicle, additional input vectors are obtained from the subsystems, and the corresponding output vectors to adjust the settings are then determined using the predictive model.
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Citations
13 Claims
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1. A method for adjusting settings in a vehicle, comprising the steps of training and operating,
wherein the training further comprises: -
constructing input vectors from sensor data acquired from vehicle subsystems, wherein each input vector defines a context; constructing, for each input vector, a corresponding output vector from adjustable settings recorded in a current context; accumulating, in a memory, a training database including pairs of the input vectors and the output vectors; learning a predictive model from the training database, wherein the predictive model predicts the corresponding output vector from the input vector; and wherein, the operating further comprises; constructing the input vectors from sensor data acquired from vehicle subsystems that defines the contexts; predicting a most likely output vector using the predictive model; and adjusting the settings according to the most likely output vector, wherein the method is performed in a processor. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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Specification