Method of effective driving behavior extraction using deep learning
First Claim
1. A computer implemented method for determining driving behavior characteristics of a driver of a vehicle comprising:
- obtaining vehicle operational data and driving context data from one or more monitoring systems over a plurality of temporal data points;
converting the obtained vehicle operational data and driving context data into sequential vehicle operational feature data and sequential driving context feature data;
associating the sequential vehicle operational feature data to the sequential driving context feature data of corresponding temporal data points of the plurality of temporal data points to form calibrated sequential vehicle operational feature data and calibrated sequential driving context feature data;
constructing a sequence table of a sequence of the plurality of temporal data points based on the calibrated sequential vehicle operational feature data and the calibrated sequential driving context feature data associated with each of the plurality of temporal data points, the sequence table being constructed by combining segmented calibrated sequential vehicle operational feature data and calibrated sequential driving context feature data from a plurality of windows, each window corresponding to a respective one temporal sample point;
feeding the sequence table into a deep neural network model for applying network learning to form a trained deep neural network model;
extracting driving behavior features from the trained deep neural network model; and
automatically determining driving behavior characteristics of the driver in the future based on the extracted driving behavior features.
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Abstract
Systems and methods for obtaining vehicle operational data and driving context data from one or more monitoring systems, including converting the obtained vehicle operational data and driving context data into sequential vehicle operational feature data and sequential driving context feature data, calibrating the sequential vehicle operational feature data and the sequential driving context feature data temporally to form calibrated sequential vehicle operational feature data and calibrated sequential driving context feature data, constructing a sequence table of temporal sample points based on the calibrated sequential vehicle operational feature data and the calibrated sequential driving context feature data, feeding the sequence table into a deep neural network model for applying network learning to form a trained deep neural network model, extracting driving behavior features from the trained deep neural network model and analyzing the extracted driving behavior features to determine driving behavior characteristics of the driver.
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Citations
17 Claims
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1. A computer implemented method for determining driving behavior characteristics of a driver of a vehicle comprising:
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obtaining vehicle operational data and driving context data from one or more monitoring systems over a plurality of temporal data points; converting the obtained vehicle operational data and driving context data into sequential vehicle operational feature data and sequential driving context feature data; associating the sequential vehicle operational feature data to the sequential driving context feature data of corresponding temporal data points of the plurality of temporal data points to form calibrated sequential vehicle operational feature data and calibrated sequential driving context feature data; constructing a sequence table of a sequence of the plurality of temporal data points based on the calibrated sequential vehicle operational feature data and the calibrated sequential driving context feature data associated with each of the plurality of temporal data points, the sequence table being constructed by combining segmented calibrated sequential vehicle operational feature data and calibrated sequential driving context feature data from a plurality of windows, each window corresponding to a respective one temporal sample point; feeding the sequence table into a deep neural network model for applying network learning to form a trained deep neural network model; extracting driving behavior features from the trained deep neural network model; and automatically determining driving behavior characteristics of the driver in the future based on the extracted driving behavior features. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A system for determining driving behavior characteristics of a driver of a vehicle, comprising:
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one or more storage devices; one or more hardware processors coupled to the one or more storage devices; one or more hardware processors operable to obtain vehicle operational data and driving context data from one or more monitoring systems over a plurality of temporal data points; one or more hardware processors operable to convert the obtained vehicle operational data and driving context data into sequential vehicle operational feature data and sequential driving context feature data; one or more hardware processors operable to associate the sequential vehicle operational feature data to the sequential driving context feature data of corresponding temporal data points of the plurality of temporal data points to form calibrated sequential vehicle operational feature data and calibrated sequential driving context feature data; one or more hardware processors operable to construct a sequence table of a sequence of the plurality of temporal data points based on the calibrated sequential vehicle operational feature data and the calibrated sequential driving context feature data associated with each of the plurality of temporal data points, the sequence table being constructed by combining segmented calibrated sequential vehicle operational feature data and calibrated sequential driving context feature data from a plurality of windows, each window corresponding to a respective one temporal sample point; one or more hardware processors operable to feed the sequence table into a deep neural network model for applying network learning to form a trained deep neural network model; one or more hardware processors operable to extract driving behavior features from the trained deep neural network model; and one or more hardware processors operable to automatically determine driving behavior characteristics of the driver in the future based on the extracted driving behavior features. - View Dependent Claims (9, 10, 11, 12, 13)
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14. A computer readable storage medium storing a program of instructions executable by a machine to perform a method of determining driving behavior characteristics of a driver of a vehicle, the method comprising:
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obtaining vehicle operational data and driving context data from one or more monitoring systems over a plurality of temporal data points; converting the obtained vehicle operational data and driving context data into sequential vehicle operational feature data and sequential driving context feature data; associating the sequential vehicle operational feature data to the sequential driving context feature data of corresponding temporal data points of the plurality of temporal data points to form calibrated sequential vehicle operational feature data and calibrated sequential driving context feature data; constructing a sequence table of a sequence of the plurality of temporal data points based on the calibrated sequential vehicle operational feature data and the calibrated sequential driving context feature data associated with each of the plurality of temporal data points, the sequence table being constructed by combining segmented calibrated sequential vehicle operational feature data and calibrated sequential driving context feature data from a plurality of windows, each window corresponding to a respective one temporal sample point; feeding the sequence table into a deep neural network model for applying network learning to form a trained deep neural network model; extracting driving behavior features from the trained deep neural network model; and automatically determining driving behavior characteristics of the driver in the future based on the extracted driving behavior features. - View Dependent Claims (15, 16, 17)
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Specification