Systems and methods for estimating movements of a vehicle using a mobile device
First Claim
1. A method of computing an orientation of a mobile device in a vehicle, the method comprising:
- collecting accelerometer data from the mobile device traveling in the vehicle, the accelerometer data comprising acceleration vectors with acceleration values for three orthogonal axes;
subdividing the accelerometer data into frames, each frame being a quantity of time in which a sample data point is taken;
calculating statistics for each frame, using a hardware computing processor, the statistics comprising (i) a mean of the acceleration vectors and (ii) a standard deviation of a magnitude of the acceleration vectors;
computing device usage delimiters, using a hardware computing processor, the device usage delimiters marking start and end points of a coherent block, the coherent block comprising consecutive frames in which the mobile device stays in the same orientation relative to the vehicle;
estimating a gravity vector, using the statistics from the accelerometer data in coherent blocks;
computing a nullspace from the gravity vector, the nullspace being a plane orthogonal to the gravity vector; and
projecting the accelerometer data onto the nullspace, the projecting resulting in an estimated orientation of the mobile device in the vehicle.
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Abstract
A method of computing an orientation of a mobile device in a vehicle includes collecting accelerometer data from the mobile device. The accelerometer data are subdivided into frames, each frame being a quantity of time in which a sample data point is taken. Statistics are calculated for each frame, including (i) a mean and (ii) a standard deviation of the magnitude of the acceleration vectors. Device usage delimiters, marking start and end points of a coherent block, are computed, the coherent block being consecutive frames in which the mobile device stays in the same orientation relative to the vehicle. A gravity vector is estimated using the statistics in coherent blocks. A nullspace is computed from the gravity vector, the nullspace being a plane orthogonal to the gravity vector. The accelerometer data is projected onto the nullspace, resulting in an estimated orientation of the mobile device in the vehicle.
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Citations
20 Claims
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1. A method of computing an orientation of a mobile device in a vehicle, the method comprising:
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collecting accelerometer data from the mobile device traveling in the vehicle, the accelerometer data comprising acceleration vectors with acceleration values for three orthogonal axes; subdividing the accelerometer data into frames, each frame being a quantity of time in which a sample data point is taken; calculating statistics for each frame, using a hardware computing processor, the statistics comprising (i) a mean of the acceleration vectors and (ii) a standard deviation of a magnitude of the acceleration vectors; computing device usage delimiters, using a hardware computing processor, the device usage delimiters marking start and end points of a coherent block, the coherent block comprising consecutive frames in which the mobile device stays in the same orientation relative to the vehicle; estimating a gravity vector, using the statistics from the accelerometer data in coherent blocks; computing a nullspace from the gravity vector, the nullspace being a plane orthogonal to the gravity vector; and projecting the accelerometer data onto the nullspace, the projecting resulting in an estimated orientation of the mobile device in the vehicle. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A method of inferring movements of a vehicle, the method comprising:
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collecting accelerometer data from the mobile device traveling in the vehicle, the accelerometer data comprising acceleration vectors with acceleration values for three orthogonal axes; subdividing the accelerometer data into frames, each frame being a quantity of time in which a sample data point is taken; calculating statistics for each frame, using a hardware computing processor, the statistics comprising (i) a mean of the acceleration vectors and (ii) a standard deviation of a magnitude of the acceleration vectors; computing device usage delimiters, using a hardware computing processor, the device usage delimiters marking start and end points of a coherent block, the coherent block comprising consecutive frames in which the mobile device stays in the same orientation relative to the vehicle; estimating a gravity vector, using the statistics from the accelerometer data in coherent blocks; computing a nullspace, using the gravity vector, the nullspace being a plane orthogonal to the gravity vector; projecting the accelerometer data onto the nullspace, wherein the nullspace provides a forward direction of vehicle movement; collecting global positioning system (GPS) data during a plurality of brief segments of time to obtain speed and position values; correlating longitudinal and lateral accelerometer data with longitudinal G-forces estimates from the GPS data, the longitudinal and lateral accelerometer data being relative to the nullspace; correcting for speed drift by (a) identifying periods of time when the vehicle is stationary, based on the GPS position values, and (b) setting G-force values to zero for those periods; and determining vehicle speed estimates, comprising calculating vehicle speed estimates for intervals between the segments of collecting GPS data. - View Dependent Claims (15, 16, 17, 18, 19, 20)
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Specification