Detecting road condition changes from probe data
First Claim
1. A method comprising:
- identifying, using a processor, a set of vehicle probe data associated with a roadway location;
performing, using the processor, a comparison of the set of vehicle probe data to a baseline for the roadway location;
dividing, using the processor, the set of vehicle probe data into a sparse subset and a low rank subset, wherein the sparse subset includes abnormalities or corrupted values with respect to the baseline; and
identifying, using the processor, a change at the roadway location based on vehicle probe data in the sparse subset.
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Abstract
Systems, methods, and apparatuses are disclosed for identifying anomalies or changes in road conditions on a roadway location. An initial low rank data matrix of initial vehicle probe data at a plurality of different times for a roadway location is provided, where the initial low rank data matrix represents a baseline of road conditions for the roadway location. A plurality of additional vehicle probe data from at least one vehicle at the roadway location is received. The additional vehicle probe data is added to the initial vehicle probe data of the initial low rank data matrix. The updated data matrix with the compiled probe data is decomposed into a low rank data matrix and a sparse data matrix. A change at the roadway location is identified based on the probe data in the sparse data matrix.
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Citations
20 Claims
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1. A method comprising:
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identifying, using a processor, a set of vehicle probe data associated with a roadway location; performing, using the processor, a comparison of the set of vehicle probe data to a baseline for the roadway location; dividing, using the processor, the set of vehicle probe data into a sparse subset and a low rank subset, wherein the sparse subset includes abnormalities or corrupted values with respect to the baseline; and identifying, using the processor, a change at the roadway location based on vehicle probe data in the sparse subset. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. An apparatus comprising:
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at least one processor; and at least one memory including computer program code for one or more programs;
the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least perform;identifying a set of probe data associated with a roadway location; performing a comparison of the set of probe data to a baseline for the roadway location; dividing the set of probe data into a sparse subset and a regular subset, wherein the sparse subset includes abnormalities or corrupted values with respect to the baseline; and identifying an event at the roadway location based on probe data in the sparse subset. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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19. A non-transitory computer-readable medium including instructions that when executed perform:
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identifying a set of probe data associated with a roadway location; performing a comparison of the set of probe data to a baseline for the roadway location; dividing the set of probe data into a sparse subset and a regular subset, wherein the sparse subset includes at least one abnormality or at least one corrupted value with respect to the baseline; and identifying an incident based on probe data in the sparse subset.
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20. A method comprising:
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identifying a set of probe data associated with a roadway location; performing a comparison of the set of probe data to a baseline for the roadway location; identifying a sparse subset from the set of probe data, wherein the sparse subset includes abnormalities or corrupted values with respect to the baseline; and identifying an event at the roadway location based on probe data in the sparse subset.
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Specification