Road condition tagging
AssigneeLytx, Inc.
InventorsDaniel Witriol, Dennis Cheng
Life of this patent
Estimating the term…
Abstract
The present application discloses a method, system, and computer system for determining a road condition classification for one or more road segments. The method includes (i) determining a set of one or more images for a particular geographic area, (ii) obtaining a set of one or more images for the particular geographic area, (iii) determining a set of road classifications for the set of road segments based at least in part on querying a machine learning model to classify the set of one or more images, and (iv) storing the set of road classifications in association with the set of road segments.
Claims25
A system, comprising:
- a memory;
- and
- one or more processors configured to:
- determine a set of one or more images for a particular geographic area;
- obtain the set of one or more images for the particular geographic area;
- determine a set of road classifications for a set of road segments associated with the particular geographic area that are based at least in part on querying a machine learning model to classify the set of one or more images, wherein determining the set of road classifications for the set of road segments comprises:
- determining a road classification for a particular road segment based on a plurality of images associated with the particular road segment, wherein determining the road classification for the particular road segment comprises aggregating predicted road classifications from the plurality of images using a hierarchical structure of road segments, wherein child road segments are aggregated into a parent road segment based on a most severe road condition among the child road segments;
- and
- store the set of road classifications in association with the set of road segments.
A method, comprising:
- determining, using a processor, a set of one or more images for a particular geographic area;
- obtaining the set of one or more images for the particular geographic area;
- determining a set of road classifications for a set of road segments associated with the particular geographic area that are based at least in part on querying a machine learning model to classify the set of one or more images, wherein determining the set of road classifications for the set of road segments comprises:
- determining a road classification for a particular road segment based on a plurality of images associated with the particular road segment, wherein determining the road classification for the particular road segment comprises aggregating predicted road classifications from the plurality of images using a hierarchical structure of road segments, wherein child road segments are aggregated into a parent road segment based on a most severe road condition among the child road segments;
- and
- storing the set of road classifications in association with the set of road segments.
A computer program product embodied in a non-transitory computer readable medium and comprising computer instructions for:
- determining, using a processor, a set of one or more images for a particular geographic area;
- obtaining a set of one or more images for the particular geographic area;
- determining a set of road classifications for a set of road segments associated with the particular geographic area that are based at least in part on querying a machine learning model to classify the set of one or more images, wherein determining the set of road classifications for the set of road segments comprises:
- determining a road classification for a particular road segment based on a plurality of images associated with the particular road segment, wherein determining the road classification for the particular road segment comprises aggregating predicted road classifications from the plurality of images using a hierarchical structure of road segments, wherein child road segments are aggregated into a parent road segment based on a most severe road condition among the child road segments;
- and
- storing the set of road classifications in association with the set of road segments.
Dependencies are inferred from the claim text.