Distributing a crowdsourced sparse map for autonomous vehicle navigation

Patent metadata

Field	Value
Publication number	US-10838426-B2
Application number	US-201715656314-A
Country	US
Kind code	B2
Filing date	Jul 21, 2017
Priority date	Jul 21, 2016
Publication date	Nov 17, 2020
Grant date	Nov 17, 2020

Abstract

Systems and methods are provided for distributing a crowdsourced sparse map for autonomous vehicle navigation. In one implementation, a method of generating a road navigation model for use in autonomous vehicle navigation may include receiving navigation information associated with a common road segment from a plurality of vehicles; storing the navigation information associated with the common road segment; generating at least a portion of an autonomous vehicle road navigation model for the common road segment based on the navigation information; and distributing the autonomous vehicle road navigation model to one or more autonomous vehicles for use in autonomously navigating along the common road segment. The autonomous vehicle road navigation model may include at least one line representation of a road surface feature extending along the common road segment, and each line representation may representing a path along the common road segment substantially corresponding with the road surface feature.

First claim

What is claimed is:

1. A method of generating a road navigation model for use in autonomous vehicle navigation, the method comprising:
receiving, by a server, navigation information from a plurality of vehicles, wherein:
the navigation information from the plurality of vehicles is associated with a common road segment;
the navigation information from the plurality of vehicles includes first position information and second position information for a road surface feature extending along the common road segment; and
the first position information and the second position information have been determined based on analysis of a plurality of images acquired as the plurality of vehicles traverse the common road segment;

storing, by the server, the navigation information associated with the common road segment;
generating, by the server, at least a portion of an autonomous vehicle road navigation model for the common road segment based on the navigation information from the plurality of vehicles, the autonomous vehicle road navigation model for the common road segment including at least one line representation of a road surface feature extending along the common road segment, wherein:
each line representation represents a path along the common road segment substantially corresponding with the road surface feature;
each line representation is constructed by aligning the first position information and the second position information; and
the road surface feature is identified through the image analysis of the plurality of images acquired as the plurality of vehicles traverse the common road segment; and

distributing, by the server, the autonomous vehicle road navigation model to one or more autonomous vehicles for use in autonomously navigating the one or more autonomous vehicles along the common road segment.

2. The method of claim 1 , wherein the autonomous vehicle road navigation model is configured to be superimposed over a map, an image, or a satellite image.

3. The method of claim 1 , wherein the plurality of road features includes road edges or lane markings.

4. The method of claim 1 , wherein generating at least a portion of the autonomous vehicle road navigation model includes identifying, based on image analysis of the plurality of images, a plurality of landmarks associated with the common road segment.

5. The method of claim 4 , wherein generating at least a portion of the autonomous vehicle road navigation model further includes accepting potential landmarks when a ratio of images in which the landmark does appear to images in which the landmark does not appear exceeds a threshold.

6. The method of claim 4 , wherein generating at least a portion of the autonomous vehicle road navigation model further includes rejecting potential landmarks when a ratio of images in which the landmark does not appear to images in which the landmark does appear exceeds a threshold.

7. A system for generating a road navigation model for use in autonomous vehicle navigation, the system comprising:
at least one network interface;
at least one non-transitory storage medium; and
at least one processing device, wherein the at least one processing device is configured to:
receive, using the network interface, navigation information from a plurality of vehicles, wherein:
the navigation information from the plurality of vehicles is associated with a common road segment;
the navigation information from the plurality of vehicles includes first position information and second position information for a road surface feature extending along the common road segment; and
the first position information and the second position information have been determined based on analysis of a plurality of images acquired as the plurality of vehicles traverse the common road segment;

store, on the non-transitory storage medium, the navigation information associated with the common road segment;
generate at least a portion of an autonomous vehicle road navigation model for the common road segment based on the navigation information from the plurality of vehicles, the autonomous vehicle road navigation model for the common road segment including at least one line representation of a road surface feature extending along the common road segment, wherein:
each line representation represents a path along the common road segment substantially corresponding with the road surface feature;
each line representation is constructed by aligning the first position information and the second position information;
and the road surface feature is identified through image analysis of a plurality of images acquired as the plurality of vehicles traverse the common road segment; and

distribute, using the network interface, the autonomous vehicle road navigation model to one or more autonomous vehicles for use in autonomously navigating the one or more autonomous vehicles along the common road segment.

8. The system of claim 7 , wherein the autonomous vehicle road navigation model is configured to be superimposed over a map, an image, or a satellite image.

9. The system of claim 7 , wherein the plurality of road features includes road edges or lane markings.

10. The system of claim 7 , wherein generating at least a portion of the autonomous vehicle road navigation model includes identifying, based on image analysis of the plurality of images, a plurality of landmarks associated with the common road segment.

11. The system of claim 10 , wherein generating at least a portion of the autonomous vehicle road navigation model further includes accepting potential landmarks when a ratio of images in which the landmark does appear to images in which the landmark does not appear exceeds a threshold.

12. The system of claim 10 , wherein generating at least a portion of the autonomous vehicle road navigation model further includes rejecting potential landmarks when a ratio of images in which the landmark does not appear to images in which the landmark does appear exceeds a threshold.

13. A non-transitory, computer-readable medium storing instructions that, when executed by at least one processing device, cause the server to:
receive navigation information from a plurality of vehicles, wherein:
the navigation information from the plurality of vehicles is associated with a common road segment;
the navigation information from the plurality of vehicles includes first position information and second position information for a road surface feature extending along the common road segment; and
the first position information and the second position information have been determined based on analysis of a plurality of images acquired as the plurality of vehicles traverse the common road segment;

store the navigation information associated with the common road segment;
generate at least a portion of an autonomous vehicle road navigation model for the common road segment based on the navigation information from the plurality of vehicles, the autonomous vehicle road navigation model for the common road segment including at least one line representation of a road surface feature extending along the common road segment, wherein:
each line representation represents a path along the common road segment substantially corresponding with the road surface feature;
each line representation is constructed by aligning the first position information and the second position information; and
the road surface feature is identified through image analysis of a plurality of images acquired as the plurality of vehicles traverse the common road segment; and

distribute the autonomous vehicle road navigation model to one or more auto

Assignees

• Mobileye Vision Technologies Ltd

Inventors

• Fridman Ofer

Classifications

• H04N23/90

  Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums · CPC title

• G01C21/3852

  Data derived from aerial or satellite images · CPC title

• G01C21/3822

  Road feature data, e.g. slope data · CPC title

• G05D1/246

  using environment maps, e.g. simultaneous localisation and mapping [SLAM] · CPC title

• G05D1/2435

  Extracting 3D information · CPC title