Crowd sourcing data for autonomous vehicle navigation

Patent metadata

Field	Value
Publication number	US-9760090-B2
Application number	US-201615272802-A
Country	US
Kind code	B2
Filing date	Sep 22, 2016
Priority date	Feb 10, 2015
Publication date	Sep 12, 2017
Grant date	Sep 12, 2017

Abstract

A method of processing vehicle navigation information for use in autonomous vehicle navigation is provided. The method includes receiving, by a server, navigation information from a plurality of vehicles. The navigation information from the plurality of vehicles is associated with a common road segment. The method also includes storing, by the server, the navigation information associated with the common road segment. The method also includes 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 method further includes 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.

First claim

What is claimed is:

1. A method of processing vehicle navigation information 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;
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, wherein the autonomous vehicle road navigation model includes a three-dimensional spline corresponding to a target trajectory along 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 navigation information includes a trajectory from each of the plurality of vehicles as each vehicle travels over the common road segment.

3. The method of claim 2 , wherein the trajectory is determined based on sensed motion of a camera, including three-dimensional translation and three-dimensional rotational motions.

4. The method of claim 1 , wherein the navigation information includes a lane assignment.

5. The method of claim 1 , wherein generating at least a portion of the autonomous vehicle road navigation model includes clustering vehicle trajectories along the common road segment and determining the target trajectory along the common road segment based on the clustered vehicle trajectories.

6. The method of claim 5 , wherein the target trajectory is associated with a single lane of the common road segment.

7. The method of claim 5 , wherein the autonomous vehicle road navigation model includes a plurality of target trajectories, each associated with a separate lane of the common road segment.

8. The method of claim 5 , wherein determining the target trajectory along the common road segment based on the clustered vehicle trajectories includes finding a mean or average trajectory based on the clustered vehicle trajectories.

9. The method of claim 1 , wherein the three-dimensional spline is defined by less than 10 kilobytes per kilometer.

10. The method of claim 1 , wherein the autonomous vehicle road navigation model includes identification of at least one landmark, including a position of the at least one landmark.

11. The method of claim 10 , wherein the position of the at least one landmark is determined based on position measurements performed using sensor systems associated with the plurality of vehicles.

12. The method of claim 11 , wherein the position measurements are averaged to obtain the position of the at least one landmark.

13. The method of claim 10 , wherein the at least one landmark includes at least one of a traffic sign, an arrow marking, a lane marking, a dashed lane marking, a traffic light, a stop line, a directional sign, a landmark beacon, or a lamppost.

14. The method of claim 1 , wherein the three-dimensional spline includes one or more three-dimensional polynomials connecting a plurality of data points.

15. The method of claim 14 , wherein at least one of the data points is associated with the navigation information.

16. The method of claim 1 , wherein the navigation information includes road geometry data or road profile data.

17. A navigation system for a vehicle, the system comprising:
at least one processor programmed to:
receive from a camera, at least one environmental image associated with the vehicle;
analyze the at least one environmental image to determine navigation information related to the vehicle;
transmit the navigation information from the vehicle to a server;
receive, from the server, at least one update to an autonomous vehicle road navigation model based on the transmitted navigation information, wherein the autonomous vehicle road navigation model includes a three-dimensional spline corresponding to a target trajectory along the road segment; and
cause at least one navigational maneuver by the vehicle based on the updated autonomous vehicle road navigation model.

18. The navigation system of claim 17 , wherein the navigation information includes a trajectory of the vehicle as the vehicle travels over the road segment.

19. A server for processing vehicle navigation information for use in autonomous vehicle navigation, comprising:
a communication unit configured to communicate with a plurality of vehicles; and
at least one processor programmed to:
receive, via the communication unit, the navigation information from the vehicles;
generate at least a portion of an autonomous vehicle road navigation model, wherein the autonomous vehicle road navigation model includes a three-dimensional spline corresponding to a target trajectory along a road segment; and
transmit at least the portion of the autonomous vehicle road navigation model to at least one of the vehicles to cause a navigational maneuver by the at least one of the vehicles based on the portion of the autonomous vehicle road navigation model.

20. The server of claim 19 , wherein the navigation information includes a trajectory from each of the plurality of vehicles as each vehicle travels over the road segment.

21. The server of claim 19 , wherein the portion of autonomous vehicle road navigation model includes an update to the autonomous vehicle road navigation model.

22. The server of claim 19 , wherein the three-dimensional spline includes one or more three-dimensional polynomials connecting a plurality of data points.

23. The server of claim 22 , wherein at least one of the data points is associated with the navigation information.

24. The server of claim 19 , wherein the navigation information includes road geometry data or road profile data.

Assignees

• Mobileye Vision Technologies Ltd

Inventors

• Shashua Amnon
• Gdalyahu Yoram
• Springer Ofer
• Reisman Aran
• Braunstein Daniel

Classifications

• G01C21/32

  Structuring or formatting of map data · CPC title

• G01C21/30 Primary

  Map- or contour-matching · CPC title

• B60W2555/60

  Traffic rules, e.g. speed limits or right of way · CPC title

• G06T7/00

  Image analysis · CPC title

• G01C21/3623

  using a camera or code reader, e.g. for optical or magnetic codes · CPC title