Sparse map autonomous vehicle navigation

Patent metadata

Field	Value
Publication number	US-9946260-B2
Application number	US-201615272624-A
Country	US
Kind code	B2
Filing date	Sep 22, 2016
Priority date	Feb 10, 2015
Publication date	Apr 17, 2018
Grant date	Apr 17, 2018

Abstract

A system for sparse map autonomous navigation of a vehicle along a road segment may include at least one processor. The at least one processor may be programmed to receive a sparse map of the road segment. The sparse map may have a data density of no more than 1 megabyte per kilometer. The at least one processor may be programmed to receive from a camera, at least one image representative of an environment of the vehicle, and determine an autonomous navigational response for the vehicle based on the analysis of the sparse map and the at least one image received from the camera.

First claim

What is claimed is:

1. A system for sparse map autonomous navigation of a vehicle along a road segment, the system comprising:
at least one processor programmed to:
receive a sparse map of the road segment, wherein the sparse map has a data density of no more than 1 megabyte per kilometer and the sparse map includes a planned trajectory for the road segment that deviates no more than 30 centimeters from a center of a lane in the road segment;
receive from a camera, at least one image representative of an environment of the vehicle;
analyze the sparse map and the at least one image received from the camera; and
determine an autonomous steering action for the vehicle based on the analysis of the sparse map and the at least one image received from the camera.

2. The system of claim 1 , wherein the sparse map includes a polynomial representation of a target trajectory along the road segment.

3. The system of claim 1 , wherein the sparse map includes one or more recognized landmarks.

4. The system of claim 3 , wherein the recognized landmarks are spaced apart in the sparse map at a rate of no more than 0.5 per kilometer.

5. The system of claim 3 , wherein the recognized landmarks are spaced apart in the sparse map at a rate of no more than 1 per kilometer.

6. The system of claim 3 , wherein the recognized landmarks are spaced apart in the sparse map at a rate of no more than 1 per 100 meters.

7. The system of claim 1 , wherein the sparse map has a data density of no more than 100 kilobytes per kilometer.

8. The system of claim 1 , wherein the sparse map has a data density of no more than 10 kilobytes per kilometer.

9. A method for sparse map autonomous navigation of a vehicle along a road segment, the method comprising:
receiving a sparse map of the road segment, wherein the sparse map has a data density of no more than 1 megabyte per kilometer and the sparse map includes a planned trajectory for the road segment that deviates no more than 30 centimeters from a center of a lane in the road segment;
receiving from a camera, at least one image representative of an environment of the vehicle;
analyzing the sparse map and the at least one image received from the camera; and
determining an autonomous steering action for the vehicle based on the analysis of the sparse map and the at least one image received from the camera.

10. The method of claim 9 , wherein the sparse map includes a polynomial representation of a target trajectory along the road segment.

11. The method of claim 9 , wherein the sparse map includes one or more recognized landmarks.

12. The method of claim 11 , wherein the recognized landmarks are spaced apart in the sparse map at a rate of no more than 0.5 per kilometer.

13. The method of claim 11 , wherein the recognized landmarks are spaced apart in the sparse map at a rate of no more than 1 per kilometer.

14. The method of claim 11 , wherein the recognized landmarks are spaced apart in the sparse map at a rate of no more than 1 per 100 meters.

15. The method of claim 9 , wherein the sparse map has a data density of no more than 100 kilobytes per kilometer.

16. The method of claim 9 , wherein the sparse map has a data density of no more than 10 kilobytes per kilometer.

17. A non-transitory computer readable medium storing instructions causing at least one processor to perform sparse map autonomous navigation of a vehicle along a road segment may include receiving a sparse map of the road segment, the instructions causing the processor to perform the steps of:
receiving a sparse map of the road segment, wherein the sparse map has a data density of no more than 1 megabyte per kilometer and the sparse map includes a planned trajectory for the road segment that deviates no more than 30 centimeters from a center of a lane in the road segment;
receiving from a camera, at least one image representative of an environment of the vehicle;
analyzing the sparse map and the at least one image received from the camera; and
determining an autonomous steering action for the vehicle based on the analysis of the sparse map and the at least one image received from the camera.

18. The non-transitory computer readable medium of claim 17 , wherein the sparse map includes a polynomial representation of a target trajectory along the road segment.

19. The non-transitory computer readable medium of claim 17 , wherein the sparse map includes one or more recognized landmarks.

20. The non-transitory computer readable medium of claim 19 , wherein the recognized landmarks are spaced apart in the sparse map at a rate of no more than 0.5 per kilometer.

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

• B60W2710/20

  Steering systems · CPC title

• G01C21/14

  by recording the course traversed by the object (G01C21/16 takes precedence) · CPC title