Methods and systems for high definition map generation

Patent metadata

Field	Value
Publication number	US-12422274-B2
Application number	US-202318296842-A
Country	US
Kind code	B2
Filing date	Apr 6, 2023
Priority date	Apr 6, 2023
Publication date	Sep 23, 2025
Grant date	Sep 23, 2025

Abstract

Disclosed herein are methods and systems (sensors) that allow revision of HD maps for lane lines as the lane lines are created. In a non-limiting example, a method comprises receiving, by a processor from a sensor associated with a vehicle configured to paint a lane line, a color attribute, a patterns attribute, and a location of a lane line painted on a road by the vehicle; determining, by the processor, using the location received from the sensor, whether the road has an existing lane line; and revising, by the processor, a high definition map associated with at least one autonomous vehicle by removing the existing lane line from the high definition map and inserting the lane line in the high definition map.

First claim

What is claimed is:

1. A method comprising:
receiving, by a processor from a sensor associated with a vehicle configured to paint a lane line, a color attribute, a pattern attribute, and a location of the lane line painted on a road by the vehicle;
determining, by the processor, using the location received, whether the road has an existing lane line;
revising, in real-time, by the processor, a high-definition digital map associated with at least one autonomous vehicle by removing the existing lane line from the high-definition digital map and inserting the lane line in the high-definition digital map at the time of line painting to enable real-time updates to the high-definition digital map; and
transmitting, by the processor, instructions to an autonomy computing system of an autonomous vehicle to change to a revised high-definition digital map, wherein the autonomy computing system is configured to control operation of the autonomous vehicle to navigate according to the revised high-definition digital map.

2. The method according to claim 1 , wherein the location is received from a second sensor associated with the vehicle.

3. The method according to claim 2 , wherein the location is received by the processor in real-time as the lane line is painted on the road.

4. The method according to claim 1 , wherein the sensor monitors a paint reservoir associated with the vehicle.

5. The method according to claim 1 , further comprising:
displaying, by the processor, a representation of the high-definition digital map.

6. The method according to claim 1 , further comprising:
transmitting, by the processor, the revised high-definition digital map to a second processor.

7. The method according to claim 1 , wherein the pattern attribute indicates whether the lane line is solid or dashed.

8. A system comprising:
a non-transitory computer readable medium containing instructions that are executed by at least one processor configured to:
receive, from a sensor associated with a vehicle configured to paint a lane line, a color attribute, a pattern attribute, and a location of the lane line painted on a road by the vehicle;
determine using the location received, whether the road has an existing lane line;
revise, in real time, a high-definition digital map associated with at least one autonomous vehicle by removing the existing lane line from the high-definition digital map and inserting the lane line in the high-definition digital map at the time of line painting to enable real-time updates to the high-definition digital map; and
transmit, by the at least one processor, instructions to an autonomy computing system of an autonomous vehicle to change to a revised high-definition digital map, wherein the autonomy computing system is configured to control operation of the autonomous vehicle to navigate according to the revised high-definition digital map.

9. The system according to claim 8 , wherein the location is received from a second sensor associated with the vehicle.

10. The system according to claim 9 , wherein the location is received by the at least one processor in real-time as the lane line is painted on the road.

11. The system according to claim 8 , wherein the sensor monitors a paint reservoir associated with the vehicle.

12. The system according to claim 8 , wherein the instructions further cause the at least one processor to:
display a representation of the high-definition digital map.

13. The system according to claim 8 , wherein the instructions further cause the at least one processor to:
transmit the revised high-definition digital map to a second processor.

14. The system according to claim 8 , wherein the pattern attribute indicates whether the lane line is solid or dashed.

15. A method comprising:
monitoring, in real-time, by at least one processor from a sensor, a color value, a pattern attribute, and a location of a lane line painted on a road by a vehicle at the time of line painting;
transmitting, by the at least one processor, the color value, the pattern attribute, and the location of the lane line to a second processor, whereby the at least one processor revises, in real-time, a high-definition digital map based on received data from the sensor at the time of line painting to enable real-time updates to the high-definition digital map; and
transmitting, by the at least one processor, instructions to an autonomy computing system of an autonomous vehicle to change to a revised high-definition digital map, wherein the autonomy computing system is configured to control operation of the autonomous vehicle to navigate according to the revised high-definition digital map.

16. The method according to claim 15 , wherein the pattern attribute indicates whether the lane line is solid or dashed.

17. The method according to claim 15 , wherein the location is monitored in real-time as the lane line is painted on the road.

18. The method according to claim 15 , wherein the second processor uses the color value, the pattern attribute, and the location of the lane line to update the high-definition digital map in real time.

Assignees

• Torc Robotics Inc

Inventors

• Chilton Ryan

Classifications

• G01C21/3848

  Data obtained from both position sensors and additional sensors · CPC title

• E01C23/222 Primary

  specially adapted for automatic spraying of interrupted, individual or variable markings · CPC title

• G01C21/3815 Primary

  Road data · CPC title