Vehicle reflection identification

Patent metadata

Field	Value
Publication number	US-12306339-B2
Application number	US-202318349203-A
Country	US
Kind code	B2
Filing date	Jul 10, 2023
Priority date	Jul 10, 2023
Publication date	May 20, 2025
Grant date	May 20, 2025

Abstract

A computer includes a processor and a memory, and the memory stores instructions executable by the processor to determine a value over time derived from a region of sensor data from an optical sensor of a host vehicle; determine that the value over time matches a stored temporal pattern; upon determining that the value over time matches the stored temporal pattern, classify an object at the region as a surface reflecting a signal from an illuminator of an origin vehicle; and actuate a component of the host vehicle based on a classification of the object at the region.

First claim

What is claimed is:

1. A computer comprising a processor and a memory, the memory storing instructions executable by the processor to:
determine a value over time derived from a region of sensor data from an optical sensor of a host vehicle;
determine that the value over time matches a stored temporal pattern, the stored temporal pattern being an encoding in a signal from an illuminator of an origin vehicle;
upon determining that the value over time matches the stored temporal pattern, classify an object at the region as a surface reflecting the signal from the illuminator of the origin vehicle; and
actuate a component of the host vehicle based on a classification of the object at the region.

2. The computer of claim 1 , wherein the origin vehicle is the host vehicle, and the instructions further include instructions to instruct the illuminator to illuminate according to the stored temporal pattern.

3. The computer of claim 1 , wherein the stored temporal pattern is a visible light communication (VLC) signal.

4. The computer of claim 3 , wherein the VLC signal is a pulse-based transmission.

5. The computer of claim 1 , wherein the instructions further include instructions to identify a potential vehicle in the sensor data, the region being part of the potential vehicle.

6. The computer of claim 5 , wherein the instructions further include instructions to, upon determining that the value over time matches the stored temporal pattern, classify the potential vehicle as a nonvehicle.

7. The computer of claim 5 , wherein the instructions further include instructions to, upon determining that the value over time does not match the stored temporal pattern, classify the potential vehicle as a vehicle.

8. The computer of claim 5 , wherein the instructions further include instructions to identify a light source of the potential vehicle, the region corresponding to the light source.

9. The computer of claim 8 , wherein the instructions further include instructions to, upon determining that the value over time derived from a second region of the sensor data matches the stored temporal pattern, refrain from classifying the potential vehicle as a nonvehicle, the second region corresponding to a portion of the potential vehicle other than the light source.

10. The computer of claim 1 , wherein the instructions further include instructions to determine a phase offset between the value over time and the stored temporal pattern.

11. The computer of claim 10 , wherein the instructions further include instructions to determine a distance to the surface based on the phase offset.

12. The computer of claim 1 , wherein the instructions further include instructions to determine that the value over time includes multiple matches of the stored temporal pattern, and upon determining that the value over time includes multiple matches of the stored temporal pattern, filter out one match of the stored temporal pattern from the value over time.

13. The computer of claim 12 , wherein the instructions further include instructions to determine phase offsets of the matches, and select one match of the matches to filter out based on the phase offsets.

14. The computer of claim 1 , wherein the value over time is an intensity value.

15. The computer of claim 1 , wherein the optical sensor is a camera.

16. The computer of claim 1 , wherein the origin vehicle is the host vehicle, and the illuminator is incorporated into the optical sensor.

17. The computer of claim 16 , wherein the optical sensor is one of a lidar or a radar.

18. The computer of claim 1 , wherein the origin vehicle is the host vehicle, and the illuminator is at least one of a headlight, a daytime running light, a taillight, or a turn signal of the host vehicle.

19. The computer of claim 1 , wherein the component of the host vehicle includes at least one of a brake system or a steering system.

20. A method comprising:
determining a value over time derived from a region of sensor data from an optical sensor of a host vehicle;
determining that the value over time matches a stored temporal pattern, the stored temporal pattern being an encoding in a signal from an illuminator of an origin vehicle;
upon determining that the value over time matches the stored temporal pattern, classifying an object at the region as a surface reflecting the signal from the illuminator of the origin vehicle; and
actuating a component of the host vehicle based on a classification of the object at the region.

Assignees

• Ford Global Tech Llc

Inventors

• Herman david michael

Classifications

• B60Q1/346

  with automatic actuation · CPC title

• B60T7/12 Primary

  for automatic initiation; for initiation not subject to will of driver or passenger {(limiting speed of vehicles other than rail vehicles B60K31/00)} · CPC title

• B62D15/026

  combined with automatic distance control, i.e. electronic tow bar · CPC title

• B60Q1/30

  for indicating rear of vehicle, e.g. by means of reflecting surfaces · CPC title

• B60Q2300/40

  Indexing codes relating to other road users or special conditions · CPC title