Handling unmapped speed limit signs

Patent metadata

Field	Value
Publication number	US-12422273-B2
Application number	US-202318093611-A
Country	US
Kind code	B2
Filing date	Jan 5, 2023
Priority date	Jan 5, 2023
Publication date	Sep 23, 2025
Grant date	Sep 23, 2025

Abstract

Disclosed herein are system, method, and computer program product embodiments for handling unmapped speed limit signs. For example, the method includes receiving sensor data from a sensor of a vehicle, identifying a traffic sign within a field of view of the vehicle based on the sensor data, identifying one or more lane segments of a road associated with the identified traffic sign based on a determination that the identified traffic sign is not mapped in a priori map, and updating an attribute associated with a segment of the one or more lane segments of the road based on a determination that a detected attribute corresponding to the identified sign is more restrictive than an attribute associated with the lane segment in the a priori map.

First claim

What is claimed is:

1. A method, comprising:
identifying, using one or more computer devices, a traffic sign within a field of view of a vehicle based on the sensor data from a sensor of a vehicle;
identifying, using the one or more computer devices, one or more lane segments of a road associated with the identified traffic sign based on a determination that the identified traffic sign is not mapped in a priori map;
updating, by the one or more computer devices, an attribute associated with a segment of the one or more lane segments of the road based on a determination that a detected attribute corresponding to the identified traffic sign is more restrictive than the attribute associated with the lane segment in the a priori map;
identifying, by the one or more computer devices, a neighbor segment of a proximate lane segment and a successor segment of the proximate lane segment, wherein the proximate lane segment is within a position and an orientation threshold of the identified traffic sign, and wherein the neighbor segment and the successor segment have a same travel direction as the proximate lane segment;
updating, by the one or more computer devices, a speed limit associated with at least one of the neighbor segment or the successor segment in response to a failure to identify a mapped traffic sign associated with the neighbor segment or the successor segment; and
adjusting, by the one or more computer devices, a vehicle trajectory for the vehicle based on the identified traffic sign and a predicted action of an actor that is proximate to the vehicle, wherein the predicted action is predicted based on the identified traffic sign and the updated speed limit.

2. The method of claim 1 , further comprising:
tracking a probability distribution of a type of the identified traffic sign over time.

3. The method of claim 1 , wherein the identified traffic sign is a speed limit sign and wherein the attribute is a speed limit associated with the one or more lane segments.

4. The method of claim 1 , further comprising:
comparing data associated with the identified traffic sign with a record of false positive detections; and
disregarding the identified traffic sign based on a determination that the identified traffic sign is a false positive.

5. The method of claim 1 , further comprising:
logging an annotation for the identified traffic sign when the identified traffic sign is an unmapped sign; and
updating the a priori map based on a determination that the unmapped sign is a permanent traffic sign.

6. The method of claim 1 , further comprising:
comparing the identified traffic sign to signs in the a priori map to determine whether the identified traffic sign is mapped, wherein the identified traffic sign is mapped when a type of the identified traffic sign matches a type of a mapped sign in the a priori map and is within a position and orientation tolerance of the mapped sign.

7. The method of claim 1 , further comprising:
updating a record of false positive detections in response to determining that the identified traffic sign is a false positive detection.

8. A system, comprising:
a memory; and
at least one processor coupled to the memory and configured to:
identify a traffic sign within a field of view of a vehicle based on the sensor data from a sensor of the vehicle;
identify one or more lane segments of a road associated with the identified traffic sign based on a determination that the identified traffic sign is not mapped in a priori map;
update an attribute associated with a segment of the one or more lane segments of the road based on a determination that a detected attribute corresponding to the identified traffic sign is more restrictive than the attribute associated with a lane segment in the a priori map;
identify a neighbor segment of a proximate lane segment and a successor segment of the proximate lane segment, wherein the proximate lane segment is within a position and an orientation threshold of the identified traffic sign, and wherein the neighbor segment and the successor segment have a same travel direction as the proximate lane segment;
update a speed limit associated with at least one of the neighbor segment or the successor segment in response to a failure to identify a mapped traffic sign associated with the neighbor segment or the successor segment; and
adjust a vehicle trajectory for the vehicle based on the identified traffic sign and a predicted action of an actor that is proximate to the vehicle, wherein the predicted action is predicted based on the identified traffic sign and the updated speed limit.

9. The system of claim 8 , wherein the at least one processor is further configured to:
track a probability distribution of a type of the identified traffic sign over time.

10. The system of claim 8 , wherein the identified traffic sign is a speed limit sign and wherein the attribute is a speed limit associated with the one or more lane segments.

11. The system of claim 8 , wherein the at least one processor is further configured to:
compare data associated with the identified traffic sign with a record of false positive detections; and
disregard the identified traffic sign based on a determination that the identified traffic sign is a false positive.

12. The system of claim 8 , wherein the at least one processor is further configured to:
log an annotation for the identified traffic sign when the identified traffic sign is an unmapped sign; and
update the a priori map based on a determination that the unmapped sign is a permanent traffic sign.

13. A non-transitory computer-readable medium having instructions stored thereon that, when executed by at least one computing device, cause the at least one computing device to perform operations comprising:
identifying a traffic sign within a field of view of a vehicle based on sensor data from a sensor of the vehicle;
identifying one or more lane segments of a road associated with the identified traffic sign based on a determination that the identified traffic sign is not mapped in a priori map; and
updating an attribute associated with a segment of the one or more lane segments of the road based on a determination that a detected attribute corresponding to the identified sign is more restrictive than an attribute associated with the lane segment in the a priori map;
identifying a neighbor segment of a proximate lane segment and a successor segment of the proximate lane segment, wherein the proximate lane segment is within a position and an orientation threshold of the identified traffic sign, and wherein the neighbor segment and the successor segment have a same travel direction as the proximate lane segment;
updating a speed limit associated with at least one of the neighbor segment or the successor segment in response to a failure to identify a mapped traffic sign associated with the neighbor segment or the successor segment; and
adjusting a vehicle trajectory for the vehicle based on the identified traffic sign and a predicted action of an actor that is proximate to the vehicle, wherein the predicted action is predicted based on the identified traffic sign and the updated speed limit.

14. The non-transitory computer-readable medium of claim 13 , the operations further comprising:
tracking a probability distribution of a type of the identified traffic sign over time.

15. The non-transitory computer-readable medium of claim 13 , the operations further comprising:
comparing data associated with the identified traffic sign with a record of false positive detections; and
disregarding the identified traff

Assignees

• Argo Ai Llc
• Volkswagen Group Of America Invest Llc

Inventors

• Seegmiller Neal
• Barone Patrick
• Cai Xi
• Khurana Aman
• Jaekel Joshua
• Saranin Arsenii
• Tafish Hasan

Classifications

• G01C21/3461

  Preferred or disfavoured areas, e.g. dangerous zones, toll or emission zones, intersections, manoeuvre types or segments such as motorways, toll roads or ferries · CPC title

• G06V20/582 Primary

  of traffic signs · CPC title

• G08G1/096725

  where the received information generates an automatic action on the vehicle control · CPC title

• G08G1/096844

  where the complete route is dynamically recomputed based on new data · CPC title

• G08G1/096827

  where the route is computed onboard · CPC title