IP Library Granted Patent US 12,441,325
Granted Patent B2
US 12,441,325 · App. 17/937,931 · Granted Oct 14, 2025

Systems and methods for detecting water along driving routes

Inventors: Laura W. Shane (Park City, UT); Suzanne L. Woll (Livermore, CA)
Assignee: Kodiak Robotics, Inc.
B60W40/06G06V20/588B60W2420/408
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Quick Facts
Patent No.
US 12,441,325
App. No.
17/937,931
Granted
Oct 14, 2025
Kind
B2
Abstract

Systems and methods for determining a degree of wetness of a road surface from Light Detection and Ranging (LiDAR) point clouds are provided. The method comprises generating, using a LiDAR system, at least one point cloud, wherein the LiDAR system comprises a processor, and, using the processor, identifying and isolating one or more road surface points within a point cloud of the at least one point cloud, wherein the one or more road surface points indicate a road surface portion within an environment of the point cloud, analyzing the one or more road surface points to determine a number of the one or more road surface points that are zero intensity returns, and, based on the number of zero intensity returns, determining a degree of wetness of the road surface.

Claims (38)

1. A method for determining a degree of wetness of a road surface from Light Detection and Ranging (LiDAR) point clouds, comprising:

generating, using a LiDAR system, at least one point cloud, wherein the LiDAR system comprises a processor; and

using the processor:

identifying and isolating one or more points within the at least one point cloud that are associated with the road surface;

analyzing the identified one or more points to determine a number thereof that have zero intensity return values; and

based on the number of identified points that have zero intensity return values, determining a degree of wetness of the road surface.

2. The method of claim 1 , wherein the LiDAR system has a sensitivity of approximately 905 nm.

3. The method of claim 1 , wherein determining the degree of wetness comprises, when the number of identified points that have zero intensity return values is below a first threshold, determining that the road surface is not wet.

4. The method of claim 3 , wherein determining the degree of wetness comprises, when the number of identified points that have zero intensity return values is greater than the first threshold and below a second threshold, determining the road surface is wet with no accumulation of water along the road surface.

5. The method of claim 4 , wherein determining the degree of wetness comprises, when the number of identified points that have zero intensity return values is greater than the second threshold and less than a third threshold, determining the road surface is wet, with streaming water present.

6. The method of claim 5 , wherein determining the degree of wetness comprises, when the number of identified points that have zero intensity return values is greater than the third threshold, determining the road surface is wet, with flooding present.

7. The method of claim 1 , further comprising reducing a speed of the vehicle based on the degree of wetness of the road surface.

8. A system for determining a degree of wetness of a road surface from Light Detection and Ranging (LiDAR) point clouds, comprising:

a vehicle; and

a LiDAR system, coupled to the vehicle, the LiDAR system comprising:

one or more LiDAR sensors; and

a processor, configured to:

generate at least one point cloud;

identify and isolate one or more points within the at least one point cloud that are associated with the road surface;

analyze the identified one or more points to determine a number thereof that have zero intensity return values; and

based on the number of identified points that have zero intensity return values, determine a degree of wetness of the road surface.

9. The system of claim 8 , wherein the LiDAR system has a sensitivity of approximately 905 nm.

10. The system of claim 8 , wherein determining the degree of wetness comprises, when the number of identified points that have zero intensity return values is below a first threshold, determining that the road surface is not wet.

11. The system of claim 10 , wherein determining the degree of wetness comprises, when the number of identified points that have zero intensity return values is greater than the first threshold and below a second threshold, determining the road surface is wet with no accumulation of water along the road surface.

12. The system of claim 11 , wherein determining the degree of wetness comprises, when the number of identified points that have zero intensity return values is greater than the second threshold and less than a third threshold, determining the road surface is wet, with streaming water present.

13. The system of claim 12 , wherein determining the degree of wetness comprises, when the number of identified points that have zero intensity return values is greater than the third threshold, determining the road surface is wet, with flooding present.

14. The system of claim 8 , wherein the processor is further configured to reduce a speed of the vehicle based on the degree of wetness of the road surface.

15. A system, comprising:

at least one Light Detection and Ranging (LiDAR) system, coupled to a vehicle, configured to generate one or more point clouds of an environment; and

a computing device, comprising a processor and a memory, coupled to the vehicle, configured to store programming instructions that, when executed by the processor, cause the processor to:

identify and isolate one or more points within a point cloud of one or more point clouds that are associated with a road surface within the environment;

analyze the identified one or more points to determine a number thereof that have zero intensity return values; and

based on the number of identified points that have zero intensity return values, determine a degree of wetness of the road surface.

16. The system of claim 15 , wherein determining the degree of wetness comprises, when the number of identified points that have zero intensity return values is below a first threshold, determining that the road surface is not wet.

17. The system of claim 16 , wherein determining the degree of wetness comprises, when the number of identified points that have zero intensity return values is greater than the first threshold and below a second threshold, determining the road surface is wet with no accumulation of water along the road surface.

18. The system of claim 17 , wherein determining the degree of wetness comprises, when the number of identified points that have zero intensity return values is greater than the second threshold and less than a third threshold, determining the road surface is wet, with streaming water present.

19. The system of claim 18 , wherein determining the degree of wetness comprises, when the number of identified points that have zero intensity return values is greater than the third threshold, determining the road surface is wet, with flooding present.

20. The system of claim 15 , wherein the programming instructions are further configured, when executed by the processor, to cause the processor to reduce a speed of the vehicle based on the degree of wetness of the road surface.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 18, 2025
From: SHANE, LAURA W.; WOLL, SUZANNE L.
To: KODIAK ROBOTICS, INC.
Reel/Frame 072293/0440 →
SECURITY INTEREST Recorded Jun 12, 2024
From: KODIAK ROBOTICS, INC.
To: HORIZON TECHNOLOGY FINANCE CORPORATION
Reel/Frame 067711/0909 →
Continuity (1)
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