ACTIVE LIGHT SENSORS FOR DETERMINING EXPECTED TRACTION VALUE OF A ROAD SEGMENT

• US 20170168495A1
• Filed: 12/12/2016
• Published: 06/15/2017
• Est. Priority Date: 12/10/2015
• Status: Abandoned Application

• Current Assignee: Uatc, LLC (Uber Technologies, Inc.)
• Original Assignee: Uber Technologies, Inc.
• Inventors: Wood, Matthew, Rander, Peter, Vandenberg, Dirk, Bradley, David McAllister
• Application Number:
  US15/376,592
• Publication Number:
  US 20170168495A1
• Time in Patent Office: Days
• CPC Class Codes: B60W 10/184 with wheel brakes
• CPC Class Codes: B60W 10/20 including control of steering systems
• CPC Class Codes: B60W 2420/408 Radar; Laser, e.g. lidar
• CPC Class Codes: B60W 2555/20 Ambient conditions, e.g. wind or rain
• CPC Class Codes: B60W 2710/182 Brake pressure, e.g. of fluid or between pad and disc
• CPC Class Codes: B60W 2710/207 Steering angle of wheels
• CPC Class Codes: B60W 2720/10 Longitudinal speed
• CPC Class Codes: B60W 30/18172 Preventing, or responsive to skidding of wheels
• CPC Class Codes: B60W 40/068 Road friction coefficient
• CPC Class Codes: G01N 2021/1793 Remote sensing
• CPC Class Codes: G01N 2033/1873 ice or snow
• CPC Class Codes: G01N 21/4738 Diffuse reflection precedence is given to G01N21/55 - G01N21/57 if specular component is taken into consideration, e.g. also for testing fluids, fibrous materials
• CPC Class Codes: G01N 33/18 Water

Abstract

A system and method to control a vehicle, provides for directing light onto a region of a road surface on which the vehicle is moving. A variation in a characteristic of a reflection of the directed light is determined. Accumulated precipitation is detected on at least the region of the road based on the determined variation.

Claims

1. A method for operating a vehicle, the method comprising:

directing light onto a region of a road surface on which the vehicle is moving;

determining, over the region of the road surface, a variation in a characteristic of a reflection of the directed light; and

detecting accumulated precipitation on at least the region of the road surface based on the determined variation.

2. The method of claim 1, wherein the signal characteristic includes at least one of an intensity or power of the reflection.

3. The method of claim 1, wherein directing light onto the region includes controlling a LiDar device that directs a laser onto the road surface.

4. The method of claim 3, wherein detecting accumulated precipitation is performed using a LiDar device that is mounted on the vehicle to detect both accumulated precipitation and objects on the roadway.

5. The method of claim 1, further comprising:

classifying the accumulated precipitation based on the variation in the characteristic of the reflection.

6. The method of claim 5, wherein classifying the accumulated precipitation includes estimating a coefficient of friction for a portion of the roadway on which the accumulated precipitation is detected.

7. The method of claim 5, wherein classifying the accumulated precipitation includes classifying the precipitation as one of snow, ice, or water.

8. The method of claim 5, wherein classifying the accumulated precipitation includes determining elevation of accumulated snow on the roadway.

9. The method of claim 1, further comprising selecting one or more vehicle operations in response to detecting the accumulated precipitation.

10. The method of claim 8, wherein the selected one or more operations includes steering the vehicle to avoid the region of the road surface.

11. The method of claim 8, wherein the selected one or more operations includes slowing the vehicle in advance of reaching the region of the vehicle.

12. The method of claim 1, further comprising:

estimating a traction value of the region of the roadway based on the detected accumulated precipitation;

measuring, as the vehicle travels over the region of the roadway, one or more sensor values that correlate to the traction value on the roadway; and

comparing the estimated traction value to the traction value that is correlated from the measured one or more sensor values.

13. The method of claim 12, wherein estimating the traction value of the region of the roadway includes implementing a model to determine the traction.

14. The method of claim 13, further comprising training the model based on comparing the estimated traction value to the traction value that is correlated from the measured one or more sensor values.

15. A control system for a vehicle, the control system comprising:

a memory to store a set of instructions;

one or more processors to execute instructions stored in memory to;

direct light onto a region of a road surface on which the vehicle is moving;

determine, over the region of the road surface, a variation in a characteristic of a reflection of the directed light; and

detect accumulated precipitation on at least the region of the road surface based on the determined variation.

16. The control system of claim 15, wherein the signal characteristic includes at least one of an intensity or power of the reflection.

17. The control system of claim 15, wherein the signal characteristic includes at least one of an intensity or power of the reflection.

18. The control system of claim 15, wherein directing light onto the region includes controlling a LiDar device that directs a laser onto the road surface.

19. The control system of claim 15, further comprising a LiDar to provide the directed light, wherein the processor determines a variation in an intensity or power of a return reflection of the directed light.

20. The control system of claim 19, wherein the one or more processors classify the accumulated precipitation based on the return reflection of the directed light from the LiDar.