Methods and systems for detecting weather conditions including wet surfaces using vehicle onboard sensors

• US 9,207,323 B2
• Filed: 04/11/2013
• Issued: 12/08/2015
• Est. Priority Date: 04/11/2013
• Status: Active Grant

• Current Assignee: Waymo LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Zhu, Jiajun, Dolgov, Dmitri, Ferguson, Dave
• Primary Examiner(s): Alsomiri, Isam
• Assistant Examiner(s): Abraham, Samantha K
• Application Number:
  US13/860,664
• Publication Number:
  US 20140307247A1
• Time in Patent Office: 971 Days
• Field of Search: 356/4.01, 356/4.07, 356/5.01, 356/3.01
• US Class Current: 1/1
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• 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 2556/55 using telemetry
• CPC Class Codes: B60W 40/064 Degree of grip
• CPC Class Codes: B60W 60/0053 from vehicle to occupant
• CPC Class Codes: G01S 13/66 Radar-tracking systems; Analogous systems
• CPC Class Codes: G01S 13/865 Combination of radar systems with lidar systems
• CPC Class Codes: G01S 13/867 Combination of radar systems with cameras
• CPC Class Codes: G01S 13/931 of land vehicles
• CPC Class Codes: G01S 17/66 Tracking systems using electromagnetic waves other than radio waves
• CPC Class Codes: G01S 17/86 Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
• CPC Class Codes: G01S 17/931 of land vehicles
• CPC Class Codes: G01S 17/95 for meteorological use
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

Example methods and systems for detecting weather conditions including wet surfaces using vehicle onboard sensors are provided. An example method includes receiving laser data collected for an environment of a vehicle. The method also includes determining laser data points that are associated with one or more objects in the environment, and based on laser data points being unassociated with the one or more objects in the environment, identifying an indication that a surface on which the vehicle travels is wet. The method may further include receiving radar data collected for the environment of the vehicle that is indicative of a presence of the one or more objects in the environment of the vehicle, and identifying the indication that the surface on which the vehicle travels is wet further based on laser data points being unassociated with the one or more objects in the environment indicated by the radar data.

Claims

1. A method comprising:

receiving laser data collected for an environment of a vehicle, wherein the laser data includes a plurality of laser data points;

receiving radar data collected for the environment of the vehicle, wherein the radar data is indicative of a presence of one or more tracked objects in the environment of the vehicle;

determining, by a computing device, laser data points of the plurality of laser data points that are associated with the one or more tracked objects in the environment indicated by the radar data;

determining, by the computing device, laser data points of the plurality of laser data points that are unassociated with the one or more tracked objects in the environment indicated by radar data; and

identifying by the computing device an indication that a surface on which the vehicle travels is wet based at least on the determining that the laser data points that are unassociated with the one or more tracked objects in the environment indicated by the radar data.

2. The method of claim 1, further comprising:

determining a speed of the vehicle, and

wherein identifying by the computing device the indication that the surface on which the vehicle travels is wet is further based on the speed of the vehicle being above a threshold.

3. The method of claim 1, wherein the vehicle is travelling along a roadway, and the method further comprises:

determining a speed of a given vehicle that is substantially in front of the vehicle; and

determining that laser data points which are unassociated with the one or more tracked objects in the environment are collected for an area of the environment substantially in front of the vehicle; and

wherein identifying by the computing device the indication that the surface on which the vehicle travels is wet is further based on the speed of the given vehicle that is substantially in front of the vehicle being above a threshold.

4. The method of claim 1, wherein the vehicle is configured to operate in an autonomous mode, and the method further comprises based on the indication that the surface on which the vehicle travels is wet, determining a driving decision for the vehicle.

5. The method of claim 1, wherein the vehicle is configured to operate in an autonomous mode, and the method further comprises based on the indication that the surface on which the vehicle travels is wet, providing instructions to indicate a request to transition to a manual mode.

6. The method of claim 1, wherein:

receiving radar data collected for the environment of the vehicle comprises receiving the radar data from a radar sensor coupled to the vehicle; and

receiving laser data collected for the environment of the vehicle comprises receiving the laser data from a laser sensor coupled to the vehicle.

7. The method of claim 1, further comprising:

determining that a number of laser data points of the plurality of laser data points are associated with a location below an expected elevation of the surface on which the vehicle travels; and

wherein identifying by the computing device the indication that the surface on which the vehicle travels is wet is further based on the number of laser data points being above a threshold number.

8. The method of claim 1, further comprising:

receiving precipitation data from a precipitation sensor associated with the vehicle; and

identifying a second indication that the roadway is wet based on the precipitation data.

9. The method of claim 1, further comprising:

receiving weather information for a location of the vehicle from a server over a network; and

identifying a second indication that the roadway is wet based on the weather information.

10. The method of claim 1, further comprising:

determining a location of the vehicle;

determining a distribution of expected values of laser data for the surface on which the vehicle travels for dry conditions based on the location of the vehicle;

comparing the determined distribution to the laser data collected for the environment of the vehicle; and

based on a difference between the determined distribution and the laser data collected for the environment of the vehicle being above a threshold, identifying by the computing device a second indication that the surface on which the vehicle travels is wet.

11. The method of claim 10, wherein the distribution of expected values of laser data is based on a composition of the surface.

12. The method of claim 1, further comprising:

determining laser data points of the plurality of laser data points that are indicative of lane markers in the environment of the vehicle; and

based on a number of the lane markers indicated by the laser data points being below an expected amount, identifying by the computing device a second indication that the surface on which the vehicle travels is wet.

13. The method of claim 1, further comprising:

receiving image data collected for the environment of the vehicle;

determining an amount of the image data being indicative of reflections of the one or more tracked objects in the environment of the vehicle; and

based on the amount of the image data being indicative of reflections of the one or more tracked objects in the environment of the vehicle being above a threshold, identifying by the computing device a second indication that the surface on which the vehicle travels is wet.

14. The method of claim 1, further comprising:

receiving images captured from a camera coupled to the vehicle; and

identifying an additional indication that the roadway is wet based on the images.

15. A non-transitory computer readable storage medium having stored therein instructions, that when executed by a computing device, cause the computing device to perform functions comprising:

receiving laser data collected for an environment of a vehicle, wherein the laser data includes a plurality of laser data points;

receiving radar data collected for the environment of the vehicle, wherein the radar data is indicative of a presence of one or more tracked objects in the environment of the vehicle;

determining laser data points of the plurality of laser data points that are associated with the one or more tracked objects in the environment indicated by the radar data;

determining laser data points of the plurality of laser data points that are unassociated with the one or more tracked objects in the environment indicated by the radar data; and

identifying an indication that a surface on which the vehicle travels is wet based at least on the determining that the laser data points that are unassociated with the one or more tracked objects in the environment indicated by the radar data;

based on the indication that the surface on which the vehicle travels is wet, determining a driving decision for the vehicle; and

providing instructions to the vehicle of the determined driving decision.

16. The non-transitory computer readable storage medium of claim 15, wherein the functions further comprise:

determining a speed of the vehicle, and

wherein identifying the indication that the surface on which the vehicle travels is wet is further based on the speed of the vehicle being above a threshold.

17. A system, comprising:

at least one processor; and

data storage comprising instructions executable by the at least one processor to cause the system to perform functions comprising;

receiving laser data collected for an environment of a vehicle, wherein the laser data includes a plurality of laser data points;

receiving radar data collected for the environment of the vehicle, wherein the radar data is indicative of a presence of one or more tracked objects in the environment of the vehicle;

determining laser data points of the plurality of laser data points that are associated with the one or more tracked objects in the environment indicated by the radar data;

determining laser data points of the plurality of laser data points that are unassociated with the one or more tracked objects in the environment indicated by the radar data; and

identifying by the computing device an indication that a surface on which the vehicle travels is wet based at least on the determining that the laser data points that are unassociated with the one or more tracked objects in the environment indicated by the radar data;

based on the indication that the surface on which the vehicle travels is wet, determining a driving decision for the vehicle; and

providing instructions to the vehicle of the determined driving decision.

18. The system of claim 17, wherein the vehicle is travelling along a roadway, and the functions further comprise:

determining a speed of a given vehicle that is substantially in front of the vehicle;

determining that laser data points which are unassociated with the one or more tracked objects in the environment are collected for an area of the environment substantially in front of the vehicle; and

wherein identifying the indication that the surface on which the vehicle travels is wet is further based on the speed of the given vehicle that is substantially in front of the vehicle being above a threshold.