Sinkhole detection systems and methods

• US 10,372,128 B2
• Filed: 11/21/2016
• Issued: 08/06/2019
• Est. Priority Date: 11/21/2016
• Status: Active Grant

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: Myers, Scott Vincent, Micks, Ashley Elizabeth, Gurghian, Alexandru Mihai, Banvait, Harpreetsingh, Mahmoudieh, Parsa
• Primary Examiner(s): Goldman, Richard A
• Application Number:
  US15/357,980
• Publication Number:
  US 20180143631A1
• Time in Patent Office: 988 Days
• Field of Search: 701 23, 701 41, 701 37, 701 40, 701532, 382224
• CPC Class Codes: B60W 30/00 Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
• CPC Class Codes: G01S 13/867 Combination of radar systems with cameras
• CPC Class Codes: G01S 13/87 Combinations of radar systems, e.g. primary radar and secondary radar
• CPC Class Codes: G01S 13/931 of land vehicles
• CPC Class Codes: G01S 15/86 Combinations of sonar systems with lidar systems; Combinations of sonar systems with systems not using wave reflection
• CPC Class Codes: G01S 15/931 of land vehicles
• 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 2013/9323 Alternative operation using light waves
• CPC Class Codes: G01S 2013/9324 Alternative operation using ultrasonic waves
• CPC Class Codes: G01S 2013/93271 in the front of the vehicles
• CPC Class Codes: G01S 7/41 using analysis of echo signal for target characterisation; Target signature; Target cross-section
• CPC Class Codes: G01S 7/4808 Evaluating distance, position or velocity data
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G06F 18/25 Fusion techniques
• CPC Class Codes: G06V 10/80 Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level multimodal speaker identification or verification G10L17/10
• CPC Class Codes: G06V 20/56 exterior to a vehicle by using sensors mounted on the vehicle
• CPC Class Codes: G08G 1/09626 where the origin of the information is within the own vehicle, e.g. a local storage device, digital map
• CPC Class Codes: G08G 1/0967 Systems involving transmission of highway information, e.g. weather, speed limits transmission of navigation instructions to the vehicle G08G1/0968
• CPC Class Codes: G08G 1/096791 where the origin of the information is another vehicle
• CPC Class Codes: G08G 1/162 : event-triggered
• CPC Class Codes: G08G 1/167 : Driving aids for lane monitoring, lane changing, e.g. blind spot detection

Abstract

Example sinkhole detection systems and methods are described. In one implementation, a method receives data from multiple sensors mounted to a vehicle and analyzes the received data to identify a sinkhole in a roadway ahead of the vehicle. If a sinkhole is identified, the method adjusts vehicle operations and reports the sinkhole to a shared database and/or another vehicle.

Claims

1. A method comprising:

receiving data from a plurality of sensors mounted to a vehicle;

analyzing, using one or more processors, the received data to identify a sinkhole in a roadway ahead of the vehicle; and

responsive to identification of a sinkhole in the roadway;

adjusting vehicle operations; and

reporting the sinkhole to at least one of a shared database and another vehicle;

wherein analyzing the received data to identify a sinkhole in the roadway includes;

receiving drive history data describing the roadway ahead of the vehicle, the drive history data including a road elevation for the roadway ahead of the vehicle;

determining an actual elevation of a second vehicle on the roadway ahead of the vehicle; and

detecting a difference between the actual elevation and the road elevation;

in response to detecting a difference between the actual elevation and the road elevation, identifying the sinkhole in the roadway ahead of the vehicle.

2. The method of claim 1, wherein the plurality of sensors include one or more of a Lidar sensor, a radar sensor, and a camera.

3. The method of claim 1, further comprising fusing the data received from the plurality of vehicle sensors.

4. The method of claim 1, wherein analyzing the received data to identify a sinkhole in the roadway includes detecting an area in the roadway that does not return Lidar ground plane points.

5. The method of claim 1, wherein analyzing the received data to identify a sinkhole in the roadway includes detecting an area in data from a camera that does not indicate a roadway surface.

6. The method of claim 1, wherein analyzing the received data to identify a sinkhole in the roadway includes detecting a descent of another vehicle with respect to the roadway.

7. The method of claim 1, wherein analyzing the received data to identify a sinkhole in the roadway includes detecting a rise of a back of another vehicle with respect to the roadway.

8. The method of claim 1, wherein reporting the sinkhole to another vehicle includes communicating with the another vehicle using vehicle-to-vehicle communications.

9. The method of claim 1, wherein adjusting vehicle operations includes stopping the vehicle or maneuvering around the sinkhole.

10. The method of claim 1, wherein the vehicle is an autonomous vehicle.

11. A method comprising:

receiving data from a plurality of sensors mounted to a first vehicle;

analyzing, using one or more processors, the received data to identify movement of a second vehicle in a roadway ahead of the first vehicle; and

responsive to identification of movement of the second vehicle;

determining the existence of a sinkhole in the roadway ahead of the first vehicle;

adjusting operation of the first vehicle; and

reporting the sinkhole to at least one of a shared database and another vehicle;

wherein determining the existence of the sinkhole in the roadway ahead of the first vehicle comprises;

receiving drive history data describing the roadway ahead of the vehicle, the drive history data including a road elevation for the roadway ahead of the vehicle;

determine an actual elevation of a second vehicle on the roadway ahead of the vehicle according to the received data from the plurality of sensors; and

detecting a difference between the actual elevation and the road elevation for the roadway ahead of the vehicle; and

in response to detecting the difference is detected between the actual elevation and the road surface height, determining that the sinkhole is in the roadway ahead of the vehicle.

12. The method of claim 11, wherein the plurality of sensors include one or more of a Lidar sensor, a radar sensor, and a camera.

13. The method of claim 11, wherein identifying the movement of the second vehicle includes identifying a descent of the second vehicle with respect to the roadway surface.

14. The method of claim 11, wherein identifying the movement of the second vehicle includes a rise of the back of the second vehicle with respect to the roadway surface.

15. The method of claim 11, wherein reporting the sinkhole to another vehicle includes communicating with the another vehicle using vehicle-to-vehicle communications.

16. The method of claim 11, wherein adjusting operation of the first vehicle includes stopping the first vehicle or maneuvering the first vehicle around the sinkhole.

17. An apparatus comprising:

a plurality of sensors mounted to a vehicle and configured to capture sensor data;

a plurality of vehicle control actuators configured to adjust operation of the vehicle; and

a sinkhole detection system coupled to the plurality of sensors and the plurality of vehicle control actuators, the sinkhole detection system configured to receive and analyze the sensor data to identify a sinkhole in a roadway ahead of the vehicle, the sinkhole detection further configured, responsive to identification of a sinkhole in the roadway, to;

adjust vehicle operations using the plurality of vehicle control actuators; and

report the sinkhole to at least one of a shared database and another vehicle;

wherein the sinkhole detection system is programmed to;

receive drive history data describing the roadway ahead of the vehicle, the drive history data including a road elevation for the roadway ahead of the vehicle;

determine an actual elevation of the roadway ahead of the vehicle according to the sensor data; and

if a difference is detected between the actual elevation and the road elevation, identify the sinkhole in the roadway ahead of the vehicle.

18. The apparatus of claim 17, wherein the plurality of sensors include one or more of a Lidar sensor, a radar sensor, and a camera.