OPTICAL ROUTE EXAMINATION SYSTEM AND METHOD

• US 20150269722A1
• Filed: 09/08/2014
• Published: 09/24/2015
• Est. Priority Date: 03/18/2014
• Status: Abandoned Application

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Naithani, Nidhi, Rao, Dattaraj Jagdish, Nelson, Scott Daniel, Naphade, Nikhil Uday
• Application Number:
  US14/479,847
• Publication Number:
  US 20150269722A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06T 2207/30108 Industrial image inspection
• CPC Class Codes: G06T 2207/30256 Lane; Road marking
• CPC Class Codes: G06T 7/0004 Industrial image inspection
• CPC Class Codes: G06V 20/588 Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road

Abstract

Optical route examination systems and methods described herein obtain image data of a field of view of a camera disposed onboard a first vehicle as the first vehicle moves along a first route, and autonomously examine the image data onboard the first vehicle to identify one or more of a feature of interest or a designated object.

Claims

1. A method comprising:

obtaining image data of a field of view of a camera disposed onboard a first vehicle as the first vehicle moves along a first route; and

autonomously examining the image data onboard the first vehicle to identify one or more of a feature of interest or a designated object.

2. The method of claim 1, wherein the feature of interest is a gauge distance between two or more portions of the first route, and autonomously examining the image data includes determining one or more changes in the gauge distance.

3. The method of claim 2, further comprising identifying a segment of the first route as being damaged responsive to the one or more changes in the gauge distance indicating one or more of:

an increasing trend and a decreasing trend subsequent to the increasing trend, or

the decreasing trend and the increasing trend subsequent to the decreasing trend.

4. The method of claim 3, wherein the segment of the first route is identified as being damaged responsive to the increasing trend occurring over at least one or more of a first designated time or a first designated distance and the decreasing trend also occurring over at least one or more of a second designated time or a second designated distance.

5. The method of claim 4, wherein the segment of the first route is identified as being damaged responsive to the one or more of the first designated time or distance and the one or more of the second designated time or distance being within at least one of an outer designated time limit or an outer designated distance limit.

6. The method of claim 1, wherein the designated object is a sign, and further comprising:

determining a location of the sign; and

autonomously examining the image data to determine information displayed on the sign.

7. The method of claim 6, further comprising storing the location of the sign and the information displayed on the sign in a memory structure configured to be used by at least one of the first vehicle or one or more second vehicles to automatically control operations of the at least one of the first vehicle or the one or more second vehicles.

8. The method of claim 1, wherein the designated object is a wayside asset, and autonomously examining the image data includes determining that the wayside asset is one or more of damaged, missing, or malfunctioning based at least in part on the image data.

9. The method of claim 1, wherein the designated object is safety equipment located at a crossing between the first route being traveled by the first vehicle and a second route, and autonomously examining the image data includes determining that one or more of:

a gate of the safety equipment has not moved to block movement of one or more second vehicles through the crossing along the second route, or a light signal of the safety equipment is not activated, or a sign of the safety equipment is at least one of missing or damaged.

10. A system comprising:

one or more image analysis processors configured to be disposed onboard a first vehicle as the first vehicle moves along a first route, the one or more image analysis processors also configured to obtain image data of a field of view of a camera disposed onboard the first vehicle and to autonomously examine the image data onboard the first vehicle to identify one or more of a feature of interest or a designated object.

11. The system of claim 10, wherein the feature of interest is a gauge distance between two or more portions of the first route, and the one or more image analysis processors are configured to autonomously determine one or more changes in the gauge distance.

12. The system of claim 11, wherein the one or more image analysis processors are configured to identify a segment of the first route as being damaged responsive to the one or more changes in the gauge distance indicating one or more of:

an increasing trend and a decreasing trend subsequent to the increasing trend, or

the decreasing trend and the increasing trend subsequent to the decreasing trend.

13. The system of claim 12, wherein the one or more image analysis processors are configured to identify the segment of the first route as being damaged responsive to the increasing trend occurring over at least one or more of a first designated time or a first designated distance and the decreasing trend also occurring over at least one or more of a second designated time or a second designated distance.

14. The system of claim 13, wherein the one or more image analysis processors are configured to identify the segment of the first route as being damaged responsive to the one or more of the first designated time or distance and the one or more of the second designated time or distance being within at least one of an outer designated time limit or an outer designated distance limit.

15. The system of claim 10, wherein the designated object is a sign, and the one or more image analysis processors are configured to determine a location of the sign, autonomously examine the image data to determine information displayed on the sign, and store the location of the sign and the information displayed on the sign in a memory structure configured to be used by at least one of the first vehicle or one or more second vehicles to automatically control operations of the at least one of the first vehicle or the one or more second vehicles.

16. The system of claim 10, wherein the designated object is a wayside asset, and the one or more image analysis processors are configured to autonomously determine that the wayside asset is one or more of damaged, missing, or malfunctioning based at least in part on the image data.

17. The system of claim 10, wherein the designated object is safety equipment located at a crossing between the first route being traveled by the first vehicle and a second route, and the one or more image analysis processors are configured to autonomously determine that one or more of:

a gate of the safety equipment has not moved to block movement of one or more second vehicles through the crossing along the second route, or a light signal of the safety equipment is not activated, or a sign of the safety equipment is at least one of missing or damaged.

18. A method comprising:

examining image data of a track having plural rails, the image data obtained from a camera onboard a vehicle moving along the track;

determining gauge distances of the track based at least in part on the image data; and

identifying a segment of the track as having one or more damaged rails based on trends in the gauge distances of the track.

19. The method of claim 18, wherein identifying the segment of the track as having one or more damaged rails includes identifying a first trend in the gauge distances and an opposite second trend in the gauge distances subsequent to the first trend.

20. The method of claim 19, wherein identifying the segment of the track as having one or more damaged rails occurs responsive to determining that the first trend and the second trend each occur over at least one or more of a designated time or distance.