US20150235094A1 - Vehicle imaging system and method - Google Patents

Vehicle imaging system and method Download PDF

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Publication number
US20150235094A1
US20150235094A1 US14457353 US201414457353A US2015235094A1 US 20150235094 A1 US20150235094 A1 US 20150235094A1 US 14457353 US14457353 US 14457353 US 201414457353 A US201414457353 A US 201414457353A US 2015235094 A1 US2015235094 A1 US 2015235094A1
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Prior art keywords
image data
route
condition
wayside
wayside devices
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Pending
Application number
US14457353
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Mark Bradshaw Kraeling
Matthew Lawrence Blair
Shannon Joseph Clouse
Scott Daniel Nelson
Nidhi Naithani
Dattaraj Jagdish Rao
Anwarul Azam
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General Electric Co
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General Electric Co
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    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00791Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes
    • G06K9/00805Detecting potential obstacles
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60RVEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R1/00Optical viewing arrangements
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B61RAILWAYS
    • B61LGUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L23/00Control, warning, or like safety means along the route or between vehicles or vehicle trains
    • B61L23/04Control, warning, or like safety means along the route or between vehicles or vehicle trains for monitoring the mechanical state of the route
    • B61L23/042Track changes detection
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B61RAILWAYS
    • B61LGUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L23/00Control, warning, or like safety means along the route or between vehicles or vehicle trains
    • B61L23/04Control, warning, or like safety means along the route or between vehicles or vehicle trains for monitoring the mechanical state of the route
    • B61L23/042Track changes detection
    • B61L23/047Track or rail movements
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00442Document analysis and understanding; Document recognition
    • G06K9/00476Reading or recognising technical drawings or geographical maps
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00791Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N5/00Details of television systems
    • H04N5/222Studio circuitry; Studio devices; Studio equipment ; Cameras comprising an electronic image sensor, e.g. digital cameras, video cameras, TV cameras, video cameras, camcorders, webcams, camera modules for embedding in other devices, e.g. mobile phones, computers or vehicles
    • H04N5/225Television cameras ; Cameras comprising an electronic image sensor, e.g. digital cameras, video cameras, camcorders, webcams, camera modules specially adapted for being embedded in other devices, e.g. mobile phones, computers or vehicles
    • H04N5/2251Constructional details
    • H04N5/2254Mounting of optical parts, e.g. lenses, shutters, filters or optical parts peculiar to the presence or use of an electronic image sensor
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N7/00Television systems
    • H04N7/18Closed circuit television systems, i.e. systems in which the signal is not broadcast
    • H04N7/181Closed circuit television systems, i.e. systems in which the signal is not broadcast for receiving images from a plurality of remote sources

Abstract

An imaging system and method generate image data within a field of view that includes a cab of the vehicle and a portion of a route being traveled on and/or wayside devices disposed along the route. The cab includes a space where an operator of the vehicle is located. The image data generated by the camera is examined to identify route damage, a deteriorating condition of the route, and/or a condition of the wayside devices. The condition of the wayside devices can include damage to the wayside devices, a missing wayside device, deterioration of the wayside devices, or a change in terrain.

Description

    CROSS-REFERENCE TO RELATED APPLICATIONS
  • This application claims priority to U.S. Provisional Application No. 61/940,660, which was filed on 17 Feb. 2014, and is titled “Route Imaging System And Method” (the “'660 Application”), U.S. Provisional Application No. 61/940,610, which also was filed on 17 Feb. 2014, and is titled “Wayside Imaging System And Method” (the “'610 Application”), U.S. Provisional Application No. 61/940,813, which was filed on 17 Feb. 2014, and is titled “Portable Camera System And Method For Transportation Data Communication” (the “'813 Application”), and U.S. Provisional Application No. 61/940,696, which was filed on 17 Feb. 2014, and is titled “Vehicle Image Data Management System And Method” (the '696 Application”). The entire disclosures of these applications (e.g., the '660 Application, the '610 Application, the '813 Application, and the '696 Application) are incorporated by reference.
  • FIELD
  • Embodiments of the subject matter described herein relate to imaging systems, such as imaging systems onboard or near vehicle systems.
  • BACKGROUND
  • Vehicle systems such as trains or other rail vehicles can include cameras disposed on or near the vehicle systems. These cameras can be used to record actions occurring outside of the vehicle systems. For example, forward facing cameras can continuously record video of the locations ahead of a train. If a collision between the train and another vehicle occurs (e.g., an automobile is struck at a crossing), then this video can later be reviewed to determine liability for the collision, whether the other vehicle improperly moved through a gate or signal, whether the train was moving too fast, or the like. But, the image data obtained by these cameras typically is only saved on a temporary loop. Older image data is discarded when no accidents occur, even though this image data may represent one or more other problems with the vehicle and/or track.
  • In order to inspect routes, wayside devices disposed along the routes traveled by the vehicle systems, or the like, crews are periodically sent out over the routes to inspect the condition of the wayside devices. This is a labor intensive and costly operation that also ties up the routes, and can interfere with regular and normal operations of other transportation using the routes. Additionally, because this is a periodic operation, a fault in the route or in a wayside device may not be observed by inspection crews in time to prevent catastrophic events.
  • BRIEF DESCRIPTION
  • In one example of the inventive subject matter described herein, a system (e.g., an imaging system) includes a digital camera configured to be disposed in a first vehicle system. The camera is configured to generate image data within a field of view of the camera. The field of view includes at least a portion of a cab of the first vehicle system and at least one of a portion of a route being traveled by the first vehicle system or one or more wayside devices disposed along the route being traveled by the first vehicle system. The cab includes a space where an operator of the first vehicle system is located during travel of the first vehicle system. The system also can include one or more analysis processors configured to examine the image data generated by the camera to identify at least one of damage to the route, a deteriorating condition of the route, or a condition of the one or more wayside devices. The condition of the one or more wayside devices includes at least one of damage to the one or more wayside devices, a missing wayside device, deterioration of the one or more wayside devices, or a change in terrain at or near the one or more wayside devices.
  • In another example of the inventive subject matter described herein, another method (e.g., an imaging method) includes generating image data within a field of view of a camera disposed onboard a first vehicle system. The field of view includes at least a portion of a cab of the first vehicle system and at least one of a portion of a route being traveled by the first vehicle system or one or more wayside devices disposed along the route being traveled by the first vehicle system. The cab includes a space where an operator of the first vehicle system is located during travel of the first vehicle system. The method also can include examining, using one or more analysis processors, the image data generated by the camera to identify at least one of damage to the route, a deteriorating condition of the route, or a condition of the one or more wayside devices. The condition includes at least one of damage to the one or more wayside devices, a missing wayside device, deterioration of the one or more wayside devices, or a change in terrain at or near the one or more wayside devices.
  • In another example of the inventive subject matter described herein, another system (e.g., an imaging system) includes a digital camera configured to be disposed in a rail vehicle. The camera is configured to generate image data within a field of view of the camera. The field of view includes at least a portion of a cab of the rail vehicle and at least one of a portion of a track outside of the rail vehicle or one or more wayside devices along the track being traveled by the rail vehicle. The cab includes a space where an operator of the rail vehicle is located during travel of the rail vehicle. The system also includes one or more analysis processors configured to be disposed onboard the rail vehicle and to examine the image data generated by the camera to identify a condition of at least one of the track or the one or more wayside devices. The condition includes at least one of damage to the track, damage to the one or more wayside devices, a missing wayside device, or a changing condition of terrain at or near the one or more wayside devices.
  • In another example of the inventive subject matter described herein, a system (e.g., an imaging system) includes a digital camera and one or more analysis processors. The digital camera is configured to be disposed in a first vehicle system to generate image data within a field of view of the camera. The field of view includes at least a portion of a cab of the first vehicle system and one or more wayside devices disposed along a route being traveled by the first vehicle system. The cab includes a space where an operator of the first vehicle system is located during travel of the first vehicle system. The one or more analysis processors are configured to examine the image data generated by the camera to identify a condition of the one or more wayside devices. The condition includes at least one of damage to the one or more wayside devices, a missing wayside device, deterioration of the one or more wayside devices, or a change in terrain at or near the one or more wayside devices.
  • In another example of the inventive subject matter described herein, a method (e.g., a method for imaging) includes generating image data within a field of view of a camera disposed onboard a first vehicle system. The field of view includes at least a portion of a cab of the first vehicle system and one or more wayside devices disposed along a route being traveled by the first vehicle system. The cab includes a space where an operator of the first vehicle system is located during travel of the first vehicle system. The method also includes examining (using one or more analysis processors) the image data generated by the camera to identify a condition of the one or more wayside devices. The condition includes at least one of damage to the one or more wayside devices, a missing wayside device, deterioration of the one or more wayside devices, or a change in terrain at or near the one or more wayside devices.
  • In another example of the inventive subject matter described herein, another system (e.g., a rail vehicle imaging system) includes a digital camera and one or more analysis processors. The camera is configured to be disposed in a rail vehicle and to generate image data within a field of view of the camera. The field of view includes at least a portion of a cab of the rail vehicle and one or more wayside devices along a track being traveled by the rail vehicle. The cab includes a space where an operator of the rail vehicle is located during travel of the rail vehicle. The one or more analysis processors are configured to be disposed onboard the rail vehicle and to examine the image data generated by the camera to identify a condition of the one or more wayside devices. The condition includes at least one of damage to the one or more wayside devices, a missing wayside device, or a changing condition of terrain at or near the one or more wayside devices.
  • In one example of the inventive subject matter described herein, a system (e.g., an imaging system) includes a digital camera and one or more analysis processors. The digital camera is configured to be disposed in a first vehicle system and to generate image data within a field of view of the camera. The field of view includes at least a portion of a cab of the first vehicle system and a portion of a route being traveled by the first vehicle system. The cab includes a space where an operator of the first vehicle system is located during travel of the first vehicle system. The one or more analysis processors are configured to examine the image data generated by the camera to identify at least one of damage to the route or a deteriorating condition of the route.
  • In another example of the inventive subject matter described herein, a method (e.g., an imaging method) includes generating image data within a field of view of a camera disposed onboard a first vehicle system. The field of view includes at least a portion of a cab of the first vehicle system and a portion of a route being traveled by the first vehicle system. The cab includes a space where an operator of the first vehicle system is located during travel of the first vehicle system. The method also includes examining (using one or more analysis processors) the image data generated by the camera to identify at least one of damage to the route or a deteriorating condition of the route.
  • In another example of the inventive subject matter described herein, another system (e.g., an imaging system) includes a digital camera and one or more analysis processors. The digital camera is configured to be disposed in a rail vehicle and to generate image data within a field of view of the camera. The field of view includes at least a portion of a cab of the rail vehicle and a portion of a track being traveled by the rail vehicle. The cab includes a space where an operator of the rail vehicle is located during travel of the rail vehicle. The one or more analysis processors are configured to be disposed onboard the rail vehicle and to examine the image data generated by the camera to identify at least one of damage to the track or a deteriorating condition of the track.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • The subject matter described herein will be better understood from reading the following description of non-limiting embodiments, with reference to the attached drawings, wherein below:
  • FIG. 1 is a schematic illustration of a vehicle system having a wayside imaging system disposed thereon according to one embodiment;
  • FIG. 2 illustrates an image representative of image data generated by a camera shown in FIG. 1 for examination by one or more analysis processors shown in FIG. 1 according to one embodiment;
  • FIG. 3 illustrates one example of a comparison between the image data acquired by and output from the camera shown in FIG. 1 with baseline image data according to one embodiment;
  • FIG. 4 illustrates another example of a comparison between the image data acquired by and output from the camera shown in FIG. 1 with baseline image data according to one embodiment;
  • FIG. 5 illustrates an image representative of additional image data generated by the camera shown in FIG. 1 for examination by the analysis processor shown in FIG. 1 according to one embodiment;
  • FIG. 6 illustrates one example of a comparison between the image data acquired by and output from the camera shown in FIG. 1 with baseline image data according to one embodiment;
  • FIG. 7 illustrates a flowchart of a method for imaging one or more wayside devices disposed along a route traveled by one or more vehicle systems according to one embodiment;
  • FIG. 8 illustrates an image representative of image data generated by a camera shown in FIG. 1 for examination by an analysis processor shown in FIG. 1 according to one embodiment;
  • FIG. 9 illustrates one example of a comparison between a route shown in FIG. 1 as represented by image data generated by the camera shown in FIG. 1 with a baseline route image according to one embodiment;
  • FIG. 10 illustrates a schematic diagram of a vehicle consist having one or more imaging systems shown in FIG. 1 in accordance with one embodiment;
  • FIG. 11 illustrates a top view of the vehicle consist shown in FIG. 10 according to one embodiment; and
  • FIG. 12 illustrates a flowchart of a method for imaging a route traveled by one or more vehicle systems according to one embodiment.
  • DETAILED DESCRIPTION
  • One or more embodiments of the inventive subject matter described herein relate to imaging systems and methods for vehicle systems. While several examples of the inventive subject matter are described in terms of rail vehicles (e.g., trains, locomotive, locomotive consists, and the like), not all embodiments of the inventive subject matter is limited to rail vehicles. At least some of the inventive subject matter may be used in connection with other off-highway vehicles (e.g., vehicles that are not permitted or designed for travel on public roadways, such as mining equipment), automobiles, marine vessels, airplanes, or the like.
  • FIG. 1 is a schematic illustration of a vehicle system 100 having an imaging system 102 disposed thereon according to one embodiment. The vehicle system 100 includes a single vehicle, such as a single rail vehicle (e.g., locomotive), but alternatively may include two or more vehicles mechanically coupled with each other to travel together along a route 104, such as a train or other vehicle consist.
  • The imaging system 102 includes one or more cameras 106 that obtain image data of the interior and/or exterior of the vehicle system 100. The camera 106 shown in FIG. 1 is an internal or interior camera that is coupled with the vehicle system 100 so that a field of view 110 of the camera (e.g., the space that is imaged or otherwise represented by image data generated by the camera) includes at least part of an interior of the vehicle system 100. For example, the camera 106 in FIG. 1 may be referred to as a cab camera that is disposed inside a cab of the vehicle system 100 where an operator of the vehicle system 100 is located to control and/or monitor operations of the vehicle system 100.
  • The camera 106 can be positioned and oriented so that the field of view of the camera 106 includes the interior space of the cab in the vehicle system 100, as well as a portion of the exterior of the vehicle system 100. This portion of the exterior of the vehicle system 100 can be the space outside of the vehicle system 100 that is viewable through one or more windows 108 of the vehicle system 100. In the illustrated example, the camera 106 is oriented so that at least a portion of the route 104 that is ahead of the vehicle system 100 is viewable in the field of view 110 of the camera 106. In this way, the camera 106 can be used to both monitor events inside the vehicle system 100 and examine the route and/or wayside devices outside of the vehicle system 100, as described herein. For example, the camera 106 can be used to record performance of the operator of the vehicle system 100 to ensure that the operator is controlling the vehicle system 100 safely, according to rules, requirements, or regulations, is present and aware, and the like. The camera 106 may then also be used to determine if any external problems exist with the route and/or the wayside devices.
  • As described herein, one or more wayside devices also may be within the field of view 110 of the camera 106. These wayside devices include equipment, systems, assemblies, and the like, that are located outside of the vehicle system 100 at, near, or alongside the route 104. The wayside devices can provide functionality to guide, warn, examine, or otherwise assist travel of the vehicle system 100. By way of non-limiting examples, the wayside devices can include signals that display signs, illuminate lights, or otherwise visually notify an onboard operator of the vehicle system 100 of a vacancy or occupancy of an upcoming segment of the route 104, a reduced speed limit, an upcoming segment of the route 104 being repaired or maintained, or the like. The wayside devices can include examination systems that examine the vehicle system 100 as the vehicle system 100 travels past the wayside devices. Examples of such wayside devices can include cameras, infrared detectors, radio frequency identification (RFID) transponders, readers, or tags, or the like. Other wayside devices can include systems that communicate with the vehicle system 100 using wired and/or wireless connections, such as by wirelessly communicating messages to the vehicle system 100 and/or communicating messages through the route 104 (e.g., as electric signals communicated through one or more conductive rails of the route 104). Optionally, the wayside devices may include other devices or systems.
  • The images and/or video captured and output by the camera 106 can record actions performed by the operator onboard the vehicle system 100, but also may capture the wayside devices as the vehicle system 100 travels past the wayside devices. While the camera 106 may be disposed onboard and inside the vehicle system 100 in one embodiment, the camera 106 may be oriented such that the field of view 110 of the camera 106 includes the wayside devices (e.g., through one or more windows 108 of the vehicle system 100).
  • Optionally, the imaging system 102 can include one or more external or exterior cameras, or the camera 106 may be an external or exterior camera. An external or exterior camera is a camera that is coupled with the vehicle system 100 outside of the cab (e.g., on an exterior surface of the vehicle system 100) so that the field of view 110 of the camera 106 includes at least part of the exterior of the vehicle system 100. For example, the field of view 110 can capture portions of the route 104 and/or the wayside devices during movement of the vehicle system 100 on the route 104.
  • The camera 106 may be a digital camera capable of obtaining relatively high quality image data (e.g., static or still images and/or videos). For example, the camera 106 may be Internet protocol (IP) cameras that generate packetized image data. The camera 106 can be a high definition (HD) camera capable of obtaining image data at relatively high resolutions. For example, the camera 106 may obtain image data having at least 480 horizontal scan lines, at least 576 horizontal scan lines, at least 720 horizontal scan lines, at least 1080 horizontal scan lines, or an even greater resolution. The image data generated by the camera 106 can include still images and/or videos.
  • A controller 112 of the imaging system 102 includes or represents hardware circuits or circuitry that includes and/or is connected with one or more computer processors, such as one or more computer microprocessors. The controller 112 can dictate operational states of the camera 106, save image data obtained by the camera 106 to one or more memory devices 114 of the imaging system 102, generate alarm signals responsive to identifying one or more problems with the route 104 and/or the wayside devices based on the image data that is obtained, or the like.
  • The memory device 114 includes one or more computer readable media used to at least temporarily store the image data provided by the camera 106. Without limitation, the memory device 114 can include a computer hard drive, flash drive, optical disk, or the like. The memory device 114 may be disposed entirely onboard the vehicle system 100, or may be at least partially stored off-board the vehicle system 100, such as in a dispatch facility, another vehicle, or the like.
  • During travel of the vehicle system 100 along the route 104, the camera 106 can generate image data representative of images and/or video of the field of view 110 of the camera 106. This image data can represent actions occurring in the interior of the vehicle system 100 (e.g., the operator changing operational settings of the vehicle system 100). For example, one use for the image data may be for an accident investigation, where the actions of an onboard operator are examined to determine if the operator was present at the controls of the vehicle system 100 at the time of the accident, if the operator was awake and aware leading up to the accident, if the proper actions were taken leading up to the accident (e.g., a horn or other alarm was activated, the brakes were engaged, etc.), and the like.
  • Additionally or alternatively, the image data may be used to inspect the health of the route 104, status of wayside devices along the route 104 being traveled on by the vehicle system 100, or the like. As described above, the field of view 110 of the camera 106 can encompass at least some of the route 104 and/or wayside devices disposed ahead of the vehicle system 100 along a direction of travel of the vehicle system 100. During movement of the vehicle system 100 along the route 104, the camera 106 can obtain image data representative of the route 104 and/or the wayside devices for examination to determine if the route 104 and/or wayside devices are functioning properly, or have been damaged, need repair, and/or need further examination.
  • The image data created by the camera 106 can be referred to as machine vision, as the image data represents what is seen by the imaging system 102 in the field of view 110 of the camera 106. One or more analysis processors 116 of the imaging system 102 may examine the image data to identify conditions of the route 104 and/or wayside devices. Optionally, the analysis processor 116 can examine the terrain at, near, or surrounding the route 104 and/or wayside devices to determine if the terrain has changed such that maintenance of the route 104, wayside devices, and/or terrain is needed. For example, the analysis processor 116 can examine the image data to determine if vegetation (e.g., trees, vines, bushes, and the like) is growing over the route 104 or a wayside device (such as a signal) such that travel over the route 104 may be impeded and/or view of the wayside device may be obscured from an operator of the vehicle system 100. As another example, the analysis processor 116 can examine the image data to determine if the terrain has eroded away from, onto, or toward the route 104 and/or wayside device such that the eroded terrain is interfering with travel over the route 104, is interfering with operations of the wayside device, or poses a risk of interfering with operation of the route 104 and/or wayside device. Thus, the terrain “near” the route 104 and/or wayside device may include the terrain that is within the field of view of the camera 106 when the route 104 and/or wayside device is within the field of view of the camera 106, the terrain that encroaches onto or is disposed beneath the route 104 and/or wayside device, and/or the terrain that is within a designated distance from the route 104 and/or wayside device (e.g., two meters, five meters, ten meters, or another distance).
  • The analysis processor 116 can represent hardware circuits and/or circuitry that include and/or are connected with one or more computer processors, such as one or more computer microprocessors. While the analysis processor 116 is shown as being disposed onboard the vehicle system 100, optionally, all or part of the analysis processor 116 may be located off-board of the vehicle system 100, such as in a dispatch facility or other location.
  • Acquisition of HD image data from the camera 106 can allow for the analysis processor 116 to have access to sufficient information to examine individual video frames, individual still images, several video frames, or the like, and determine the condition of the wayside devices and/or terrain at or near the wayside device. The HD image data optionally can allow for the analysis processor 116 to have access to sufficient information to examine individual video frames, individual still images, several video frames, or the like, and determine the condition of the route 104. The condition of the route 104 can represent the health of the route 104, such as a state of damage to one or more rails of a track, the presence of foreign objects on the route, overgrowth of vegetation onto the route, and the like. As used herein, the term “damage” can include physical damage to the route (e.g., a break in the route, pitting of the route, or the like), movement of the route from a prior or designated location, growth of vegetation toward and/or onto the route, deterioration in the supporting material (e.g., ballast material) beneath the route, or the like. For example, the analysis processor 116 may examine the image data to determine if one or more rails are bent, twisted, broken, or otherwise damaged. Optionally, the analysis processor 116 can measure distances between the rails to determine if the spacing between the rails differs from a designated distance (e.g., a gauge or other measurement of the route).
  • In one embodiment, because the HD image data includes a sufficiently large amount of data, the analysis processor 116 may examine the image data for damage to the route 104 in real time. By “real time,” it is meant that the analysis processor 116 examines the image data to identify damage to the route 104, examine the wayside device, and/or examine nearby terrain while the vehicle system 100 is moving along the route 104. Optionally, the analysis processor 116 (and/or another off-board analysis processor 116) may perform post-hoc processing and/or analysis of the image data. “Post-hoc” refers to the examination of the image data after the vehicle system 100 has completed a trip. For example, during a trip of the vehicle system 100 from a starting location to a destination location, the camera 106 can generate image data that captures views of the route 104 and/or wayside devices. Real time examination of this image data includes examination of the image data while the vehicle system 100 is moving from the starting location to the destination location, while post-hoc examination of the image data includes examination of the image data onboard and/or off-board the vehicle system 100 after the vehicle system 100 has arrived at the destination location (and/or is no longer moving).
  • The analysis of the image data by the analysis processor 116 can be performed using one or more image and/or video processing algorithms, such as edge detection, pixel metrics, comparisons to benchmark images, object detection, gradient determination, or the like.
  • Edge detection refers to the examination of the image data to identify edges of objects in the image data, such as the edges of the rails of a track. As one example, the edges of the objects can be identified by finding the pixels in one or more frames of the image data that have the same or similar (e.g., within a designated range of each other) intensity and/or that are located adjacent or near each other (e.g., within a designated distance of each other). Those pixels having the same or similar intensity and located adjacent or near each other can be identified as representing an object. The pixels on the outer edges of the object can be differentiated from other pixels that are outside of the object based on differences between the pixel intensities. For example, the differences in intensities between pixels within the object may be smaller than the differences in intensities between a pixel on the outer edge of the object and a pixel outside of the object (and/or that is adjacent to or near the outer edge of the object). Based on these differences, the analysis processor 116 can identify the edges of the object.
  • Pixel metrics can refer to one or more algorithms that measure qualities of the pixels to identify objects in the image data. While pixel intensities are described above, optionally, pixel metrics can include measuring color, luminance, or another parameter of the pixels in the image data. The pixel metrics can be compared or otherwise examined in order to determine locations of objects (e.g., rails) in the image data for identifying damage to the route 104.
  • The use of benchmark images includes the analysis processor 116 comparing actual image data to one or more benchmark images to determine if any differences (e.g., significant differences other than noise) between the actual and benchmark images are present. The benchmark images can include previously acquired image data of a wayside device and/or nearby terrain. The previously acquired image data may be obtained at a time when the wayside device and/or nearby terrain was known to be in good or at least acceptable condition. Optionally, the benchmark image may be an image or video that is created (e.g., not an actual image) to represent the shape or other appearance of the wayside device and/or nearby terrain. The created benchmark image may be designed to represent the wayside device and/or nearby terrain when the wayside device and/or nearby terrain are in good or at least acceptable condition.
  • The analysis processor 116 can compare the actual image data with the benchmark image data if the shape, size, arrangement, color, or the like, of objects, edges, pixels, or the like, identified the actual image data are the same as or within a designated range of each other. For example, the analysis processor 116 can identify edges of objects in the actual image data (e.g., using edge detection algorithms described above or in another manner). These edges can be used to estimate the shape, location, and/or arrangement of objects in the actual image data. Some of these objects can represent the wayside devices and/or the terrain nearby. The identified objects in the actual image data can be compared with the known shape, location, and/or arrangement of objects in the benchmark image data. Depending on the amount of spatial overlap and/or the lack of spatial overlap between the object(s) in the actual image data and the object(s) in the benchmark image data, the analysis processor 116 may determine that the wayside device is or is not in the proper position, has or has not been damaged, and the like. For example, if the object(s) in the actual image data match or are relatively close to matching the object(s) in the benchmark image data, then the analysis processor 116 can determine that the wayside device and/or nearby terrain is in acceptable condition. Otherwise, the analysis processor 116 can determine that the wayside device and/or nearby terrain is damaged, has moved, or otherwise is in an unacceptable position.
  • The analysis processor 116 can examine one or more parameters of the pixels, such as the intensities, color, luminance, or the like, of the pixels in one or more areas of the actual image data from the camera 106 to determine gradients of these pixel parameters. The gradients can represent a degree or rate at which these parameters change over a designated area, such as across a frame of the image data or another area or distance. The analysis processor 116 can compare the determined gradients to one or more designated gradients that are associated with image data representative of the wayside device and/or nearby terrain that is in acceptable condition (e.g., not damaged, overgrown, eroded, or the like). If the determined gradients differ from the designated gradients, then the analysis processor 116 can determine that the image data does not include the wayside device, or that the wayside device and/or nearby terrain is damaged or otherwise in unacceptable condition.
  • With continued reference to the imaging system 102 shown in FIG. 1, FIG. 2 illustrates an image 200 representative of image data generated by the camera 106 for examination by the analysis processor 116 according to one embodiment. The image 200 illustrates portions of rails 202, 204 of the route 104 as viewed from the interior camera 106 through the windows 108 of the vehicle system 100. Also viewable in the image 200 alongside the route 104 is an inspection wayside device 206 and a signaling wayside device 208. The inspection wayside device 206 may inspect one or more components of the vehicle system 100 as the vehicle system 100 moves past the inspection wayside device 206. For example, the inspection wayside device 206 may include an infrared detector, or “hot box detector,” or other inspection device. The signaling wayside device 208 is shown as a light signal that changes color to indicate a status of an upcoming segment of the route 104 and/or a speed that the vehicle system 100 should use, such as by illuminating one or more lights with a green, yellow, or red color. While only one light 210 is shown in the signaling wayside device 208, optionally, the signaling wayside device 208 may include multiple lights or may signal the vehicle system 100 in another manner.
  • As described above, the analysis processor 116 can examine the image data to identify objects (e.g., shapes) in the image data. These shapes may correspond to the wayside devices 206, 208 and/or terrain near the wayside devices 206, 208. The shapes of these objects can be identified using pixel metrics, edge detection, pixel gradients, comparisons to benchmark images, object detection, or the like.
  • The analysis processor 116 can compare the actual image data shown in FIG. 2 with benchmark image data that represents locations of where objects representative of the wayside devices 206, 208 and/or nearby terrain are to be located. In order to determine which benchmark image data to compare to the actual image data, the analysis processor 116 can determine the location of the vehicle system 100 and select at least one set of benchmark image data from several sets of benchmark image data (e.g., stored on the memory device 114 or otherwise accessible by the analysis processor 116). The different sets of benchmark image data can be representative of the wayside devices at different locations along the route 104. Once the analysis processor 116 identifies the location of the vehicle system 100 when the image data shown in the image 200 was obtained, the analysis processor 116 can obtain the benchmark image data representative of the wayside devices and/or nearby terrain associated with that location.
  • In order to determine the locations of the vehicle system 100, the imaging system 102 can include or be coupled with a location determining device 118 that generates location data representative of where the vehicle system 100 is located. The location determining device 118 can represent a global positioning system (GPS) receiver, a radio frequency identification (RFID) transponder that communicates with RFID tags or beacons disposed alongside the route 104, a computer that triangulates the location of the vehicle system 100 using wireless signals communicated with cellular towers or other wireless signals, a speed sensor (that outputs data representative of speed, which is translated into a distance from a known or entered location by the controller 112), or the like. The location determining device 118 can include an antenna 120 (and associated hardware receiver or transceiver circuitry) for determining the location data. The analysis processor 116 can receive this data and can determine the location of the vehicle system 100.
  • The location data can be associated with the image data in order to indicate where the portion of the route 104 that is shown in the image data is located. For example, the location data can be included in the image data as metadata or other data that is saved with the image data. Optionally, the location data may be stored separately from the image data but associated with the image data, such as in a table, list, database, or other memory structure. The location and/or time information can be shown on the image 200, such as by overlaying this information on the image. The location and/or time information can represent the location where the image data that is shown in the image 200 was acquired and/or when this image data was acquired. For example, the location and/or time information can indicate the GPS coordinates of the segment of the route 104 that is shown in the image 200.
  • In one embodiment, the location data may be used to control when the camera 106 obtains image data and/or which image data is examined by the analysis processor 116. For example, different areas, or zones, may be identified as including wayside devices to be examined using the image data acquired and output by the camera 106. Responsive to the vehicle system 100 entering into such a zone based on the location data, the camera 106 may begin obtaining and/or sending image data to the analysis processor 116, and/or the analysis processor 116 may begin examining the image data. Upon exit from the zone, the camera 106 may stop obtaining and/or sending the image data to the analysis processor 116, and/or the analysis processor 116 may stop examining the image data. Alternatively, the analysis processor 116 may only examine the image data that is acquired by the camera 106 when the vehicle system 100 is inside such a zone.
  • The analysis processor 116 examines the image data to identify problems with the route 104. In one aspect, the analysis processor 116 compares locations and/or arrangements of the route 104 in the image data with designated locations and/or arrangements of the route 104, such as which can be stored in the memory device 114.
  • FIG. 3 illustrates one example of a comparison between the image data acquired by and output from the camera 106 with baseline image data according to one embodiment. The baseline image data represents how the wayside devices 206, 208 and/or surrounding terrain is expected to appear in the image data output by the camera 106 if the wayside devices 206, 208 are in acceptable condition (e.g., have not been moved, vandalized or otherwise damaged, are not overgrown with vegetation, are not covered due to erosion, or the like).
  • The baseline image data includes baseline objects 300, 302, 304 shown in dashed lines in FIG. 3. These objects 300, 302, 304 represent where the wayside devices 206, 208 are expected to be when the vehicle system 100 is at or near a designated location associated with the baseline objects 300, 302, 304 and the wayside devices 206, 208 and/or nearby terrain are in acceptable condition. The baseline objects 300, 302, 304 may change location, size, arrangement, or the like, for image data acquired when the vehicle system 100 is in another location.
  • The analysis processor 116 can determine the locations of the objects representative of the wayside devices 206, 208 (e.g., the signal, the light, the inspection device, or the like) from the actual image data that is output by the camera 106 and compare this to the baseline objects of the baseline image data. The comparison can involve determining if the actual objects (e.g., representative of the wayside devices 206, 208) are in the same or overlapping locations as the baseline objects in the image data or image 200. In the illustrated example, the analysis processor 116 can determine that the object representative of the wayside device 206 is in the same location as the baseline object 304 or overlaps the area encompassed by the baseline object 304 for a least a designated fraction of the baseline object 304. If the actual imaged object and the baseline object overlap by at least this designated fraction, then the analysis processor 116 can determine that the wayside device 206, 208 is in acceptable condition. Otherwise, the analysis processor 116 may determine that the wayside device 206, 208 and/or terrain is in an unacceptable condition.
  • The designated fraction may be a percentage such as 50%, 60%, 70%, 80%, 90%, or another amount, depending on how sensitive the analysis processor 116 is to be in identifying problems with the wayside devices 206, 208 and/or nearby terrain. For example, lowering the designated fraction may cause the analysis processor 116 to identify more problems with the wayside devices 206, 208 and/or terrain, but also may cause the analysis processor 116 to falsely identify such problems when no problems actually exist. Increasing the designated fraction may cause the analysis processor 116 to identify fewer problems with the wayside devices 206, 208 and/or terrain, but also may cause the analysis processor 116 to miss some identification of some problems.
  • Based on the large amount of overlap between the signal wayside device 208 and the baseline object 300, between the light 210 and the baseline object 302, and/or between the inspection wayside device 206 and the baseline object 304, the analysis processor 116 can determine that the wayside devices 206, 208 and/or the terrain are in acceptable condition.
  • FIG. 4 illustrates another example of a comparison between the image data acquired by and output from the camera 106 with baseline image data according to one embodiment. In contrast to the image data shown in FIG. 3, the image data shown in FIG. 4 includes a foreign object 400 at least partially obstructing the view of the inspection wayside device 206 and the signaling wayside device 208 being damaged (e.g., bent out of position and the light 210 shown in FIGS. 2 and 3 being removed or damaged). The foreign object 400 can represent growth of vegetation on or around the wayside device 206, erosion of the terrain onto or around the wayside device 206, or another object disposed on or near the wayside device 206. The presence of the foreign object 400 may interfere with functions of the wayside device 206. Similarly, the damage to the wayside device 208 may interfere with signaling functions of the wayside device 208.
  • The analysis processor 116 can compare the actual objects in the image data representative of the wayside devices 206, 208 with the baseline objects 300, 302, 304 to determine if the actual objects match the baseline objects. For example, the analysis processor 116 can calculate the amount of overlap between the actual objects and the baseline objects 300, 302, 304. With respect to the wayside device 208 and the baseline object 300, very little overlap exists. With respect to the light 210 and the baseline object 302, the damage or removal of the light 210 may prevent the analysis processor 116 from identifying any object where the light 210 should be located. With respect to the wayside device 206 and the baseline object 304, the object 400 (e.g., eroded terrain, vegetation, other foreign objects, or the like) is partially blocking the view of the wayside device 206.
  • The analysis processor 116 can determine that the object 400 is not part of the wayside device 206 based on edge detection between the object 400 and the wayside device 206, differences in pixel metrics between the object 400 and the wayside device 206, or the like. The presence of the object 400 prevents the analysis processor 116 from identifying the wayside device 206 as being in acceptable condition because not enough of the wayside device 206 overlaps the baseline object 304. For example, because the fraction of the baseline object 304 that is overlapped by the wayside device 206 does not exceed a designated amount, the analysis processor 116 may determine that the wayside device 206 is not in a location where the wayside device 206 was installed, that the wayside device 206 has become damaged or stolen, that the terrain is occluding the view of the wayside device 206, or the like.
  • Responsive to identifying the unacceptable conditions of the wayside devices 206, 208, the analysis processor 116 may flag or otherwise mark the image data that represents the damage. By “flag” or “mark,” it is meant that the portion or subset of the image data that includes the damaged section of the route 104 can be saved to the memory device 114 with additional data (e.g., metadata or other information) that indicates which portion of the image data represents these wayside devices 206, 208. Optionally, the analysis processor 116 may save data representative of which portion of the image data shows these wayside devices 206, 208 in another location (e.g., separate from the image data).
  • In the illustrated example, the image 200 generated from the image data includes location and/or time information 214 that is shown on the image. The location and/or time information 214 can represent the location where the image data that is shown in the image 200 was acquired and/or when this image data was acquired. For example, the location and/or time information 214 can indicate the GPS coordinates of the wayside devices 206, 208 that are shown in the image 200. This information can be overlaid on the image 200 to assist viewers of the image 200 in determining where and/or when the wayside devices 206, 208 were identified as being damaged or otherwise in unacceptable condition.
  • The analysis processor 116 can generate one or more reporting signals responsive to identifying the unacceptable conditions of the wayside devices 206, 208. The reporting signals can include the portions of the image data that show the wayside devices 206, 208. For example, the reporting signals can include an edited version of the image data, with the portions of the image data that show the wayside devices 206, 208 included and other portions of the image data that do not show the wayside devices 206, 208 not included.
  • The reporting signals with the included edited image data can be locally saved onto the memory device 114 onboard the vehicle system 100 and/or communicated to an off-board location having a memory device 114 for storing the edited image data. As described above, location data may be included in the image data such that the location data is included in the edited image data.
  • In one aspect, the analysis processor 116 may examine image data of the wayside devices obtained at different times to determine if the conditions of the wayside devices are changing over time. For example, the analysis processor 116 can compare image data of the same location of the route 104 obtained at different times over the course of several days, weeks, months, or years. Based on this comparison and changes in the wayside devices, the analysis processor 116 can determine that the condition of the wayside devices is exhibiting a downward or negative trend.
  • The analysis processor 116 can compile the image data of the same section of the route 104 obtained at different times into compilation image data. This compilation image data (and/or other image data described herein) can be presented to an operator of the imaging system 102, such as on a display device 122. The display device 122 may be a monitor, television, touchscreen, or other output device that visually presents image data. The display device 122 can be disposed onboard the vehicle system 100 and/or at an off-board facility, such as a dispatch center or elsewhere. The operator can examine the compilation image data to identify the changes in the route 104 over time. Optionally, the analysis processor 116 may use one or more software algorithms, such as edge detection, pixel metrics, or the like, to identify objects in the compilation image data. The analysis processor 116 can then automatically identify changes or trends in the condition of the wayside devices using the compilation image data.
  • In one embodiment, the memory device 114 and/or the analysis processor 116 may receive image data of the same wayside devices obtained by different vehicle systems 100. For example, as separate vehicle systems 100 that are not traveling together travel over the same segment of the route 104 obtain image data of the wayside devices at different times, the image data can be sent to the analysis processor 116 and/or memory device 114. The analysis processor 116 and/or memory device 114 can be disposed onboard of off-board the vehicle system 100. The analysis processor 116 can examine this image data of the same wayside devices from diverse sources (e.g., the imaging systems 102 on different vehicle systems 100) to identify damage to the wayside devices and/or trends in the condition of the wayside devices.
  • A communication system 124 of the imaging system 102 represents hardware circuits or circuitry that include and/or are connected with one or more computer processors (e.g., microprocessors) and communication devices (e.g., wireless antenna 126 and/or wired connections 128) that operate as transmitters and/or transceivers for communicating signals with one or more locations disposed off-board the vehicle system 100. For example the communication system 124 may wirelessly communicate signals (e.g., image data) via the antenna 126 and/or communicate the signals over the wired connection 128 (e.g., a cable, bus, or wire such as a multiple unit cable, train line, or the like) to a facility and/or another vehicle system, or the like.
  • In one embodiment, the imaging system 102 is disposed onboard a vehicle system 100 that propels cargo. For example, instead of the imaging system 102 being disposed onboard a specially outfitted vehicle (e.g., a vehicle designed for the sole purpose of inspecting the route), the imaging system 102 may be disposed onboard a vehicle system that is designed to propel cargo so that the imaging system 102 can inspect the wayside devices 206, 208 at the same time that the vehicle system 100 is moving cargo (e.g., goods such as commodities, commercial products, or the like). The imaging system 102 may automatically obtain and/or examine image data during travel of the vehicle system 102 during other operations of the vehicle system 100 (e.g., moving freight) and, as a result, anomalies (e.g., damage) to the wayside devices 206, 208 can be identified on a repeated basis. As the vehicle system 100 travels and the imaging system 102 discovers problems with the wayside devices 206, 208, the communication system 124 may communicate (e.g., transmit and/or broadcast) alarm signals to notify others of the damage to the wayside devices 206, 208, trends in the conditions of the wayside devices 206, 208, or the like, to one or more off-board locations. For example, upon identifying a problem with one or more of the wayside devices 206, 208, the imaging system 102 can cause the communication system 124 to send an alarm signal to a repair facility so that one or more maintenance crews of workers can be sent to the location of the wayside devices 206, 208 for further inspection of the wayside devices 206, 208 and/or repair to the wayside devices 206, 208.
  • FIG. 5 illustrates an image 1100 representative of additional image data generated by the camera 106 for examination by the analysis processor 116 according to one embodiment. The image 1100 illustrates portions of the rails 202, 204 of the route 104 as viewed from the interior camera 106 through the windows 108 of the vehicle system 100. Also viewable in the image 1100 between the rails 202, 204 are supporting bodies 1102. The supporting bodies 1102 can represent ties, such as railroad ties, railway ties, crossties, railway sleepers, or other bodies that support the rails 202, 204 and/or assist in keeping the rails 202, 204 parallel to each other. As described above, the analysis processor 116 can examine the image data to identify objects (e.g., shapes) in the image data. These shapes may correspond to the supporting bodies 1102. The shapes of these objects can be identified using pixel metrics, edge detection, pixel gradients, comparisons to benchmark images, object detection, or the like. The analysis processor 116 examines the image data to identify problems with the route 104. In one aspect, the analysis processor 116 compares locations and/or arrangements of the route 104 in the image data with designated locations and/or arrangements of the route 104, such as which can be stored in the memory device 114.
  • FIG. 6 illustrates one example of a comparison between the image data acquired by and output from the camera 106 with baseline image data according to one embodiment. The baseline image data represents how the supporting bodies 1102 are expected to appear in the image data output by the camera 106 if the supporting bodies 1102 are in acceptable condition (e.g., have not been moved or otherwise damaged). The baseline image data includes baseline objects 1200 shown in dashed lines in FIG. 6. These objects 1200 represent where the supporting bodies 1102 are expected to be when the vehicle system 100 is at or near a designated location associated with the baseline objects 1200 and the supporting bodies 1102. The baseline objects 300, 302, 304 may change location, size, arrangement, or the like, for image data acquired when the vehicle system 100 is in another location.
  • The analysis processor 116 can determine the locations of the objects representative of the supporting bodies 1102 from the actual image data that is output by the camera 106 and compare this to the baseline objects of the baseline image data. The comparison can involve determining if the actual objects are in the same or overlapping locations as the baseline objects in the image data or image 1100. In the illustrated example, the analysis processor 116 can determine that one of the objects representative of one of the supporting bodies 1102 is in the same location as one of the baseline objects 1200 or overlaps the area encompassed by the baseline object 1200 for a least a designated fraction of the baseline object 1200. As a result, the outer boundaries of the baseline object 1200 are not visible outside of or inside of the object representative of one of the supporting bodies 1102.
  • But, another object representative of a supporting body 1102 in the image data 1100 appears to be angled with respect to another baseline object 1200. The analysis processor 116 can compare the edges of the supporting body 1102 with the baseline object 1200, the overlap (or lack of overlap) between the areas in the image data 1100 that are encompassed by the supporting body 1102 and the baseline object 1200, or the like, to determine if the supporting body 1102 is out of position. In the illustrated example, the analysis processor 116 may determine that the supporting body 1102 has shifted or otherwise moved out of position due to the area encompassed by the supporting body 1102 only overlapping the area encompassed by the baseline object 1200 by less than a designated threshold amount.
  • As described above, responsive to determining that the supporting body 1102 is out of position, the analysis processor 116 may flag or otherwise mark the image data 1100. The image data 1100 may be saved with or otherwise associated with time and/or location data to assist in later determining where the out-of-position supporting body 1102 is located. The analysis processor 116 can generate one or more reporting signals responsive to identifying the unacceptable condition of the supporting body 1102, similar to as described above.
  • FIG. 7 illustrates a flowchart of a method 500 for imaging one or more wayside devices disposed along a route traveled by one or more vehicle systems according to one embodiment. The method 500 may be used to obtain image data of the wayside devices to determine if one or more problems exist with the wayside devices, such as damage to the wayside devices, a deteriorating condition of the wayside devices, or the like. At least one embodiment of the method 500 may be practiced using the imaging system 102 (shown in FIG. 1) described herein.
  • At 502, image data of one or more wayside devices are obtained from a camera onboard a vehicle system. For example, a camera that is positioned to obtain video of an operator disposed on the vehicle system also may obtain video of wayside devices disposed outside the vehicle system along a route being traveled by the vehicle system. This camera may be installed to monitor actions (or lack thereof) of an operator for liability or other purposes (e.g., such as in post-accident investigations or reconstructions), but that also may obtain video of the wayside devices, such as through windows of the vehicle system.
  • At 504, the image data is examined. As described above, the image data can be examined in real time and/or after travel of the vehicle system is complete. The image data can be examined to identify locations and/or arrangements of the wayside devices. At 506, a determination is made as to whether the image data indicates a problem with the wayside devices. For example, the image data can be examined to determine if the wayside devices are damaged, vandalized, stolen, or the like, and/or if other objects are on or near the wayside devices such that the objects could prevent the wayside devices from performing one or more functions.
  • If the image data indicates a problem with the wayside devices, then one or more corrective actions may need to be taken. As a result, flow of the method 400 can proceed to 514. On the other hand, if the image data does not indicate such a problem, then additional image data (e.g., previously and/or subsequently acquired image data of the same wayside devices) may be examined to determine if the conditions of the wayside devices are deteriorating, if foreign objects (e.g., vegetation) are moving toward the wayside devices, or the like. As a result, flow of the method 500 can proceed to 508. Alternatively, no further analysis is performed on this or other image data, and the method 500 can terminate.
  • At 508, additional image data of the same wayside devices can be obtained. This additional image data may be generated by one or more cameras at different times than when the image data is obtained at 502. For example, the additional image data can be generated by cameras of imaging systems on other vehicle systems on prior days, weeks, months, or years, and/or subsequent days, weeks, months, or years.
  • At 510, the image data and additional image data are compared with each other and examined. The image data and additional image data are compared and examined in order to determine if the image data and additional image data exhibit changes in the wayside devices over time. For example, while a single or multiple set of the image data acquired at one or more times may not indicate damage to the wayside devices due to the damage being relatively minor, examining more image data acquired over longer periods of time may illustrate a change and/or damage to the wayside devices more than a smaller amount of image data and/or image data obtained over shorter time periods.
  • At 512, a determination is made as to whether the image data and the additional image data indicate a trend in the condition of the one or more wayside devices. For example, the image data and additional image data can be examined to determine if the wayside device are gradually becoming more damaged, if the wayside device is gradually changing location, if vegetation is growing toward and/or onto the wayside device, if the ground near the wayside device is eroding or building up onto the wayside device, or the like. Alternatively, the image data acquired at different times can be examined to identify damage to the wayside device without identifying a trend in the condition of the route.
  • If the image data and additional image data indicate a problem with the wayside device, then one or more corrective actions may need to be taken. As a result, flow of the method 500 can proceed to 514. On the other hand, if the image data and the additional image data do not indicate such a problem, then flow of the method 500 may return to 502 so that additional image data of the same or other wayside devices may be obtained. Alternatively, no further analysis is performed on this or other image data, and the method 500 can terminate.
  • At 514, one or more alarm signals are generated. The alarm signals may be communicated from the analysis processor (which is onboard and/or off-board a vehicle system) to an off-board facility to request further inspection of the wayside device and/or repair to the wayside device. Optionally, an alarm signal may be communicated to one or more vehicle systems to warn the vehicle systems of the identified problem with the wayside device. In one aspect, the alarm signal can be communicated to a scheduling system that generates schedules for vehicle systems so that the scheduling system can alter the schedules of the vehicle systems to avoid and/or slow down over the section of the route where the wayside device identified as having the problem is located.
  • FIG. 8 illustrates another image 600 representative of image data generated by the camera 106 for examination by the analysis processor 116 according to one embodiment. The image 600 illustrates portions of the rails 202, 204 of the route 104 as viewed from the interior camera 106 through the windows 108 of the vehicle system 100. As described above, the analysis processor 116 can examine the image data to identify edges 606, 608, 610, 612 of the rails 202, 204. These edges can be used to determine locations of the rails 202, 204 in the image 200.
  • As described above, location data can be associated with the image data in order to indicate where the portion of the route 104 that is shown in the image data is located. For example, the location data can be included in the image data as metadata or other data that is saved with the image data. Optionally, the location data may be stored separately from the image data but associated with the image data, such as in a table, list, database, or other memory structure. In the illustrated example, the image 200 generated from the image data includes the location and/or time information 214 that is shown on the image.
  • The analysis processor 116 examines the image data to identify problems with the route 104. In one aspect, the analysis processor 116 compares locations and/or arrangements of the route 104 in the image data with designated locations and/or arrangements of the route 104, such as which can be stored in the memory device 114.
  • FIG. 9 illustrates one example of a comparison between the route 104 as represented by the image data generated by the camera 106 with a baseline route image 700 according to one embodiment. The baseline route image 700 represents how the route 104 (e.g., the rails 202, 204 of the route 104) is to appear in the image data if the route 104 is not damaged. For example, the baseline route image 700 can represent locations of the route 104 prior to the route 104 being damaged or degrading.
  • The baseline route image 700 using dashed lines while locations of the rails 202, 204 are shown using solid lines in FIG. 8. With respect to the rail 202, the location of the rail 202 in the image data exactly or closely matches or otherwise corresponds to the designated location of the rail 202 that is represented by the baseline route image 700 (e.g., the location of the rail 202 is within a designated range of distances, pixels, or the like). As a result, the dashed lines of the baseline route image 700 that correspond to the rail 202 are not visible due to the solid lines of the actual rail 202 in the image data.
  • With respect to the rail 204, however, the location of the rail 204 in the image data does not exactly or closely match the designated location of the rail 204 in the baseline route image 700. As a result, the baseline route image 700 and the rail 204 do not exactly or closely overlap in the image data.
  • In one example, the analysis processor 116 can identify this mismatch between the baseline route image 700 and the image data and determine that one or more of the rails 202, 204 have become damaged, such as by being bent, twisted, broken, or otherwise damaged. Optionally, the analysis processor 116 can measure distances between the rails 202, 204 in the image data and compare these distances to one or more designated distances representative of the gauge of the route 104. If the measured distances differ from the designated distances by more than a threshold amount, then the analysis processor 116 determines that the route 104 is damaged at or near the location where the image data was obtained (as determined from the location data).
  • Responsive to identifying the damage to the route 104, the analysis processor 116 may flag or otherwise mark the image data that represents the damage. By “flag” or “mark,” it is meant that the portion or subset of the image data that includes the damaged section of the route 104 can be saved to the memory device 114 with additional data (e.g., metadata or other information) that indicates which portion of the image data represents the damaged section of the route 104. Optionally, the analysis processor 116 may save data representative of which portion of the image data includes the damaged portion of the route 104 in another location (e.g., separate from the image data).
  • The analysis processor 116 can generate one or more reporting signals responsive to identifying one or more damaged sections of the route 104. The reporting signals can include the portions of the image data that show the damaged sections. For example, the reporting signals can include an edited version of the image data, with the portions of the image data that show the damaged sections of the route included and other portions of the image data that do not show the damaged sections not included.
  • The reporting signals with the included edited image data can be locally saved onto the memory device 114 onboard the vehicle system 100 and/or communicated to an off-board location having a memory device 114 for storing the edited image data. As described above, location data may be included in the image data such that the location data is included in the edited image data.
  • In one aspect, the analysis processor 116 may examine image data of the same route 104 obtained at different times to determine if the health of the route 104 is changing over time. For example, the analysis processor 116 can compare image data of the same location of the route 104 obtained at different times over the course of several days, weeks, months, or years. Based on this comparison and changes in the shape, location, arrangement, and the like, of the rails of the route 104, other objects near the route 104 (e.g., vegetation, ballast material, erosion or movement of hills near the route 104, etc.), and the like, the analysis processor 116 can determine that the health of the route 104 at that location is exhibiting a downward or negative trend. For example, the location of one or more rails may gradually change, the vegetation and/or hillside may gradually move toward and/or encroach onto the rails, the amount of ballast material may gradually change, or the like.
  • The analysis processor 116 can compile the image data of the same section of the route 104 obtained at different times into compilation image data. This compilation image data (and/or other image data described herein) can be presented to an operator of the imaging system 102, such as on the display device 122. The operator can examine the compilation image data to identify the changes in the route 104 over time. Optionally, the analysis processor 116 may use one or more software algorithms, such as edge detection, pixel metrics, or the like, to identify objects in the compilation image data. The analysis processor 116 can then automatically identify changes or trends in the health of the route 104 using the compilation image data.
  • In one embodiment, the memory device 114 and/or the analysis processor 116 may receive image data of the same section of the route 104 obtained by different vehicle systems 100. For example, as separate vehicle systems 100 that are not traveling together travel over the same segment of the route 104 obtain image data of the route 104 at different times, the image data can be sent to the analysis processor 116 and/or memory device 114. The analysis processor 116 and/or memory device 114 can be disposed onboard of off-board the vehicle system 100. The analysis processor 116 can examine this image data of the same segment of the route 104 from diverse sources (e.g., the imaging systems 102 on different vehicle systems 100) to identify damage to the route and/or trends in the health of the route 104.
  • In one embodiment, the imaging system 102 is disposed onboard a vehicle system 100 that propels cargo. For example, instead of the imaging system 102 being disposed onboard a specially outfitted vehicle (e.g., a vehicle designed for the sole purpose of inspecting the route), the imaging system 102 may be disposed onboard a vehicle system that is designed to propel cargo so that the imaging system 102 can inspect the route 104 at the same time that the vehicle system 100 is moving cargo (e.g., goods such as commodities, commercial products, or the like). The imaging system 102 may automatically obtain and/or examine image data during travel of the vehicle system 102 during other operations of the vehicle system 100 (e.g., moving freight) and, as a result, anomalies (e.g., damage) to the route 104 can be identified on a repeated basis. As the vehicle system 100 travels and the imaging system 102 discovers problems with the route 104, the communication system 124 may communicate (e.g., transmit and/or broadcast) alarm signals to notify others of the damage to the route 104, trend in health of the route 104, or the like, to one or more off-board locations. For example, upon identifying a problem with the route 104, the imaging system 102 can cause the communication system 124 to send an alarm signal to a repair facility so that one or more maintenance crews of workers can be sent to the location of the problem for further inspection of the route 104 and/or repair to the route 104.
  • FIG. 10 illustrates a schematic diagram of a vehicle consist 800 having one or more imaging systems 102 in accordance with one embodiment. The vehicle consist 800 can include two or more vehicle systems 100 (e.g., vehicle systems 100 a-c) mechanically connected with each other directly or by one or more other vehicles 802 (e.g., non-propulsion generating vehicles such as rail cars, or other propulsion-generating vehicle systems). The vehicle systems 100 and/or the cameras 106 (shown in FIG. 1) of the imaging systems 102 may be oriented in different directions. For example, the cameras 106 onboard the vehicle systems 100 a, 100 b may be oriented along a direction of movement of the vehicle consist 800, while the camera 106 onboard the vehicle system 100 c may be oriented in an opposite direction (e.g., rearward). The vehicle systems 100 may have separate imaging systems 102, or a single imaging system 102 may span across multiple vehicle systems 100. For example, an imaging system 102 may include a controller 112 (shown in FIG. 1) that controls multiple cameras 106 onboard different vehicle systems 100 in the consist 800 and/or an analysis processor 116 (shown in FIG. 1) that examines image data obtained from multiple cameras 106 disposed onboard different vehicle systems 100 in the consist 800.
  • The imaging systems 102 onboard the different vehicle systems 100 in the same vehicle consist 800 can coordinate operation of the cameras 106 onboard the different vehicle systems 100. For example, a first vehicle system 100 a can relay information to a second vehicle system 100 b or 100 c in the same vehicle consist 800. The imaging system 102 of the first vehicle system 100 a may identify a segment of the route 104 and/or a wayside device that may be damaged (as described above). Responsive to this identification, the controller 112 and/or the analysis processor 116 can instruct another camera 106 onboard the same or a different vehicle system 100 of the consist 800 to change one or more operational settings and obtain additional image data. This additional image data may then be examined to confirm or refute identification of damage to the route and/or wayside device.
  • The operational settings that may be changed can include the focus, position, resolution, or the like, of the camera 106 onboard the second vehicle system 100. For example, responsive to image data acquired by a first camera 106 onboard the vehicle system 100 a indicating that the route and/or wayside device is potentially damaged, the controller 112 and/or analysis processor 116 can send a signal to one or more additional cameras 106 disposed onboard the vehicle system 100 b and/or 100 c. This signal can instruct the additional camera(s) 106 to change focus (e.g., to increase or decrease the focal distance or point of the cameras 106) to obtain clearer image data of the potentially damaged route segment and/or wayside device. The signal optionally can direct the additional camera(s) 106 to change position (e.g., to change tilt, rotation, pitch, yaw, or the like) so that the image data of the additional camera(s) 106 encompasses the potentially damaged route segment and/or wayside device. The signal may instruct the additional camera(s) 106 to change resolution (e.g., a number of pixels per unit area) so that more image data of the potentially damaged route segment and/or wayside device is obtained.
  • The controller 112 and/or analysis processor 116 may send information to cause the camera 106 of the second vehicle system 100 to obtain image data of one or more locations of interest that may include the potentially damaged route and/or wayside device. For example, if a first locomotive goes over a piece of track, and the image data obtained by the first locomotive identifies an area of the track and/or wayside equipment that may be need of repair or further inspection, then information could be relayed to a second locomotive (for instance to the rear distributed power unit at the rear of the train) to focus in on that particular rail or location, and even change the resolution to get a better image data of the issue. Optionally, the information can be relayed between different vehicle consists that are not connected with each other. For example, responsive to identifying a damaged route and/or wayside device, the controller 112 and/or analysis processor 116 of an imaging system 102 onboard one vehicle consist 800 can direct the communication system 124 (shown in FIG. 1) to transmit and/or broadcast an assistance signal to one or more other vehicle consists 800. This signal can request the other vehicle consists 800 obtain image data of the damaged route and/or wayside device so that the damage can be confirmed, refuted, further characterized, or the like.
  • FIG. 11 illustrates a top view of the vehicle consist 800 shown in FIG. 10 according to one embodiment. Only the vehicle system 100 a and the vehicle system 100 c are shown in FIG. 11. The imaging system 102 may determine an orientation of the field of view 110 of one or more cameras 106. For example, the imaging system 102 may be able to automatically determine if the field of view 110 of a camera 106 is oriented forward or backward relative to a direction of travel 900 of the consist 800. This could help identify trouble areas of the tracks, and also just be another way to determine direction as opposed to a hard switch.
  • As one example, the imaging system 102 can use a change in the size of an object 902 in the field of view 110 of a camera 106. As the consist 800 approaches and moves by the object 902 (e.g., a wayside device, sign, or signal), the object 902 may change in size in the image data obtained by the camera 106 of the vehicle system 100 a. As the consist 800 passes the object 902, the object 902 may appear in the image data obtained by the camera 106 of the vehicle system 100 c and then change size.
  • If the object 902 is detected in the image data and the object 902 gets smaller in the image data over time (e.g., in the image data obtained by the camera 106 of the vehicle system 100 c), then the analysis processor 116 of the imaging system 102 can determine that the camera 106 is facing opposite of the direction of travel 900 of the vehicle consist 800. Conversely, if the object 902 is progressively getting larger in the image data (e.g., in the image data obtained by the camera 106 of the vehicle system 100 a), then the imaging system 102 may determine that the field of view 110 of the camera 106 is oriented in the same direction as the direction of travel 900.
  • Optionally, changing intensities of colors or lights in the image data may be used to determine the direction in which a camera 106 is facing. The locations of wayside signals can be updated in the memory device 114 (shown in FIG. 1) so the controller 112 and/or analysis processor 116 of the vehicle consist 800 knows which wayside signals to communicate with and where the limits of the wayside signals are located. If the analysis processor 116 identifies red, yellow, or green light (or another color) in an expected location of the wayside signal in the image data, and the light is getting more intense (e.g., brighter, as could occur in the image data obtained by the camera 106 of the vehicle system 100 a as the consist 800 passes a light along the direction of travel 900), then the analysis processor 116 can determine that the camera 106 is facing toward the direction of travel 900 of the vehicle consist 800. Conversely, if the intensity of the light is decreasing (e.g., becoming dimmer, as could occur in the image data obtained by the camera 106 of the vehicle system 100 c), then the analysis processor 116 can determine that the camera 106 is facing away from the direction of travel 900. The analysis processor 116 can combine this analysis of the light intensity with the changing size of the wayside device (e.g., signal) in order to determine the direction that the camera 106 is facing. Optionally, the analysis processor 116 can examine changing sizes of objects or changing light intensities, but not both, to determine orientations of cameras 106.
  • The analysis processor 116 can use the determination of which direction a camera is facing to direct the camera 106 to change operational settings. For example, the analysis processor 116 can determine which direction the camera 106 of the vehicle system 100 c is facing using changing object sizes and/or light intensities. The analysis processor 116 can direct this camera 106 where to focus, change the field of view, or the like, based on this orientation. For example, if the image data obtained by the camera 106 of the vehicle system 100 a identifies damage to the rail 204 of the route 104, then the analysis processor 116 can direct the camera 106 of the vehicle system 100 c to change the focus, field of view, resolution, or the like, of the camera 106 so that the image data captures the rail 204. The analysis processor 116 could direct the camera 106 of the vehicle system 100 c to focus in on the rail 204 and exclude the rail 202 from the field of view in the image data. As a result, the same track is examined by the cameras on the leading and trailing vehicles.
  • FIG. 12 illustrates a flowchart of a method 400 for imaging a route traveled by one or more vehicle systems according to one embodiment. The method 400 may be used to obtain image data of a route and to determine if one or more problems exist with the route, such as damage to the route, a deteriorating health (e.g., condition) of the route, or the like. At least one embodiment of the method 400 may be practiced using the imaging system 102 (shown in FIG. 1) described herein.
  • At 402, image data of the route is obtained from a camera onboard a vehicle system. For example, a camera that is positioned to obtain video of an operator disposed on the vehicle system also may obtain video of a portion of the route. This camera may be installed to monitor actions (or lack thereof) of an operator for liability or other purposes (e.g., such as in post-accident investigations or reconstructions), but that also may obtain video of a portion of the route, such as through windows of the vehicle system.
  • At 404, the image data is examined. As described above, the image data can be examined in real time and/or after travel of the vehicle system is complete. The image data can be examined to identify locations and/or arrangements of components of the route, such as the relative locations and/or spacing of rails of a track. The image data optionally can be examined to monitor conditions of other objects on or near the route, as described above.
  • At 406, a determination is made as to whether the image data indicates a problem with the route. For example, the image data can be examined to determine if the route is broken, bent, twisted, or the like, and/or if other objects are on or near the route such that the objects could cause problems for travel along the route for the vehicle system obtaining the image data and/or another vehicle system.
  • If the image data indicates a problem with the route, then one or more corrective actions may need to be taken. As a result, flow of the method 400 can proceed to 414. On the other hand, if the image data does not indicate such a problem, then additional image data (e.g., previously and/or subsequently acquired image data of the same segment of the route) may be examined to determine if the condition of the route is deteriorating, if foreign objects (e.g., vegetation) are moving toward the route over time, if ballast material needs cleaning and/or replacing, or the like. As a result, flow of the method 400 can proceed to 408. Alternatively, no further analysis is performed on this or other image data, and the method 400 can terminate.
  • At 408, additional image data of the same segment of the route can be obtained. This additional image data may be generated by one or more cameras at different times than when the image data is obtained at 402. For example, the additional image data can be generated by cameras of imaging systems on other vehicle systems on prior days, weeks, months, or years, and/or subsequent days, weeks, months, or years.
  • At 410, the image data and additional image data are compared with each other and examined. The image data and additional image data are compared and examined in order to determine if the image data and additional image data exhibit changes in the route over time. For example, while a single or multiple set of the image data acquired at one or more times may not indicate damage to the route due to the damage being relatively minor, examining more image data acquired over longer periods of time may illustrate a change in locations and/or damage to the route more than a smaller amount of image data and/or image data obtained over shorter time periods.
  • At 412, a determination is made as to whether the image data and the additional image data indicate a trend in the condition (e.g., health) of the route. For example, the image data and additional image data can be examined to determine if the route is gradually becoming more damaged, if the route is gradually changing location, if vegetation is growing toward and/or onto the route, or the like. Alternatively, the image data acquired at different times can be examined to identify damage to the route without identifying a trend in the condition of the route.
  • If the image data and additional image data indicate a trending problem with the route, then one or more corrective actions may need to be taken. As a result, flow of the method 400 can proceed to 414. On the other hand, if the image data and the additional image data do not indicate such a trending problem, then flow of the method 400 may return to 402 so that additional image data of the route may be obtained. Alternatively, no further analysis is performed on this or other image data, and the method 400 can terminate.
  • At 414, one or more alarm signals are generated. The alarm signals may be communicated from the analysis processor (which is onboard and/or off-board a vehicle system) to an off-board facility to request further inspection of the route and/or repair to the route. Optionally, an alarm signal may be communicated to one or more vehicle systems to warn the vehicle systems of the identified problem with the route. In one aspect, the alarm signal can be communicated to a scheduling system that generates schedules for vehicle systems so that the scheduling system can alter the schedules of the vehicle systems to avoid and/or slow down over the section of the route identified as having the problem.
  • In one example of the inventive subject matter described herein, a system (e.g., a wayside device imaging system) includes a digital camera and one or more analysis processors. The digital camera is configured to be disposed in a first vehicle system to generate image data within a field of view of the camera. The field of view includes at least a portion of a cab of the first vehicle system and one or more wayside devices disposed along a route being traveled by the first vehicle system. The cab includes a space where an operator of the first vehicle system is located during travel of the first vehicle system. The one or more analysis processors are configured to examine the image data generated by the camera to identify a condition of the one or more wayside devices. The condition includes at least one of damage to the one or more wayside devices, a missing wayside device, deterioration of the one or more wayside devices, or a change in terrain at or near the one or more wayside devices.
  • In one aspect, the condition that is identified includes only one of the damage to the one or more wayside devices, the missing wayside device, the deterioration of the one or more wayside devices, or the change in terrain at or near the one or more wayside devices. Optionally, the condition that is identified includes all of the damage to the one or more wayside devices, the missing wayside device, the deterioration of the one or more wayside devices, or the change in terrain at or near the one or more wayside devices. Alternatively, the condition that is identified includes two to three, but not all, of the damage to the one or more wayside devices, the missing wayside device, the deterioration of the one or more wayside devices, or the change in terrain at or near the one or more wayside devices.
  • In another aspect, the condition that is identified includes the damage to the route, the deteriorating condition of the route, and the condition of the one or more wayside devices. The condition of the one or more wayside devices can include damage to the one or more wayside devices, a missing wayside device, deterioration of the one or more wayside devices, and a change in terrain at or near the one or more wayside devices.
  • Optionally, the condition that is identified includes damage to the route and a deteriorating condition of the route, but does not include damage to the one or more wayside devices, the missing wayside device, the deterioration of the one or more wayside devices, or the change in terrain at or near the one or more wayside devices.
  • In another aspect, the condition that is identified includes damage to one or more wayside devices, a missing wayside device, deterioration of the one or more wayside devices, and a change in terrain at or near the one or more wayside devices, but does not include damage to the route or a deteriorating condition of the route.
  • In one aspect, the digital camera is a high definition camera.
  • In one aspect, the one or more analysis processors are configured to be disposed onboard the first vehicle system for examination of the image data.
  • In one aspect, the one or more analysis processors are configured to identify the condition of the one or more wayside devices based on at least one of an edge detection algorithm, pixel metrics, an object detection algorithm, baseline image data, or a pixel gradient in the image data.
  • In one aspect, the one or more wayside devices include a signaling light and the one or more analysis processors are configured to identify a broken or missing light of the signaling light based on the image data.
  • In one aspect, the one or more analysis processors are configured to edit the image data acquired during a trip of the first vehicle system to create edited image data that includes the image data representative of the condition of the one or more wayside devices and that does not include other image data.
  • In one aspect, the one or more analysis processors are configured to determine a location of the first vehicle system when the image data representative of the one or more wayside devices is acquired. The one or more analysis processors are configured to examine the image data representative of the one or more wayside devices and to not examine the image data acquired at one or more other locations.
  • In one aspect, the one or more analysis processors are configured to examine the image data from two or more previous trips of the first vehicle system and at least a second vehicle system over a common segment of the route to identify the condition of the one or more wayside devices.
  • In one aspect, the one or more analysis processors are configured to determine a location of the first vehicle system when the image data representative of at least one of damage to the route, the deteriorating condition of the route, or the condition of the one or more wayside devices is obtained. The one or more analysis processors also can be configured to examine the image data representative of at least one of the damage to the route, the deteriorating condition of the route, or the condition of the one or more wayside devices at the location, but to not examine the image data acquired at one or more other locations.
  • In another example of the inventive subject matter described herein, a method (e.g., for imaging a wayside device) includes generating image data within a field of view of a camera disposed onboard a first vehicle system. The field of view includes at least a portion of a cab of the first vehicle system and one or more wayside devices disposed along a route being traveled by the first vehicle system. The cab includes a space where an operator of the first vehicle system is located during travel of the first vehicle system. The method also includes examining (using one or more analysis processors) the image data generated by the camera to identify a condition of the one or more wayside devices. The condition of the one or more wayside devices includes at least one of damage to the one or more wayside devices, a missing wayside device, deterioration of the one or more wayside devices, or a change in terrain at or near the one or more wayside devices.
  • In one aspect, the image data is generated and examined while the first vehicle system is moving along the route.
  • In one aspect, the condition of the one or more wayside devices is identified based on at least one of an edge detection algorithm, pixel metrics, an object detection algorithm, baseline image data, or a pixel gradient in the image data.
  • In one aspect, the one or more wayside devices include a signaling light and the image data is examined to identify a broken or missing light of the signaling light based on the image data.
  • In one aspect, the method also includes editing the image data acquired during a trip of the first vehicle system to create edited image data that includes the image data representative of the condition of the one or more wayside devices and that does not include other image data.
  • In one aspect, the method also includes determining a location of the first vehicle system when the image data representative of the one or more wayside devices is acquired. The image data representative of the one or more wayside devices is examined based on the location, and the image data acquired at one or more other locations is not examined.
  • In one aspect, the image data is examined from two or more previous trips of the first vehicle system and at least a second vehicle system over a common segment of the route to identify the condition of the one or more wayside devices.
  • In another example of the inventive subject matter described herein, another system (e.g., a rail vehicle imaging system) includes a digital camera and one or more analysis processors. The camera is configured to be disposed in a rail vehicle and to generate image data within a field of view of the camera. The field of view includes at least a portion of a cab of the rail vehicle and one or more wayside devices along a track being traveled by the rail vehicle. The cab includes a space where an operator of the rail vehicle is located during travel of the rail vehicle. The one or more analysis processors are configured to be disposed onboard the rail vehicle and to examine the image data generated by the camera to identify a condition of the one or more wayside devices. The condition includes at least one of damage to the one or more wayside devices, a missing wayside device, or a changing condition of terrain at or near the one or more wayside devices.
  • In one aspect, the digital camera is a high definition camera.
  • In one aspect, the one or more analysis processors are configured to identify the condition of the one or more wayside devices based on at least one of an edge detection algorithm, pixel metrics, an object detection algorithm, baseline image data, or a pixel gradient in the image data.
  • In one aspect, the one or more wayside devices include at least one of an inspection wayside device that inspects the rail vehicle as the rail vehicle moves past the inspection wayside device or a signaling wayside device that communicates information with the rail vehicle as the rail vehicle moves past the signaling wayside device.
  • In one aspect, the one or more analysis processors are configured to determine a location of the rail vehicle when the image data representative of the condition of the one or more wayside devices is imaged.
  • In one example of the inventive subject matter described herein, a system (e.g., an imaging system) includes a digital camera and one or more analysis processors. The digital camera is configured to be disposed in a first vehicle system and to generate image data within a field of view of the camera. The field of view includes at least a portion of a cab of the first vehicle system and a portion of a route being traveled by the first vehicle system. The cab includes a space where an operator of the first vehicle system is located during travel of the first vehicle system. The one or more analysis processors are configured to examine the image data generated by the camera to identify at least one of damage to the route or a deteriorating condition of the route.
  • In one aspect, the digital camera is a high definition camera.
  • In one aspect, the one or more analysis processors are configured to be disposed onboard the first vehicle system for examination of the image data.
  • In one aspect, the one or more analysis processors are configured to identify the at least one of damage to the route or the deteriorating condition of the route using at least one of edge detection algorithms or pixel metrics.
  • In one aspect, the one or more analysis processors are configured to identify the damage to the route as shifting of one or more supporting bodies that connect rails of the route, bending of the rails of the route, twisting of the rails of the route, or spacing between the rails of the route that differs from a designated distance.
  • In one aspect, the one or more analysis processors are configured to edit the image data acquired during a trip of the first vehicle system to create edited image data that includes the image data representative of the at least one of damage to the route or the deteriorating condition of the route and that does not include other image data.
  • In one aspect, the one or more analysis processors are configured to determine a location of the first vehicle system when the image data representative of where the at least one of damage to the route or the deteriorating condition of the route is imaged.
  • In one aspect, the one or more analysis processors are configured to examine the image data from two or more previous trips of the first vehicle system and at least a second vehicle system over a common segment of the route to identify the at least one of damage to the route or the deteriorating condition of the route.
  • In another example of the inventive subject matter described herein, a method (e.g., an imaging method) includes generating image data within a field of view of a camera disposed onboard a first vehicle system. The field of view includes at least a portion of a cab of the first vehicle system and a portion of a route being traveled by the first vehicle system. The cab includes a space where an operator of the first vehicle system is located during travel of the first vehicle system. The method also includes examining (using one or more analysis processors) the image data generated by the camera to identify at least one of damage to the route or a deteriorating condition of the route.
  • In one aspect, the image data is generated and examined while the first vehicle system is moving along the route.
  • In one aspect, the at least one of damage to the route or the deteriorating condition of the route is identified by using at least one of edge detection algorithms or pixel metrics.
  • In one aspect, the damage to the route is identified by the one or more analysis processors as shifting of one or more supporting bodies that connect rails of the route, bending of the rails of the route, twisting of the rails of the route, or spacing between the rails of the route that differs from a designated distance.
  • In one aspect, the method also includes editing the image data acquired during a trip of the first vehicle system to create edited image data that includes the image data representative of the at least one of damage to the route or the deteriorating condition of the route and that does not include other image data.
  • In one aspect, the method also includes determining a location of the first vehicle system when the image data representative of where the at least one of damage to the route or the deteriorating condition of the route is imaged.
  • In one aspect, examining the image data includes examining the image data from two or more previous trips of the first vehicle system and at least a second vehicle system over a common segment of the route to identify the at least one of damage to the route or the deteriorating condition of the route.
  • In another example of the inventive subject matter described herein, another system (e.g., an imaging system) includes a digital camera and one or more analysis processors. The digital camera is configured to be disposed in a rail vehicle and to generate image data within a field of view of the camera. The field of view includes at least a portion of a cab of the rail vehicle and a portion of a track being traveled by the rail vehicle. The cab includes a space where an operator of the rail vehicle is located during travel of the rail vehicle. The one or more analysis processors are configured to be disposed onboard the rail vehicle and to examine the image data generated by the camera to identify at least one of damage to the track or a deteriorating condition of the track.
  • In one aspect, the digital camera is a high definition camera.
  • In one aspect, the one or more analysis processors are configured to identify the at least one of damage to the track or the deteriorating condition of the track using at least one of edge detection algorithms or pixel metrics.
  • In one aspect, the one or more analysis processors are configured to identify the damage to the track as bending of rails of the track, twisting of the rails of the track, or spacing between the rails of the track that differs from a designated distance.
  • In one aspect, the one or more analysis processors are configured to determine a location of the rail vehicle when the image data representative of where the at least one of damage to the track or the deteriorating condition of the track is imaged.
  • In one example of the inventive subject matter described herein, a system (e.g., an imaging system) includes a digital camera and one or more analysis processors. The digital camera is configured to be disposed in a first vehicle system and to generate image data within a field of view of the camera. The field of view includes at least a portion of a cab of the first vehicle system and a portion of a route being traveled by the first vehicle system. The cab includes a space where an operator of the first vehicle system is located during travel of the first vehicle system. The one or more analysis processors are configured to examine the image data generated by the camera to identify at least one of damage to the route or a deteriorating condition of the route.
  • In one aspect, the digital camera is a high definition camera.
  • In one aspect, the one or more analysis processors are configured to be disposed onboard the first vehicle system for examination of the image data.
  • In one aspect, the one or more analysis processors are configured to identify the at least one of damage to the route or the deteriorating condition of the route using at least one of edge detection algorithms or pixel metrics.
  • In one aspect, the one or more analysis processors are configured to identify the damage to the route as bending of rails of the route, twisting of the rails of the route, or spacing between the rails of the route that differs from a designated distance.
  • In one aspect, the one or more analysis processors are configured to edit the image data acquired during a trip of the first vehicle system to create edited image data that includes the image data representative of the at least one of damage to the route or the deteriorating condition of the route and that does not include other image data.
  • In one aspect, the one or more analysis processors are configured to determine a location of the first vehicle system when the image data representative of where the at least one of damage to the route or the deteriorating condition of the route is imaged.
  • In one aspect, the one or more analysis processors are configured to examine the image data from two or more previous trips of the first vehicle system and at least a second vehicle system over a common segment of the route to identify the at least one of damage to the route or the deteriorating condition of the route.
  • In another example of the inventive subject matter described herein, a method (e.g., an imaging method) includes generating image data within a field of view of a camera disposed onboard a first vehicle system. The field of view includes at least a portion of a cab of the first vehicle system and a portion of a route being traveled by the first vehicle system. The cab includes a space where an operator of the first vehicle system is located during travel of the first vehicle system. The method also includes examining (using one or more analysis processors) the image data generated by the camera to identify at least one of damage to the route or a deteriorating condition of the route.
  • In one aspect, the image data is generated and examined while the first vehicle system is moving along the route.
  • In one aspect, the at least one of damage to the route or the deteriorating condition of the route is identified by using at least one of edge detection algorithms or pixel metrics.
  • In one aspect, the damage to the route is identified by the one or more analysis processors as bending of rails of the route, twisting of the rails of the route, or spacing between the rails of the route that differs from a designated distance.
  • In one aspect, the method also includes editing the image data acquired during a trip of the first vehicle system to create edited image data that includes the image data representative of the at least one of damage to the route or the deteriorating condition of the route and that does not include other image data.
  • In one aspect, the method also includes determining a location of the first vehicle system when the image data representative of where the at least one of damage to the route or the deteriorating condition of the route is imaged.
  • In one aspect, examining the image data includes examining the image data from two or more previous trips of the first vehicle system and at least a second vehicle system over a common segment of the route to identify the at least one of damage to the route or the deteriorating condition of the route.
  • In another example of the inventive subject matter described herein, another system (e.g., an imaging system) includes a digital camera and one or more analysis processors. The digital camera is configured to be disposed in a rail vehicle and to generate image data within a field of view of the camera. The field of view includes at least a portion of a cab of the rail vehicle and a portion of a track being traveled by the rail vehicle. The cab includes a space where an operator of the rail vehicle is located during travel of the rail vehicle. The one or more analysis processors are configured to be disposed onboard the rail vehicle and to examine the image data generated by the camera to identify at least one of damage to the track or a deteriorating condition of the track.
  • In one aspect, the digital camera is a high definition camera.
  • In one aspect, the one or more analysis processors are configured to identify the at least one of damage to the track or the deteriorating condition of the track using at least one of edge detection algorithms or pixel metrics.
  • In one aspect, the one or more analysis processors are configured to identify the damage to the track as bending of rails of the track, twisting of the rails of the track, or spacing between the rails of the track that differs from a designated distance.
  • In one aspect, the one or more analysis processors are configured to determine a location of the rail vehicle when the image data representative of where the at least one of damage to the track or the deteriorating condition of the track is imaged.
  • In another example of the inventive subject matter described herein, a system (e.g., an imaging system) includes a digital camera configured to be disposed in a first vehicle system. The camera is configured to generate image data within a field of view of the camera. The field of view includes at least a portion of a cab of the first vehicle system and at least one of a portion of a route being traveled by the first vehicle system or one or more wayside devices disposed along the route being traveled by the first vehicle system. The cab includes a space where an operator of the first vehicle system is located during travel of the first vehicle system. The system also can include one or more analysis processors configured to examine the image data generated by the camera to identify at least one of damage to the route, a deteriorating condition of the route, or a condition of the one or more wayside devices. The condition of the one or more wayside devices includes at least one of damage to the one or more wayside devices, a missing wayside device, deterioration of the one or more wayside devices, or a change in terrain at or near the one or more wayside devices.
  • In one aspect, the one or more analysis processors are configured to identify at least one of the damage to the route, the deteriorating condition of the route, or the condition of the one or more wayside devices based on at least one of an edge detection algorithm, pixel metrics, an object detection algorithm, baseline image data, or a pixel gradient in the image data.
  • In one aspect, the one or more analysis processors are configured to edit the image data acquired during a trip of the first vehicle system to create edited image data that includes the image data representative of the at least one of the damage to the route, the deteriorating condition of the route, or the condition of the one or more wayside devices but that does not include other image data.
  • In one aspect, the one or more analysis processors are configured to determine a location of the first vehicle system when the image data representative of at least one of damage to the route, the deteriorating condition of the route, or the condition of the one or more wayside devices is obtained. The one or more analysis processors also can be configured to examine the image data representative of at least one of damage to the route, a deteriorating condition of the route, or a condition of the one or more wayside devices, the condition of the one or more wayside devices including at least one of damage to the one or more wayside devices but to not examine the image data acquired at one or more other locations.
  • In another example of the inventive subject matter described herein, another method (e.g., an imaging method) includes generating image data within a field of view of a camera disposed onboard a first vehicle system. The field of view includes at least a portion of a cab of the first vehicle system and at least one of a portion of a route being traveled by the first vehicle system or one or more wayside devices disposed along the route being traveled by the first vehicle system. The cab includes a space where an operator of the first vehicle system is located during travel of the first vehicle system. The method also can include examining, using one or more analysis processors, the image data generated by the camera to identify at least one of damage to the route, a deteriorating condition of the route, or a condition of the one or more wayside devices. The condition includes at least one of damage to the one or more wayside devices, a missing wayside device, deterioration of the one or more wayside devices, or a change in terrain at or near the one or more wayside devices.
  • In one aspect, the at least one of damage to the route, the deteriorating condition of the route, or the condition of the one or more wayside devices is identified based on at least one of an edge detection algorithm, pixel metrics, an object detection algorithm, baseline image data, or a pixel gradient in the image data.
  • In one aspect, the method also includes editing the image data acquired during a trip of the first vehicle system to create edited image data that includes the image data representative of the at least one of damage to the route, the deteriorating condition of the route, or the condition of the one or more wayside devices but does not include other image data.
  • In one aspect, the method also includes determining a location of the first vehicle system when the image data representative of the at least one of damage to the route, the deteriorating condition of the route, or the condition of the one or more wayside devices is generated. The image data that is representative of the at least one of damage to the route, the deteriorating condition of the route, or the condition of the one or more wayside devices is examined based on the location and the image data acquired at one or more other locations is not examined.
  • In another example of the inventive subject matter described herein, another system (e.g., an imaging system) includes a digital camera configured to be disposed in a rail vehicle. The camera is configured to generate image data within a field of view of the camera. The field of view includes at least a portion of a cab of the rail vehicle and at least one of a portion of a track outside of the rail vehicle or one or more wayside devices along the track being traveled by the rail vehicle. The cab includes a space where an operator of the rail vehicle is located during travel of the rail vehicle. The system also includes one or more analysis processors configured to be disposed onboard the rail vehicle and to examine the image data generated by the camera to identify a condition of at least one of the track or the one or more wayside devices. The condition includes at least one of damage to the track, damage to the one or more wayside devices, a missing wayside device, or a changing condition of terrain at or near the one or more wayside devices.
  • In one aspect, the one or more analysis processors are configured to identify the condition of at least one of the track or the one or more wayside devices based on at least one of an edge detection algorithm, pixel metrics, an object detection algorithm, baseline image data, or a pixel gradient in the image data.
  • In one aspect, the one or more analysis processors are configured to determine a location of the rail vehicle when the image data representative of the condition of at least one of the track or the one or more wayside devices is imaged.
  • It is to be understood that the above description is intended to be illustrative, and not restrictive. For example, the above-described embodiments (and/or aspects thereof) may be used in combination with each other. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the inventive subject matter without departing from its scope. While the dimensions and types of materials described herein are intended to define the parameters of the inventive subject matter, they are by no means limiting and are exemplary embodiments. Many other embodiments will be apparent to one of ordinary skill in the art upon reviewing the above description. The scope of the inventive subject matter should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled. In the appended claims, the terms “including” and “in which” are used as the plain-English equivalents of the respective terms “comprising” and “wherein.” Moreover, in the following claims, the terms “first,” “second,” and “third,” etc. are used merely as labels, and are not intended to impose numerical requirements on their objects. Further, the limitations of the following claims are not written in means-plus-function format and are not intended to be interpreted based on 35 U.S.C. § 112(f), unless and until such claim limitations expressly use the phrase “means for” followed by a statement of function void of further structure.
  • This written description uses examples to disclose several embodiments of the inventive subject matter and also to enable a person of ordinary skill in the art to practice the embodiments of the inventive subject matter, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the inventive subject matter is defined by the claims, and may include other examples that occur to those of ordinary skill in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements with insubstantial differences from the literal languages of the claims.
  • The foregoing description of certain embodiments of the inventive subject matter will be better understood when read in conjunction with the appended drawings. To the extent that the figures illustrate diagrams of the functional blocks of various embodiments, the functional blocks are not necessarily indicative of the division between hardware circuitry. Thus, for example, one or more of the functional blocks (for example, processors or memories) may be implemented in a single piece of hardware (for example, a general purpose signal processor, microcontroller, random access memory, hard disk, and the like). Similarly, the programs may be stand-alone programs, may be incorporated as subroutines in an operating system, may be functions in an installed software package, and the like. The various embodiments are not limited to the arrangements and instrumentality shown in the drawings.
  • As used herein, an element or step recited in the singular and proceeded with the word “a” or “an” should be understood as not excluding plural of said elements or steps, unless such exclusion is explicitly stated. Furthermore, references to “one embodiment” of the inventive subject matter are not intended to be interpreted as excluding the existence of additional embodiments that also incorporate the recited features. Moreover, unless explicitly stated to the contrary, embodiments “comprising,” “including,” or “having” an element or a plurality of elements having a particular property may include additional such elements not having that property.

Claims (20)

    What is claimed is:
  1. 1. A system comprising:
    a digital camera configured to be disposed in a first vehicle system, the camera configured to generate image data within a field of view of the camera, the field of view including at least a portion of a cab of the first vehicle system and at least one of a portion of a route being traveled by the first vehicle system or one or more wayside devices disposed along the route being traveled by the first vehicle system, the cab including a space where an operator of the first vehicle system is located during travel of the first vehicle system; and
    one or more analysis processors configured to examine the image data generated by the camera to identify at least one of damage to the route, a deteriorating condition of the route, or a condition of the one or more wayside devices, the condition of the one or more wayside devices including at least one of damage to the one or more wayside devices, a missing wayside device, deterioration of the one or more wayside devices, or a change in terrain at or near the one or more wayside devices.
  2. 2. The system of claim 1, wherein the digital camera is a high definition camera.
  3. 3. The system of claim 1, wherein the one or more analysis processors are configured to be disposed onboard the first vehicle system for examination of the image data.
  4. 4. The system of claim 1, wherein the one or more analysis processors are configured to identify at least one of the damage to the route, the deteriorating condition of the route, or the condition of the one or more wayside devices based on at least one of an edge detection algorithm, pixel metrics, an object detection algorithm, baseline image data, or a pixel gradient in the image data.
  5. 5. The system of claim 1, wherein the one or more wayside devices include a signaling light and the one or more analysis processors are configured to identify a broken or missing light of the signaling light based on the image data.
  6. 6. The system of claim 1, wherein the one or more analysis processors are configured to identify the damage to the route as shifting of one or more supporting bodies that connect rails of the route, bending of the rails of the route, twisting of the rails of the route, or a spacing between the rails of the route that differs from a designated distance.
  7. 7. The system of claim 1, wherein the one or more analysis processors are configured to edit the image data acquired during a trip of the first vehicle system to create edited image data that includes the image data representative of the at least one of the damage to the route, the deteriorating condition of the route, or the condition of the one or more wayside devices but that does not include other image data.
  8. 8. The system of claim 1, wherein the one or more analysis processors are configured to determine a location of the first vehicle system when the image data representative of at least one of damage to the route, the deteriorating condition of the route, or the condition of the one or more wayside devices is obtained, and the one or more analysis processors are configured to examine the image data representative of at least one of the damage to the route, the deteriorating condition of the route, or the condition of the one or more wayside devices at the location, but to not examine the image data acquired at one or more other locations.
  9. 9. A method comprising:
    generating image data within a field of view of a camera disposed onboard a first vehicle system, the field of view including at least a portion of a cab of the first vehicle system and at least one of a portion of a route being traveled by the first vehicle system or one or more wayside devices disposed along the route being traveled by the first vehicle system, the cab including a space where an operator of the first vehicle system is located during travel of the first vehicle system; and
    examining, using one or more analysis processors, the image data generated by the camera to identify at least one of damage to the route, a deteriorating condition of the route, or a condition of the one or more wayside devices, the condition of the one or more wayside devices including at least one of damage to the one or more wayside devices, a missing wayside device, deterioration of the one or more wayside devices, or a change in terrain at or near the one or more wayside devices.
  10. 10. The method of claim 9, wherein the image data is generated and examined while the first vehicle system is moving along the route.
  11. 11. The method of claim 9, wherein the at least one of damage to the route, the deteriorating condition of the route, or the condition of the one or more wayside devices is identified based on at least one of an edge detection algorithm, pixel metrics, an object detection algorithm, baseline image data, or a pixel gradient in the image data.
  12. 12. The method of claim 9, wherein the one or more wayside devices include a signaling light and the image data is examined to identify a broken or missing light of the signaling light based on the image data.
  13. 13. The method of claim 9, wherein the damage to the route is identified by the one or more analysis processors as a shifting of one or more supporting bodies that connect rails of the route, bending of the rails of the route, twisting of the rails of the route, or a spacing between the rails of the route that differs from a designated distance.
  14. 14. The method of claim 9, further comprising editing the image data acquired during a trip of the first vehicle system to create edited image data that includes the image data representative of the at least one of damage to the route, the deteriorating condition of the route, or the condition of the one or more wayside devices but does not include other image data.
  15. 15. The method of claim 9, further comprising determining a location of the first vehicle system when the image data representative of the at least one of damage to the route, the deteriorating condition of the route, or the condition of the one or more wayside devices is generated, wherein the image data representative of the at least one of damage to the route, the deteriorating condition of the route, or the condition of the one or more wayside devices is examined based on the location and the image data acquired at one or more other locations is not examined
  16. 16. A system comprising:
    a digital camera configured to be disposed in a rail vehicle, the camera configured to generate image data within a field of view of the camera, the field of view including at least a portion of a cab of the rail vehicle and at least one of a portion of a track outside of the rail vehicle or one or more wayside devices along the track being traveled by the rail vehicle, the cab including a space where an operator of the rail vehicle is located during travel of the rail vehicle; and
    one or more analysis processors configured to be disposed onboard the rail vehicle and to examine the image data generated by the camera to identify a condition of at least one of the track or the one or more wayside devices, the condition including at least one of damage to the track, damage to the one or more wayside devices, a missing wayside device, or a changing condition of terrain at or near the one or more wayside devices.
  17. 17. The system of claim 16, wherein the digital camera is a high definition camera.
  18. 18. The system of claim 16, wherein the one or more analysis processors are configured to identify the condition of the at least one of the track or the one or more wayside devices based on at least one of an edge detection algorithm, pixel metrics, an object detection algorithm, baseline image data, or a pixel gradient in the image data.
  19. 19. The system of claim 16, wherein the one or more wayside devices include at least one of an inspection wayside device that inspects the rail vehicle as the rail vehicle moves past the inspection wayside device or a signaling wayside device that communicates information with the rail vehicle as the rail vehicle moves past the signaling wayside device.
  20. 20. The system of claim 16, wherein the one or more analysis processors are configured to determine a location of the rail vehicle when the image data representative of the condition of the at least one of the track or the one or more wayside devices is imaged.
US14457353 2014-02-17 2014-08-12 Vehicle imaging system and method Pending US20150235094A1 (en)

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US14457353 US20150235094A1 (en) 2014-02-17 2014-08-12 Vehicle imaging system and method
US14541370 US10110795B2 (en) 2002-06-04 2014-11-14 Video system and method for data communication
CN 201580014352 CN106061822B (en) 2014-02-17 2015-01-30 Vehicle imaging systems and methods
AU2015217536A AU2015217536A1 (en) 2014-02-17 2015-01-30 Video system and method for data communication
CN 201580020130 CN106537900A8 (en) 2014-02-17 2015-01-30 Video system and method for data communication
PCT/US2015/013735 WO2015123035A1 (en) 2014-02-17 2015-01-30 Video system and method for data communication
PCT/US2015/013720 WO2015123034A8 (en) 2014-02-17 2015-01-30 Vehicle imaging system and method
AU2015217535A AU2015217535A1 (en) 2014-02-17 2015-01-30 Vehicle imaging system and method
AU2015218266A AU2015218266A1 (en) 2014-02-17 2015-02-17 Aerial camera system and method for identifying route-related hazards
CN 201580020285 CN106458238A8 (en) 2014-02-17 2015-02-17 The method of aerial photography equipment and systems used to identify the hazards associated route
PCT/US2015/016151 WO2015123669A1 (en) 2014-02-17 2015-02-17 Aerial camera system and method for identifying route-related hazards
US14624069 US9873442B2 (en) 2002-06-04 2015-02-17 Aerial camera system and method for identifying route-related hazards
US14884233 US9919723B2 (en) 2002-06-04 2015-10-15 Aerial camera system and method for determining size parameters of vehicle systems
US15819877 US20180097288A1 (en) 2014-02-17 2017-11-21 Aerial camera system, method for identifying route-related hazards, and microstrip antenna

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