Control system for railway yard and related methods

1. A control system for a railway yard with a plurality of railroad tracks, the control system comprising:

a plurality of remote control locomotives (RCLs) and sets of railcars respectively associated therewith on the plurality of railroad tracks;

a plurality of railyard sensors configured to generate railyard sensor data of the plurality of railroad tracks; and

a server in communication with said plurality of RCLs and said plurality of railyard sensors, said server configured to

generate a database associated with the sets of railcars based upon the railyard sensor data, the database comprising, for each railcar, a railcar type value, a railcar logo image, and a vehicle classification value, and

selectively control said plurality of RCLs to position the sets of railcars within the plurality of railroad tracks based upon the railyard sensor data,

wherein said plurality of railyard sensors comprises an image sensor configured to generate railyard image data, and a proximity sensor configured to detect a presence of plurality of RCLs, and

wherein said server is configured to identify each railcar based upon the railyard image data.

2. The control system of claim 1 wherein each RCL comprises a geolocation device configured to generate a geolocation value for a respective RCL, a wireless transceiver configured to communicate with said server, and a controller coupled to said wireless transceiver and said geolocation device; and wherein said controller is configured to transmit the geolocation value for the respective RCL to said server.

3. The control system of claim 1 wherein said server is configured to monitor said plurality of RCLs for railyard traffic violations.

4. The control system of claim 1 wherein said server is configured to perform optical character recognition (OCR) on the railyard image data.

5. The control system of claim 1 wherein said server is configured to perform machine learning on the railyard image data.

6. The control system of claim 5 wherein said server is configured to execute a first machine learning model comprising a convolutional neural network (CNN) trained to predict a location of text sequences in the railyard image data.

7. The control system of claim 6 wherein said server is configured to execute a second machine learning model comprising a recurrent neural network (RNN) for scanning the text sequences and predicting a sequence of missing characters.

8. The control system of claim 1 wherein each railcar comprises one of a container, a railcar container, a trailer, a chassis, a boxcar, a cargobeamer car, a coil car, a combine car, a flatcar, a schnable car, a gondola car, a Presflo and Prestwin car, a bulk cement wagon car, a roll-block car, a slate wagon car, a stock car, a tank car, a milk car, a transporter wagon car, and a well car.

9. A server for controlling a railway yard with a plurality of railroad tracks, a plurality of remote control locomotives (RCLs) and sets of railcars respectively associated therewith on the plurality of railroad tracks, the plurality of RCLs being communication with the server, a plurality of railyard sensors in communication with the server and configured to generate railyard sensor data of the plurality of railroad tracks, the server comprising:

a processor and memory coupled thereto and configured to:

generate a database associated with the sets of railcars based upon the railyard sensor data, the database comprising, for each railcar, a railcar type value, a railcar logo image, and a vehicle classification value, and

selectively control said plurality of RCLs to position the sets of railcars within the plurality of railroad tracks based upon the railyard sensor data,

wherein said plurality of railyard sensors comprises an image sensor configured to generate railyard image data, and a proximity sensor configured to detect a presence of plurality of RCLs, and

wherein said processor is configured to identify each railcar based upon the railyard image data.

10. The server of claim 9 wherein each RCL comprises a geolocation device configured to generate a geolocation value for a respective RCL, a wireless transceiver configured to communicate with said server, and a controller coupled to said wireless transceiver and said geolocation device; and wherein said controller is configured to transmit the geolocation value for the respective RCL to said server.

11. The server of claim 9 wherein said processor is configured to monitor said plurality of RCLs for railyard traffic violations.

12. The server of claim 9 wherein said processor is configured to perform optical character recognition (OCR) on the railyard image data.

13. The server of claim 9 wherein said processor is configured to perform machine learning on the railyard image data.

14. The server of claim 13 wherein said processor is configured to execute a first machine learning model comprising a convolutional neural network (CNN) trained to predict a location of text sequences in the railyard image data; and wherein said processor is configured to execute a second machine learning model comprising a recurrent neural network (RNN) for scanning the text sequences and predicting a sequence of missing characters.

15. The server of claim 9 wherein each wherein each railcar comprises one of a container, a railcar container, a trailer, a chassis, a boxcar, a cargobeamer car, a coil car, a combine car, a flatcar, a schnable car, a gondola car, a Presflo and Prestwin car, a bulk cement wagon car, a roll-block car, a slate wagon car, a stock car, a tank car, a milk car, a transporter wagon car, and a well car.

16. A method for operating a control system for a railway yard with a plurality of railroad tracks, the control system comprising a plurality of remote control locomotives (RCLs) and sets of railcars respectively associated therewith on the plurality of railroad tracks, and a plurality of railyard sensors configured to generate railyard sensor data of the plurality of railroad tracks, the method comprising:

operating a server in communication with the plurality of RCLs and the plurality of railyard sensors to generate a database associated with the sets of railcars based upon the railyard sensor data, the database comprising, for each railcar, a railcar type value, a railcar logo image, and a vehicle classification value; and

operating the server to selectively control the plurality of RCLs to position the sets of railcars within the plurality of railroad tracks based upon the railyard sensor data,

wherein said plurality of railyard sensors comprises an image sensor configured to generate railyard image data, and a proximity sensor configured to detect a presence of plurality of RCLs, and

wherein said server is configured to identify each railcar based upon the railyard image data.

17. The method of claim 16 wherein each RCL comprises a geolocation device configured to generate a geolocation value for a respective RCL, a wireless transceiver configured to communicate with the server, and a controller coupled to the wireless transceiver and the geolocation device; and further comprising transmitting the geolocation value for the respective RCL to the server.

18. The method of claim 16 further comprising operating the server to monitor the plurality of RCLs for railyard traffic violations.

19. The method of claim 16 wherein each railcar comprises one of a container, a railcar container, a trailer, a chassis, a boxcar, a cargobeamer car, a coil car, a combine car, a flatcar, a schnable car, a gondola car, a Presflo and Prestwin car, a bulk cement wagon car, a roll-block car, a slate wagon car, a stock car, a tank car, a milk car, a transporter wagon car, and a well car.