Patent Application
20240067242
The present disclosure relates to railway signaling, and more particularly relates to a system and method for managing operations of a train relative to a fouling mark.
A fouling mark is provided between two converging railway tracks or lines at a point beyond which center-to-center distance between the railway tracks is less than a stipulated minimum distance.
Typically, a guard of the train is responsible for ensuring, through visual inspection, that the train on the main line A or the loop line B has cleared the fouling mark. If the guard fails to clear the fouling mark, risk of collision with another train increases.
In existing art, Head of Train devices provides a manual mechanism for determining distance travelled by a train in specific interval of time. In particular, the driver may press a button provided within a control panel inside the cab of the train, upon seeing a fouling mark, to see how far the train has travelled beyond the fouling mark. As may be understood, the existing art relies heavily on judgment of the driver and the guard to determine if the train has successfully cleared the fouling mark.
Considering the above, there exists a need for a mechanism that enables a train to successfully declare a fouling mark without the necessity for manual intervention.
In an aspect of the present disclosure, a system for managing operations of a train relative to a fouling mark is disclosed. The system comprises one or more sources, an End-of-Train device mounted at a rear-end of the train, a Head-of-Train device mounted at a front-end of the train communicatively coupled to the End-of-train device and the one or more sources.
The Head-of-Train device is configured to detect the fouling mark based on inputs from the one or more sources. In an embodiment, the one or more sources comprise at least one of a sensing unit mounted on the train, a wayside unit and a cloud server. The inputs from the one or more sources comprises at least one of a GNSS location of the fouling mark and a distance-to-the-fouling mark, and wherein the distance-to-the-fouling mark is a distance between the train and the fouling mark when the train is approaching the fouling mark.
The Head-of-Train device is further configured to dynamically determine whether the train clears the fouling mark, upon detecting the fouling mark. In an embodiment, the Head-of-Train device is configured to dynamically determine whether the train clears the fouling mark by comparing the GNSS location of the fouling mark and a real-time GNSS location of the End-of-Train device. In another embodiment, the Head-of-Train device is configured to dynamically determine whether the train clears the fouling mark based on a confirmation message received from the cloud server, wherein the confirmation message indicates that the End-of-Train device has crossed the fouling mark. In yet another embodiment, the Head-of-Train device is configured to dynamically determine whether the train clears the fouling mark by dynamically computing a stopping point when the fouling mark is detected ahead of the train, based on the distance-to-the-fouling mark and a length of the train, wherein the stopping point is a location that the Head-of-Train device must reach for the train to successfully clear the fouling mark. Further, the stopping point is compared to a real-time GNSS location of the Head-of-Train device to determine if the train has cleared the fouling mark. In yet another embodiment, the Head-of-Train device is configured to dynamically determine whether the train clears the fouling mark by dynamically computing a stopping distance for the train based on a distance travelled by the train in real-time after the Head-of-Train device crosses the fouling mark, wherein the train successfully clears the fouling mark when the stopping distance reduces to zero.
The Head-of-Train device is further configured to identify one or more actions to be performed using a predefined logic, before the train clears the fouling mark. In an embodiment, the one or more actions comprises generating a notification indicating a position of the train relative to the fouling mark, on a driver machine interface of the train. In another embodiment, the one or more actions comprises broadcasting a status message indicating that clearing of the fouling mark by the train is incomplete, to one or more apparatus associated with a railway signaller. In yet another embodiment, the one or more actions comprises transmitting a status message, to the cloud server, indicating that clearing of the fouling mark by the train is incomplete, wherein the status message enables the cloud server to further transmit a notification, to trailing trains, indicating that clearing of the fouling mark by the train is incomplete. The Head-of-Train device is further configured to execute one or more machine-readable instructions for performing the one or more actions identified.
In an embodiment, the Head-of-Train device is further configured to transmit an update message indicative of the GNSS location of the fouling mark to the cloud server, wherein the cloud server updates an artificial intelligence model based on the GNSS location of the fouling mark for enabling subsequent identification of the fouling mark by at least one of the cloud server and the Head-of-Train device.
In another aspect of the present disclosure, a method for managing operation of a train relative to a fouling mark is disclosed. The method comprises detecting, by a Head-of-Train device mounted at a front-end of the train, the fouling mark based on inputs from one or more sources, wherein the Head-of-Train device is communicatively coupled to an End-of-Train device mounted at a rear-end of the train. In an embodiment, the one or more sources comprise at least one of a sensing unit mounted on the train, a wayside unit and a cloud server. The inputs from the one or more sources comprises at least one of a GNSS location of the fouling mark and a distance-to-the-fouling mark, and wherein the distance-to-the-fouling mark is a distance between the train and the fouling mark when the train is approaching the fouling mark.
The method further comprises dynamically determining, by the Head-of-Train device, whether the train clears the fouling mark upon detecting the fouling mark. In an embodiment, dynamically determining whether the train clears the fouling mark comprises comparing the GNSS location of the fouling mark and a real-time GNSS location of the End-of-Train device. In another embodiment, dynamically determining whether the train clears the fouling mark based on a confirmation message received from the cloud server, wherein the confirmation message indicates that the End-of-Train device has crossed the fouling mark. In yet another embodiment, dynamically determining whether the train clears the fouling mark comprises dynamically computing a stopping point when the fouling mark is detected ahead of the train, based on the distance-to-the-fouling mark and a length of the train, wherein the stopping point is a location that the Head-of-Train device must reach for the train to successfully clear the fouling mark. Further, the stopping point is compared to a real-time GNSS location of the Head-of-Train device to determine if the train has cleared the fouling mark. In yet another embodiment, dynamically determining whether the train clears the fouling mark comprises dynamically computing a stopping distance for the train based on a distance travelled by the train in real-time after the Head-of-Train device crosses the fouling mark, wherein the train successfully clears the fouling mark when the stopping distance reduces to zero.
The method further comprises identifying, by the Head-of-Train device, one or more actions to be performed using a predefined logic, before the train clears the fouling mark. In an embodiment, the one or more actions comprises generating a notification indicating a position of the train relative to the fouling mark, on a driver machine interface of the train. In another embodiment, the one or more actions comprises broadcasting a status message indicating that clearing of the fouling mark by the train is incomplete, to one or more apparatus associated with a railway signaler. In yet another embodiment, the one or more actions comprises transmitting a status message, to the cloud server, indicating that clearing of the fouling mark by the train is incomplete, wherein the status message enables the cloud server to further transmit a notification, to trailing trains, indicating that clearing of the fouling mark by the train is incomplete. The method further comprises executing, by the Head-of-Train device, one or more machine-readable instructions for performing the one or more actions identified.
In an embodiment, the method further comprises transmitting, by the Head-of-Train device, an update message indicative of the GNSS location of the fouling mark to the cloud server, wherein the cloud server updates an artificial intelligence model based on the GNSS location of the fouling mark for enabling subsequent identification of the fouling mark by at least one of the cloud server and the Head-of-Train device.
The above-mentioned attributes, features, and advantages of this disclosure and the manner of achieving them, will become more apparent and understandable (clear) with the following description of embodiments of the disclosure in conjunction with the corresponding drawings. The illustrated embodiments are intended to illustrate, but not limit the disclosure.
The present disclosure is further described hereinafter with reference to illustrated embodiments shown in the accompanying drawings, in which:
Hereinafter, embodiments for carrying out the present disclosure are described in detail. The various embodiments are described with reference to the drawings, wherein like reference numerals are used to refer to like elements throughout. In the following description, for purpose of explanation, numerous specific details are set forth in order to provide a thorough understanding of one or more embodiments. It may be evident that such embodiments may be practiced without these specific details.
The Head-of-Train device 210 comprises a first processing unit 225, a first memory 230, a first Global Navigation Satellite System (GNSS) receiver 235 and a first communication unit 240 as shown in
The first memory 230 may include one or more of a volatile memory and a non-volatile memory. The first memory 230 may be coupled for communication with the first processing unit 225. The first processing unit 225 may execute instructions and/or code stored in the first memory 230. A variety of computer-readable storage media may be stored in and accessed from the first memory 230. The first memory 230 may include any suitable element for storing data and machine-readable instructions, such as read only memory, random access memory, erasable programmable read only memory, electrically erasable programmable read only memory, hard drive, removable media drive for handling compact disks, digital video disks, diskettes, magnetic tape cartridges, memory cards, and the like.
The first memory 230 comprises a fouling mark monitoring module 245 that is stored in the form of machine-readable instructions for execution by the first processing unit 225. These machine-readable instructions when executed by the first processing unit 225, causes the Head-of-Train device 210 to perform one or more functions necessary for the Head-of-Train device 210 for providing associated with managing operation of the train 205 relative to a fouling mark. The first memory 230 also stores a unique identifier associated with the Head-of-Train device 210.
The first GNSS receiver 235 enables the Head-of-Train device 210 to receive GNSS data from a plurality of Global Navigation Satellite System (GNSS) satellites. Based on the GNSS data, the first processing unit 225 determines the GNSS location of the Head-of-Train device 210. The term ‘GNSS location’ as used herein, refers to a geographical coordinate computed based on the GNSS data received from GNSS satellites. Non-limiting examples of Global Navigation Satellite Systems include, Global Positioning System (GPS), Galileo, GLONASS and BeiDou.
The first communication unit 240 enables the Head-of-Train device 210 to communicate with the End-of-Train device 215 through Radio Frequency (RF) Communication. Similarly, the first communication unit 240 is also configured to enable communication between the Head-of-Train device 210 and other apparatus including but not limited to, the cloud server 216, the sensing unit 220, wayside units, other onboard systems on the train 205 or communication systems on other trains. In the present embodiment, the first communication unit 240 enables transmission of the real-time GNSS location of the Head-of-Train device 210, over periodic intervals to the cloud server 216. Further, the first communication unit 240 may also be configured to transmit other information such as GNSS location of fouling marks, a status of the train 205 or one or more subsystems on the train 205, status messages etc. to the cloud server 216.
The End-of-Train device 215 comprises a second processing unit 250, a second memory 255, a second GNSS receiver 260 and a second communication unit 265 as shown in
The second memory 255 may include one or more of a volatile memory and a non-volatile memory. The second memory 255 may be coupled for communication with the second processing unit 250. The second processing unit 250 may execute instructions and/or code stored in the second memory 255. A variety of computer-readable storage media may be stored in and accessed from the second memory 255. The second memory 255 may include any suitable element for storing data and machine-readable instructions, such as read only memory, random access memory, erasable programmable read only memory, electrically erasable programmable read only memory, hard drive, removable media drive for handling compact disks, digital video disks, diskettes, magnetic tape cartridges, memory cards, and the like.
The second memory 255 comprises a fouling clearance assist module 270, stored in the form of machine-readable instructions and executable by the second processing unit 250. These machine-readable instructions when executed by the second processing unit 250, causes the End-of-Train device 215 to perform one or more functions for managing operations of the train 205 relative to a fouling mark. The second GNSS receiver 260 enables the End-of-Train device 215 to receive GNSS data from a plurality of GNSS satellites. Based on the GNSS data received by the second GNSS receiver 260, the second processing unit 250 determines the GNSS location of the End-of-Train device 215.
The second communication unit 265 enables the End-of-Train device 215 to communicate with the Head-of-Train device 210 through Radio Frequency (RF) Communication. The second communication unit 265 also enables communication between the End-of-Train device 215 and other apparatus including but not limited to, the cloud server 216, the sensing unit 220, wayside units, other onboard systems on the train 205 or communication systems on other trains. In the present embodiment, the real-time GNSS location of the End-of-Train device 215 is transmitted to the cloud server 216, over periodic intervals. In an implementation, the GNSS location of the End-of-Train device 215 is transmitted to the cloud server 216 continuously during a specific interval of time. For example, the interval of time may correspond to time period between detection of a fouling mark and clearing of the fouling mark by the train 205. As used herein, the phrase ‘clearing the fouling mark’ refers to a situation wherein all wheels of the train 205 have crossed the fouling mark, i.e., when the End-of-Train device 215 has crossed the fouling mark.
The cloud server 216 comprises a third processing unit 272, a third memory 274, a storage unit 276, a third communication unit 278, a network interface 280, a standard interface or bus 282 as shown in
The storage unit 276 comprises a non-volatile memory which includes a database 284. The database 284 stores GNSS locations corresponding to fouling marks in one or more predefined regions or geographical territories. In another embodiment, the Head-of-Train device 210 and/or the End-of-Train device 215 may communicate with the cloud server 216 using a publish-subscribe mechanism. In an implementation, the publish-subscribe mechanism may be implemented based on MQTT protocol. For example, the Head-of-Train device 210 may subscribe to a topic associated with fouling mark locations on the cloud server 216, and the cloud server 216 may publish fouling mark locations, e.g., based on a GNSS location of the Head-of-Train device 210, to an endpoint associated with the Head-of-Train device 210.
In an implementation, the database 284 may also store unique identifiers corresponding to the Head-of-Train devices and End-of-Train devices for every train operating within a geographical territory. In an example, the unique identifiers are assigned to each of the Head-of-Train devices and End-of-Train devices by an Original Equipment Manufacturer. In another example, the unique identifiers are provided based on naming conventions specified by railway authorities. As the Head-of-Train device 210 is fixed permanently to the locomotive, the database 284 may store a unique identifier associated with the locomotive or the train 205 in place of the unique identifier of the Head-of-Train device 210.
In yet another example, the unique identifiers corresponding to the End-of-Train device 215 and the Head-of-Train device 210 is mapped to a unique identifier associated with the train 205 by a driver of the train 205 via a client device. The driver may further update the cloud server 216 with the unique identifiers through the client device. In yet another example, the driver or a maintenance personnel may configure the Head-of-Train device 210 using a unique identifier associated with the End-of-Train device 215. Further, the Head-of-Train device 210 may update the database 284 by transmitting a message containing the unique identifiers corresponding to the Head-of-Train device 210 and the End-of-Train device 215 to the cloud server 216, upon configuration. In yet another embodiment, the driver may configure the Head-of-Train device 210 with a unique identifier of the train 205. Upon configuration, the Head-of-Train device 210 may further transmit the unique identifier of the train 205 to the cloud server 216. Similarly, the End-of-Train device 210 may also transmit a unique identifier associated with the End-of-Train device 215, upon configuration or installation.
The bus 282 acts as interconnect between the third processing unit 272, the third memory 274, the storage unit 276, and the network interface 280. The third communication unit 278 enables the cloud server 216 to communicate with the End-of-Train device 215 and the Head-of-Train device 210. The third communication unit 278 may support different standard communication protocols such as Transport Control Protocol/Internet Protocol (TCP/IP), Internet Protocol Version (IPv) and MQTT.
The third processing unit 272 may include any type of computational circuit, such as, but not limited to, a microprocessor, a microcontroller, a complex instruction set computing microprocessor, a reduced instruction set computing microprocessor, a very long instruction word microprocessor, an explicitly parallel instruction computing microprocessor, a graphics processor, a digital signal processor, or any other type of processing circuit. The third processing unit 272 may also include embedded controllers, such as generic or programmable logic devices or arrays, application specific integrated circuits, single-chip computers, and the like. In general, the third processing unit 272 may comprise hardware elements and software elements. The third processing unit 272 can be configured for multithreading, i.e., the third processing unit 272 may host different calculation processes at the same time, executing the either in parallel or switching between active and passive calculation processes.
The third memory 274 includes one or more of a volatile memory and a non-volatile memory. The third memory 274 is coupled for communication with the third processing unit 272. The third processing unit 272 executes instructions and/or code stored in the third memory 274. A variety of computer-readable storage media is stored in and accessed from the third memory 274. The third memory 274 includes any suitable elements for storing data and machine-readable instructions, such as read only memory, random access memory, erasable programmable read only memory, electrically erasable programmable read only memory, hard drive, removable media drive for handling compact disks, digital video disks, diskettes, magnetic tape cartridges, memory cards, and the like.
The third memory 274 comprises a fouling point management module 286 configured for providing Head-of-Train devices associated with trains with GNSS location of upcoming fouling marks, GNSS location of an End-of-Train device communicatively linked to the respective Head-of-Train device 210 etc. The fouling point management module 286 may also enable updating of the database 284 based on GNSS locations of new fouling marks received from Head-of-Train devices. The fouling point management module 286 is stored in the third memory 274 in the form of machine-readable instructions and executable by the third processing unit 272. These machine-readable instructions when executed causes the third processing unit 272 to assist trains in clearing of fouling marks.
At step 305, the fouling mark FM is detected, by the Head-of-Train device 210, based on inputs from one or more sources. The one or more sources provide inputs for enabling the Head-of-Train device 210 to detect the fouling mark FM ahead of the train 205. In an embodiment, a source may provide an input indicating presence of the fouling mark FM at a specific GNSS location, in relation to a real-time GNSS location of at least one of the Head-of-Train device 210 and the End-of-Train device 215.
In an embodiment, the source is an imaging device mounted outside a locomotive of the train 205 in such a way that, a field of vision of the imaging device includes fouling marks provided beside a railway track along which the train 205 operates. For example, the imaging device may be an embedded camera mounted near a coupler provided outside the locomotive of the train 205. The imaging device may be configured to acquire real-time images for detecting presence of a fouling mark. Further, the imaging device may process an acquired image in real-time to identifying presence of the fouling mark. In an example, the acquired image is processed using an object recognition algorithm implemented using one or more Convolutional Neural Network (CNN) models pre-trained using a plurality of images of fouling marks. The CNN model identifies pixels corresponding to the fouling mark in the image. Upon identifying presence of the fouling mark FM, the imaging device provides an indicative of presence of the fouling mark FM to the Head-of-Train device 210. In an example, the input may be a binary value of 1 that indicates presence of the fouling mark FM.
In an embodiment, the imaging device is configured to compute a distance-to-the-fouling mark based on at least one of a size and a position of the fouling mark FM in the image. In an example, pixel coordinates of the fouling mark FM in the image may be used to determine distance-to-the-fouling mark. As the train 205 approaches the fouling mark FM, a total number of pixels covered by the fouling mark FM in the image proportionally increases. In
In another embodiment, the sensing unit 220 may include an RFID reader mounted on the train 205. For example, the RFID reader may be mounted on the locomotive of the train such that the RFID reader may ‘read’ or detect RFID tags that are embedded in or near a fouling mark. For example, when the train 205 is within a predefined distance of the RFID tag, the RFID reader detects presence of the fouling mark FM, based on detection of radio signals transmitted by a radio transmitter associated with the RFID tag. In another implementation, the radio signals comprise a message that indicates presence of the fouling mark FM. In an implementation, the radio signals may include the GNSS location of the fouling mark FM.
In yet another embodiment, the source is a wayside unit. The wayside unit may be configured to broadcast GNSS locations of fouling marks within a predetermined radius. In an example, the predetermined radius may be determined by hardware configuration of the wayside unit. The GNSS locations broadcasted by the wayside unit acts as the input to the Head-of-Train device 210. Further, the Head-of-Train device 210 may store the GNSS locations received from the wayside unit to the first memory 230.
In an embodiment, the Head-of-Train device 210 may update the cloud server 216 by transmitting an update message comprising the GNSS location of the fouling mark. In an example, transmittal of the update message may be initiated by the driver of the train 205 via the driver-machine interface, when the driver sees the fouling mark. In another example, transmittal of the update message may be based on detection of the fouling mark, by the Head-of-Train device 210, based on inputs from at least one of the sensing units and the wayside units. In another example, the update message may include GNSS locations of a plurality of fouling marks detected over a period of time. For example, if the Head-of-Train device 210 is unable to communicate with the cloud server 216 due to network issues, the GNSS locations of the fouling marks detected may be stored locally on the Head-of-Train device 210 and transmitted to the cloud server 216 when the network issue is resolved. Further, the cloud server 216 may update an artificial intelligence model based on the GNSS location of the fouling mark received from the Head-of-Train device 210, for enabling subsequent identification of the fouling mark by at least one of the cloud server 216 and the Head-of-Train device 215. For example, the artificial intelligence model may enable the cloud server 216 to dynamically classify a GNSS location received from at least one of the Head-of-Train device and the End-of-Train device 215 to determine presence of fouling mark at the GNSS location.
In an implementation, updating the artificial intelligence model may include updating a training dataset of the artificial intelligence model based on a GNSS location of the fouling mark, say A, if the training dataset previously did not include the GNSS location A. Further, the artificial intelligence model is trained based on the updated training dataset. Similarly, the artificial intelligence model may ‘learn’ over time based on GNSS locations of fouling marks received from a plurality of Head-of-Train devices similar to the Head-of-Train device 210. In a further embodiment, the artificial intelligence model may generate a location dataset comprising GNSS locations of fouling marks along a route, in response to an input dataset indicative of the route. For example, the input dataset may be a static route map.
In an embodiment, the Head-of-Train device 210 may be preconfigured before start of operation of the train 205, to store GNSS locations of each fouling mark along a route of operation of the train 205. For example, the Head-of-Train device 210 may transmit a request to the cloud server 216 during start of operation of the train 205. In another example, the request may be initiated manually by a driver of the train 205, via a driver-machine interface associated with the train 205. For example, the driver-machine interface on the train 205 may be configured to provide an option “Load fouling mark locations” to the driver. The driver may select the provided option to initiate transmission of the request to the cloud server 216. In an implementation, the request comprises a static route map indicative of the route of operation, The cloud server 216 may further transmit to the Head-of-Train device 210, the GNSS locations of each fouling mark along the route of operation based on output of the trained artificial intelligence model. For example, the cloud server 216 may update the static route map based on the GNSS locations of the fouling marks and transmit back to the Head-of-Train device 210. In other words, the updated artificial intelligence model enables subsequent identification of the fouling mark by the Head-of-Train device 210.
In another embodiment, the artificial intelligence model may be stored locally on the Head-of-Train device 210 and trained based on GNSS locations of fouling marks along a route, determined based on inputs from the one or more sources. Subsequently, the trained artificial intelligence model may further automatically detect presence of fouling marks along the route.
Alternatively, the Head-of-Train device 210 may periodically update the cloud server 216 with real-time GNSS location of the Head-of-Train device 210. In an embodiment, the Head-of-Train device 210 transmits the GNSS location of the Head-of-Train device 210 upon receiving a manual input from the driver of the train 205. For example, the driver-machine interface on the train 205 may be configured to provide an option “Clearing assist” to the driver. The driver may further select the option on the driver-machine interface to initiate the process of transmitting the real-time GNSS location of the Head-of-Train device 210. Upon receiving the GNSS location of the Head-of-Train device 210, the cloud server 216 may verify whether the GNSS location of the Head-of-Train device 210 is equal to or is close to GNSS location of at least one fouling mark. In an example, the cloud server 216 may firstly identify a predefined region corresponding to the GNSS location of the Head-of-Train device 210. Further, the cloud server 216 may query the database 284 to identify GNSS location of a plurality of fouling marks in the predefined region. Upon querying the database 284, a fouling mark geographically closest to the GNSS location of the Head-of-Train device 210 is identified.
In an embodiment, the cloud server 216 may further compute a distance-to-the-fouling mark D based on the real-time GNSS location of the Head-of-Train device 210 and the GNSS location of the fouling mark closest to the GNSS location of the Head-of-Train device 210. Further, the cloud server 216 transmits a notification comprising the computed distance-to-the-fouling mark D to the Head-of-Train device 210. In another embodiment, the cloud server 216 may transmit only the GNSS location of the fouling mark FM to the Head-of-Train device 210. The Head-of-Train device 210 may further compute the distance-to-the-fouling mark D based on the GNSS location of the fouling mark FM and the GNSS location of the Head-of-Train device 210.
At step 310, the Head-of-Train device 210 dynamically determines whether the train 205 clears the fouling mark FM, upon detecting the fouling mark FM. In an embodiment, the Head-of-Train device 210 determines whether the train 205 has cleared the fouling mark FM by comparing the GNSS location of the fouling mark FM and a real-time GNSS location of the End-of-Train device 215. For example, when the train 205 crosses the GNSS location of the fouling mark FM, the GNSS location of the End-of-Train may become equal to the GNSS location of the fouling mark FM.
In an embodiment, the cloud server 216 tracks the GNSS location of the End-of-Train device 215. Further, the cloud server 216 may compare the GNSS location of the End-of-Train device to the GNSS location of the fouling mark FM to determine whether the End-of-Train device 215 has crossed the fouling mark FM. Further, once the cloud server 216 determines that the End-of-Train device 215 has crossed the fouling mark FM, a confirmation message is sent to the Head-of-Train device 210 and the End-of-Train device 215 from the cloud server 216. The confirmation message indicates that the End-of-Train device 215 has crossed the fouling mark FM, i.e., the train 205 has cleared the fouling mark FM. Upon receiving the confirmation message, the Head-of-Train device 210 determines that the train has successfully cleared the fouling mark.
In another embodiment, the Head-of-Train device 210 may determine whether the train 205 has cleared the fouling mark FM by dynamically computing a stopping point S when the fouling mark FM is detected ahead of the train 205. For example, once the fouling mark FM is detected ahead of the train 205, the distance-to-the-fouling mark D is computed. The distance-to-the-fouling mark D may be computed by the sensing unit 220, the wayside unit, or the cloud server 216 based on distance between the GNSS location of the Head-of-Train device 215 and the GNSS location of the fouling mark FM. Further, the stopping point S is dynamically computed based on the distance-to-the-fouling mark D at an instant and the length of the train 205, when the fouling mark FM is ahead of the train 205. Herein, the term ‘stopping point’ refer to a location that indicates where the Head-of-Train device 210 must reach for the train 205 to successfully clear the fouling mark FM. Further, the Head-of-Train device 210 compares the stopping point to the real-time GNSS location of the Head-of-Train device 210 in order to determine if the train 205 has successfully cleared the fouling mark FM.
In another embodiment, the Head-of-Train device 210 may dynamically compute a stopping distance for the train 205 based on a distance travelled by the train 205 in real-time after the Head-of-Train device 210 crosses the fouling mark FM. The term ‘stopping distance’ refers to a remaining distance to be travelled by the train 205 after the Head-of-Train device 210 crosses the fouling mark FM, for the Head-of-Train device 210 to reach the stopping point. When the stopping distance reduces to zero, the train 205 successfully clears the fouling mark FM. In an embodiment, the distance travelled by the train 205 in real-time after the Head-of-Train device 210 crosses the fouling mark FM is determined based on an output of at least one tachometer attached to at least one wheel of the train 205. Here, the output of the tachometer indicates a distance travelled by the train 205 in terms of number of rotations of the wheel onto which the tachometer is attached. In an alternate embodiment, the distance travelled by the train 205 is computed as product of speed computed based on GNSS data associated with the Head-of-Train device, and a time taken by the train 205 to travel from a first GNSS location to a second GNSS location. In the present embodiment, the distance travelled by the train 205 is measured from an instance at which the Head-of-Train device 210 crosses the fouling mark FM. For example, if the Head-of-Train device 210 crosses the fouling mark FM at time 3:45:00 μm, the output of the tachometer from 3:45:00 pm onwards is analyzed, by a postprocessing unit associated with the tachometer, to determine the distance travelled by the train 205.
In an embodiment, the length of the train 205 may be computed in real-time based on, for example, distance between a GNSS location of the Head-of-Train device 210 and a GNSS location of the End-of-Train device 215 at an instant of time. The length of the train 205 is indicated by ‘L’ in
In another embodiment, the first GNSS transceiver transmits GNSS location of the Head-of-Train device 210 to the cloud server 216. Similarly, the second GNSS transceiver transmits GNSS location of the End-of-Train device 215 to the cloud server 216. The cloud server 216 further computes the length of the train 205 based on the GNSS locations of the Head-of-Train device 210 and the End-of-Train device 215 and transmits the computed length L of the train 205 to the Head-of-Train device 210.
In yet another embodiment, the Head-of-Train device 210 may be preconfigured to store the length L of the train 205. For example, the length L of the train 205 may be updated on the Head-of-Train device 210 by a driver of the train 205 at the time of starting operation of the train 205. For example, the driver may provide a manual input, to the driver machine interface, indicative of a count of cabins connected to the locomotive of the train 205. Based on the number of cabins, the Head-of-Train device 210 may compute the length L of the train 205 using a predefined logic.
The Head-of-Train device 210 is further configured to determine that the train 205 has cleared the fouling mark FM, when distance between GNSS location of the Head-of-Train device 210 and the stopping point is zero, or when distance between the GNSS location of the End-of-Train device 215 and the GNSS location of the fouling mark FM reduces to zero or when the stopping distance is zero. If the train 205 stops before clearing the fouling mark FM point as shown in
At step 315, the Head-of-Train device 210 identifies one or more actions to be performed using a predefined logic, before the train 205 clears the fouling mark FM. In an embodiment, the predefined logic may be implemented using logic gates. In another embodiment, the predefined logic may be implemented by executing a piece of code stored in the first memory 230.
In an embodiment, the one or more actions include generating a notification indicating a position of the train 205 relative to the fouling mark FM on the driver-machine interface of the train 205. In an example, the notification indicates the stopping distance. For example, a graphical representation indicating movement of the train 205 on the railway track and the stopping distance in real-time is rendered on the driver-machine interface. The driver of the train 205 may further manually control movement of the train 205 until the fouling mark FM is cleared, i.e., until the stopping distance is zero. In yet another embodiment, the one or more actions include generating a warning on the driver-machine interface if the train 205 is stopped before all the wheels have crossed the fouling mark FM.
In another embodiment, the one or more actions include broadcasting a status message indicating that clearing of the fouling mark by the train is incomplete, to one or more apparatus associated with a railway signaler. In an example, the status message may include a real-time GNSS location of the End-of-Train device 215. The one or more apparatus may include for example, Operation Control Systems (OCS), handheld devices associated with the railway signaler etc. In particular, the status message is firstly relayed to a repeater unit. The repeater unit further transmits the status message to the one or more apparatus associated with the railway signaler. In an example, the one or more apparatus may be configured to generate an audio notification and/or a visual notification indicating the real-time GNSS location of the End-of-Train device 215 superimposed on a map.
In another embodiment, the one or more actions include broadcasting a warning message for cautioning one or more trailing trains (not shown) that clearing of the fouling mark FM by the train 205 is incomplete. The term ‘trailing trains’ as used herein refers to any train (405 in
In another embodiment, the one or more actions include transmitting a status message, to the cloud server 216, indicating that clearing of the fouling mark FM by the train 205 is incomplete. The status message enables the cloud server to further transmit a notification, to trailing trains, indicating that clearing of the fouling mark by the train is incomplete. In an example, the status message comprises at least the GNSS location of at least one of the Head-of-Train device 210 and the End-of-Train device 215. The status message enables the cloud server 216 to inform one or more trailing trains that clearing of the fouling mark FM by the train 205 is incomplete.
Further, the cloud server 216 transmits a notification to driver-machine interface of one or more trailing trains to display a notification to the driver of the trailing train, so that the trailing train may take a diversion in order to avoid reaching the GNSS location of the End-of-Train device 215.
At step 325, the Head-of-Train device 210 executes one or more machine-readable instructions to the perform the one or more actions identified. For example, the instructions may be associated with configuring the driver-machine interface to generate the notification indicating the position of the train 205 relative to the fouling mark FM. In another example, the instructions may be associated with initiating transmittal of the status message comprising at least the GNSS location of at least one of the Head-of-Train device 210 and the End-of-Train device 215, to the cloud server 216. In yet another example, the instructions may be associated with configuring the End-of-Train device 215 to broadcast the warning message. In an embodiment, the one or more instructions may be automatically generated by the predefined logic, based on the one or more actions determined.
Advantageously, the present disclosure facilitates clearing of fouling marks, with minimal or no intervention from human operators such as the driver or a guard. Further, the present disclosure helps in reducing accidents resulting from rear-end collisions between a train stalled on a loop line or a main line, near a fouling mark, by intimating trailing trains that clearing of the fouling mark by the train is incomplete.
The present disclosure is not limited to a particular computer system platform, processing unit, operating system, or network. One or more aspects of the present disclosure is distributed among one or more computer systems, for example, servers configured to provide one or more services to one or more client computers, or to perform a complete task in a distributed system. For example, one or more aspects of the present disclosure is performed on a client-server system that comprises components distributed among one or more server systems that perform multiple functions according to various embodiments. These components comprise, for example, executable, intermediate, or interpreted code, which communicate over a network using a communication protocol. The present disclosure is not limited to be executable on any particular system or group of system, and is not limited to any particular distributed architecture, network, or communication protocol.
While the disclosure has been illustrated and described in detail with the help of a preferred embodiment, the disclosure is not limited to the disclosed examples. Other variations can be deducted by those skilled in the art without leaving the scope of protection of the claimed disclosure.
