System, apparatus, and method for remotely managing operation of rail vehicle

Abstract

A system (100), an apparatus (105) and a method for managing operation of a rail vehicle (102) are provided. The method includes identifying, by a processing unit (125), a virtual subsystem for managing specific operations of the vehicle based on operational data associated with the rail vehicle (102). The operational data includes values of parameters associated with operation of the rail vehicle. The method further includes generating, using the identified virtual subsystem, one or more operational instructions capable of managing operation of the rail vehicle (102) based on a configuration of the rail vehicle. The method further includes initiating execution of the one or more operational instructions capable of managing operation of the rail vehicle (102) at a system component (190) remotely positioned relative to the processing unit (125). The system component (190) is configured to execute the one or more operational instructions.

Description

[0001] This application is a divisional application. The name of the invention of the parent case is “System, device and method for remote management of rail transit vehicle operations”. The application date is September 30, 2020, and the application number is 202011055272.3. Technical Field

[0002] The present invention relates to rail automation and, more particularly, to systems, apparatus and methods for remotely managing the operation of rail vehicles. Background Art

[0003] Currently, rail vehicles have an onboard control unit that controls the operation of rail vehicles. Such onboard control units operate based on data received from multiple sources (such as driver's cabin controls, roadside units, beacons provided on rails, etc.). The data is further processed by an onboard control unit provided on the rail vehicle to perform one or more operations. For example, the operation may be associated with the application of brakes when the rail vehicle is above a predefined speed limit. However, if a problem occurs with the onboard control unit, it may be impossible to reproduce the problem at a remote development site for the purpose of defect repair. In other words, remote troubleshooting of the onboard control unit becomes difficult. Therefore, maintenance personnel may have to perform physical inspections on the rail vehicle in order to solve the problem. In one example, the rail vehicle may be taken to a maintenance workshop for solving the problem. In another example, maintenance personnel may visit the location of the rail vehicle for solving the problem. Further, the prevention of such problems may require rigorous testing during the development phase of the onboard control unit. Similarly, the upgrade of the onboard control unit may also become difficult, because it is necessary to upgrade both the hardware and software associated with the onboard control unit. The above factors may lead to an increase in the downtime of the rail vehicle. As a result, the operation of the rail vehicle is affected.

[0004] In view of the foregoing, a need exists for remotely managing the operation of rail vehicles in real time. Summary of the invention

[0005] It is therefore an object of the present invention to provide a system, apparatus and method for remotely managing the operation of a rail vehicle in real time.

[0006] The object of the present invention is achieved by a method for managing the operation of a rail vehicle as disclosed herein. As used herein, the term "rail vehicle" may refer to any vehicle that runs on rails for transporting goods or passengers or for performing maintenance activities along the rails. Non-limiting examples of rail vehicles may include passenger trains, intercity trains, high-speed rail services, higher-speed rail services, rapid transit trains, monorails, passenger transporters, freight trains, and the like. A rail vehicle may consist of a single rail car or a plurality of rail cars coupled together.

[0007] The method includes: a first processing unit identifies a virtual subsystem for managing the specific operation of the rail vehicle from a plurality of virtual subsystems based on the operational data associated with the rail vehicle. As used herein, the term "virtual subsystem" may refer to a virtual machine that simulates the functions of the logical components of the physical subsystem for managing the operation of the rail vehicle. The operational data is obtained in real time from one or more system components. The system component may refer to any remotely located equipment configured to communicate with the first processing unit. The equipment may include track equipment and track equipment. The track equipment may include equipment installed on or along the rails, and may include a transponder, a roadside signaling unit, an interlocking system, and the like. The track equipment may include equipment on the rail vehicle, and may include a sensing unit, a pantograph system, a braking system, a radio communication system, an onboard unit, a judicial recording unit (JRU), a radar system, an odometer circuit, an axis accelerometer, a cockpit control device, and the like. The track equipment may be associated with a rail vehicle being managed or another rail vehicle (e.g., a rail vehicle running on a parallel track). In addition to track equipment and track equipment, the system components may also include equipment such as transponders installed at facilities associated with railway regulatory authorities or at train stations. Further, the operating data may also be generated by another virtual subsystem. The operating data includes the values ​​of parameters associated with the operation of the rail vehicle. It must be understood that the parameters associated with the operation of the rail vehicle may include any parameters indicating the operating conditions of the rail vehicle. For example, the parameters associated with the operation of the rail vehicle may involve the following: the speed of the rail vehicle, the permitted speed of the rail vehicle, the geographical location of the rail vehicle, the distance covered by the rail vehicle from the starting point, the upcoming station, the distance of the rail vehicle to the upcoming station or stop, the number of stops, braking, the direction of the rail vehicle, the signal followed by the rail vehicle, the operating mode of the rail vehicle, the state of the communication interface on the rail vehicle, the operating state of the digital input and output associated with the fan, lights and doors, etc. In one example, the value of the parameter can be directly measured as a numerical value, such as speed and distance. In another example, the value of the parameter may not be directly measured as a numerical value, but may be converted into a numerical value using a suitable coding system. For example, the operating mode of the rail vehicle may be one of the following: manual, automatic, semi-automatic, or extended automatic. Each of the operating modes may be assigned a number, such as: manual is 0, semi-automatic is 1, automatic is 2, and extended automatic is 3.In one example, the identified virtual subsystem is associated with one or more vital functions for ensuring the safety of the rail vehicle. The vital functions may include, for example, enforcing compliance with speed constraints or signals. In another example, the identified virtual subsystem may be associated with one or more non-vital functions. The non-vital functions may include functions that are otherwise performed by the driver of the rail vehicle, such as maintaining accurate parking positions at train stations, controlling platform screen doors at train stations, opening and closing doors on the rail vehicle, operating lights, triggering notices or alarms, etc. In another example, the identified virtual subsystem may be associated with communication-related functions. The communication-related functions may include, for example, radio-based communication interfaces between control system components or between system components and the first processing unit. In one embodiment, the virtual subsystem may be identified based on the source of the operating data. For example, if the operating data is obtained from the transponder, the virtual subsystem associated with the vital function may be identified. In another embodiment, the virtual subsystem may be identified based on the type of operating data. For example, if the operational data is associated with the state of a communication interface on the rail vehicle, a virtual subsystem associated with a communication-related function may be identified. In yet another embodiment, the virtual subsystem may be identified based on the value of a parameter associated with the operational data. For example, if the speed of the rail vehicle is less than the permitted speed of the rail vehicle, a virtual subsystem associated with a non-life-critical function may be identified. Otherwise, a virtual subsystem associated with a life-critical function may be identified. In yet another embodiment, a virtual subsystem associated with a non-life-critical function is triggered based on the output of a virtual subsystem associated with a life-critical function.

[0008] Advantageously, the present invention relates to virtualizing subsystems that are traditionally hardware-based subsystems, such as Automatic Train Operation (ATO), Automatic Train Protection (ATP), and the like. More specifically, in the present invention, logical components corresponding to traditional hardware-based subsystems are located as virtual subsystems at a remote location, such as a cloud server. Thus, the virtual subsystem can be common to multiple rail vehicles, in contrast to the traditional use of separate hardware-based subsystems on each rail vehicle. Further, the virtual subsystem can be provided to a rail operator as a cloud-based service for managing the operation of the rail vehicle, wherein the rail operator can be charged for the use of the cloud-based service.

[0009] The method further includes: generating one or more operating instructions based on the configuration of the rail vehicle, the one or more operating instructions being capable of managing the operation of the rail vehicle using the identified virtual subsystem. The configuration of the rail vehicle may be based on several factors, such as: the length of the rail vehicle, the number of rail cars (or couplers) on the rail vehicle, the operating mode of the rail vehicle, the type of service associated with the rail vehicle, the OEM associated with the rail vehicle, the hardware and associated software used on the rail vehicle, the communication protocol used by the hardware to communicate with system components, and the like. In one example, the configuration of the rail vehicle may be pre-stored in a database. Further, the pre-stored configuration of the rail vehicle may be obtained based on the identification of the rail vehicle for generating the one or more operating instructions. In another example, the configuration of the rail vehicle may be determined on a self-organizing basis based on the operating data associated with the rail vehicle.

[0010] Advantageously, the virtualization of the subsystems facilitates centralized monitoring of the operation of the rail vehicle. Further, the virtualization of the subsystems also facilitates easy remote troubleshooting for defect repair and also in providing rapid technical support. The method further includes: initiating the execution of the one or more operating instructions capable of managing the operation of the rail vehicle at a system component configured to execute the one or more operating instructions. In one example, the one or more operating instructions may be associated with controlling the speed of the rail vehicle by decelerating the rail vehicle via the application of brakes. In another example, the one or more operating instructions may be associated with opening doors when the rail vehicle is docked at an appropriate location for disembarking passengers at a train station.

[0011] Advantageously, the present invention helps to reduce the amount of hardware present on a rail vehicle by using virtual subsystems to provide only the necessary operating instructions required for execution at system components rather than having separate circuitry on the rail vehicle for generating operating instructions.

[0012] The method may further include determining an anomaly in the operation of the rail vehicle based on the operational data. The term "anomaly" may refer to a deviation in the normal operation of any component of the rail vehicle. The component of the rail vehicle may be an electrical component, an electronic component, a mechanical component, an electromechanical component, and the like. In one example, the anomaly in the operation of the rail vehicle may be associated with heating, ventilation, and air conditioning (HVAC) in the rail vehicle. In another example, the anomaly may be in the form of heating of a component of the rail vehicle. In yet another example, the anomaly may be in the form of a fuse failure. In yet another example, the anomaly may be in the form of a large speed difference along an axis relative to a predefined maximum speed difference. In yet another example, the anomaly may be in the form of an abnormal speed measured by an axis accelerometer. In yet another example, the anomaly may be associated with logging data associated with the operation of the rail vehicle. In yet another example, the anomaly may be in the form of abnormal noise. In yet another example, the anomaly may be in the form of abnormal vibration. In yet another example, the anomaly may be in the form of a malfunction or inaction of a component of the rail vehicle.

[0013] In one embodiment, determining an anomaly in the operation of the rail vehicle based on the operational data includes: analyzing the operational data to determine a deviation in the value of one or more key parameters relative to a predefined value range of the one or more key parameters. Further, the anomaly is predicted based on the deviation in the value of the one or more key parameters. The key parameters may include, but are not limited to: speed, velocity, acceleration, temperature, pressure, vibration, friction, noise, frequency, etc. For example, the speed of the rail vehicle for normal operation may be in the range of 150kmph to 200kmph. If the speed of the rail vehicle measured by the shaft accelerometer is greater than 200kmph, the rail vehicle is associated with an abnormality of abnormal speed. In another example, if the temperature of a mechanical component is greater than a predefined temperature (such as 50°C), the rail vehicle is associated with an abnormality of abnormal heating of the mechanical component. The deviation in the value of the key parameter can also be based on defining railway safety supervision for the region in which the rail vehicle operates.

[0014] Advantageously, the present invention enables anomalies in the operation of a rail vehicle to be determined without the need to perform physical testing on the rail vehicle.

[0015] The method may further include: using root cause analysis techniques to determine the root cause of the anomaly in the operation of the rail vehicle. The root cause may be defined as any factor that causes the anomaly in the operation of the rail vehicle. For example, the root cause may be associated with a lack of lubrication, wear of components, improper coupling of components, electrical failure, inappropriate control commands given by the driver, faulty signaling, and the like. The root cause may be determined based on the type of the anomaly using any known root cause analysis technique. In one example, the root cause analysis technique may employ a root cause analysis model such as a neural network, a Bayesian network classifier, a support vector machine (SVM), and the like to infer the root cause based on the type of anomaly. Alternatively, the root cause may also be determined using root cause analysis techniques such as fault tree analysis, failure mode and effect analysis, and the like. In addition to determining the root cause, the root cause analysis technique may also be used to identify the location of the root cause.

[0016] Advantageously, the root cause of the anomaly may be predicted using root cause analysis techniques utilizing operational data acquired from the rail vehicle.

[0017] The method may further include predicting a safety risk associated with an anomaly in the operation of the rail vehicle. As used herein, the term "safety risk" may refer to the possibility of loss, damage, injury, debt, or any other negative consequence caused by the anomaly. In one embodiment, the safety risk may be predicted using statistical techniques. For example, the statistical technique may involve calculating a risk indicator value based on the operational data. The risk indicator value may be further used to determine the safety risk. For example, the safety risk may be associated with the following: a collision of the rail vehicle, a derailment of the rail vehicle, a fire outbreak, a loss of a communication channel between the rail vehicle and a system component, a loss of communication between the rail vehicle and the first processing unit, and the like. The method further includes determining one or more actions for mitigating the safety risk; and generating an operational instruction for implementing the one or more actions for mitigating the safety risk. The one or more actions may include, but are not limited to, engaging an emergency brake, triggering an alarm, and the like. The one or more actions may also include transmitting a notification including a recommendation or instruction for the driver or other railway authority. The recommendation may include an inspection or measure to be taken to mitigate the safety risk. For example, the recommendation may include the nearest stop and a suggestion to stop at the nearest stop to replace or repair the faulty component. In another example, the rail vehicle may be operated in an automatic mode, and the recommendation may include steps that the driver may take to avoid the safety risk. For example, first, the driver may be asked to change the operating mode from an automatic mode to a manual mode. Further, the driver may be asked to check the indications on a control panel inside the rail vehicle. Further, if the indications exist, the driver may be provided with one or more further steps to be performed to avoid the safety risk. Operational instructions for performing the one or more actions for mitigating the safety risk may be generated by a virtual subsystem identified based on the operational data. The operational instructions may be executed by the system components at the rail vehicle to mitigate the safety risk.

[0018] Advantageously, the present invention is able to automatically provide operating instructions to system components for safety risk mitigation without necessitating intervention by a human operator.

[0019] The method may further include: determining the remaining life of the rail vehicle based on anomalies in the operation of the rail vehicle. In one embodiment, the remaining life of the rail vehicle is determined based on the deviation of the value of the key parameter from a predefined value or a predefined value range. For example, a condition indicator can be calculated based on the deviation in the value of the key parameter. Further, the condition indicator can be suitable for a degradation model to determine the remaining life of the rail vehicle. In one example, the remaining life of the rail vehicle can be determined according to the remaining life of the key components (such as axles) of the rail vehicle. As used herein, the term "key component" can refer to any component that causes a high safety risk for the rail vehicle when it fails. In another embodiment, a data log associated with the operating data, maintenance history, operating conditions, operating history, age of components, etc. can also be used to determine the remaining life of the rail vehicle, for example, using statistical techniques such as regression. Alternatively or in addition to the data log associated with the rail vehicle, data logs associated with other similar rail vehicles can also be used to determine the remaining life of the rail vehicle. In one example, the other similar rail vehicles may include rail vehicles having components manufactured by the same original equipment manufacturer (OEM) as the components of the rail vehicle. In another example, the other similar rail vehicles may include rail vehicles having a configuration similar to that of the rail vehicle. In yet another example, the other similar rail vehicles may include rail vehicles operating under similar operating conditions (e.g., operating on the same route or for the same service (public transportation, mainstream transportation, freight), etc.). Further, a hazard model and probability distribution associated with the failure time of the components of the rail vehicle are used to determine the remaining life of the rail vehicle based on the data log. In yet another embodiment, the remaining life of the rail vehicle may be determined based on fault repair data associated with different components of the rail vehicle. The fault repair data may be obtained from other components that exhibit similar behavior to the components of the rail vehicle. Further, the degradation profile of the other components is determined based on the fault repair data. Further, operational data or other data in a data log associated with the rail vehicle is compared to the degradation profile to identify the closest matching degradation profile. Further, the closest matching degradation profile is used to determine the remaining life of the rail vehicle.

[0020] The method may further include optimizing the downtime of the rail vehicle by scheduling maintenance activities of the rail vehicle based on the remaining life of the rail vehicle. The maintenance activities of the rail vehicle may be scheduled when the remaining life of the rail vehicle is, for example, 30 days. The downtime of the rail vehicle may be estimated based on factors including, but not limited to, the geographic location of the rail vehicle, the type of service associated with the rail vehicle, the anomaly associated with the operation of the rail vehicle, the root cause associated with the anomaly, the availability of spare devices and service personnel, and the like. The geographic location of the rail vehicle may be used to determine the distance to the nearest station where the rail vehicle can be taken for maintenance. The type of service may be used to determine the frequency of operation of the rail vehicle and the associated schedule of the operation. The anomaly and the root cause associated with the anomaly may be used to estimate the actual repair time or the maintainability of the rail vehicle during the downtime. For example, the replacement of a component may take less time than repairing the component. The availability of spare devices and service personnel may be used to schedule the maintenance activities. For example, if the backup device is not available, the probability that the backup device can be obtained before the maintenance activity begins can also be considered for determining the downtime. In one aspect of the present invention, the service personnel can also be informed to obtain the backup device before the maintenance activity begins by sending a notification to an electronic device (not shown) associated with the service personnel. The electronic device can be a mobile phone, a personal computer, a tablet, etc. The notification can be sent a predefined number of days (such as 20 days) before the maintenance activity so that the service personnel can obtain the backup device. Similarly, the service personnel can receive multiple notifications for obtaining backup devices associated with one or more rail vehicles. In addition, the notification can also include a web link to a source for obtaining the backup device. The web link can be selected and added to the notification based on, for example, the type of backup device required. In another example, the maintenance activity can be scheduled based on the availability of the service personnel for performing the maintenance activity. Based on the above factors, the maintenance activity can be scheduled before the remaining life of the rail vehicle is exhausted in order to optimize the downtime.

[0021] Advantageously, the present invention helps to optimize the downtime of the rail vehicle, thereby ensuring maximum productivity of the rail vehicle.

[0022] The method may further include generating a report associated with the operation of the rail vehicle. The report may include information such as the following: the value of a parameter associated with the operation of the rail vehicle, the detected anomaly, the remaining life of the rail vehicle, the scheduled maintenance activities, the optimized estimated downtime, the operating instructions provided to the system components, the consequences of providing the operating instructions to the system components, and the like. The report may include both text and graphical representations, such as charts, graphs, tables, and the like. In one example, the report may be continuously updated in real time. In another example, the report may be generated periodically (such as every 15 minutes). The generated report may be further transmitted to a display unit. The display unit may be associated with service personnel, railway personnel, regulatory expectations, and the like, and may be installed on the rail vehicle or at a remote location. The display unit may be part of a personal computer, a workstation, a human-machine interface, a personal digital assistant, and the like.

[0023] Advantageously, the present invention reduces the human intervention required to manage the operation of a rail vehicle.

[0024] The object of the present invention is achieved by a device, the device comprising one or more first processing units and a first memory unit communicatively coupled to the one or more first processing units. The first memory unit comprises: a management module, which is stored in the form of machine-readable instructions executable by the one or more first processing units. The management module is configured to execute the method steps described above. The execution of the management module can also be performed using a coprocessor such as a graphics processing unit (GPU), a field programmable gate array (FPGA) or a neural processing / computing engine.

[0025] According to an embodiment of the present invention, the apparatus may be an edge computing device. As used herein, "edge computing" refers to a computing environment that can be executed on an edge device (e.g., connected to the system components at one end and connected to (one or more) remote servers (such as (one or more) computing servers or (one or more) cloud computing servers) on the other end), and the edge device may be a compact computing device with a small form factor and resource constraints in terms of computing power. Alternatively, a network of edge computing devices may also be used to implement the apparatus. Such a network of edge computing devices is referred to as a fog network.

[0026] In a preferred embodiment, the device is a cloud computing system having a cloud computing-based platform, and the cloud computing-based platform is configured to provide cloud services for managing the operation of the rail vehicle. As used herein, "cloud computing" refers to a processing environment that includes configurable computing physical and logical resources (such as networks, servers, storage, applications, services, etc.) and data distributed on a network (such as the Internet). The cloud computing platform can be implemented as a service for managing the operation of rail vehicles. In other words, the cloud computing system provides on-demand network access to a shared pool of configurable computing physical and logical resources. The network is, for example, a wired network, a wireless network, a communication network, or a network formed by any combination of these networks.

[0027] In addition, the purpose of the present invention is achieved by a system for managing the operation of a rail vehicle. The system includes: one or more system components for providing operation data associated with the operation of the rail vehicle. The operation data includes the value of a parameter associated with the operation of the rail vehicle. The system further includes: a device as described above, communicatively coupled to the one or more system components. The device is configured to manage the operation of the rail vehicle based on the operation data according to the method described above. The system components may include but are not limited to equipment on board the rail vehicle and track equipment such as transponders and roadside units. In one embodiment, the system components are configured to communicate with each other on the network in addition to communicating with the device. It must be understood that the equipment on the rail vehicle can communicate with equipment on other rail vehicles, track equipment and the device. More specifically, the system components within the rail vehicle can communicate with each other based on Ethernet technology or using radio communication, using, for example, a train communication network (TCN). The system components on the rail vehicle can communicate with track equipment or other equipment on rail vehicles based on, for example, GSM technology, WLAN, satellite communication, etc., based on, for example, train-to-roadside communication (TWC). Similarly, the system components may communicate with the device using wireless communication techniques such as Wi-Fi, satellite communications, radio communications, microwave channel communications, cellular communications, etc. In another embodiment, communications between the system components may be controlled by the device, for example using cloud communications.

[0028] In a preferred embodiment, the system further includes an onboard unit located on the rail vehicle. The onboard unit includes a plurality of interfaces for communicating with the one or more system components and the device to enable the one or more system components to communicate with the device. The device further includes one or more second processing units and a second memory communicatively coupled to the one or more second processing units. The second memory includes an offline emergency module stored in the form of machine-readable instructions executable by the one or more second processing units. The offline emergency module is configured to manage the operation of the rail vehicle when the communication between the onboard unit and the device is interrupted. In one embodiment, when the communication is interrupted, the onboard unit can manage the operation of the rail vehicle based on previously stored operating instructions. In one example, the onboard unit can provide instructions to the driver to switch from automatic mode to manual mode when the communication is interrupted. In another example, when the communication is interrupted, the onboard unit can automatically downgrade the operating mode of the rail vehicle. In another example, the onboard unit can instruct another onboard unit in another rail car on the rail vehicle to communicate with the device for managing the operation of the vehicle. In yet another example, the onboard unit may activate an emergency braking system when communications with the device are interrupted. In another embodiment, the onboard unit may use operational data captured immediately prior to the interruption of the communications to generate operational instructions to be executed by the system components.

[0029] The object of the present invention is achieved by a computer program product having machine-readable instructions stored therein, which, when executed by a processing unit, cause the processing unit to perform the method as described above.

[0030] The implementation of the invention by a computer program product and / or a computer readable medium has the following advantages: already existing management systems can be easily adapted by software updates in order to work as proposed by the invention.

[0031] The computer program product may be, for example, a computer program or may include another element in addition to the computer program. The other element may be hardware (e.g. a memory device) on which the computer program is stored, a hardware key and / or software (e.g. a document) for using the computer program, etc. or a software key for using the computer program.

[0032] The above-mentioned properties, features and advantages of the present invention and the manner of achieving them will become more obvious and understandable in the following description of the embodiments of the present invention in conjunction with the corresponding drawings. The illustrated embodiments are intended to illustrate rather than limit the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The invention is further described below with reference to the illustrated embodiments shown in the accompanying drawings, in which: Figure 1A A block diagram of a system for managing the operation of a rail vehicle according to one embodiment of the present invention is illustrated; Figure 1B A block diagram of a management module in an apparatus for managing the operation of a rail vehicle according to an embodiment of the present invention is illustrated; Figure 1C A block diagram of an onboard unit according to one embodiment of the present invention is illustrated; Figure 2 A flow chart illustrating a method for managing the operation of a rail vehicle according to one embodiment of the present invention; Figure 3 A flow chart illustrating a method for mitigating safety risks associated with a rail vehicle according to one embodiment of the present invention; Figure 4 A flow chart of a method for optimizing downtime of a rail vehicle according to one embodiment of the present invention is illustrated; Figure 5 A flow chart illustrating a method for managing life-critical operations of a rail vehicle according to an exemplary embodiment of the present invention; and Figure 6 A flow chart of a method for managing non-life critical operations of a rail vehicle according to an exemplary embodiment of the present invention is illustrated. DETAILED DESCRIPTION

[0034] Hereinafter, embodiments for implementing the present invention are described in detail. Various embodiments are described with reference to the accompanying drawings, wherein like reference numerals are used to refer to like elements throughout. In the following description, for the purpose of explanation, many specific details are set forth in order to provide a thorough understanding of one or more embodiments. It may be apparent that such embodiments may be practiced without these specific details.

[0035] refer to Figure 1A , according to one embodiment of the present invention, a block diagram of a system 100 for managing the operation of multiple rail vehicles 102-1, 102-2...102-n is shown. The system 100 includes an apparatus 105. The apparatus 105 is communicatively coupled to multiple onboard units 110-1, 110-2...110-n. The multiple onboard units 110-1-n (hereinafter collectively referred to as onboard units 110) can be associated with one or more rail vehicles among the multiple rail vehicles 102-1, 102-2...102-n. The onboard unit 110 is configured to communicate with one or more system components (not shown) and the apparatus 105. Use Figure 1C The functions of the onboard unit 110 will be explained in further detail.

[0036] In the present embodiment, the onboard unit 110 is communicatively coupled to the device 105 via a network 115. The onboard unit 110 may be connected to the network 115 via one or more access points (not shown). In one embodiment, the one or more access points may be located, for example, on a rail vehicle 102-1 (hereinafter referred to as rail vehicle 102). In another embodiment, the one or more access points may be located along the roadside of the rails on which the rail vehicle 102 moves. For example, the access point may be integrated into a roadside signaling unit. The network 115 may be based on 5G communication, Wi-Fi communication, microwave channel communication, or a combination thereof.

[0037] Device 105 may be a (personal) computer, a workstation, a virtual machine running on host hardware, a microcontroller or an integrated circuit. Alternatively, device 105 may be a physical or virtual group of computers (the technical term for a physical group of computers is a "cluster" and the technical term for a virtual group of computers is a "cloud").

[0038] The device 105 includes a first communication unit 120, one or more first processing units 125, a first display 130, a first graphical user interface (GUI) 135, a first memory 140, and a database 145 that are communicatively coupled to each other. In one embodiment, the first communication unit 120 includes a transmitter (not shown), a receiver (not shown), and a Gigabit Ethernet port (not shown). The first memory 140 may include a 2-gigabyte random access memory (RAM) stack package (PoP) stack and flash memory. The one or more first processing units 125 are configured to execute the computer program instructions defined in the module. Further, the one or more first processing units 125 are also configured to execute the instructions in the first memory 140 simultaneously.

[0039] The first processing unit 125 may include any type of computing circuit, including 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 explicit parallel instruction computing microprocessor, a graphics processor, a digital signal processor, or any other type of processing circuit. The first processing unit 125 may also include an embedded controller, such as a general or programmable logic device or array, an application specific integrated circuit, a single chip computer, etc. Generally, the first processing unit 125 may include hardware elements and software elements. The first processing unit 125 may be configured for multithreading, which simultaneously hosts different computing processes and executes them in parallel or switches between active and passive computing processes.

[0040] The first display 130 includes a high-definition multimedia interface (HDMI) display and a cooling fan (not shown). In addition, the control personnel can access the device 105 through the first GUI 135. The first GUI 135 can include a web-based interface, a web-based downloadable application interface, and the like.

[0041] The database 145 may store data logs associated with the operation of the rail vehicle 102. The data logs may include values ​​of parameters associated with the operation of the rail vehicle 102 along with corresponding timestamps. In addition, the database 145 may also store information associated with route information of the rail vehicle 102, diagnostics associated with the rail vehicle 102, maintenance activities performed on the rail vehicle 102, and the like. In one implementation, the database 145 may be stored in the first memory 140. In another embodiment, the database 145 may be stored on a database server (not shown).

[0042] The first memory 140 may be one of a volatile memory and a non-volatile memory. The first memory 140 may be coupled for communication with the first processing unit 125. The first processing unit 125 may execute machine-readable instructions and / or codes stored in the first memory 140. A variety of computer-readable storage media may be stored in the first memory 140 and accessed from the first memory 140. The first memory 140 may include any suitable element for storing data and machine-readable instructions, such as a read-only memory, a random access memory, an erasable programmable read-only memory, an electrically erasable programmable read-only memory, a hard disk drive, a removable media drive for handling a compact disk, a digital video disk, a magnetic disk, a cassette, a memory card, and the like.

[0043] In this embodiment, the first memory 140 further includes a management module 148. Figure 1B As shown in , the management module 148 includes a communication module 150, a core manager module 152, a configuration module 154, a data analysis module 156, a data log module 158, and a report generation module 160. Each of the above modules exists in the form of machine-readable instructions on any of the above-mentioned storage media, and can communicate with the first processing unit 125 and be executed by the first processing unit 125. The management module 148 is configured to manage the specific operation of the rail vehicle 102 based on at least one of the virtual automatic train operation (ATO) subsystem 166, the virtual automatic train protection (ATP) subsystem 168, and the virtual interface (ITF) subsystem 170 when executed by the first processing unit 125. The following description explains in detail the function of each of the modules in the management module 148 when executed by the one or more first processing units 125.

[0044] The communication module 150 is configured to manage communications between the device 105 and the onboard unit 110. For example, the communication module 150 may control the first communication unit 120 of the device 105 for communicating with the onboard unit 110 over the network 115. In addition, the communication module 150 may also pre-process operational data received from the onboard unit 110 by performing operations such as data conversion, filtering, smoothing, etc. Further, the communication module 150 may route the pre-processed data to one or more modules of the device 105 based on the source or value of a parameter present in the operational data.

[0045] The core manager module 152 is configured to handle operational data received from the plurality of onboard units 110. In one example, the core manager module 152 may isolate operational data received from each of the onboard units among the plurality of onboard units 110. When isolating, the core manager module 152 may identify a virtual subsystem based on the type or source of the operational data or based on the output of another virtual subsystem. More specifically, operational data associated with non-life-critical functions is provided to the virtual ATO subsystem 166, and operational data associated with life-critical functions is provided to the virtual ATP subsystem 168. In one example, the trajectory coordinates obtained from the transponder may be provided to the virtual ATP subsystem 168, based on which the virtual ATP subsystem 168 may determine whether to apply brakes or whether the rail vehicle 102 should continue to move in order to comply with speed or signal constraints associated with the location of the rail vehicle 102. The virtual ATP subsystem 168 may further generate a digital output to indicate whether the rail vehicle 102 should continue to move or apply brakes and corresponding operational instructions. In another example, the speed of the rail vehicle 102 received from the radar system 190-3 may be given to the virtual ATO subsystem 166. The virtual ATO subsystem 166 may further determine the rate of acceleration or deceleration required to control the speed of the train. The virtual ITF subsystem 170 may generate operating instructions for controlling radio communications between system components and also between one or more system components and the onboard unit 110.

[0046] The configuration module 154 is configured to modify one or more operating instructions generated based on a configuration associated with the rail vehicle 102. The configuration of the rail vehicle 102 can be based on the format of an "ini" file or other similar initialization file used when configuring software associated with one or more system components on the rail vehicle 102. In addition, the configuration can also be based on hardware associated with the system components (e.g., multiple onboard units on the rail vehicle 102).

[0047] The data logging module 158 may log the operational data received from the onboard unit 110 to the database 145. The operational data may be logged based on, for example, a timestamp associated with the operational data, an identification associated with the onboard unit 110 or the rail vehicle 102, and so forth.

[0048] The data analysis module 156 can analyze the operational data to determine trends or patterns associated with the operational data. Further, the data analysis module 156 can draw inferences from the operational data based on the analysis of the operational data. The analysis can be performed based on descriptive techniques, explanatory techniques, inferential techniques, predictive techniques, causal techniques, qualitative analysis techniques, quantitative analysis techniques, etc. The inferences drawn based on the analysis can be associated with the health status of the rail vehicle 102, the remaining life of the rail vehicle 102, anomalies associated with the operation of the rail vehicle 102, the scheduling of maintenance activities of the rail vehicle 102, etc.

[0049] The report generation module 160 can generate reports associated with the operation of the rail vehicle 102. The reports can include details such as the health of the rail vehicle 102 along with an associated timestamp, the remaining life of the rail vehicle 102, anomalies in the operation of the rail vehicle 102, scheduled maintenance activities, optimized downtime of the rail vehicle 102 if the maintenance activities are performed, etc. The reports generated by the report generation module 160 can be further displayed to the end user on a web user interface associated with the first GUI 135.

[0050] Those skilled in the art should appreciate that Figure 1A The hardware depicted in the can vary for different implementations. For example, other peripherals, such as optical drives, etc., local area network (LAN) / wide area network (WAN) / wireless (e.g., Wi-Fi) adapters, graphics adapters, disk controllers, input / output (I / O) adapters, network connection devices, can be used in addition to or in place of the hardware depicted. The depicted examples are provided for purposes of explanation only and are not intended to imply architectural limitations with respect to the present disclosure.

[0051] The system according to an embodiment of the present disclosure includes an operating system that employs a graphical user interface. The operating system permits the simultaneous presentation of multiple display windows in the graphical user interface, wherein each display window provides an interface for a different application or for a different instance of the same application. A cursor in the graphical user interface can be manipulated by a user through a pointing device. The position of the cursor can be changed, and / or an event such as a click of a mouse button can be generated to actuate a desired response.

[0052] One of various commercially available operating systems (such as Microsoft Windows TM Versions of ) may be adopted with appropriate modifications. An operating system is modified or created according to the present disclosure as described.

[0053] The present invention is not limited to a specific computer system platform, processing unit, operating system or network. One or more aspects of the present invention can be distributed between one or more computer systems (e.g., configured to provide one or more services to one or more client computers or servers that perform complete tasks in a distributed system). For example, one or more aspects of the present invention can be performed on a client-server system including components distributed between one or more server systems that perform multiple functions according to various embodiments. These components include, for example, executable, intermediate or interpreted code that communicates on a network using a communication protocol. The present invention is not limited to being executable on any particular system or system group, and is not limited to any particular distributed architecture, network or communication protocol.

[0054] refer to Figure 1C , according to one embodiment of the present invention, a block diagram of an onboard unit 110 is shown. The onboard unit 110 includes a second processing unit 175, a second memory 180, a second GUI 182, and a second communication unit 184. The second GUI 182 may include a web-based interface, a web-based downloadable application interface, etc. The second communication unit 184 may be composed of a transmitter (not shown), a receiver (not shown), and a communication port (not shown) for connecting to a network interface directly or through an access point. More specifically, the second communication unit 184 enables the onboard unit 110 to communicate with the device 105.

[0055] As used herein, the second processing unit 175 means any type of computing 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 explicit parallel instruction computing microprocessor, a graphics processor, a digital signal processor, or any other type of processing circuit. The second processing unit 175 may also include an embedded controller, such as a general or programmable logic device or array, an application specific integrated circuit, a single chip computer, etc. Generally, the second processing unit 175 may include hardware elements and software elements. The second processing unit 175 may be configured for multi-threading, which simultaneously hosts different computing processes and executes any one in parallel or switches between active and passive computing processes.

[0056] The second memory 180 may be a volatile memory and a non-volatile memory. The second memory 180 may be coupled for communication with the second processing unit 175. The second processing unit 175 may execute machine-readable instructions and / or codes stored in the second memory 180. A variety of computer-readable storage media may be stored in the second memory 180 and accessed from the second memory 180. The second memory 180 may include any suitable element for storing data and machine-readable instructions, such as a read-only memory, a random access memory, an erasable programmable read-only memory, an electrically erasable programmable read-only memory, a hard disk drive, a removable media drive for handling a compact disk, a digital video disk, a magnetic disk, a cassette, a memory card, and the like.

[0057] The onboard unit 110 further includes: a plurality of input / output (I / O) interfaces 185-1, 185-2, ... 185-9 for receiving operation data associated with the rail vehicle 102 from system components 190-1, 190-2, ... 190-3 (hereinafter collectively referred to as system components 190) in real time, and for providing operation instructions generated by the device 105 to the system components 190 for execution at the system components 190. For simplicity and ease of explanation, the present embodiment is explained by regarding the human-machine interface (HMI) 190-1, the forensic recording unit (JRU) 190-2, the radar system 190-3, the odometer pulse generator (OPG) 190-4, the transponder 190-5, the passenger information system / transportation management system (PIS / TMS) 190-6, the diagnostic system 190-7, the driver's cabin control device 190-8, and the train control device 190-9 as the system component 190. Accordingly, the plurality of I / O interfaces 185-1, 185-2, ... 185-9 include a human-machine interface (HMI) interface 185-1, a forensic recording unit (JRU) interface 185-2, a radar interface 185-3, an odometer pulse generator (OPG) interface 185-4, a transponder interface 185-5, a passenger information system / transportation management system (PIS / TMS) interface 185-6, a diagnostic interface 185-7, a driver's cockpit interface 185-8, and a train control interface 185-9. Each of the I / O interfaces 185-1, 185-2, ... 185-9 may include a transmitter (not shown), a receiver (not shown), and a communication port (not shown) that enable the onboard unit 110 to communicate with the corresponding system components.

[0058] The HMI interface 185-1 is configured to enable the onboard unit 110 to communicate with the HMI 190-1 on the rail vehicle 102. The onboard unit 110 can receive input or control commands provided by the driver through the HMI 190-1 on the HMI interface 185-1. The onboard unit 110 can also provide feedback to the driver through the HMI 190-1 on the HMI interface 185-1. In one example, the HMI 190-1 can be an LCD touch screen for receiving touch gestures. For example, a human operator can provide a touch gesture for changing the operating mode of the rail vehicle 102 from manual to semi-automatic. The LCD touch screen can also provide visual indications related to the state of the operation of the rail vehicle 102. For example, the state can include the speed of the rail vehicle 102, the permitted speed of the rail vehicle 102, the upcoming station, the estimated time to arrive at the upcoming station, etc. The visual indication can also be related to an alarm or instruction to the driver of the rail vehicle 102.

[0059] The forensic recording unit (JRU) interface 185-2 is configured to enable the onboard unit 110 to communicate with the JRU 190-2. The JRU 190-2 is a device that facilitates the collection, storage, and retrieval of life-critical information associated with the rail vehicle 102. The life-critical information may include audio and video signals related to events associated with the rail vehicle 102. For example, the video signal is collected from a CCTV unit installed across the rail vehicle 102. The onboard unit 110 can store and retrieve information stored in the JRU 190-2 through the JRU interface 185-2.

[0060] Radar interface 185-3 is configured to enable onboard unit 110 to receive the speed of rail vehicle 102 from radar system 190-3. In one example, radar system 190-3 may be mounted on rail vehicle 102 and configured to measure the speed of rail vehicle 102, for example, based on the Doppler effect.

[0061] The odometer pulse generator (OPG) interface 185-4 is configured to enable the onboard unit 110 to communicate with the OPG 190-4. The OPG 190-4 may be located on an axle of the rail vehicle 102 and may measure the distance covered by the rail vehicle 102.

[0062] Transponder interface 185-5 is configured to enable onboard unit 110 to communicate with at least one of a transponder transmission module provided on rail vehicle 102 or a transponder 190-5 provided on the rails. Each transponder may be associated with unique track coordinates that enable onboard unit 110 to determine the exact location of rail vehicle 102.

[0063] The passenger information system / transportation management system (PIS / TMS) interface 185-6 is configured to enable the onboard unit 110 to communicate with the PIS / TMS 190-6. In one example, the PIS / TMS interface 185-6 receives operational data from the PIS / TMS 190-6, such as the distance to the upcoming station, the estimated time to arrive at the upcoming station, and the duration of the stop at the upcoming station.

[0064] The diagnostic interface 185-7 is configured to enable the onboard unit 110 to communicate with a diagnostic system 190-7 on the rail vehicle 102. The diagnostic system 190-7 may record and store diagnostic information, such as faults associated with the rail vehicle 102, operational data associated with the rail vehicle 102, correlations between faults, operational status of the rail vehicle 102, and the like.

[0065] The driver's cockpit interface 185-8 is configured to enable the onboard unit 110 to communicate with the driver's cockpit control device 190-8 provided in the driver's cockpit. For example, the onboard unit 110 can receive operating data associated with the driver's cockpit control device 190-8, which is associated with the opening and closing of doors, the operation of lights, communication systems, etc. In another example, the operating data may include an operating mode of the rail vehicle 102. The operating mode may be one of the following: manual, automatic, fully automatic, semi-automatic, and extended automatic.

[0066] The train control interface 185-9 is configured to enable the onboard unit 110 to communicate with one or more train control devices 190-9. The train control device 190-9 is configured to provide control signals for driving the rail vehicle 102 and also for actuating brakes. The brakes may include an electrical braking system for primary braking and a pneumatic braking system for backup or secondary purposes. In addition to the above, the second memory 180 also includes an offline emergency module 195. The offline emergency module includes a machine-readable instruction set that manages the operation of the rail vehicle 102 when the communication between the onboard unit 110 and the device 105 is interrupted (for example, when the rail vehicle 102 passes through a tunnel). The second memory can also store predefined operating instructions to be executed when the communication between the onboard unit 110 and the device 105 is interrupted. For example, one of the predefined operating instructions can be associated with reducing the level of the operating mode of the rail vehicle 102 (such as from automatic to manual mode).

[0067] refer to Figure 2 , combined with Figure 1A , 1B1C , according to one embodiment of the present invention, shows a method 200 for managing the operation of a rail vehicle 102 . The method includes steps 205 - 215 . In one embodiment, the method 200 is implemented using the device 105 .

[0068] At step 205, a virtual subsystem for managing a specific operation of the rail vehicle 102 is identified from among a plurality of virtual subsystems based on operational data associated with the rail vehicle 102. The operational data includes values ​​of parameters associated with the operation of the rail vehicle 102.

[0069] At step 210 , one or more operating instructions capable of managing the operation of the rail vehicle 102 are generated based on the configuration of the rail vehicle 102 using the identified virtual subsystems.

[0070] At step 215, execution of the one or more operating instructions capable of managing operation of the rail vehicle 102 is initiated at a system component 190 configured to execute the one or more operating instructions. The system component 190 is remotely located relative to the first processing unit 125 (ie, the device 105).

[0071] refer to Figure 3 , combined with Figure 1A , 1B 1C , according to one embodiment of the present invention, shows a method 300 for mitigating safety risks associated with a rail vehicle 102 . The method includes steps 305 - 325 . In one embodiment, the method 300 is implemented using the device 105 .

[0072] At step 305, an anomaly in the operation of the rail vehicle 102 based on the operational data is determined by first analyzing the operational data with respect to deviations in the values ​​of one or more key parameters relative to a predefined range of values ​​for the one or more key parameters. Further, a deviation in the values ​​of one or more key parameters relative to a predefined range of values ​​for the one or more key parameters is determined. Based on the deviation in the values ​​of the one or more key parameters, an anomaly in the operation of the rail vehicle 102 is determined. For example, assume that the anomaly is the heating of an axle box present on the rail vehicle 102. The anomaly can be determined by comparing the temperature of the axle with a predefined temperature. The temperature on the axle can be measured using an infrared sensor and transmitted to the device 105 on the onboard unit 110. Further, if the measured axle temperature is greater than the predefined temperature, the rail vehicle 102 can be associated with an anomaly of overheating of the axle.

[0073] At step 310, a root cause analysis technique is used to determine a root cause associated with the anomaly in the operation of the rail vehicle 102. For example, the root cause associated with the anomaly can be determined using a neural network model. The neural network model can be pre-trained using deviation data associated with one or more rail vehicles to determine the root cause. The root cause can be identified as, for example, a lack of lubrication in a wheel bearing mounted on an axle.

[0074] At step 315, a safety risk associated with an anomaly in the operation of rail vehicle 102 is predicted. The safety risk may be predicted based on a risk indicator value determined from the operational data. For example, if the risk indicator value is greater than, for example, 8, the safety risk may be associated with a derailment of rail vehicle 102.

[0075] At step 320, one or more actions are determined to mitigate the safety risk. For example, the one or more actions may include lubricating the wheel bearings.

[0076] At step 325, an operational instruction is generated for implementing one or more actions for mitigating the safety risk. For example, the operational instruction may be associated with displaying a notification indicating the safety risk and one or more recommendations for mitigating the safety risk on the HMI 190-1. The one or more recommendations for mitigating the safety risk may be pre-stored in the database 145. For example, the recommendation may include lubricating the wheel bearings at an upcoming stop. The operational instruction is further transmitted to the onboard unit 110. The onboard unit 110 may further display the notification on the HMI 190-1.

[0077] refer to Figure 4 , combined with Figure 1A , 1B 1C and 1C show a method 400 for optimizing downtime of a rail vehicle 102 according to one embodiment of the present invention. The method 400 includes steps 405-415. In one embodiment, the method 400 is implemented using the device 105.

[0078] At step 405 , an anomaly in the operation of rail vehicle 102 is determined.

[0079] At step 410, the remaining life of the rail vehicle 102 is determined based on the anomaly in the operation of the rail vehicle 102. In one embodiment, the remaining life of the rail vehicle 102 can be determined based on the data logged by the data log module 158. More specifically, the remaining life is determined based on the hazard model and probability distribution associated with the failure time of key components available from the maintenance data in the data log. For example, the failure time of the key component can be determined using a bathtub degradation model, the failure time of another key component can be based on a Poisson distribution, and so on. Further, the remaining life of the rail vehicle 102 can be determined based on, for example, the shortest failure time among all the key components of the rail vehicle 102.

[0080] At step 415, the downtime of the rail vehicle 102 is optimized by scheduling the maintenance activities of the rail vehicle 102 based on the remaining life of the rail vehicle 102. For example, it is assumed that the remaining life of the wheel bearing is 28 days. The downtime can be optimized by scheduling the maintenance activities based on the availability of the spare wheel bearing and the service personnel. If the spare wheel bearing is easily available and the service personnel are free from, for example, 3pm to 5pm on the same day, and the actual repair time required to replace the wheel bearing is 30 minutes, the maintenance activities can be scheduled between 3pm and 4pm on the same day. However, if the spare wheel bearing is not available, the device 105 can transmit a notification of obtaining the spare wheel bearing (e.g., using a transaction portal link associated with the seller of the wheel bearing sent together with the notification) to the service personnel's electronic device. Further, the maintenance activities can be scheduled based on the availability of the service personnel after the estimated arrival time provided on the transaction portal link, after the service personnel place an order for the wheel bearing on the transaction portal, and before the remaining life of the wheel bearing on the rail vehicle 102 is exhausted.

[0081] refer to Figure 5 , combined with Figure 1A , 1B 1C, according to an exemplary embodiment of the present invention, shows a flow chart of a method 500 for managing life-critical operations of a rail vehicle 102. The method is implemented on the device 105 and is explained by taking the example of controlling the speed of the rail vehicle 102. The method includes steps 505-520.

[0082] At step 505, the device 105 receives operational data associated with the rail vehicle 102 from the onboard unit 110 located on the rail vehicle 102. The operational data is obtained from the system component 190 communicatively coupled to the onboard unit 110. In this example, the operational data includes the speed of the rail vehicle 102 received from the radar system 190-3 and the permitted speed of the rail vehicle 102 as received from the wayside signaling unit.

[0083] At step 510, the core manager module 152 identifies a virtual ATP subsystem 168 for controlling the rail vehicle 102 based on the operational data associated with the rail vehicle 102. The core manager module 152 provides the virtual ATP subsystem 168 with the distance covered by the rail vehicle 102, the speed of the rail vehicle 102, the permitted speed of the rail vehicle 102, and the location of the rail vehicle 102.

[0084] At step 515, the virtual ATP subsystem 168 may determine that the speed of the rail vehicle 102 is below the permitted speed of the rail vehicle 102. If the speed of the rail vehicle 102 is above the permitted speed or if the speed of the rail vehicle 102 is close to the permitted speed, the virtual ATP subsystem 168 may generate one or more operating instructions for limiting the speed of the rail vehicle 102 based on the configuration of the rail vehicle 102. The one or more operating instructions may be used to apply brakes.

[0085] At step 520, the one or more operating instructions are transmitted to the onboard unit 110. The onboard unit 110 may further provide control signals to a train control device associated with braking via the train control interface 185-9. The train control device may further actuate a brake valve associated with a pneumatic or electrical brake system for engaging the brake.

[0086] refer to Figure 6 , combined with Figure 1A , 1B 1C, according to an exemplary embodiment of the present invention, shows a flow chart of a method 600 for managing non-life-critical operations of a rail vehicle 102. The method 600 is explained by giving an example of a non-life-critical operation of opening doors on the rail vehicle 102 together with platform screen doors when the rail vehicle 102 is parked at an appropriate position at a train station. The method can be implemented on the device 105. The method 600 includes steps 605-620. It is assumed that the operating mode of the rail vehicle 102 is automatic. The operating mode can be determined by the virtual ATP subsystem 168.

[0087] At step 605, the device 105 receives operational data associated with the rail vehicle 102 from the onboard unit 110 located on the rail vehicle 102. The operational data may include an operating mode received from the virtual ATP subsystem 168 of the device 105, track coordinates received from the transponder 190-5 on the rail, and also track data obtained from track equipment (such as a wayside unit) or from the database 145. The track data may include information associated with the route that the rail vehicle 102 is to follow.

[0088] At step 610, the core manager module 152 identifies a virtual subsystem for managing the opening and closing of doors on the rail vehicle 102. In this example, although the opening of doors is a non-life-critical function, it is necessary to ensure that the doors of the rail vehicle 102 are not opened in a position that is unsafe for passengers boarding or disembarking the rail vehicle 102. Therefore, the core manager module 152 initially identifies a virtual ATP subsystem 168 for managing the opening of the doors of the rail vehicle 102.

[0089] At step 615, the virtual ATP subsystem 168 analyzes the trajectory data and the trajectory coordinates to determine whether the door can be opened. Further, the virtual ATP subsystem 168 generates a digital output based on the analysis of the trajectory data and the trajectory coordinates. More specifically, the virtual ATP subsystem 168 can generate a digital output indicating whether the door can be opened. For example, assume that the virtual ATP subsystem 168 generates a digital output "1" indicating that the door can be opened. The digital output "1" causes the virtual ATO subsystem 166 to be triggered to generate an operation instruction for opening the door.

[0090] At step 620, the operating instructions are transmitted to the onboard unit 110. The onboard unit 110 may further provide operating instructions from the virtual ATO subsystem 166 to train the control interface 185-9 for opening the door on the rail vehicle 102. Similarly, the virtual ATO subsystem 166 may also provide operating instructions for the synchronous operation of the platform screen door and the door of the rail vehicle 102.

[0091] The device 105 may also generate a report including the values ​​of parameters associated with the operational data, commands provided to the rail vehicle 102, detected anomalies, root causes of the anomalies, safety risks associated with the anomalies, actions taken to mitigate the safety risks, scheduled maintenance activities, optimized downtime of the rail vehicle 102 based on the scheduled maintenance activities, etc. The report may be generated, for example, during every 5 minutes of operation of the rail vehicle 102.

[0092] The present invention may take the form of a computer program product including program modules accessible from a computer-usable or computer-readable medium storing program code for use by or in conjunction with one or more computers, processors, or instruction execution systems. For the purposes of this description, a computer-usable or computer-readable medium is any device that can contain, store, transmit, propagate, or transmit a program for use by or in conjunction with an instruction execution system, device, or apparatus. The medium may be an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system (or device or apparatus), or a propagation medium in a signal carrier and a propagation medium that is itself a signal carrier is not included in the definition of a physical computer-usable medium, which includes semiconductor or solid-state memory, magnetic tape, removable computer disk, random access memory (RAM), read-only memory (ROM), rigid disk, and optical disk, such as compact disk read-only memory (CD-ROM), compact disk read / write, and DVD. Both the processor and program code used to implement each aspect of the technology may be centralized or distributed (or a combination thereof), as known to those skilled in the art.

[0093] Although the present invention has been illustrated and described in detail by means of the preferred embodiments, the present invention is not limited to the disclosed examples. Other variations may be deduced by those skilled in the art without departing from the scope of the invention claimed.

Claims

1. A computer-implemented method for remotely managing the operation of a rail vehicle (102), the method comprising: identifying, by a processing unit (125), a virtual subsystem for managing a specific operation of the rail vehicle (102) from a plurality of virtual subsystems based on operational data associated with the rail vehicle (102), wherein the operational data includes values ​​of parameters associated with the operation of the rail vehicle (102); generating one or more operating instructions capable of managing the operation of the rail vehicle (102) based on the configuration of the rail vehicle (102) using the identified virtual subsystem; as well as Execution of the one or more operating instructions capable of managing operation of the rail vehicle (102) is initiated at a system component (190) configured to execute the one or more operating instructions, wherein the system component (190) is remotely located relative to the processing unit (125).

2. The method of claim 1, wherein the virtual subsystem is associated with one or more life-critical functions for ensuring the safety of the rail vehicle (102).

3. The method of claim 1, wherein the virtual subsystem is associated with one or more non-life-critical functions for automating operation of the rail vehicle (102).

4. The method of claim 1, wherein the virtual subsystem is associated with managing a communication interface present on the rail vehicle (102).

5. The method according to any one of claims 1 to 4, further comprising: Anomalies in the operation of the rail vehicle (102) are determined based on the operational data.

6. The method of claim 5, wherein determining an anomaly in the operation of the rail vehicle (102) based on the operational data comprises: analyzing the operational data with respect to deviations in values ​​of one or more key parameters relative to a predefined range of values ​​for the one or more key parameters; determining a deviation in a value of one or more key parameters relative to a predefined range of values ​​for the one or more key parameters; as well as Anomalies in the operation of the rail vehicle (102) are determined based on deviations in the values ​​of the one or more key parameters.

7. The method according to claim 5 or 6, further comprising: Root cause analysis techniques are used to determine a root cause associated with an anomaly in the operation of the rail vehicle (102).

8. The method according to any one of claims 5 to 7, further comprising: predicting a safety risk associated with an anomaly in the operation of the rail vehicle (102); determining one or more actions for mitigating the security risk; as well as Operational instructions are generated for implementing the one or more actions for mitigating the security risk.

9. The method according to any one of claims 5 to 9, further comprising: The remaining life of the rail vehicle (102) is determined based on anomalies in the operation of the rail vehicle (102).

10. The method according to claim 9, further comprising: Downtime of a rail vehicle (102) is optimized by scheduling maintenance activities of the rail vehicle (102) based on the remaining life of the rail vehicle (102).

11. The method according to claim 1, further comprising: A report associated with the operation of the rail vehicle (102) is generated.

12. An apparatus (105) for remotely managing the operation of a rail vehicle (102), the system comprising: one or more processing units (125); as well as A memory unit (140) is communicatively coupled to the one or more processing units (125), wherein the memory unit (140) includes a management module (148) stored in the form of machine-readable instructions executable by the one or more processing units (125), wherein the management module (148) is configured to manage the operation of the rail vehicle (102) according to any one of method claims 1 to 11.

13. A system (100) for managing the operation of a rail vehicle (102), the system (100) comprising: one or more system components (190) for providing operational data associated with operation of the rail vehicle (102), wherein the operational data includes values ​​of parameters associated with operation of the rail vehicle (102); as well as The device (105) according to claim 12 is communicatively coupled to the one or more system components (190), wherein the device (105) is configured to manage the operation of the rail vehicle (102) based on the operating data according to any one of method claims 1 to 11.

14. The system (100) according to claim 13, further comprising an onboard unit (110) located on the rail vehicle (102), the onboard unit (110) comprising: a plurality of interfaces for communicating with the one or more system components (190) and the device (105) for enabling the one or more system components (190) to be communicatively coupled with the device (105); one or more processing units (175); and A memory unit (180) is communicatively coupled to the one or more processing units (175), wherein the memory unit (180) includes an offline emergency module (195) stored in the form of machine-readable instructions executable by the one or more processing units (175), wherein the offline emergency module (195) is configured to: manage the operation of the rail vehicle (102) when communication between the onboard unit (110) and the device (105) is interrupted.

15. A computer program product having machine-readable instructions stored therein, which, when executed by one or more processing units (125), cause the processing units (125) to perform the method according to any one of claims 1 to 11.

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