Traffic scheduling training system, method and equipment and computer readable medium

Abstract

The invention discloses a train dispatching training system, method and device and a computer readable medium, and relates to the field of rail transit dispatching training, and the system comprises an ATS train automatic monitoring system which is used for monitoring and analyzing the operation states of a train and a signal device according to the training moment demand, and sending the operation state of the train and the operation state of the signal device to a server; obtaining train key feature information used for generating a training scene; the virtual NPC train system is used for simulating an operation mechanism of the real ATC system, creating a virtual NPC train according to the train key feature information and simulating an operation state of an operation train so as to complete construction of a training scene and automatically control the virtual NPC train; according to the method and the device, the corresponding training scene can be generated at any moment, the whole training process is independent through automatic control of the train, the problem that the training efficiency is low due to the fact that the training scene cannot be dynamically generated and the whole training process depends in the prior art is solved, and the train dispatching training efficiency is remarkably improved.

Description

Technical Field

[0001] The present application relates to the field of rail transit dispatching training, and specifically to a train dispatching training system, method, device and computer-readable medium. Background Art

[0002] In the rail transit sector, dispatcher training requires the ability to macro-control train operations across the entire line. However, current professional training for train dispatchers relies on practical exercises during non-operating hours (i.e., nighttime). Loading multiple scenarios during training requires pre-definition of parameters such as fault type and equipment status. It is impossible to directly extract the actual operating status at any given moment from the timetable and dynamically generate training scenarios. Furthermore, existing training systems still require the coordination of drivers, stations, and other positions during train dispatching. This means that trainees must rely on multi-position collaboration or system simulation interaction, unable to completely break away from their reliance on other positions like drivers and achieve full independence in the dispatch training process. Therefore, this approach, which lacks the flexibility to select dispatch scenarios and conduct independent practical training, is not only costly but also fails to achieve accurate job matching and efficient utilization, resulting in low training efficiency. Summary of the Invention

[0003] The purpose of this application is to address the problem of low training efficiency in the existing technology due to the inability to dynamically generate training scenarios and the dependence of the entire training process; a train scheduling training system, method, equipment and computer-readable medium are proposed, in which the ATS train automatic monitoring system analyzes the key feature information of the train according to the training time requirements, the virtual NPC train system simulates the operation mechanism of the real ATC system, and creates a virtual NPC train according to the ATS train automatic monitoring system and simulates the train operation status to generate dynamic training scenarios, and automatically controls the virtual NCP train at the same time, overcoming the problem of low training efficiency in the existing technology due to the inability to dynamically generate training scenarios and the dependence of the entire training process. This application can generate corresponding training scenarios according to any time, and the automatic control of the train realizes the independence of the entire training process, which significantly improves the efficiency of train scheduling training.

[0004] To achieve the above objectives, the technical solutions adopted in the embodiments of the present application are as follows: In a first aspect, an embodiment of the present application provides a vehicle dispatching training system, the system comprising: The ATS automatic train monitoring system monitors and analyzes the operating status of trains and signaling equipment according to training schedule requirements, obtaining key train feature information used to generate training scenarios; The virtual NPC train system is used to simulate the operating mechanism of a real ATC system, create a virtual NPC train based on the key feature information of the train and simulate the operating status of the operating train to complete the construction of the training scenario and automatically control the virtual NPC train.

[0005] In this solution, the ATS train automatic monitoring system monitors and analyzes the operating status of the trains and signal equipment of the completed timetable, and can obtain the operating parameters of the actual operating trains and signal equipment at any time, thereby providing accurate data support for the virtual NPC train system to create the virtual NPC trains and their operating status required for training; since the training time requirements are dynamically changing, this application specifically analyzes the real train and signal equipment information of the rail transit system at the completed time according to the time requirements of each trainee, and then generates a virtual NPC train for that time in a targeted manner, avoiding the complex process of establishing the training scenario and improving the flexibility and adaptability of the training scenario; by simulating the operating mechanism of the real ATC system, the virtual NPC train simulates the operating status of the operating train, thereby constructing a complete training scenario and realizing a dynamic generation mechanism for the training scenario. In this train scheduling training system, the virtual NPC train is automatically controlled by the virtual NPC train system, that is, the virtual NPC train is a fully automatic train that cooperates with the scheduling exclusively for the training scenario, so that the trainees can independently complete the scheduling training tasks without the cooperation of other job roles, realizing the independence of the entire training process, thereby improving the training efficiency.

[0006] Preferably, the ATS automatic train monitoring system includes: The monitoring subsystem is used to interact with the ATC system and the wayside control system to obtain the coordinated monitoring information of all operating trains and signal equipment by the ATC onboard system and the wayside control system; The parsing subsystem is used to parse the collaborative monitoring information to obtain key feature information of the train for generating training scenarios.

[0007] Preferably, parsing the collaborative monitoring information to obtain key train feature information for generating a training scenario includes: Based on the historical completed timetable of the operating trains, obtaining the collaborative monitoring information at each time; Matching the time information required for training with the historical completion time table, and using the collaborative monitoring information corresponding to the matched historical completion time as the target parsing object; The train's location information, status information, early or late arrival information, number information and running direction information are extracted according to the target parsing object to obtain the train's key feature information for generating training scenarios.

[0008] Preferably, extracting the train location information according to the target parsing object includes: Extract the platform area information where the train is located at the corresponding time based on the time information required for training; Based on the platform area information combined with the train dynamic positioning information monitored by the ATC system and the track occupancy information monitored by the wayside control system, the position offset of the train in the block section is comprehensively analyzed to obtain the train position information.

[0009] Preferably, the virtual NPC train system includes: The simulated ATC system is configured to receive a dispatch instruction, generate the virtual NPC train based on the key characteristic information of the train corresponding to the historical completion time according to the required training time, and initialize the control logic of the virtual NPC train by simulating the operation mechanism of the real ATC system; The simulated vehicle TCMS system is used to control the operating conditions of the virtual NPC train and to link the simulated ATC system to generate a full-process scenario of train operation to complete the construction of dynamic training scenarios and automatic control of the virtual NPC train.

[0010] Preferably, the step of generating the virtual NPC train based on the key train feature information corresponding to the historical completion time according to the required training time, and simulating the operation mechanism of the real ATC system to initialize the control logic of the virtual NPC train includes: Determine the training start time based on the train operation period; Based on the training start time, the train's location information, status information, early or late information, number information, and running direction information are obtained at the corresponding historical completion time. The virtual NPC train is created according to the train's location information, status information, early or late arrival information, number information and running direction information, and the basic attribute information, driving mode and running status of the virtual NPC train are initialized.

[0011] Preferably, the linking of the simulated ATC system to generate a full-process scenario of train operation to complete the construction of a dynamic training scenario and the automatic control of the virtual NPC train includes: The TCMS system simulates the internal equipment status of the operating train and interacts with the ATC system to perform the operation parameters and fault information of the virtual NPC train; When the running status of the virtual NPC train reaches the operating train status corresponding to the timetable, the current time point is bound to the virtual clock of the virtual NPC train system, so that the clock of the train scheduling training system is uniformly adjusted to the current time point, completing the establishment of the full process scenario; Synchronously, the internal equipment and operating conditions of the virtual NPC train are managed according to the dispatching instructions, and the automatic control of the virtual NPC train is completed in combination with the automatic driving mode of the virtual NPC.

[0012] In a second aspect, an embodiment of the present application provides a driving dispatch training method, comprising: Monitor and analyze the operating status of trains and signaling equipment according to training time requirements to obtain key train feature information for generating training scenarios; Based on the dispatch instructions, a virtual NPC train is created according to the key characteristics of the train by simulating the operating mechanism of the real ATC system and the operating status of the operating train is simulated to build a dynamic training scenario and visualize the scenario on the ATS interface; The virtual NPC train is controlled based on the dynamic training scenario to perform a scheduling training task.

[0013] In a third aspect, an embodiment of the present application provides an electronic device comprising: a processor, a memory, and a network interface, wherein the memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory through the network interface, and the processor executes the machine-readable instructions to perform the steps of the vehicle scheduling training method described in the second aspect above.

[0014] In a fourth aspect, an embodiment of the present application provides a computer-readable medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the vehicle dispatching training method described in the second aspect are executed.

[0015] Beneficial effects of this application: 1. By analyzing the operating status of all trains in the timetable and restoring these train states to the operating scenarios at that moment, train participants can achieve dynamic and flexible training scenarios. The dispatching system can automatically load information such as trackside equipment status, train location and parameters at the selected time point, eliminating the need to manually configure faults or equipment status item by item, reducing human errors, simplifying the pre-training process of dispatching training, and improving training efficiency. 2. By creating a virtual train and initializing the control logic of the virtual train through the virtual NPC train system, the virtual train has the basic train operation functions of the main line and the system initialization function. This solves the problem that dispatching training requires the cooperation of drivers, and can complete dispatching training independently, reducing training costs and further improving training efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Other features, objects, and advantages of the present application will become more apparent upon reading the detailed description of non-limiting embodiments made with reference to the following drawings. The drawings are provided for illustration purposes only and are not to be construed as limiting the present application. Like reference numerals are used throughout the drawings to denote like parts.

[0017] Figure 1 A schematic diagram of a driving dispatch training system module provided in an embodiment of the present application.

[0018] Figure 2 A schematic diagram of train timetable information provided in an embodiment of the present application.

[0019] Figure 3 A detailed schematic diagram of the analysis of key feature information of a train provided in an embodiment of the present application.

[0020] Figure 4 A flow chart of a vehicle dispatching training method provided in an embodiment of the present application.

[0021] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solutions and advantages of this application more clear, the application is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific implementation method described here is only an optimal embodiment of this application, which is only used to explain this application and does not limit the scope of protection of this application. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0023] Example 1: Figure 1 As shown, a driving dispatch training system includes: The ATS automatic train monitoring system is used to monitor and analyze the operating status of trains and signal equipment according to training time requirements, and obtain key train feature information for generating training scenarios.

[0024] In this embodiment, the ATS automatic train monitoring system completes the management and control of subway operating trains and signal equipment by coordinating with other subsystems in the ATC system, and parses the completed timetable and the details of other system messages received by ATS. According to the time information required for training, the key feature information of the train at the corresponding time point is analyzed on the timetable, so as to generate the train operation scenario required for scheduling training based on the key feature information of the train. The operation scenario at least includes the basic attribute information and operation status of the train.

[0025] The virtual NPC train system is used to simulate the operating mechanism of a real ATC system, create a virtual NPC train based on the key feature information of the train and simulate the operating status of the operating train to complete the construction of the training scenario and automatically control the virtual NPC train.

[0026] In this embodiment, the virtual NPC train system can use the parsed key feature information of the train to generate training scenarios, without the need for manual pre-compilation of scenarios, simplifying the pre-training process and realizing the dynamic scene loading capability of selecting a point and practicing, thereby helping to improve the efficiency of scheduling training.

[0027] Specifically, the ATS automatic train monitoring system includes: The monitoring subsystem is used to interact with the ATC system and the wayside control system to obtain the coordinated monitoring information of all operating trains and signal equipment by the ATC onboard system and the wayside control system; The parsing subsystem is used to parse the collaborative monitoring information to obtain key feature information of the train for generating training scenarios.

[0028] In this embodiment, the monitoring subsystem is linked to the ATC system and receives information about operating trains and trackside equipment, known as collaborative monitoring information, from the ATC system. The parsing subsystem parses the timetable and historical system messages received by the ATS to generate this collaborative monitoring information. This allows the user to select any time point as the training start point, automatically generating a full-line train operation scenario based on the timetable corresponding to that start point based on the collaborative monitoring information.

[0029] Specifically, parsing the collaborative monitoring information to obtain key train feature information for generating a training scenario includes: Based on the historical completed timetable of the operating trains, obtaining the collaborative monitoring information at each time; Matching the time information required for training with the historical completion time table, and using the collaborative monitoring information corresponding to the matched historical completion time as the target parsing object; The train's location information, status information, early or late arrival information, number information and running direction information are extracted according to the target parsing object to obtain the train's key feature information for generating training scenarios.

[0030] In some embodiments, the train position information indicates that the train runs to a certain position on the line at the selected training start time; the status information indicates the train's operating mode, operating conditions, speed information, etc. at this time. In the subsequent scheduling training process, the operating status of the virtual train will be initialized based on these status information, so that the training scenario is more in line with the real operation scenario, improving the authenticity and reliability of the training; the train early or late information indicates the deviation information between the train and the current train and the planned time information at this time, among which, if the current train runs ahead of the planned time, it is considered to be early, and if the current train runs later than the planned time, it is considered to be late; the train number signal indicates the train number, destination code and other information of the train at this time; the train's running direction refers to whether the train needs to run on the main line or in the direction on the line.

[0031] Specifically, the user selects any time point during the subway operation period as the training start time. The ATS automatic train monitoring system extracts the train position information at that time point from the timetable, determines the basic data such as the train's station interval, train number, and running direction, extracts the train's real-time mileage from the message sent to ATS by the ATC system, and analyzes the train's driving mode, operating conditions and other status data to simulate the train's running status.

[0032] In this embodiment, by analyzing key characteristic information such as the train's location, status, early or late arrival, number, and direction of travel, a highly realistic training scenario can be systematically constructed without the need for real trains or drivers, reducing training costs. It also supports the generation of scenarios at any time and in any combination, achieving flexibility in training scenarios. It can also repeatedly generate a specific training scenario based on the selected time, achieving training effectiveness and resource availability, significantly improving scenario restoration, and enhancing the targeted nature of training.

[0033] Specifically, extracting the train location information according to the target parsing object includes: Extract the platform area information where the train is located at the corresponding time based on the time information required for training; Based on the platform area information combined with the train dynamic positioning information monitored by the ATC system and the track occupancy information monitored by the wayside control system, the position offset of the train in the block section is comprehensively analyzed to obtain the train position information.

[0034] It should be noted that for the train's location information, the timetable can only analyze which two stations the train is in, and it is not possible to accurately locate the train at the time point. Therefore, it is necessary to combine the mileage information and speed sent by the ATC system and the occupancy information sent by the interlocking system to calculate the train's position offset information in which block section and which section.

[0035] Among them, the occupancy status data of the occupied information track segment includes at least the track segment number, occupancy status and occupancy timestamp; the detected track segment is identified by the track segment number, whether the track segment is currently occupied or idle is obtained by the occupancy status, and the specific time when the segment is occupied or released is recorded by the occupancy timestamp.

[0036] In some embodiments, the position offset of the train can be expressed as: ,Here the rough section of the rough train is determined by the timetable, the range is narrowed down to the block section by the occupancy information, and the position offset is calculated by the mileage information.

[0037] Specifically, the position offset is calculated based on the starting mileage of the block section and the current mileage of the train sent by the onboard ATC, for example: ; Then, the rationality of the position offset is verified in combination with the train speed information. If the speed is 0 km / h and the mileage remains unchanged, it means that the train is stationary at the current position; if the speed is not 0 km / h, the mileage difference and time difference before and after the time point are used to reversely verify whether the position calculation conforms to the motion trajectory, and whether there is any overspeeding or jump.

[0038] It is understandable that since the key characteristic information of the train is analyzed at the same time, the timetable, ATC mileage, and interlocking occupancy information are precisely aligned at the same time point, further ensuring the accuracy of the position offset.

[0039] In some examples, such as Figure 2 As shown, we first select 12:30 as the time point for this training. We then obtain the train number and location information from the timetable at 12:30 to generate a timetable information diagram for that time. Based on this information diagram, we determine the operation status of the four trains at a certain time. We can draw a vertical arrow line in the diagram. This vertical arrow line will pass through the timetable lines of the four trains and intersect with them respectively, namely, with trains numbered M001002, M002002, M003002, and M004002. In the diagram, the green line represents the platform, the yellow line represents the train's upward path, and the purple line represents the train's downward path. When the yellow and purple lines cross the green line, a horizontal line will appear that overlaps with the green line, indicating the train's stay time at the platform. From this analysis, it was found that the four trains were M001002 at the Xingzhuang Station platform, M002002 between stations 15 and 16, M003002 between stations 13 and Hunan Road Station, and M004002 at the 11th station platform.

[0040] Furthermore, after obtaining the train stopping at the platform, the specific position of the train in the section is calculated based on the interlocking occupancy information, mileage information and speed parsed from the timetable, such as Figure 3 As shown, information extraction is performed in the parsed train list (i.e., a visual list of key feature information of the train).

[0041] Specifically, the virtual NPC train system includes: The simulated ATC system is configured to receive a dispatch instruction, generate the virtual NPC train based on the key characteristic information of the train corresponding to the historical completion time according to the required training time, and initialize the control logic of the virtual NPC train by simulating the operation mechanism of the real ATC system; The simulated vehicle TCMS system is used to control the operating conditions of the virtual NPC train and to link the simulated ATC system to generate a full-process scenario of train operation to complete the construction of dynamic training scenarios and automatic control of the virtual NPC train.

[0042] Specifically, the virtual NPC train is generated based on the key feature information of the train corresponding to the historical completion time according to the required training time, and the control logic of the virtual NPC train is initialized by simulating the operation mechanism of the real ATC system, including: Determine the training start time based on the train operation period; Based on the training start time, the train's location information, status information, early or late information, number information, and running direction information are obtained at the corresponding historical completion time. The virtual NPC train is created according to the train's location information, status information, early or late arrival information, number information and running direction information, and the basic attribute information, driving mode and running status of the virtual NPC train are initialized.

[0043] Specifically, the linkage with the simulated ATC system to generate a full-process scenario of train operation to complete the construction of dynamic training scenarios and the automatic control of the virtual NPC train includes: The TCMS system simulates the internal equipment status of the operating train and interacts with the ATC system to perform the operation parameters and fault information of the virtual NPC train; When the running status of the virtual NPC train reaches the operating train status corresponding to the timetable, the current time point is bound to the virtual clock of the virtual NPC train system, so that the clock of the train scheduling training system is uniformly adjusted to the current time point, completing the establishment of the full process scenario; Synchronously, the internal equipment and operating conditions of the virtual NPC train are managed according to the dispatching instructions, and the automatic control of the virtual NPC train is completed in combination with the automatic driving mode of the virtual NPC.

[0044] In this embodiment, the basic attribute information, driving mode and running status of the virtual NPC train are initialized. Specifically, the virtual NPC train system automatically generates a corresponding virtual train based on the parsed train number, running direction and other information, and initializes its basic attributes, such as vehicle model and formation; at the same time, the parsed mileage information and block section are synchronized to the virtual train, and the automatic driving mode information is synchronized to the virtual train, so that the virtual train automatically starts the automatic driving function, thereby eliminating the need for manual intervention and ensuring that users can independently complete the entire training process.

[0045] In addition, the parsed early or late times are converted into the operating parameters of the virtual train, so that it can automatically continue the delayed status in subsequent operations. For example, if it is delayed by five minutes, it will arrive at the station at the planned time + 5 minutes.

[0046] Furthermore, when the operating status of the virtual NPC train reaches the operating train status corresponding to the timetable, the clocks of the ATS train automatic monitoring system and the virtual NPC train system are uniformly adjusted to the selected time point to ensure that all equipment status is completely consistent with the time point. After the basic attribute information, driving mode and operating status of the virtual NPC train are initialized and the virtual clock is synchronized, the target training scenario is obtained.

[0047] Among them, the virtual NPC train is created and automatically controlled through the virtual NPC train system. After the time point is selected, the automatic loading of the scene can be completed quickly. Therefore, there is no need to manually configure train parameters or fault scenarios, and there is no need to rely on manual compilation of scenarios or cooperation of multiple positions. The entire training process is automated, thereby improving training efficiency, solving the problem of full-process dependence of existing technical training, and significantly reducing training costs.

[0048] In some embodiments, the virtual NPC train system is a combination of train control systems and vehicle systems in a simulated real ATC system. The difference from a conventional train control system is that the virtual NPC train system automatically creates a virtual NPC train based on the train's key feature information, namely the train's location information, status information, early or late arrival information, number information and running direction information, and automatically controls the virtual NPC train, including the initialization, upgrading and downgrading modes, and entry and exit of the virtual NPC train.

[0049] Furthermore, the virtual NPC train does not require manual driving and must undergo train positioning, wheel diameter calibration, and mode upgrade to FAM mode before it has the automatic driving function. When the virtual NPC train is created and the train control logic is initialized, the virtual train is configured to fully automatic driving mode. Therefore, the virtual NPC train is a fully automatic train used to cooperate with scheduling training for exclusive training scenarios.

[0050] Furthermore, at the start of training, the training system keeps time frozen. After the administrator issues the "start training" command, the virtual clock starts running and the virtual train continues to run according to the parsed status and plan.

[0051] In other embodiments, multi-system linkage simulations can also be performed. For example, the interlocking system simulated in the virtual NPC system can preemptively lock relevant routes based on analyzed occupancy information, while the simulated ATP system can generate safety protection curves based on train position and speed to achieve the response of trackside equipment in training scenarios. Furthermore, the training system can automatically or manually inject complex faults to fully simulate the emergencies encountered in real operations.

[0052] In some examples, the loading process for dispatch training is as follows: based on the parsed train position, the interlocking and regional control trackside systems are loaded and started first, and then the virtual NPC train system is loaded directly on the main line section and platform based on the parsed train position. After the virtual NPC train is started, it is automatically upgraded to the mode state of the original timetable operating train according to the parsed status information, including automatic upgrading of the driving mode, automatic assignment of train early and late information, automatic assignment of train number information and train operation direction. At this time, the virtual NPC train has the basic conditions for train operation. When the trackside system and the train system reach the state corresponding to the selected time point, the system binds this time point to the virtual clock, sends the virtual clock to the timetable to adjust the clock of the entire system to this time point, and then issues the training content: at this time, the virtual NPC train will continue to run at the selected time point for unified command by the dispatcher.

[0053] In this embodiment, through the automatic loading process of training scenarios of "data analysis → virtual train initialization → full system time synchronization", the automatic conversion from historical operating data to training scenarios is realized, which ensures the authenticity and effectiveness of the training content and significantly improves the training efficiency.

[0054] like Figure 4 As shown, the embodiment of the present application provides a driving scheduling training method corresponding to the driving scheduling training system, and the driving scheduling training method is applied to the driving scheduling training system as described in the previous embodiment. Specifically, the driving scheduling training method includes: Monitor and analyze the operating status of trains and signaling equipment according to training time requirements to obtain key train feature information for generating training scenarios; Based on the dispatch instructions, a virtual NPC train is created according to the key characteristics of the train by simulating the operating mechanism of the real ATC system and the operating status of the operating train is simulated to build a dynamic training scenario and visualize the scenario on the ATS interface; The virtual NPC train is controlled based on the dynamic training scenario to perform a scheduling training task.

[0055] In some embodiments, trainees can issue dispatch instructions through the ATS interface, such as adjusting the operation plan and issuing temporary speed limits. The virtual train will respond in real time and feedback the results through the ATS interface, such as automatically adjusting the speed after receiving the speed limit instruction, to form a closed-loop interaction between man and machine.

[0056] In this embodiment, the corresponding training scenarios are generated by accurately extracting key features to ensure a high degree of match between the virtual scenarios and the historical operating status, avoid the limitations of manually preset scenario parameters and system-predefined scenarios, and directly use real data to dynamically generate scenarios at any time, overcoming the distortion caused by subjective design; by simulating the ATC system mechanism, the virtual NPC train can automatically respond to dispatch instructions and simulate the control logic of the real train without human intervention, realizing the automation and independence of the train dispatch training process, overcoming the limitation that training requires the coordination of drivers or multiple positions, and improving the independence and efficiency of training.

[0057] like Figure 5 As shown, an embodiment of the present application further provides an electronic device, including: a processor 51, a memory 52, and a network interface 53. The memory 52 stores machine-readable instructions executable by the processor 51. When the electronic device is running, the processor 51 and the memory 52 communicate through the network interface 53. When the machine-readable instructions are executed by the processor 51, the steps of the vehicle scheduling training method in the above embodiment are performed.

[0058] An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the vehicle scheduling training method in the above embodiment are executed.

[0059] The above specific implementation methods are preferred implementation methods of the present application, and are not intended to limit the specific implementation scope of the present application. The scope of the present application includes but is not limited to the specific implementation methods. Any equivalent changes made in accordance with the shape, structure, and method of the present application are within the scope of protection of the present application.

Claims

1. A driving dispatch training system, characterized by: include: The ATS automatic train monitoring system monitors and analyzes the operating status of trains and signaling equipment according to training schedule requirements, obtaining key train feature information used to generate training scenarios; The virtual NPC train system is used to simulate the operating mechanism of a real ATC system, create a virtual NPC train based on the key feature information of the train and simulate the operating status of the operating train to complete the construction of the training scenario and automatically control the virtual NPC train.

2. The vehicle dispatching training system according to claim 1, characterized in that: The ATS automatic train monitoring system includes: The monitoring subsystem is used to interact with the ATC system and the wayside control system to obtain the coordinated monitoring information of all operating trains and signal equipment by the ATC onboard system and the wayside control system; The parsing subsystem is used to parse the collaborative monitoring information to obtain key feature information of the train for generating training scenarios.

3. The vehicle dispatching training system according to claim 2 is characterized in that: The step of parsing the collaborative monitoring information to obtain key train feature information for generating a training scenario includes: Based on the historical completed timetable of the operating trains, obtaining the collaborative monitoring information at each time; Matching the time information required for training with the historical completion time table, and using the collaborative monitoring information corresponding to the matched historical completion time as the target parsing object; The train's location information, status information, early or late arrival information, number information and running direction information are extracted according to the target parsing object to obtain the train's key feature information for generating training scenarios.

4. The vehicle dispatching training system according to claim 3 is characterized in that: Extracting the train location information according to the target parsing object includes: Extract the platform area information where the train is located at the corresponding time based on the time information required for training; Based on the platform area information combined with the train dynamic positioning information monitored by the ATC system and the track occupancy information monitored by the wayside control system, the position offset of the train in the block section is comprehensively analyzed to obtain the train position information.

5. The vehicle dispatching training system according to claim 3 is characterized in that: The virtual NPC train system includes: The simulated ATC system is configured to receive a dispatch instruction, generate the virtual NPC train based on the key characteristic information of the train corresponding to the historical completion time according to the required training time, and initialize the control logic of the virtual NPC train by simulating the operation mechanism of the real ATC system; The simulated vehicle TCMS system is used to control the operating conditions of the virtual NPC train and to link the simulated ATC system to generate a full-process scenario of train operation to complete the construction of dynamic training scenarios and automatic control of the virtual NPC train.

6. The vehicle dispatching training system according to claim 5, characterized in that: The method of generating the virtual NPC train based on the key feature information of the train corresponding to the historical completion time according to the required training time, and simulating the operation mechanism of the real ATC system to initialize the control logic of the virtual NPC train includes: Determine the training start time based on the train operation period; Based on the training start time, the train's location information, status information, early or late information, number information, and running direction information are obtained at the corresponding historical completion time. The virtual NPC train is created according to the train's location information, status information, early or late arrival information, number information and running direction information, and the basic attribute information, automatic driving mode and running status of the virtual NPC train are initialized.

7. The vehicle dispatching training system according to claim 5, characterized in that: The linkage with the simulated ATC system to generate a full-process scenario of train operation to complete the construction of dynamic training scenarios and the automatic control of the virtual NPC train includes: The TCMS system simulates the internal equipment status of the operating train and interacts with the ATC system to perform the operation parameters and fault information of the virtual NPC train; When the running status of the virtual NPC train reaches the operating train status corresponding to the timetable, the current time point is bound to the virtual clock of the virtual NPC train system, so that the clock of the train scheduling training system is uniformly adjusted to the current time point, completing the establishment of the full process scenario; Synchronously, the internal equipment and operating conditions of the virtual NPC train are managed according to the dispatching instructions, and the automatic control of the virtual NPC train is completed in combination with the automatic driving mode of the virtual NPC.

8. A vehicle dispatching training method, characterized by: Applicable to the vehicle dispatching training system according to any one of claims 1 to 7 above, the method comprising: Monitor and analyze the operating status of trains and signaling equipment according to training time requirements to obtain key train feature information for generating training scenarios; Based on the dispatch instructions, a virtual NPC train is created according to the key characteristics of the train by simulating the operating mechanism of the real ATC system and the operating status of the operating train is simulated to build a dynamic training scenario and visualize the scenario on the ATS interface; The virtual NPC train is controlled based on the dynamic training scenario to perform a scheduling training task.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate via the bus, and the processor executes the machine-readable instructions to perform the steps of the vehicle dispatching training method described in claim 8.

10. A computer-readable medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the steps of the vehicle dispatching training method according to claim 8 are executed.

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