A CIR operating line automatic selection method

Abstract

This invention discloses an automatic route selection method for CIR (Circuit Interchange) systems. It can automatically set pre-constructed route data and process route information, reducing manual intervention and improving efficiency. Furthermore, the route data learning server can generate pre-constructed route data through artificial intelligence algorithms, and then correct it through a self-learning mechanism and dynamic correction mechanism to ensure the quality of the pre-constructed route data and the accuracy of route selection. In addition, the pre-constructed route data supports both remote and local upgrades. Overall, this invention effectively improves the automation and intelligence level of railway dispatching systems, ensures efficient and safe train operation, fills a technological gap in related fields, and further enhances the operational efficiency and stability of railway transportation systems.

Description

Technical Field

[0001] This invention relates to the field of rail transit technology, and in particular to a method for automatic selection of CIR operating lines. Background Technology

[0002] The Carrier Integrated Wireless Communication (CIR) equipment is an onboard wireless communication terminal device installed on locomotives, EMUs, and self-propelled special equipment. A CIR consists of a main unit, a Management Interface (MMI), transceivers, speakers, a printer terminal, a locomotive data acquisition encoder, connecting cables, antennas, feeders, and combiners. The CIR has dispatch communication capabilities under GSM-R and 450MHz standards, and is being upgraded to include 5G-R and 400MHz standards for voice communication between drivers, dispatchers, and station staff. Simultaneously, the CIR also transmits dispatch commands, train tail pressure readings, wireless train number verification, and train protection alarms. Currently, the CIR has become the main equipment installed on high-speed railways, passenger dedicated lines, and mainline EMUs and locomotives, meeting various communication needs between train drivers, ground traffic controllers, and other relevant personnel on the train.

[0003] Because the CIR satellite positioning unit needs to select track route information when the train reaches the track branching area, the traditional route selection method requires manual editing and generation of pre-prepared route data files, which are then injected into the satellite positioning unit via USB drive. The driver then queries the pre-prepared route information based on the train number and manually selects the route to run on the CIR device. However, frequent route selection interferes with the driver's normal train operation and increases the driver's workload.

[0004] In view of this, the present invention is hereby proposed. Summary of the Invention

[0005] The purpose of this invention is to provide an automatic selection method for CIR (Circuit Irregular Rail) operation routes, which can improve the automation and intelligence of the system, ensure the safety, accuracy and efficiency of train operation, and provide more accurate data support and decision-making basis in railway transportation.

[0006] The objective of this invention is achieved through the following technical solution: A method for automatic selection of CIR operating lines includes: Pre-made route data is configured in the CIR device. When a train arrives at a route selection area where the line branches, the CIR device compares the train number and the route selection area where the train is located with the pre-made route data. Based on the comparison result, the corresponding route selection area data is automatically selected from the pre-made route data, and the route is determined accordingly. The pre-constructed route data is generated by the line data learning server using artificial intelligence algorithms and adjusted through a self-learning mechanism, with a dynamic correction mechanism introduced for data correction. When updating the pre-constructed route data in the CIR device, a remote update method is used, whereby the line data learning server transmits the updated pre-constructed route data to the CIR device, or a local upgrade method is used, whereby the line data learning server packages all the pre-constructed route data into a complete local upgrade data package and imports the complete local upgrade data package into the CIR device through an external storage device for pre-constructed route data updates.

[0007] As can be seen from the technical solution provided by the present invention, pre-set route data and route information can be automatically set and processed, reducing manual intervention and improving efficiency. Furthermore, the route data learning server can generate pre-set route data through artificial intelligence algorithms, and can then correct it through a self-learning mechanism and a dynamic correction mechanism to ensure the quality of the pre-set route data and the accuracy of route selection. In addition, the pre-set route data supports both remote and local upgrades. Overall, the present invention effectively improves the automation and intelligence level of the railway dispatching system, ensures the high efficiency and safety of train operation, fills a technological gap in related fields, and further enhances the operational efficiency and stability of the railway transportation system. Attached Figure Description

[0008] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0009] Figure 1 This is a schematic diagram of an automatic CIR operating line selection method provided in an embodiment of the present invention.

[0010] Figure 2 This is a schematic diagram of prefabricated route data provided in an embodiment of the present invention.

[0011] Figure 3 This is a schematic diagram of the line data learning server provided in an embodiment of the present invention. Detailed Implementation

[0012] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0013] First, the following explanations are provided for the terms that may be used in this article: The terms "comprising," "including," "containing," "having," or other similar semantic descriptions should be interpreted as non-exclusive inclusion. For example, including a technical feature element (such as raw material, component, ingredient, carrier, dosage form, material, size, part, component, mechanism, device, step, process, method, reaction conditions, processing conditions, parameter, algorithm, signal, data, product or article of manufacture, etc.) should be interpreted as including not only the expressly listed technical feature element, but also other technical feature elements that are not expressly listed and are well-known in the art.

[0014] The term "composed of" excludes any technical features not expressly listed. When used in a claim, it closes the claim to exclude all technical features other than those expressly listed, except for associated conventional impurities. If the term appears only in a clause of a claim, it limits the claim to the elements expressly listed in that clause; elements recited in other clauses are not excluded from the overall claim.

[0015] The following is a detailed description of the automatic selection method for CIR operating lines provided by this invention. Contents not described in detail in the embodiments of this invention are prior art known to those skilled in the art. Where specific conditions are not specified in the embodiments of this invention, conventional conditions in the art or conditions recommended by the manufacturer shall apply. Instruments used in the embodiments of this invention, unless otherwise specified by the manufacturer, are all commercially available conventional products.

[0016] Example 1 This invention provides an automatic CIR (Circuit Interchange) route selection method, which can reduce manual intervention, improve efficiency, further enhance the intelligence of railway transportation, and better ensure that trains run safely, smoothly, comfortably, and uninterruptedly at specified speeds. It has significant practical implications and wide application value. Figure 1 As shown, this mainly includes: configuring pre-made route data in the CIR device; when a train arrives at a route selection area where the line branches, the CIR device compares the train number and the route selection area where the train is located with the pre-made route data; based on the comparison result, it automatically selects the corresponding route selection area data from the pre-made route data and determines the running line accordingly. The pre-constructed route data is generated by the line data learning server using artificial intelligence algorithms and adjusted through a self-learning mechanism, with a dynamic correction mechanism introduced for data correction. When updating the pre-constructed route data in the CIR device, a remote update method is used, whereby the line data learning server transmits the updated pre-constructed route data to the CIR device, or a local upgrade method is used, whereby the line data learning server packages all the pre-constructed route data into a complete local upgrade data package and imports the complete local upgrade data package into the CIR device through an external storage device for pre-constructed route data updates.

[0017] In this embodiment of the invention, the pre-made route data for each train trip includes: train number, number of route selection areas involved in the train number, data of all route selection areas, and check code.

[0018] The preferred implementation methods for each of the above steps are as follows: (1) Pre-constructed route data is generated by the route data learning server using artificial intelligence algorithms, including: The line data learning server collects historical train data, including historical operation data, historical route selection information, kilometer markers, train speed, and stopping time. By analyzing historical train data, it predicts future operation conditions and generates corresponding route data. When it receives manually selected route information uploaded by the CIR device, it uses artificial intelligence algorithms to generate pre-made route data corresponding to each train number according to predetermined rules.

[0019] (2) Adjustments through self-learning mechanisms include: If the CIR device compares the train number and the line selection area where the train is located with the pre-prepared route data, and the comparison result shows that the train number and the line selection area where the train is located do not match the pre-prepared route data, then the operating route is selected manually, and the information of the manually selected operating route is transmitted to the line data learning server; the line data learning server adjusts itself according to the information of the manually selected operating route through a self-learning mechanism.

[0020] (3) Introducing a dynamic correction mechanism for data correction includes: By monitoring the train's operating status in real time and comparing it with pre-prepared route data, if a deviation is found, the line data learning server adjusts the pre-prepared route data based on the train's operating status in real time. Furthermore, the line data learning server performs multi-level data correction based on different train numbers, train timetable adjustments, and different environmental conditions.

[0021] (4) Using a remote update method, the updated prefabricated route data is transmitted from the line data learning server to the CIR equipment, including: The CIR device sends an update request to the line data learning server, which includes the train number that needs to be updated and its corresponding line selection area data; After receiving the request, the route data learning server provides the latest route selection area data based on the train number.

[0022] (5) When the train dispatch center needs to update the data of the CIR device, the line data learning server sends the latest line selection area data to each CIR device through the data transmission channel. During the update process, the line data server sends the line selection area data containing all train number information to each CIR device, which also includes the total check code and the check code set of each train number. During the data transmission process, the check code and encryption technology are used. The CIR device that receives the data first performs the verification. If the verification passes, the data is decrypted.

[0023] (6) A solution for dynamic updates and emergency response was also designed: In the event of an emergency, the train dispatch center will send the latest emergency route adjustment information to the CIR equipment through the line data learning server; The route data learning server periodically obtains real-time feedback from CIR devices to check the applicability and update status of the data. If a problem is found in the route selection of a CIR device, the route data learning server makes adjustments and pushes new pre-made route data. Those skilled in the art will understand that the pre-made route data is intended to guide the CIR in route selection during route selection. However, if the driver does not follow the automatic route selection based on the pre-made route data, it indicates a problem with the pre-made route data, requiring the server to regenerate the pre-made route data and update the old data.

[0024] (7) Through local upgrade, the line data learning server packages all pre-built route data into a complete local upgrade data package, and imports the complete local upgrade data package into the CIR device through an external storage device for pre-built route data updates, including: The line data learning server exports all pre-made route data related to train operation according to the requirements of the CIR equipment, and after verification and optimization, forms a complete local upgrade data package; The complete local upgrade data package is imported into the CIR device via an external storage device. The CIR device verifies the integrity and correctness of the complete local upgrade data package. Once the verification is successful, the data is installed, and the local pre-built routing data is updated.

[0025] To more clearly demonstrate the technical solution and its effects provided by the present invention, the method provided by the embodiments of the present invention will be described in detail below with reference to specific examples.

[0026] I. Overall Overview of the Plan

[0027] This invention provides an automatic route selection method for CIR (Circuit Interchange) train operations, optimizing train route information selection in railway dispatching systems. It aims to address the inefficiency caused by drivers manually selecting routes when encountering routes during train operation. Furthermore, it addresses the impact of frequent manual route selection on driver control, and considers the uncertainty of freight train routes, route changes due to timetable adjustments, and the impact of remote upgrades on the GSM-R network. This invention proposes a series of optimization schemes for automatic route selection and remote upgrades to improve the system's automation and intelligence, ensuring safe, accurate, and efficient train operation. This invention can provide more accurate data support and decision-making basis in railway transportation.

[0028] II. Detailed introduction of the plan.

[0029] As previously mentioned, the CIR (Circuit Irregularity Regulator) automatic route selection method provided by this invention optimizes train route information selection in railway dispatching systems. Therefore, it enables CIR equipment to automatically select routes when necessary conditions are met, forming a CIR route selection optimization technical solution. The entire solution incorporates artificial intelligence technology to improve train operation efficiency, reduce manual intervention, and achieve dynamic, real-time route selection optimization. The entire solution has three key parts: a pre-constructed route data generation and correction technology, a remote update technology for CIR pre-constructed route information, and a local upgrade data package generation technology. Each part will be described in detail below.

[0030] 1. Technical solution for generating and correcting pre-constructed route data.

[0031] (A1) Generation of prefabricated route data.

[0032] Pre-defined route data refers to route selection data that is pre-defined and stored during train operation, taking into account different train numbers and operating conditions. Pre-defined route data typically includes information such as train departure and arrival times, stations, planned routes, and possible alternative routes; the specific content will be described later. Through this pre-defined route data, the train dispatching system can pre-set routes, enabling trains to automatically select the optimal route under different operating conditions.

[0033] In traditional train dispatching systems, pre-prepared route data is typically compiled manually and adjusted only during system updates or malfunctions. However, due to the limitations of manual compilation, the data is often incomplete, erroneous, or outdated. To improve the accuracy and stability of the system, this invention designs pre-prepared route data consisting of a general summary and train number route information, such as... Figure 2As shown, the pre-made route data for each train mainly includes the train number, the number of route selection areas involved in the train, all route selection area data, and a check code.

[0034] In this embodiment of the invention, the pre-made route data and the train timetable are unified. The train timetable clearly defines the routes for different train numbers. The pre-made route data helps drivers automatically select routes. When there is no pre-made route data, drivers need to manually select routes. However, when the train timetable changes, the old pre-made route data is no longer applicable. At this time, the route data learning server needs to generate new pre-made route data for each train number based on the driver's route selection operation.

[0035] (A1.1) Intelligent Data Generation: Using artificial intelligence algorithms and a line data learning server, pre-prepared route data is automatically generated and updated based on the actual train operation. In this embodiment of the invention, a line data learning server is set up to generate and correct data based on line selection area information and auxiliary information. The data in the line data learning server is as follows: Figure 3 As shown, this mainly includes: route selection area information, route information, and auxiliary information. The route selection area information is generated and modified manually and remains unchanged during operation, only being used internally by the route data learning server. Pre-built route data can be dynamically updated based on the learning progress and sent to the CIR via remote upgrades.

[0036] In practical applications, after receiving manually selected route information (i.e., route selection data made by drivers in the route selection area) uploaded by CIR devices, the route data learning server uses artificial intelligence algorithms to generate pre-prepared route data corresponding to each train number according to predetermined rules. The route data learning server collects historical train operation data, speed, stopping time, and other information, analyzes this historical data to identify potential patterns and trends, and uses this to predict future operating conditions, generating corresponding route data to ensure that the generated pre-prepared route information better meets actual operational needs.

[0037] (A1.2) Self-learning mechanism: When a train arrives at a line selection area where the line branches off, the CIR device compares the train's current train number and the current line selection area with pre-prepared route information and automatically adjusts accordingly. If the information matches the pre-prepared route, the pre-prepared route is selected; otherwise, the driver can manually select the route. Each time the driver performs a manual route selection operation through the CIR device, the CIR device uploads the route selection information to the line data learning server via the GSM-R network. The line data learning server continuously adjusts the newly generated operating data based on the manually selected route information through a self-learning mechanism.

[0038] In this embodiment of the invention, the artificial intelligence algorithm configured in the line data learning server can be a neural network model, and a self-learning threshold (some parameters of the model) can be set. When it is found that the pre-built route data generated by the server is always incorrect, it indicates that the neural network model on the line data learning server needs to be modified.

[0039] Preferably, during the self-learning process, data from the TAX box (locomotive safety information integrated monitoring device) on the train can be obtained, and the "train number verification" can be used to determine whether the train is a freight car or a passenger car. Furthermore, by independently identifying the freight car number and eliminating its interference with the self-learning process, the problem of uncertainty in freight car operation routes is solved.

[0040] (A2) Correction mechanism.

[0041] To ensure that the generated pre-built route data is always optimal, this invention designs a dynamic correction mechanism. The specific correction process is as follows: (A2.1) Data Comparison and Correction. The route data learning server periodically performs data correction and optimization to ensure that the generated pre-built route data matches the actual operating conditions. By comparing with real-time data, the route data learning server can identify and correct inaccurate data, thereby improving the accuracy of the route data.

[0042] Specifically, the system monitors train operation status in real time and compares it with pre-prepared route data. If discrepancies are detected, the route data learning server adjusts the route selection strategy based on the real-time data. For example, if a route experiences severe delays during a certain period, the route data learning server optimizes route selection for the same time period in the future based on this information.

[0043] (A2.2) Multi-level data correction: The route data learning server performs multi-level data correction based on different train numbers, train timetable adjustments, and different environmental conditions (such as weather and traffic). For example, in the event of severe weather such as heavy rain or snow, some sections of the route may become impassable. The route data learning server dynamically adjusts the route data based on weather forecasts and actual road conditions to ensure that trains can select the best alternative routes.

[0044] 2. CIR prefabricated route information remote update technology solution.

[0045] (B1) Remote update request.

[0046] With the increasing complexity of train operation networks, traditional route update methods can no longer meet the demands for real-time performance and accuracy. Especially in large-scale, high-speed train operation systems, ensuring that the route selection of each train is synchronized with the latest scheduling information is crucial.

[0047] This invention proposes a pre-fabricated route information update mechanism based on remote updates, which enables real-time updates to CIR devices via a dedicated railway communication network (such as GSM-R). When the CIR device detects that pre-fabricated route data needs updating, it automatically sends an update request to the line data learning server, including the train number to be updated and its corresponding line selection area data. Upon receiving the request, the line data learning server provides the latest line selection area data based on the train number.

[0048] Preferably, in order to avoid the impact of excessive GSM-R network load on train operation, many trains may need to update pre-prepared route data under the same network base station. If they are updated at the same time, it will put great pressure on the network. Therefore, it is necessary to limit the number of trains that update pre-prepared route data at the same time, so that these trains queue up to update the pre-prepared route data.

[0049] (B2) Data transmission and verification.

[0050] (B2.1) Real-time transmission: When the train dispatch center needs to update the data of the CIR devices, the line data learning server sends the latest line selection area data to each CIR device through a high-speed data transmission channel (such as a GSM-R network). During the update process, the line data learning server sends updated data containing all train number information to the CIR devices. The data packet contains the total checksum and the checksum set for each train number.

[0051] (B2.2) Data Verification Mechanism: During data transmission, checksums and encryption technologies are used to ensure data integrity and security. Upon receiving data, the CIR device first performs a verification to confirm its correctness. If the verification passes, the CIR device will automatically update the cross-path data in its memory.

[0052] (B3) Dynamic updates and emergency response.

[0053] During train operation, unexpected events may occur (such as track faults, abnormal weather, etc.), which can affect the normal operation of the train. Therefore, this technical solution also includes an emergency response mechanism to ensure that the CIR equipment can dynamically adjust the track selection based on changes in real-time data.

[0054] (B3.1) Emergency Data Updates: In the event of an emergency, the train dispatch center will promptly send the latest emergency route adjustment information to the CIR equipment via a remote update system. For example, if a line experiences a fault, the line data learning server will automatically push alternative routes to ensure smooth train operation.

[0055] (B3.2) Real-time data feedback: The line data learning server periodically obtains real-time feedback from the CIR devices to check the applicability and update status of the data. If a problem is found in the line selection of a CIR device, the line data learning server immediately makes adjustments and pushes new data.

[0056] 3. Local upgrade data package generation technology solution.

[0057] (C1) Local upgrade requirement.

[0058] While remote update technology can address most of the data update needs of train dispatching systems, in certain special circumstances, such as the lack of network connectivity or the CIR device being located far from network coverage, the CIR device may not be able to receive real-time updated data. For locomotives without GSM-R network access, pre-prepared route data in the CIR can be updated locally.

[0059] (C2) Generation and transmission of upgrade data packets.

[0060] (C2.1) Data Packaging and Verification: Based on the requirements of the CIR equipment, the line data learning server exports all pre-prepared route data related to train operation, including route selection rules, timetables, operating status, and manual route selection information for each train number. The line data learning server verifies and optimizes the data to form a complete local upgrade data package. The data package is verified to ensure no data is lost or corrupted.

[0061] (C2.2) Data packet transmission method: In areas without network connectivity, data packets can be transmitted to the CIR device via a USB drive. The train dispatch center can also manually transmit upgrade data packets to the CIR device using a USB flash drive, depending on the specific needs of the CIR device.

[0062] (C3) Local installation and application.

[0063] (C3.1) Offline Data Installation: The data package will be imported via the local USB port. The CIR device will first verify the integrity and correctness of the data package, and then proceed with the data installation after confirming that there are no errors.

[0064] (C3.2) Local execution and update: Once the data is successfully imported, the CIR device will perform a route selection operation based on the new data to ensure that the train can run according to the latest route data.

[0065] The solution provided in this invention has the following advantages: by independently identifying freight car number categories and eliminating their interference with the self-learning process, the uncertainty of freight car routes is solved; simultaneously, by setting a reasonable self-learning threshold, high-quality data is filtered out, avoiding the negative impact of erroneous operations on the system and ensuring the accuracy of the route selection strategy; when route changes are caused by timetable adjustments or other factors, the route data learning server can dynamically adjust the route data and enable manual route selection mode, ensuring the flexible adaptability of train dispatching; furthermore, through refined management of the remote upgrade process, the impact of excessive GSM-R network load on train operation is effectively avoided. This technical solution effectively improves the automation and intelligence level of the railway dispatching system, ensures the efficiency and safety of train operation, fills the technical gap in related fields, and further improves the operational efficiency and stability of the railway transportation system.

[0066] Through the above description of the embodiments, those skilled in the art can clearly understand that the above embodiments can be implemented by software, or by using software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions of the above embodiments can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, mobile hard drive, etc.), including several instructions to cause a computer device (such as a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0067] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims. The information disclosed in the background section is intended only to enhance the understanding of the overall background technology of the present invention and should not be construed as an admission or implication in any way that such information constitutes prior art known to those skilled in the art.

Claims

1. A method for automatically selecting CIR operating lines, characterized in that, include: Pre-made route data is configured in the CIR device. When a train arrives at a route selection area where the line branches, the CIR device compares the train number and the route selection area where the train is located with the pre-made route data. Based on the comparison result, the corresponding route selection area data is automatically selected from the pre-made route data, and the route is determined accordingly. The pre-constructed route data is generated by the line data learning server using artificial intelligence algorithms and adjusted through a self-learning mechanism, with a dynamic correction mechanism introduced for data correction. When updating the pre-constructed route data in the CIR device, a remote update method is used, whereby the line data learning server transmits the updated pre-constructed route data to the CIR device, or a local upgrade method is used, whereby the line data learning server packages all the pre-constructed route data into a complete local upgrade data package and imports the complete local upgrade data package into the CIR device through an external storage device for pre-constructed route data updates.

2. The automatic selection method for CIR operating lines according to claim 1, characterized in that, The pre-constructed route data is generated by a route data learning server using artificial intelligence algorithms, including: The line data learning server collects historical train data, including historical operation data, historical route selection information, kilometer markers, train speed, and stopping time. By analyzing historical train data, it predicts future operation conditions and generates corresponding route data. When it receives manually selected route information uploaded by the CIR device, it uses artificial intelligence algorithms to generate pre-made route data corresponding to each train number according to predetermined rules.

3. The automatic selection method for CIR operating lines according to claim 1, characterized in that, The adjustments made through a self-learning mechanism include: If the CIR device compares the train number and the line selection area where the train is located with the pre-prepared route data, and the comparison results show that the train number and the line selection area where the train is located do not match the pre-prepared route data, then the operating route is selected manually, and the information of the operating route selected manually is transmitted to the line data learning server. The line data learning server adjusts itself based on the operating line information selected manually through a self-learning mechanism.

4. The automatic selection method for CIR operating lines according to claim 1, characterized in that, The introduction of a dynamic correction mechanism for data correction includes: By monitoring the train's operating status in real time and comparing it with pre-made route data, if a deviation is found, the pre-made route data is adjusted based on the train's operating status monitored in real time by the line data learning server. Furthermore, the line data learning server performs multi-level data corrections based on different train numbers, train timetable adjustments, and different environmental conditions.

5. The method for automatic selection of CIR operating lines according to claim 1, characterized in that, The method of remotely updating the pre-fabricated route data, whereby the line data learning server transmits the updated data to the CIR device, includes: The CIR device sends an update request to the line data learning server, which includes the train number that needs to be updated and its corresponding line selection area data; After receiving the request, the route data learning server provides the latest route selection area data based on the train number.

6. The automatic selection method for CIR operating lines according to claim 5, characterized in that, Also includes: When the train dispatch center needs to update the data of the CIR devices, the line data learning server sends the latest line selection area data to each CIR device through the data transmission channel; During the update process, the line data server sends the line selection area data containing all train number information to each CIR device, which also includes the total check code and the check code set for each train number. During data transmission, a checksum and encryption technology are used. The CIR device that receives the data first performs a check. If the check passes, the data is decrypted.

7. The method for automatic selection of CIR operating lines according to claim 5, characterized in that, It also includes solutions for dynamic updates and emergency response: In the event of an emergency, the train dispatch center will send the latest emergency route adjustment information to the CIR equipment through the line data learning server; The line data learning server periodically obtains real-time feedback from the CIR device to check the applicability and update status of the data. If a problem is found in the route selection of a CIR device, the route data learning server will make adjustments and push new pre-made route data.

8. The method for automatic selection of CIR operating lines according to claim 1, characterized in that, The local upgrade method involves the line data learning server packaging all pre-built route data into a complete local upgrade data package, which is then imported into the CIR device via an external storage device for updating the pre-built route data. The line data learning server exports all pre-made route data related to train operation according to the requirements of the CIR equipment, and after verification and optimization, forms a complete local upgrade data package; The complete local upgrade data package is imported into the CIR device via an external storage device. The CIR device verifies the integrity and correctness of the complete local upgrade data package. Once the verification is successful, the data is installed, and the local pre-built routing data is updated.

9. A method for automatically selecting CIR operating lines according to any one of claims 1 to 8, characterized in that, The pre-made route data for each train trip includes: train number, number of route selection zones involved in the train number, data of all route selection zones, and check code.

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