Freight train positioning test method and device, storage medium and electronic equipment

Abstract

This application discloses a method, apparatus, storage medium, and electronic device for positioning testing of freight trains. The method includes: acquiring satellite positioning information, driver-input departure information, identification and message information of the first group of physical transponders, and track installation position information of the first group of physical transponders; verifying the validity of each piece of information to obtain the validity status corresponding to each piece of information; combining the validity statuses of each piece of information to form a validity status combination result; generating a test scenario set based on the validity status combination result, scenario dimension layering rules, operating condition probability weighting strategy, and anomaly coupling rules; adjusting the triggering timing and triggering intensity of the target test operating condition based on the test scenario set and the real-time operating status parameters of the freight train; collecting the operating response data of the onboard system and the interaction status data between the onboard system and the radio block center during the simulation of the target test operating condition; verifying the operating response data and the interaction status data; and generating test results.

Description

Technical Field

[0001] This application relates to the field of freight train positioning test technology, and in particular to a freight train positioning test method, device, storage medium and electronic equipment. Background Technology

[0002] In the field of freight train positioning testing technology, the safe operation of freight train positioning systems relies on comprehensive verification of the onboard system's response behavior under various operating conditions. Traditional testing schemes struggle to cover complex scenarios involving abnormal combinations of multi-source positioning information and dynamic changes in operating conditions. They cannot fully verify the onboard system's safety response logic and positioning reliability when positioning-related information fluctuates or abnormal operating conditions occur. This can lead to the omission of potential risks in critical fault scenarios, making it difficult to meet the high-safety-level testing requirements of freight train positioning systems and failing to provide sufficient testing assurance for freight train operation safety. Summary of the Invention

[0003] In view of the above problems, this application provides a freight train positioning test method, device, storage medium and electronic device.

[0004] To solve the above-mentioned technical problems, this application proposes the following solution: Firstly, this application provides a method for testing the positioning of freight trains. The method includes: acquiring satellite positioning information of the freight train, driver-input departure information, identification and message information of the first group of physical transponders, and track installation location information of the first group of physical transponders; verifying the validity of each piece of information to obtain the validity status of each piece of information; combining the validity statuses of each piece of information to form a validity status combination result; generating a test scenario set based on the validity status combination result, scenario dimension layering rules, operating condition probability weighting strategy, and anomaly coupling rules; determining and adjusting the triggering timing and triggering intensity of the target test operating condition based on the test scenario set and the real-time operating status parameters of the freight train to simulate the abnormal and normal states of the target test operating condition; collecting the operating response data of the onboard system and the interaction status data between the onboard system and the radio block center during the simulation of the target test operating condition; verifying the operating response data and interaction status data to determine whether the response behavior of the onboard system in the target test operating condition meets the rule requirements; and generating test results.

[0005] Secondly, this application provides a freight train positioning test device, which includes: The acquisition module is used to acquire the satellite positioning information of the freight train, the departure information input by the driver, the identification and message information of the first group of physical transponders, and the track installation position information of the first group of physical transponders. It verifies the validity of each piece of information, obtains the validity status of each piece of information, and combines the validity status of each piece of information to form a validity status combination result. The generation module is used to generate a set of test scenarios based on the results of the validity state combination, the scenario dimension layering rules, the working condition probability weighting strategy, and the anomaly coupling rules. The testing module is used to determine and adjust the triggering timing and intensity of the target test condition based on the test scenario set and the real-time status parameters of the freight train operation, so as to simulate the abnormal and normal states of the target test condition. The results analysis module is used to collect the operational response data of the vehicle system and the interaction status data between the vehicle system and the radio block center during the target test condition simulation. It verifies the operational response data and interaction status data to determine whether the response behavior of the vehicle system in the target test condition meets the rule requirements and generates test results.

[0006] To achieve the above objectives, according to a third aspect of this application, a storage medium is provided, the storage medium including a stored program, wherein, when the program is executed, the device where the storage medium is located is controlled to perform the freight train positioning test method of the first aspect described above.

[0007] To achieve the above objectives, according to a fourth aspect of this application, an electronic device is provided, the device including at least one processor, and at least one memory and bus connected to the processor; wherein the processor and memory communicate with each other through the bus; the processor is used to call program instructions in the memory to execute the freight train positioning test method of the first aspect described above.

[0008] By employing the above-described technical solution, the technical solution provided in this application has at least the following advantages: This application first verifies the validity of the satellite positioning information required for freight train positioning, the driver's input departure information, the identification and message information of the first set of physical transponders, and the track installation location information of the first set of physical transponders. After clarifying the valid or invalid state of each type of information, these states are combined to form a valid state combination result. This operation covers all possible valid combinations of multi-source positioning information from the source. Whether it is a single information failure or multiple information failures simultaneously, it can be completely sorted out through state combination. By verifying and combining the states of multi-source information one by one, this operation provides a complete scenario foundation for subsequent accurate simulation of complex working conditions, ensuring that no key test scenarios are missed due to incomplete information state coverage.

[0009] Based on the aforementioned effective state combination results, a test scenario set is generated by combining scenario-dimensional hierarchical rules, operating condition probability weighting strategies, and anomaly coupling rules. Then, the triggering timing and intensity of the target test operating condition are determined and adjusted according to the test scenario set and the real-time operating status parameters of the freight train. This transforms abstract information state combinations into specific test operating conditions that fit the actual operating characteristics of freight trains. Through scenario generation rules, different information effectiveness combinations can be mapped to normal or abnormal scenarios in actual operation, while the operating condition probability weighting strategy and anomaly coupling rules further ensure the rationality and typicality of the scenarios. Simultaneously, adjusting the triggering timing and intensity in conjunction with the real-time operating parameters of the freight train dynamically adapts to changes in position, speed, etc., during freight train operation, avoiding a disconnect between static testing and actual operation. This realistically reproduces the operating environment when positioning information is abnormal and operating conditions change dynamically, providing practical test conditions for verifying the onboard system's response logic.

[0010] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0011] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 A flowchart illustrating a freight train positioning test method provided in an embodiment of this application is shown. Figure 2 This illustration shows a structural schematic diagram of a freight train positioning test device provided in an embodiment of this application; Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of this application is shown. Detailed Implementation

[0012] The following section provides a detailed explanation of the positioning test method for freight trains, with reference to the accompanying drawings. Figure 1 This is a flowchart illustrating a freight train positioning test method provided in this application. It specifically includes the following steps: Step 110: Obtain the satellite positioning information of the freight train, the departure information input by the driver, the identification and message information of the first group of physical transponders, and the track installation position information of the first group of physical transponders. Verify the validity of each piece of information to obtain the validity status of each piece of information. Combine the validity status of each piece of information to form a validity status combination result.

[0013] For acquiring satellite positioning information, satellite signals are collected in real time through an onboard satellite positioning receiving module (such as a GNSS receiver). This module establishes a data interaction channel with the freight train's onboard control system and receives satellite positioning data at a preset sampling frequency (usually 1Hz-10Hz, which can be adjusted according to the freight train's operating speed and test accuracy requirements). This data includes parameters such as the freight train's latitude and longitude coordinates, positioning accuracy factor (PDOP), satellite signal strength, and signal lock status. In the validity verification stage, the satellite signal lock status is first determined. If the module does not lock any satellites or the number of locked satellites is less than 4 (meeting the minimum number of satellites required for positioning calculation), the satellite positioning information is directly deemed invalid (recorded as 0). If the number of locked satellites meets the standard, the positioning accuracy factor is further verified. When the PDOP value is greater than a preset threshold (usually set to 3, which can be adjusted according to the track environment, such as complex mountainous areas or densely populated urban areas, where it can be appropriately relaxed to 5), the positioning accuracy is considered insufficient to meet the test requirements and is deemed invalid. Simultaneously, the latitude and longitude coordinates of the satellite positioning are compared with the coordinate range of the route in the electronic orbital map. If the coordinates exceed the reasonable error range of the current operating orbit (usually ±50m, combined with the transponder positioning correction accuracy setting), it is also judged as invalid. The satellite positioning information is judged to be valid (recorded as 1) only when the number of satellite signal locks meets the standard, the PDOP value meets the requirements, and the coordinates are within a reasonable range.

[0014] The driver obtains departure information through the freight train driver's human-machine interface (DMI). Before the freight train departs, the driver inputs relevant departure information on the DMI, including the departure track number, departure direction, and initial position reference point (such as the nearest transponder number). After input, the DMI encrypts and transmits the information to the information processing unit of the onboard control system. During validity verification, the completeness of the information is first checked. If the driver has not entered key fields such as the departure track number or initial position reference point, the information is directly judged as incorrect (recorded as 0). If the information fields are complete, it is further matched with the track information in the track line database to check if the track number entered by the driver exists on the current line. If the track number does not exist or the departure direction conflicts with the actual allowed running direction of the track (e.g., the track only allows uphill running, but the driver enters downhill), the information is judged as incorrect. Furthermore, considering the current physical location of the freight train (preliminarily determined by the onboard speed sensor and initial positioning data), if the distance between the initial position reference point entered by the driver and the actual location of the freight train exceeds a preset deviation threshold (usually 100m, to avoid significant discrepancies between the driver's input and the actual location), it is also judged as an error. Only when the information fields are complete, the track and direction match, and the deviation of the initial position reference point is within a reasonable range, is the driver's input departure information judged as correct (recorded as 1).

[0015] The acquisition of identification and message information for the first group of physical transponders relies on the onboard transponder transmission module (BTM). When a freight train reaches the transponder deployment location, the BTM establishes short-range wireless communication (typically 2m-5m, dynamically adjusting the communication timing according to the freight train's speed) with the first group of physical transponders beside the track via its onboard antenna. It receives identification information (including the transponder's unique number, the number of transponders in the group, and their arrangement) and message information (covering track characteristic data such as track gradient, curve radius, speed limit, and link information) sent by the transponders. Validity verification is conducted from two aspects: identification integrity and message legality. During identification verification, if the BTM does not receive the transponder identification signal, or if the received identification signal is missing a unique number, or if the number of transponders in the group does not match the actual number deployed (e.g., if two transponders are deployed on the track as a group, but the BTM only receives the identification of one transponder), then the identification information is deemed abnormal. During message verification, the message format is first verified to conform to railway industry transponder message standards (such as the TB / T 3550 series standards). If there are issues such as missing fields, encoding errors, or mismatched check codes, the message information is deemed abnormal. Simultaneously, the line characteristic data in the message is compared with the corresponding data in the electronic track map. For example, if the speed limit value in the message deviates from the speed limit requirement for that section in the electronic map by more than 5 km / h, or if the subsequent transponder number in the link information is inconsistent with the link plan in the electronic map, the message is deemed abnormal. Only when the identifier is complete, the message format is valid, and the data matches is the identifier and message information of the first group of entity transponders deemed correct (recorded as 1); otherwise, it is deemed incorrect (recorded as 0).

[0016] The acquisition of the track installation location information for the first group of physical transponders involves combining basic data from track line construction with the onboard system's position correction logic. First, the designed installation location data (including latitude and longitude coordinates, mileage markers along the track line, and offset relative to the track centerline) of the first group of physical transponders is retrieved from the track line database. Simultaneously, the actual sensing position of the transponder is calculated using the freight train position when the onboard BTM receives the transponder signal (combined with preliminary satellite positioning data and speed sensor integral data). During validity verification, the latitude and longitude coordinates of the designed installation location are compared with the actual sensing location. If the deviation exceeds a preset position error threshold (typically ±0.5m, a core accuracy requirement for transponder positioning), the track installation location information is considered to be deviated (recorded as 0). Simultaneously, the mileage markers of the transponder installation location are checked to ensure they are consistent with the track line's mileage system. If the markers exceed the current line's mileage range or the mileage interval with adjacent transponders does not meet design requirements (e.g., the designed interval between adjacent transponders is 500m, but the actual interval deviation exceeds 10m), it is also considered a deviation. In addition, the offset of the transponder relative to the center line of the track is checked. If the offset exceeds ±0.3m (the installation range that ensures the vehicle-mounted antenna can stably receive signals), it is also judged as a position information deviation. Only when the deviation between the designed position and the actual perceived position is within the error threshold, the mileage marker is consistent, and the offset is compliant, is the track installation position information of the first group of physical transponders judged to be matched (recorded as 1).

[0017] After verifying the validity of each piece of information and obtaining the corresponding validity status (satellite positioning information valid / invalid, driver input departure information correct / incorrect, first group of entity transponder identifier and message information correct / incorrect, first group of entity transponder track installation position information matched / deviation, corresponding to binary status 1 or 0 respectively), the validity status is combined in the order of "satellite positioning information status - driver input departure information status - first group of entity transponder identifier and message information status - first group of entity transponder track installation position information status" to form a validity status combination result. For example, when the satellite positioning information is valid (1), the driver input departure information is correct (1), the first group of entity transponder identifier and message information is correct (1), and the track installation position information matches (1), the combination result is "1-1-1-1"; when the satellite positioning information is invalid (0), the driver input departure information is incorrect (0), the first group of entity transponder identifier and message information is incorrect (0), and the track installation position information deviation is (0), the combination result is "0-0-0-0". Through the above combination rules, 2 4=16 basic validity state combinations, covering all possible validity combinations of four types of information, providing comprehensive basic data support for the subsequent generation of test scenario sets based on scenario-dimensional hierarchical rules, working condition probability weighting strategies and anomaly coupling rules, while ensuring that each combination result can correspond to the information state that may occur in the actual operation of freight trains, meeting the requirements of authenticity and comprehensiveness of test scenarios.

[0018] Based on the aforementioned 16 basic validity state combinations, we can further focus on the validity associations of three core positioning information categories: satellite positioning information, driver-input departure information, and the first set of physical transponder information and location. This leads to the extraction of eight key combination scenarios, specifically: 1. Satellite valid - Driver input correct - Transponder correct; 2. Satellite valid - Driver input correct - Transponder incorrect; 3. Satellite valid - Driver input incorrect - Transponder correct; 4. Satellite valid - Driver input incorrect - Transponder incorrect; 5. Satellite invalid - Driver input correct - Transponder correct; 6. Satellite invalid - Driver input correct - Transponder incorrect; 7. Satellite invalid - Driver input incorrect - Transponder correct; 8. Satellite invalid - Driver input incorrect - Transponder incorrect. Among them, combination 4 (satellite valid - driver input error - transponder error) and combination 8 (all three are incorrect) involve the failure of two or more types of core information at the same time. There is currently no clear and effective positioning protection method. When generating test scenario sets according to the scenario dimension layering rules in the future, these two combinations should be marked as "high-risk scenarios to be verified" and given higher priority (it is recommended that the weight value be no less than 0.15). In the verification process, the inspection of the vehicle system response behavior should be strengthened, and the focus should be on confirming whether there are potential risks such as positioning drift and abnormal mode switching in the system. This is to avoid driving safety problems caused by the lack of protection logic and to ensure that the test scenarios can cover both normal situations and targeted investigation of high-risk weak links.

[0019] Step 120: Generate a test scenario set based on the validity state combination results, scenario dimension layering rules, working condition probability weighting strategy, and anomaly coupling rules.

[0020] After verifying and combining the validity and status of the freight train's satellite positioning information, driver-input departure information, the identification and message information of the first set of physical transponders, and track installation location information, the basic valid status combinations are transformed into a test scenario set covering actual operating conditions through multi-dimensional scenario segmentation, dynamic weight adjustment, and coupled scenario expansion. The entire process combines track topology data, historical fault statistics, and system safety requirements to ensure the comprehensiveness and rationality of scenario generation. The specific implementation process is as follows: First, the basic scenarios are categorized dimensionally, classifying all valid state combinations from environmental, mode, and fault dimensions to form a basic scenario set. The environmental dimension is based on the actual topological characteristics of the track line. Topological parameters of the current test line are retrieved from the electronic track map, including the number of tracks (single track / multi-track), line type (tunnel / elevated / ground line), turnout density, and spacing between adjacent transponders. For example, when the valid state combination is "satellite positioning failure + transponder position normal," if the test line is multi-track and contains more than 3 sets of turnouts, and the current operating section is a tunnel (tunnel length exceeding 500m, severe satellite signal obstruction), then this combination is classified as "multi-track - tunnel section - transponder position normal environment." If the line is single-track and has no complex structures, only local curves (curve radius 300m-500m), then it is classified as "single track - ground curve - transponder position normal environment." For effective satellite positioning status combinations, the electromagnetic environment parameters around the line (such as whether it is near high-voltage lines or communication base stations) are also combined to supplement the subcategories of "strong electromagnetic interference environment" and "no electromagnetic interference environment" to ensure that the environmental dimension division can reflect the impact of different scenarios on positioning signals.

[0021] The mode dimension division is based on the matching relationship between the control level and validity status of freight trains. First, the commonly used operating modes of freight trains and the positioning information requirements of each mode are clarified. The full mode requires valid satellite positioning and correct driver input information. The guidance mode requires valid satellite positioning or normal transponder information. The authorized visual mode requires correct driver input information and the transponder list to be enabled. The unauthorized visual mode does not require RBC-issued vehicle permit (MA) but requires transponder information support. Based on this, the validity status combination is associated with the mode. For example, the combination of "valid satellite positioning (1) - correct driver input (1) - normal transponder identification (1) - normal transponder position (1)" corresponds to the two categories of "full mode" and "guidance mode". The combination of "failed satellite positioning (0) - correct driver input (1) - normal transponder identification (1) - normal transponder position (1)" corresponds to "authorized visual mode". If the mode switching command is triggered manually on the DMI, the on-board system will switch the authorized visual mode to the unauthorized visual mode. Then, this combination further corresponds to the "unauthorized visual mode". The combination of "driver input error (0) - other information arbitrary" is classified as "mode switching abnormal scenario" because it cannot meet the input requirements of the normal mode, and is marked as a scenario that requires key testing of the vehicle system mode protection logic.

[0022] The fault classification is based on the type and quantity of failure information. First, the classification criteria for failure information are defined. Satellite positioning failures include signal loss, exceeding accuracy limits (PDOP>5), and coordinate offset (exceeding the track range ±50m). Driver input errors include incorrect track numbering, initial position reference point deviation (>100m), and departure direction conflict. Transponder failures include missing / incorrect identifiers, message format violations (checksum mismatch), and position deviation (>±0.5m). Link information anomalies include exceeding the link window (transponder position exceeds the link window range) and inconsistent directions (conflict with electronic map link direction).

[0023] Based on the above fault dimension classification, a new subdivision "transponder list usage status" is added. Combined with the link information status, the scenario division is further refined to better reflect the fusion processing logic of the on-board system for multi-source positioning information in actual operation: In the scenario where the transponder list is enabled, if the transponder list is enabled according to the rules during the operation of a freight train, when the first group of physical transponders is included in the list and the link information is normal, it can be determined as a "list matching - link normal" scenario. In this scenario, the test focus should be on the priority identification logic of the on-board system for the list transponders, to confirm whether the system prioritizes the identification, message and location information of the transponders in the list to correct the positioning deviation input by the satellite or the driver, so as to ensure the accuracy of the positioning results. When a transponder is not included in the list but the link information is normal, it is judged as a "list mismatch - link normal" scenario. In this case, it is necessary to focus on verifying the safety protection logic of the vehicle system, checking whether it can trigger the overreach mode in a timely manner after receiving the transponder information and update the transponder to the new Last Related Transponder Group (LRBG). At the same time, the timing of the mode switch (requiring a delay of ≤3s from receiving the transponder to triggering the overreach mode) and the accuracy of the LRBG update (the new LRBG number must be consistent with the actual identifier of the transponder) should be recorded. In the scenario where the transponder list is not enabled, regardless of whether the transponder is in the preset list, the system must use the link information as the core judgment basis. If the transponder is not within the coverage of the link information, it is necessary to verify whether the vehicle system processes it according to the logic of "not receiving the first group of physical transponders". That is, do not update the LRBG, do not adjust the current positioning result, and the driver human-machine interface (DMI) does not display any abnormal status. Only record the event information of "transponder not within the link range" in the system background log to avoid interference with the normal positioning process due to non-critical transponder information.

[0024] Meanwhile, for two typical cases of abnormal link information, special test logic needs to be added to improve the verification of fault scenarios: In the transponder out-of-window scenario, if the transponder is in the link information list but its actual position is outside the specified range of the link window (e.g., the link window is set to mileage K10+200 to K10+500, and the actual position of the transponder is K10+600), it is necessary to verify whether the vehicle system can accurately identify the out-of-window status and trigger the link response. Specifically, this includes recording the out-of-window deviation value (accurate to 0.1m), not updating the LRBG, and sending an out-of-window alarm message to the Radio Block Center (RBC) within 5 seconds. The message must include the unique number of the out-of-window transponder, the actual detection position, and the preset range of the link window so that the RBC can synchronously grasp the abnormal positioning situation. In a transponder direction error scenario, if the transponder direction marked in the link information (e.g., the uphill lane) is inconsistent with the actual received transponder direction (e.g., the downhill lane), there is a high probability of an error in the electronic map data. In this case, it is necessary to verify whether the vehicle system can immediately switch to the "overdrive mode", save the currently received transponder information and delete other historical LRBGs, and disconnect from the RBC to avoid erroneous data interaction. The DMI interface should simultaneously display a red warning pop-up window for "Direction Error - Overdrive Status", and the warning information should continue to be displayed until the fault is manually confirmed to be resolved, ensuring that the driver can promptly grasp the abnormal status.

[0025] Subsequently, the state combinations were categorized based on the number of failure messages: combinations with only one type of failure message (such as satellite positioning signal loss only, or driver inputting a wrong track only) were classified as "single-dimensional failure scenarios." Combinations with two or more types of failure messages (such as satellite positioning failure + driver input error, or transponder message error + link information overlay) were classified as "multi-dimensional coupled failure scenarios." Additionally, for critical positioning devices like transponders, special failure scenarios such as "transponder packet parsing anomaly" (BTM cannot parse messages) and "missing transponder in a group" (a group should contain two transponders but only one is received) were added separately to ensure that the failure dimensions cover all types of positioning anomalies that may occur in actual operation.

[0026] After completing the basic scenario segmentation, the weight allocation and correction stage begins. This process relies on historical operational fault statistics of similar freight trains (typically collecting fault records from the same line and train model over the past 3 years, with a sample size of no less than 1000 records). First, core state combinations are extracted: based on the industry-standard freight train positioning safety risk level classification (e.g., TB / T XXXX-XXXX), the positioning failure risk of each state combination is quantified into a risk value. Risk value = (satellite failure weight × satellite failure state) + (driver input error weight × input error state) + (transponder failure weight × transponder failure state) + (linkage anomaly weight × linkage anomaly state). The weights for each failure type are set according to the degree of safety impact (satellite failure weight 0.3, driver input error weight 0.25, transponder failure weight 0.35, linkage anomaly weight 0.1). When the risk value is ≥0.6, it is judged as "high risk", 0.4≤risk value<0.6 is "medium risk", and risk value<0.4 is "low risk". State combinations of "medium risk" and above are extracted as core state combinations (e.g., "satellite failure + transponder failure" risk value=0.3+0.35=0.65, which is high risk), and positioning information state constraints are set for each type of core combination (e.g., high risk combinations must meet the requirement of "at least including transponder failure or satellite failure").

[0027] The initial weight allocation is based on the historical frequency of core combinations. The occurrence frequency of each core combination in the fault records over the past three years is statistically analyzed, and the frequency percentage is calculated and used as the initial weight. For example, if "satellite failure in tunnel + normal transponder position" occurs 120 times in 1000 fault records, with a frequency percentage of 12%, then the initial weight is set to 0.12. If "driver input error + link information pop-up" occurs 30 times, with a frequency percentage of 3%, then the initial weight is set to 0.03. Weight correction is then based on the actual probability of occurrence of coupled scenarios. The frequency of coupled scenarios that meet the positioning information state constraints is calculated using historical data. If the single-dimensional scenario of "satellite failure" has occurred 200 times historically, and 80 of those instances involve simultaneous transponder message errors, the coupling probability is 80 / 200 = 0.4. Therefore, the weight of the coupled scenario "satellite failure + transponder message error" is corrected to "initial weight of satellite failure single-dimensional scenario × 0.4" (e.g., if the initial weight of satellite failure is 0.15, the corrected weight of the coupled scenario is 0.06). If a certain coupled scenario has an extremely low historical occurrence frequency (e.g., "driver input error + satellite failure + transponder position deviation" only occurs 5 times, accounting for 0.5%), but has a risk value as high as 0.9 (high risk), then its weight should be appropriately increased to 0.01 (higher than the original frequency percentage) to ensure that high-risk scenarios are not ignored due to their low historical frequency.

[0028] Finally, scenario expansion is performed to generate composite test scenarios. This step constructs a location information failure correlation matrix based on abnormal coupling rules. First, two core correlation logics are identified: The first is the coupling logic between satellite positioning and the transponder. When freight trains operate in areas with weak satellite signals, such as tunnels and viaducts, satellite positioning fails simultaneously, and the transponder is susceptible to line vibration, leading to unstable message transmission. The probability of both failing simultaneously is twice as high as on ground lines. The second is the coupling logic between driver input and link information. When the driver inputs an incorrect track number, the link information retrieved by the onboard system based on the incorrect track will inevitably mismatch with the actual track, resulting in link information exceeding the window or incorrect direction. The probability of both failing simultaneously is close to 1 (approximately 0.95). Based on these two logics, an correlation matrix is ​​constructed. The rows of the matrix represent "single-dimensional failure types" (satellite failure S, driver input error D, transponder failure Y, link anomaly L), and the columns represent "potentially coupled failure types." The matrix elements are the probabilities P of both failing simultaneously (e.g., P(S,Y)=0.4, P(D,L)=0.95, P(S,D)=0.15).

[0029] Based on the correlation matrix, the basic scenario prototype is expanded as follows: For the single-dimensional scenario of "only satellite positioning failure (S=1, D=0, Y=0, L=0)," two coupled scenarios are added: "satellite failure + transponder message error (S=1, Y=1, message checksum mismatch)" and "satellite failure + transponder position deviation (S=1, Y=1, position deviation ±0.8m)." The positioning information status constraints of the coupled scenarios must clearly state that "satellite failure type is signal loss, and transponder failure type is message / position problem." For the single-dimensional scenario of "only driver input error (D=1, S=0, Y=0, L=0)," two coupled scenarios are added: "driver input error + link information window exceeding the window (D=1, L=1, transponder position exceeds the link window by 10m)" and "driver input error + inconsistent link direction (D=1, L=1, opposite to the electronic map link direction)." The constraints are that "driver input error type is incorrect track number, and link anomaly type is window / direction error."

[0030] Simultaneously, dimensional attributes are defined for the expanded composite scenarios: For example, in the composite scenario of "satellite failure + transponder message error," the environment dimension is "multi-track - tunnel section" (a typical environment for satellite failure), the mode dimension is "authorized visual mode" (a common mode when satellite fails), and the fault dimension is "two-dimensional coupled fault" (satellite + transponder failure). In the composite scenario of "driver input error + link information overlay," the environment dimension is "multi-track - turnout area" (complex tracks easily lead to input errors), the mode dimension is "mode switching abnormal scenario," and the fault dimension is "two-dimensional coupled fault" (input + link abnormality). Finally, all scenarios are sorted based on the scenario weight sequence (basic scenario prototype weight and composite scenario corrected weight). Scenarios with weights from high to low are included in the test scenario set. Scenarios with weights below 0.005 (such as the four-dimensional coupled scenario of "satellite failure + driver input error + transponder failure + link anomaly", which has only appeared once in history) are used as alternative scenarios. This ensures that the test scenario set can prioritize the coverage of high-probability, high-risk operating conditions while also taking into account low-probability but critical extreme scenarios, providing comprehensive scenario support for the triggering and verification of subsequent test conditions.

[0031] Step 130: Based on the test scenario set and the real-time status parameters of the freight train operation, determine and adjust the triggering timing and intensity of the target test condition to simulate the abnormal and normal states of the target test condition.

[0032] After generating a test scenario set covering multiple dimensions, the triggering timing and intensity of the target test conditions are accurately determined and dynamically adjusted by combining the real-time status parameters of freight train operation. This ensures that the simulation can realistically reproduce the positioning information interaction logic during freight train operation and adapt to the real-time response capability of the onboard system. The specific implementation process requires relying on track topology data, freight train dynamic monitoring data, and system performance parameters to complete the timing determination and intensity optimization step by step.

[0033] When determining the triggering timing of the operating condition, the key track location nodes are first preset based on the positioning information state constraints and track topology basic data of each scenario in the test scenario set. Feature locations strongly related to the positioning logic are extracted through the track electronic map, including the last related transponder group (LRBG) update associated location (such as the transponder deployment point 200m-500m away from the previous LRBG, the specific spacing is adjusted according to the line design speed, set to 300m for 120km / h lines and 500m for 200km / h lines), the over-progression mode trigger associated location (such as the track section 100m-200m before the signal, which needs to match the signal display status and the freight train running direction), the link information processing associated location (such as the start and end points of the link window, i.e., the boundary of the track mileage range corresponding to the transponder in the link information), and the transponder priority determination associated location (such as the turnout area where multiple transponder groups intersect, which needs to distinguish the priority of the main line and the siding transponder). Subsequently, real-time operational status parameters of the freight train are collected using onboard GPS, speed sensors, and axle temperature monitoring equipment. The focus is on extracting the freight train's real-time location information (latitude and longitude coordinates, track mileage markers) and approach speed (instantaneous speed, acceleration). Using the onboard system's position matching algorithm, the real-time location is compared with preset key track nodes to calculate the relative distance between the freight train and each node. When the relative distance is less than or equal to a preset warning distance (usually 50m, dynamically adjusted according to the freight train's speed, increasing to 80m at high speeds), the system is determined to enter the condition triggering prediction stage, and the timestamp at this point is recorded as the prediction initiation point. When the freight train continues to run until the relative distance is 0 (i.e., reaching a key location node) or meets preset triggering conditions (such as passing directly above a transponder or when a signal displays a red light), the timestamp is recorded as the official triggering point. For example, in the scenario of "satellite positioning failure - transponder position normal", the preset LRBG update node is the transponder at track mileage K10+300. When the freight train's real-time position is K10+250 and its speed is 80km / h, with a relative distance of 50m, the pre-judgment is triggered. When the freight train reaches K10+300 and receives the transponder signal, the LRBG update condition is officially triggered.

[0034] In addition to the triggering logic of the above-mentioned conventional scenarios, for the "stationary vehicle positioning" scenario that is common in the start-up phase of freight trains, it is necessary to add exclusive triggering timing and intensity determination rules to cover the positioning verification requirements of freight trains in a stationary state: In the scenario where stationary vehicle positioning is successful, if the freight train obtains the initial LRBG through stationary vehicle positioning reverse search (i.e., reverse calculation based on historical positioning data and track topology), it is necessary to first preset a "reverse search result confirmation node". This node is usually set as the track mileage marker (accurate to 1m) corresponding to the initial LRBG. Combined with the real-time position parameters of the freight train (in a stationary state, the position update frequency is usually ≤1Hz to reduce data redundancy), when the system determines that the relative distance between the freight train and this node is 0, the "stationary vehicle positioning verification condition" can be triggered. Based on the current control level of the freight train, the trigger intensity can be further divided: In full mode, the trigger intensity is set to level one, requiring simultaneous verification of the LRBG update logic and the RBC movement authorization (MA) reception process. The delay from triggering the condition to receiving the MA must be ≤10s, and the line range included in the MA must match the initial LRBG. In guided mode, the trigger intensity is set to level two, focusing on the LRBG update logic. It is necessary to confirm that the new LRBG number is consistent with the reverse search result, with an update delay of ≤5s. In unauthorized visual mode (triggered manually by the driver on the DMI), the trigger intensity is set to level three, requiring only verification of the basic functions of transponder reception and LRBG update, without needing to associate it with the RBC interaction process, thus simplifying the testing complexity of low-priority scenarios.

[0035] In scenarios where stationary vehicle positioning fails, if a freight train fails to acquire a valid initial LRBG within 30 seconds after activating the stationary vehicle positioning function, a "positioning failure alarm node" needs to be preset. At this time, a "positioning failure emergency condition" is triggered, with the trigger strength uniformly set to the highest level to verify the system's emergency response capability. It is necessary to check whether the onboard system can immediately and automatically switch to visual authorization mode, while simultaneously enabling transponder list-assisted positioning, and sending a positioning failure alarm message to the RBC within 5 seconds. The message must completely include key parameters such as the positioning failure duration, the current satellite signal status (e.g., signal strength, number of locked satellites), and the departure information entered by the driver, so that the RBC can remotely determine the cause of the anomaly. If the system does not automatically enable the transponder list, it is necessary to further verify the functional recovery after the driver manually enables the list to ensure the integrity of the positioning logic in emergency scenarios.

[0036] In terms of operating condition adjustment logic, the triggering strategy is dynamically optimized based on the real-time status parameters of the freight train: If the freight train experiences a positional deviation of ≤0.5m due to slight track vibration after successful positioning of the stationary train (which is a normal physical error), the triggering time of the operating condition needs to be delayed by 5s to avoid triggering abnormal operating conditions due to instantaneous deviation and to ensure the accuracy of the test results; If real-time monitoring reveals that the RBC data interaction rate is lower than 80kbps (lower than the normal adaptation requirement), the triggering intensity of the "stationary train positioning verification operating condition" needs to be appropriately reduced. For example, the synchronous verification of "LRBG update + MA reception" in full mode is adjusted to "first complete the LRBG update verification (lasting 10s), then trigger the MA reception verification". By reducing peak data interaction, the verification failure caused by insufficient bandwidth is avoided, ensuring that the system can still stably complete the test process when communication conditions are poor.

[0037] In the trigger strength classification stage, a tiered standard is established based on the type of positioning failure in different scenarios, combined with signal characteristics and the degree of information deviation. For satellite positioning failure scenarios, the satellite signal attenuation amplitude is used as the core indicator. The signal strength is monitored through the vehicle-mounted satellite receiver module, and the trigger strength is divided into three levels: Level 1 is slight signal attenuation (intensity -85dBm to -100dBm, PDOP value 3-5, positioning accuracy deviation 5m-10m), corresponding to the "satellite positioning accuracy decline" condition. Level 2 is moderate signal attenuation (intensity -100dBm to -120dBm, PDOP value 5-8, positioning accuracy deviation 10m-20m), corresponding to the "unstable satellite positioning" condition. Level 3 is complete signal loss (intensity below -120dBm, PDOP value greater than 8, positioning coordinates cannot be calculated), corresponding to the "satellite positioning failure" condition. Different intensities trigger different positioning correction strategies for the vehicle system (e.g., Level 1 activates transponder-assisted correction, Level 3 directly switches to visual mode). For transponder malfunction scenarios, the intensity is categorized by the type of error in the identifier or message: Level 1 intensity is a minor anomaly in the transponder identifier (e.g., reversed transponder number order within the group, but complete message data), corresponding to the "transponder identifier sorting error" condition. Level 2 intensity is a partial error in the transponder message (e.g., mismatched checksum, but correct key fields such as the line speed limit), corresponding to the "partial transponder message failure" condition. Level 3 intensity is a complete loss of the transponder identifier or a completely unparseable message, corresponding to the "complete transponder failure" condition. Different intensity triggers different onboard responses (e.g., Level 1 only indicates an identifier anomaly, while Level 3 directly triggers the over-the-top mode). For driver input information errors, the intensity is categorized by the range of information deviation: Level 1 intensity is an initial position reference point deviation (100m-200m, not affecting track judgment), corresponding to the "minor input position deviation" condition. Level 2 intensity is an incorrect track number but still within the same station range, corresponding to the "input track error" condition. Level 3 intensity indicates an incorrect departure direction (e.g., an upward input is a downward input), corresponding to the "input direction conflict" condition. Level 1 intensity only triggers a location reminder, while Level 3 intensity directly prohibits departure and prompts for re-entry.

[0038] The timing and intensity of the triggering conditions are adjusted based on the dynamic changes in real-time operating parameters of the freight train to ensure compatibility with the onboard system's response capabilities. Regarding timing adjustment, the freight train's acceleration (positive / negative) and position update frequency (typically 1Hz-10Hz) are collected in real time. The onboard system's timing analysis algorithm is used to determine the matching degree between the determined triggering timing and the current operating state. For example, if the freight train's acceleration is -2m / s²... 2(Emergency deceleration) Due to deceleration, the relative distance between the key location node corresponding to the original preset formal triggering time and the real-time position of the freight train increases. At this time, the formal triggering time needs to be postponed until the relative distance meets the triggering condition again. If the position update frequency is lower than the preset threshold (e.g., lower than 2Hz, data transmission delay), the predicted start time will be advanced by 10s-15s to allow more data processing time and avoid missing the formal triggering opportunity. The matching degree is determined by calculating the "overlap between the actual triggering window and the preset window". Overlap = (actual triggerable time interval ∩ preset triggering time interval) duration / preset triggering time interval duration. When the overlap is lower than 80% (matching threshold), the predicted start time and the formal triggering time are automatically adjusted to ensure that the working condition triggering is synchronized with the freight train's operating status.

[0039] Regarding trigger intensity adjustment, the focus is on monitoring the vehicle system response delay (the time from triggering the operating condition to system feedback, normal range 0.5s-2s) and the Radio Block Center (RBC) data exchange rate (unit: kbps, normal range 100kbps-500kbps) to assess the compatibility between the intensity and the system's processing capacity. If the vehicle system response delay exceeds the compatibility threshold (e.g., 3s), it indicates that the current trigger intensity is too high (e.g., simultaneously triggering satellite failure + complete transponder failure), resulting in excessive system processing load. In this case, the intensity gradient needs to be reduced, for example, adjusting "satellite positioning failure (level 3) + complete transponder failure (level 3)" to "unstable satellite positioning (level 2) + partial transponder message failure (level 2)" to reduce the number of abnormal information the system needs to process. If the RBC data interaction rate is lower than the adaptation requirement (e.g., below 80kbps), it indicates that the communication bandwidth between the RBC and the vehicle system is insufficient. In this case, it is necessary to optimize the trigger strength superposition method for multi-information coupling failure scenarios. For example, the simultaneous triggering of "driver input error (level 3) + link information pop-up (level 3)" should be adjusted to "triggering the link information pop-up (level 3) 10 seconds after the driver input error (level 3) is triggered," to avoid the peak data interaction exceeding the bandwidth capacity. After adjustment, the system response latency and RBC interaction rate need to be re-monitored until both indicators return to the normal range, ensuring that the trigger strength of the operating conditions always matches the system processing capacity, simulating real abnormal operating conditions without causing the vehicle system or RBC to overload and crash.

[0040] Step 140: Collect the operational response data of the vehicle system and the interaction status data between the vehicle system and the radio block center during the target test condition simulation. Verify the operational response data and interaction status data to determine whether the response behavior of the vehicle system in the target test condition meets the rule requirements and generate test results.

[0041] During the target test condition simulation, the system's operational response data and the interaction status data between the vehicle system and the Radio Block Center (RBC) are acquired in real time through multi-dimensional data acquisition channels. The data is then analyzed based on a standardized verification process to determine whether the vehicle system's response behavior conforms to preset rules, and finally, traceable and quantifiable test results are generated.

[0042] During the data acquisition phase, a comprehensive data collection system covering the entire process from "internal status of the onboard system to vehicle-to-ground interaction" is established. For the operational response data of the onboard system, core parameters are collected in real time through the built-in data interfaces of the onboard control system (such as CAN bus interface and Ethernet interface). These parameters include the operating status of onboard equipment (e.g., whether the satellite positioning module is in signal lock-in state, whether the transponder transmission module (BTM) is parsing messages normally, and the driver's human-machine interface (DMI) display mode), positioning-related calculation results (e.g., the latest update record of the relevant transponder group (LRBG), the real-time calculated latitude and longitude coordinates and track mileage of the freight train, and the positioning accuracy deviation), and safety control commands (e.g., whether the overreach mode is triggered, whether a stop command is generated, and the timestamp of the mode switching command). The acquisition frequency must match the frequency of changes in operating conditions, typically set to 10Hz-20Hz, to ensure the capture of instantaneous state changes (e.g., the system response when satellite signals are suddenly lost). Simultaneously, data displayed on the interface (e.g., LRBG number, operating mode identifier, and fault alarm pop-ups) is collected synchronously through DMI screenshot recording and video recording equipment as a basis for visual verification.

[0043] For the interaction status data between the vehicle-mounted system and the RBC, interaction information is collected using data packet capture devices on the vehicle-to-ground communication link (such as Ethernet packet capture tools and GSM-R / 5G-R communication analyzers). This includes data transmission direction (vehicle-mounted to RBC / RBC to vehicle-mounted), interaction data types (such as location reporting messages, driving permission (MA) messages, link information messages, and fault alarm messages), data transmission parameters (such as message sending / receiving timestamps, message length, checksum, and retransmission count), and communication status indicators (such as link connection status, signal strength, data transmission delay, and packet loss rate). During the collection process, the interaction messages need to be parsed in real time to extract key fields (such as the route mileage range in MA, and the transponder number and window range in link information), and cross-referenced with the interaction data recorded locally by the vehicle-mounted system to avoid data loss or errors caused by single-path collection. For example, in the "satellite positioning failure - transponder message error" condition, it is necessary to simultaneously collect the overreach mode command triggered by the vehicle system, the "overreach status" alarm pop-up displayed by the DMI, the timestamp of the vehicle fault alarm message received by the RBC, and the link disconnect command fed back by the RBC, to ensure complete recording of the entire process data from condition triggering to system response to vehicle-to-ground interaction.

[0044] The data verification process involves feature extraction, standard comparison, and anomaly tracing in several steps to ultimately determine the compliance of the response behavior. First, feature parameters are extracted. From the collected operational response data and interaction status data, core features strongly correlated with the target test conditions are selected. These include data time-series features (such as the time difference between LRBG update time and transponder signal reception time, the time interval between triggering the overreach mode and satellite signal loss, and the time delay between RBC issuing MA and onboard confirmation reception), state change features (such as the state transition sequence from "full mode" to "visual mode," the record of LRBG number updates from old to new values, and the logic of the appearance and disappearance of DMI interface alarm information), and abnormal fluctuation features (such as the fluctuation range of positioning accuracy deviation suddenly jumping from the normal range (±5m) to over 20m, and the trend of data transmission delay suddenly increasing from 100ms to 1s). These feature parameters are organized into structured data sequences (such as storing time-series features in the form of "timestamp-parameter value") to provide a standardized data format for subsequent comparisons.

[0045] Subsequently, feature comparison verification is performed, quantifying and comparing the extracted feature parameters with the preset standard feature vector for operating conditions. This standard feature vector is based on industry standards for freight train operation control (such as the TB / T 3550 series standards) and onboard system design specifications. For example, in the operating condition of "driver input error - transponder not in link information", the standard timing feature is "the onboard system triggers the overreach mode within 3 seconds after receiving the transponder signal" and "the LRBG is updated to the current transponder within 2 seconds after the overreach mode is triggered". The standard status change feature is "the DMI interface immediately displays a red 'overreach alarm' pop-up window and continues until the fault is cleared". The standard interaction feature is "the onboard system sends a fault alarm message to the RBC within 5 seconds after the overreach mode is triggered, and the RBC sends a link status confirmation message within 10 seconds". During the comparison, the compliance degree is quantified by calculating the feature matching degree value. Matching degree = (number of features that meet the standard / total number of features) × 100%. For example, if 7 out of 8 features meet the standard in a certain operating condition, the matching degree is 87.5%. For time-series features, a reasonable time deviation of ±1s is allowed (considering system processing delay). For status-related features, they must fully comply with the standards (e.g., mode switching sequences and alarm display logic must not deviate). For abnormal fluctuation features, the fluctuation amplitude must be controlled within the standard's allowable range (e.g., positioning accuracy deviation fluctuation must not exceed ±3m).

[0046] If the feature matching degree is lower than the preset threshold (usually set to 90%, and 95% for high-safety-level conditions), an anomaly response tracing analysis is initiated. The root cause of the discrepancy is determined through data correlation analysis and logical deduction. First, a correlation graph of "condition triggering - data acquisition - system response" is constructed, associating abnormal feature parameters with the corresponding condition triggering nodes and data acquisition timestamps. For example, in the case of an anomaly with excessive positioning accuracy deviation, it is necessary to trace the satellite signal strength, transponder message parsing results, and the working status of the onboard computing module when the deviation occurred to determine whether the positioning calculation was inaccurate due to a sudden attenuation of the satellite signal (strength below -120dBm) or invalid correction data due to an incorrect transponder message checksum. Simultaneously, the onboard system log and RBC interaction log are compared to check for data transmission anomalies (such as a packet loss rate exceeding 5% leading to untimely RBC command reception) or onboard system response logic errors (such as failure to delete old LRBGs according to rules). For example, in the "transponder message error" condition, if the vehicle system does not trigger the stop command, the source is traced back to the fact that the BTM module did not transmit the message error signal to the vehicle control unit, which is determined to be an abnormal hardware data interaction link; if the BTM has transmitted the error signal but the vehicle control unit does not execute the command, it is determined to be an abnormal system response logic, forming an abnormal source tracing result that includes "abnormal characteristics - influencing factors - root cause type".

[0047] Finally, by combining the feature matching degree values ​​and the anomaly tracing results, a complete test result is generated. The test result includes three core parts: First, basic operating condition information, recording the test scenario type (e.g., "satellite positioning failure - multiple lanes - authorized visual mode"), the timing and intensity of the operating condition trigger (e.g., "formal triggering at K10+500, satellite signal completely lost (level 3 intensity)"), and the data acquisition period (accurate to the second). Second, compliance judgment results. If the matching degree is ≥ the threshold and there are no major anomaly tracing results (e.g., no logical errors or hardware failures), it is judged as "compliant with the rule requirements," and the key characteristics of compliance are listed (e.g., "LRBG update time meets the standard within 3 seconds" and "RBC interaction delay ≤ 1 second"). If the matching degree is < the threshold or there are major anomalies (e.g., logical errors causing failure to trigger safety commands), it is judged as "non-compliant with the rule requirements," and the difference characteristics are explained in detail (e.g., "overreach mode trigger delay of 5 seconds, exceeding the standard 1 second deviation range") and the tracing conclusion (e.g., "delay caused by incorrect priority setting of vehicle system response logic"). Thirdly, optimization suggestions should be provided, including specific improvement directions for non-compliance items (such as "adjusting the priority of the vehicle system response logic and setting the overreach mode trigger command as the highest priority"), and summarizing reusable testing experience for compliance items (such as "the transponder correction logic is stable after satellite signal loss in this scenario and can be extended to similar circuit tests"). Test results should be presented in a structured report format, with additional screenshots of key data during the operating condition simulation process (such as DMI alarm interface, RBC interaction message parsing results) and anomaly tracing analysis diagrams to ensure that the results are traceable and verifiable, providing a clear basis for the optimization and upgrading of the vehicle system.

[0048] To further enhance the operability of testing methods and the objectivity of result judgment, the following provides test implementation cases and expected result judgment criteria for typical scenarios, transforming abstract verification logic into concrete and executable test steps, while clarifying compliance boundaries: The first typical case is the scenario of "satellite failure - activation of transponder list - transponder in list". The operating parameters for this scenario need to be set to match the actual tunnel or strong electromagnetic interference environment: satellite positioning failure (signal strength < -120dBm, PDOP value > 8, unable to generate valid positioning coordinates), the driver inputs the correct departure information (track number is "track 3", the initial position reference point is the nearby transponder "BG010", and the deviation from the actual position is ≤ 50m), the first group of physical transponders "BG011" is included in the transponder list, and the freight train is initially in full mode. The corresponding expected response characteristics need to cover the complete state switching and information interaction process: within 3 seconds after detecting the loss of satellite signal, the onboard system automatically switches from full mode to authorized visual mode (the upper left corner of the DMI interface displays a green "visual authorization" icon, with no alarm prompts). When the freight train runs directly above transponder "BG011", within 5 seconds after the onboard BTM module receives and parses the transponder information, it sends a "vehicle position information valid" report message to the RBC. Within 10 seconds of receiving the message, the RBC sends a "track clear confirmation" message to the onboard system. After the driver clicks the confirmation button on the DMI, the onboard system must receive the driving authorization (MA) issued by the RBC within 10 seconds. The line range in the MA must cover the next signal "X12". Within 5 seconds of receiving the MA, the system automatically switches from visual authorization mode back to full mode (the DMI interface indicator switches to "full mode" in blue). The compliance judgment criteria for this scenario need to quantify the timing and functional indicators: if the delays of all the above timing nodes (mode switching, reporting location, receiving confirmation message, receiving MA, and switching back to full mode) are within the threshold, and the feature matching degree is ≥95%, and there are no abnormal traceability results (such as no data packet loss or logical judgment errors), then it is judged to be compliant with the rules. If a certain timing element exceeds the threshold (e.g., MA reception delay reaches 15s), it is necessary to compare the vehicle-to-ground communication log with the RBC processing record to trace whether it is caused by excessive RBC load or signal attenuation in the tunnel. If it is confirmed that it is a delay in the vehicle system interaction logic, it is determined to be non-compliant and the priority scheduling of MA reception needs to be optimized.

[0049] The second typical case is the scenario of "driver input error - transponder not in the link information". The operating parameters are set to focus on positioning anomalies caused by human error: satellite positioning is valid (signal strength ≥ -85dBm, PDOP value ≤ 3, positioning coordinates deviation from track range ≤ 5m), the driver inputs incorrect departure information (mistakenly inputting "track 2" instead of "track 4", initial position reference point deviation reaches 120m, departure direction conflicts with the actual track allowable direction), the first set of physical transponders "BG025" is not within the coverage of the current link information (the link information only includes "BG020-BG024"), and the freight train is initially in guidance mode. The expected response characteristics should highlight the system's safety protection trigger logic: within 3 seconds after the onboard system receives the transponder "BG025" information via BTM, it switches to the over-progression mode, and ATP triggers emergency braking. Within 2 seconds after switching to the over-progression mode, the original LRBG (the original LRBG was "BG018", generated based on the incorrect driver input) is automatically deleted. Set transponder "BG025" as the new LRBG and update its identifier, message, and location data in system memory. Within 5 seconds of the new LRBG update, send a "Driver Input Error" alarm message to the RBC. The message must include key information such as the incorrectly entered track number, the new LRBG number "BG025", and the timestamp of the overreach mode trigger. Compliance determination requires simultaneous fulfillment of functional and timing requirements: if the overreach mode trigger delay is ≤3s, the LRBG update number is correct, the alarm pop-up is complete, and the feature matching degree is ≥90%, then it is determined to comply with the rules. If it does not switch to overreach mode, and tracing reveals that the onboard system did not determine the condition of "transponder not in connection information," which is a core logic deficiency, then it is determined to be non-compliant, and a real-time comparison algorithm between connection information and transponder identifier needs to be added.

[0050] The third typical case is the "transponder message error - link information normal" scenario. The operating parameters are set for trackside equipment failure: satellite positioning is valid, driver input of departure information is correct, the first group of physical transponders "BG030" has an error (checksum does not match preset value, key field "line speed limit value" is missing), link information is normal ("BG030" is in the link list, located within the link window), and the freight train is initially in full mode. The expected response characteristics need to verify the system's emergency handling of key data errors: the onboard system detects an error when parsing the transponder message and triggers a reckless mode within 2 seconds. Within 3 seconds of triggering the reckless mode, all LRBGs (including the initial LRBG "BG028" and the temporarily updated "BG029") are deleted. Within 5 seconds of deleting the LRBGs, the communication connection with the RBC is actively disconnected (vehicle-to-ground communication link status shows "disconnected," and the "RBC connection" icon on the DMI interface shows disconnected). Simultaneously, the DMI interface displays "transponder message error" and triggers ATP normal braking. After parking, the driver is prompted to ease off the brakes, and the system prohibits manual switching to other operating modes. Compliance determination requires confirmation of the completeness of emergency measures: if the above state changes (triggering an overreaction, deleting the LRBG, disconnecting the RBC, displaying an alarm) fully match the preset standards, and the delays of each step are within the threshold, then it is determined to be compliant with the rules. If only an alarm is triggered but the RBC is not disconnected, and it is confirmed through tracing that the "RBC disconnection logic" is set to a low priority, causing it to be blocked by other tasks, then it is determined to be non-compliant with the rules, and the priority of the disconnection logic needs to be adjusted to ensure safe isolation under critical faults.

[0051] Furthermore, as a response to the above Figure 1 The implementation of the method embodiment shown in this application provides a freight train positioning test device. This device embodiment corresponds to the foregoing method embodiments. For ease of reading, this embodiment will not repeat the details of the foregoing method embodiments one by one, but it should be clear that the device in this embodiment can correspondingly implement all the contents of the foregoing method embodiments. Specifically, as shown... Figure 2 As shown, the freight train positioning test device 200 includes: The acquisition module 210 is used to acquire the satellite positioning information of the freight train, the departure information input by the driver, the identification and message information of the first group of physical transponders, and the track installation position information of the first group of physical transponders. It verifies the validity of each piece of information, obtains the validity status of each piece of information, and combines the validity status of each piece of information to form a validity status combination result. The generation module 220 is used to generate a set of test scenarios based on the combination results of validity states, the hierarchical rules of scenario dimensions, the probability weighting strategy of working conditions, and the anomaly coupling rules. Test module 230 is used to determine and adjust the triggering timing and intensity of the target test condition based on the test scenario set and the real-time status parameters of the freight train operation, so as to simulate the abnormal and normal states of the target test condition. The results analysis module 240 is used to collect the operational response data of the vehicle system and the interaction status data between the vehicle system and the radio block center during the target test condition simulation process, verify the operational response data and interaction status data, and determine whether the response behavior of the vehicle system in the target test condition meets the rule requirements, and generate test results.

[0052] Furthermore, such as Figure 2 As shown, the generation module 220 is specifically used to divide the state combinations in the validity state combination results into a basic scenario set from the environmental dimension, mode dimension, and fault dimension; to assign initial weights to the basic scenarios based on the occurrence probability of each basic scenario in the target test condition in the statistical data of the operation failure of similar freight trains; to correct the initial weights of the basic scenarios with information coupling failures to obtain the weight-corrected basic scenarios; and to expand and combine the weight-corrected basic scenarios to generate a test scenario set.

[0053] Furthermore, such as Figure 2 As shown, the generation module 220 is specifically used to convert the positioning failure risk level of each state combination in the effective state combination result into a corresponding risk level based on the freight train positioning safety risk level classification standard; extract state combinations with risk levels reaching or exceeding a preset risk threshold as core state combinations; use each type of core state combination as a basic scenario prototype; and determine the positioning information state constraints corresponding to each basic scenario prototype; determine the corresponding environmental dimension category for each basic scenario prototype based on track topology characteristics; determine the corresponding mode dimension category for each basic scenario prototype based on the freight train control level; and determine the corresponding fault dimension category for each basic scenario prototype based on the number of failure information; and count the occurrence frequency of each core state combination in the effective state combination result, based on the occurrence frequency... First, determine the risk weights for each core state combination, and assign initial weight values ​​to the basic scenario prototypes with determined environment, mode, and fault dimension categories according to the risk weights. Then, calculate the probability of occurrence of coupled scenarios that meet the location information state constraints based on the operational fault statistics of similar freight trains. Correct the initial weight values ​​of the basic scenario prototypes based on the occurrence probabilities to generate a scenario weight sequence. Next, construct a location information failure correlation matrix based on the abnormal coupling rules and the location information state constraints of the basic scenario prototypes. Expand the corrected basic scenario prototypes based on the location information failure correlation matrix to generate composite test scenarios, and assign corresponding weights to the composite test scenarios based on the scenario weight sequence. Finally, sort the basic scenario prototypes and the implemented composite test scenarios according to the scenario weight sequence to obtain a test scenario set.

[0054] Furthermore, such as Figure 2 As shown, the generation module 220 is specifically used to determine the first type of association logic between satellite positioning information failure and the first group of entity transponder identifiers or message anomalies, and the second type of association logic between driver input departure information errors and link information anomalies, based on the abnormal coupling rules; it constructs a positioning information failure association matrix based on the first type of association logic, the second type of association logic, and the positioning information state constraints of the basic scenario prototype, including whether the satellite positioning information is valid or invalid, whether the driver input departure information is accurate or incorrect, whether the first group of entity transponder identifiers and messages are complete or incomplete, and whether the track installation position of the first group of entity transponders matches or deviates; and based on the positioning information failure association matrix, it corrects the basic scenario prototype... The test scenario is designed to address single-dimensional failure constraints, including single failures of satellite positioning information, single errors in driver input departure information, single anomalies in the first group of transponders, and single anomalies in link information. This is supplemented by multi-dimensional coupled failure scenario conditions, such as simultaneous occurrences of satellite positioning information failure and transponder message incompleteness, simultaneous existence of departure information errors and link information deviations, and simultaneous occurrences of satellite positioning failure and transponder identification anomalies. These conditions form the core scenario conditions for the composite test scenario. Based on these core scenario conditions, the environmental dimension category, mode dimension category, and fault dimension category of the multi-information coupled failure category are determined for the composite test scenario. The positioning information state constraints of the composite test scenario are then clarified, thus forming the composite test scenario.

[0055] Furthermore, such as Figure 2 As shown, test module 230 is specifically used to, based on the positioning information state constraints and track topology basic data corresponding to each scenario in the test scenario set, preset key track position nodes that match the scenarios of the last relevant transponder group update, overreach mode triggering, link information processing, and transponder priority determination. Combined with the real-time position information of the freight train in the real-time status parameters of the freight train operation, it determines the relative distance and approach speed between the freight train and the key track position nodes, and determines the predicted start time and formal triggering time for the corresponding working condition. The trigger intensity of the overreach mode triggering corresponding to the satellite positioning failure scenario in the test scenario set is divided according to the signal attenuation amplitude; the trigger intensity of the last relevant transponder group update and transponder priority determination corresponding to the transponder anomaly scenario in the test scenario set is divided according to the identifier or message error type; and the trigger intensity of the link information processing corresponding to the driver input information error scenario in the test scenario set is divided according to the range of information deviation impact.

[0056] Furthermore, such as Figure 2As shown, the test module 230 is specifically used to determine the matching degree between the determined triggering time of the working condition and the current operating state of the freight train based on the dynamic failure characteristics of each scenario in the test scenario set, combined with the freight train acceleration and real-time position update frequency in the real-time status parameters of the freight train operation. If the matching degree is lower than the matching threshold, the triggering time of the working condition is adjusted. According to the on-board system response delay and the radio block center data interaction rate in the real-time status parameters of the freight train operation, the adaptability of the determined triggering intensity of the working condition and the system processing capacity is evaluated. If the on-board system response delay is higher than the adaptability threshold, the triggering intensity gradient of the corresponding working condition is reduced. If the radio block center data interaction rate is lower than the adaptability requirement, the triggering intensity superposition method of the multi-information coupling failure scenario is optimized.

[0057] Furthermore, such as Figure 2 As shown, the result analysis module 240 is specifically used to extract feature parameters associated with the target test condition from the running response data and interaction status data. The feature parameters include data time sequence features, state change features, and abnormal fluctuation features. The data time sequence features, state change features, and abnormal fluctuation features are compared with the preset test condition response standard feature vector to obtain the corresponding feature matching degree values. Combined with the abnormal response tracing analysis, the root cause of the difference data with feature matching degree values ​​lower than the preset threshold is located to determine whether the difference is caused by abnormal response logic or abnormal data transmission of the vehicle system, thus forming an abnormal tracing result. Based on the feature matching degree values ​​and the abnormal tracing result, it is determined whether the response behavior of the vehicle system in the target test condition meets the preset rule requirements.

[0058] Optionally, the freight train positioning test device may be an electronic device with data processing capabilities, or a functional module within such electronic device, without limitation.

[0059] For example, the electronic device can be a server, which can be a single server or a server cluster consisting of multiple servers. As another example, the electronic device can be a mobile phone, tablet computer, desktop computer, laptop computer, handheld computer, notebook computer, ultra-mobile personal computer (UMPC), netbook, as well as cellular phones, personal digital assistants (PDAs), augmented reality (AR) devices, virtual reality (VR) devices, and other terminal devices. As yet another example, the electronic device can also be a recording device, video surveillance equipment, etc. This application does not impose any special limitations on the specific form of the electronic device.

[0060] The following example uses an electronic device for positioning testing on freight trains. Figure 3 As shown, Figure 3 The hardware structure of an electronic device 300 provided in this application.

[0061] like Figure 3 As shown, the electronic device 300 includes a processor 310, a communication line 320, and a communication interface 330.

[0062] Optionally, the electronic device 300 may also include a memory 340. The processor 310, memory 340, and communication interface 330 can be connected via a communication line 320.

[0063] The processor 310 can be a central processing unit (CPU), a general-purpose processor, a network processor (NP), a digital signal processor (DSP), a microprocessor, a microcontroller, a programmable logic device (PLD), or any combination thereof. The processor 310 can also be any other device with processing capabilities, such as a circuit, device, or software module, without limitation.

[0064] In one example, processor 310 may include one or more CPUs, for example Figure 3 CPU0 and CPU1 in the CPU.

[0065] As an optional implementation, the electronic device 300 may include multiple processors, for example, in addition to processor 310, it may also include processor 370. A communication line 320 is used to transmit information between the components included in the electronic device 300.

[0066] Communication interface 330 is used for communication with other devices or other communication networks. These other communication networks can be Ethernet, Radio Access Network (RAN), Wireless Local Area Networks (WLAN), etc. Communication interface 330 can be a module, circuit, transceiver, or any device capable of enabling communication.

[0067] The memory 340 is used to store instructions. These instructions can be computer programs.

[0068] The memory 340 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and / or instructions; it may also be a random access memory (RAM) or other type of dynamic storage device capable of storing information and / or instructions; it may also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices, etc., without limitation.

[0069] It should be noted that the memory 340 can exist independently of the processor 310, or it can be integrated with the processor 310. The memory 340 can be used to store instructions, program code, or some data, etc. The memory 340 can be located inside or outside the electronic device 300, without restriction.

[0070] The processor 310 is configured to execute instructions stored in the memory 340 to implement the communication method provided in the following embodiments of this application. For example, when the electronic device 300 is a terminal or a chip in a terminal, the processor 310 can execute instructions stored in the memory 340 to implement the steps performed by the sending end in the following embodiments of this application.

[0071] As an optional implementation, the electronic device 300 also includes an output device 350 and an input device 360. The output device 350 can be a display screen, speaker, or other device capable of outputting data from the electronic device 300 to the user. The input device 360 ​​can be a keyboard, mouse, microphone, joystick, or other device capable of inputting data into the electronic device 300.

[0072] It should be pointed out that, Figure 3 The structure shown does not constitute a limitation on the electronic device, except... Figure 3 In addition to the components shown, the electronic device may include more or fewer components than illustrated, or combine certain components, or have different component arrangements.

[0073] The freight train positioning test device and application scenarios described in this application are intended to more clearly illustrate the technical solutions of this application and do not constitute a limitation on the technical solutions provided in this application. As those skilled in the art will know, with the evolution of freight train positioning test devices and the emergence of new business scenarios, the technical solutions provided in this application are also applicable to similar technical problems.

[0074] This application provides a storage medium storing a program that, when executed by a processor, implements the freight train positioning test method.

[0075] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0076] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0077] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for testing the positioning of freight trains, characterized in that, The method includes: The system acquires satellite positioning information of freight trains, driver-input departure information, identification and message information of the first group of physical transponders, and track installation location information of the first group of physical transponders. It then verifies the validity of each piece of information to obtain the validity status of each piece of information. Finally, it combines the validity statuses of each piece of information to form a validity status combination result. Based on the validity state combination results, scenario dimension layering rules, working condition probability weighting strategy, and anomaly coupling rules, a test scenario set is generated; Based on the test scenario set and the real-time status parameters of the freight train operation, determine and adjust the triggering timing and intensity of the target test condition to simulate the abnormal and normal states of the target test condition. The system collects operational response data of the vehicle system and interaction status data between the vehicle system and the radio block center during the target test condition simulation. The operational response data and the interaction status data are verified to determine whether the response behavior of the vehicle system in the target test condition meets the rule requirements, and test results are generated.

2. The method according to claim 1, characterized in that, Based on the validity state combination results, scenario dimension layering rules, working condition probability weighting strategy, and anomaly coupling rules, a test scenario set is generated, including: The validity state combination results are divided into three dimensions: environment, mode, and fault, to form a basic scenario set. Based on the probability of occurrence of each basic scenario in the target test condition from the statistical data of operational failures of similar freight trains, initial weights are assigned to the basic scenarios. The initial weights of the basic scenario with information coupling failure are corrected to obtain the basic scenario with corrected weights; The base scenarios, after weight correction, are expanded and combined to generate a set of test scenarios.

3. The method according to claim 2, characterized in that, The validity state combination results are dimensionally divided into environmental, pattern, and fault dimensions to form a basic scenario set. Based on the occurrence probability of each basic scenario in the target test condition from the statistical data of similar freight train operation faults, initial weights are assigned to the basic scenarios. The initial weights of basic scenarios with information coupling failures are corrected to obtain weight-corrected basic scenarios. These weight-corrected basic scenarios are then expanded and combined to generate a test scenario set, including: Based on the classification standard for safety risk levels of freight train positioning, the degree of positioning failure risk corresponding to each state combination in the effective state combination results is converted into the corresponding risk level. State combinations with risk levels reaching or exceeding a preset risk threshold are extracted as core state combinations. Each type of core state combination is used as a basic scenario prototype, and the positioning information state constraints corresponding to each basic scenario prototype are determined. Based on the track topology characteristics, the corresponding environmental dimension category is determined for each basic scenario prototype; based on the freight train control level, the corresponding mode dimension category is determined for each basic scenario prototype; and based on the number of failure information, the corresponding fault dimension category is determined for each basic scenario prototype. The frequency of occurrence of each core state combination in the effective state combination results is counted, and the risk weight of each core state combination is determined based on the frequency of occurrence. Initial weight values ​​are then assigned to the basic scenario prototype with determined environment, mode, and fault dimension categories according to the risk weights. Based on the statistical data of operational failures of similar freight trains, the probability of occurrence of coupled scenarios that meet the state constraints of the positioning information is calculated. The initial weight value of the basic scenario prototype is corrected based on the probability of occurrence, and a scenario weight sequence is generated. Based on the abnormal coupling rule, a location information failure correlation matrix is ​​constructed by combining the location information state constraints of the basic scene prototype. The modified basic scene prototype is then expanded based on the location information failure correlation matrix to generate a composite test scene. The composite test scene is then assigned corresponding weights based on the scene weight sequence. The basic scenario prototype and the implementation composite test scenario are sorted according to the scenario weight sequence to obtain the test scenario set.

4. The method according to claim 3, characterized in that, Based on the abnormal coupling rule, a location information failure correlation matrix is ​​constructed by combining the location information state constraints of the basic scenario prototype. The modified basic scenario prototype is then expanded based on this location information failure correlation matrix to generate a composite test scenario, including: Based on the abnormal coupling rules, the first type of association logic between satellite positioning information failure and the first group of entity transponder identification or message abnormality is determined, and the second type of association logic between driver input departure information error and link information abnormality is determined; Based on the first type of association logic, the second type of association logic, and the positioning information status constraints of the basic scenario prototype, such as whether the satellite positioning information is valid or invalid, whether the driver's input departure information is accurate or incorrect, whether the identifier of the first group of entity transponders is complete or incomplete, and whether the track installation position of the first group of entity transponders matches or deviates, a positioning information failure association matrix is ​​constructed. Based on the aforementioned location information failure correlation matrix, the single-dimensional failure state constraints in the corrected basic scenario prototype, namely, single failure of satellite positioning information, single error of driver input departure information, single anomaly of the first group of entity transponders, and single anomaly of link information, are supplemented with multi-dimensional coupled failure scenario conditions, namely, simultaneous occurrence of satellite positioning information failure and transponder message incompleteness, simultaneous existence of departure information error and link information deviation, and simultaneous occurrence of satellite positioning failure and transponder identification anomaly, thus forming the core scenario conditions of the composite test scenario. Based on the core scenario conditions, the environmental dimension category, mode dimension category, and fault dimension category of the multi-information coupling failure category of the composite test scenario are determined, and the location information state constraints of the composite test scenario are clarified to form the composite test scenario.

5. The method according to any one of claims 1-4, characterized in that, Based on the test scenario set and real-time operating status parameters of freight trains, determine the triggering timing and intensity of the target test condition, including: Based on the positioning information state constraints and track topology basic data corresponding to each scenario in the test scenario set, the key track position nodes that match the scenarios of the last related transponder group update, overreach mode triggering, link information processing, and transponder priority determination are preset. Combined with the real-time position information of the freight train in the real-time status parameters of the freight train operation, the relative distance and approach speed between the freight train and the key track position nodes are determined, and the predicted start time and formal trigger time of the corresponding working condition are determined. The trigger intensity of the satellite positioning failure scenario corresponding to the overreach mode in the test scenario set is divided according to the signal attenuation amplitude. The trigger intensity of the transponder abnormal scenario corresponding to the last related transponder group update and transponder priority determination in the test scenario set is divided according to the identification or message error type. The trigger intensity of the driver input information error scenario corresponding to the link information processing in the test scenario set is divided according to the information deviation impact range.

6. The method according to claim 5, characterized in that, Based on the test scenario set and real-time operating status parameters of freight trains, adjust the triggering timing and intensity of the target test condition, including: Based on the dynamic failure characteristics of each scenario in the test scenario set, and combined with the freight train acceleration and real-time position update frequency in the real-time status parameters of the freight train operation, the matching degree between the determined working condition triggering time and the current freight train operation status is determined. If the matching degree is lower than the matching threshold, the working condition triggering time is adjusted. Based on the onboard system response delay and radio block center data interaction rate in the real-time status parameters of freight train operation, the compatibility between the determined trigger intensity of the operating condition and the system processing capacity is evaluated. If the onboard system response delay is higher than the compatibility threshold, the trigger intensity gradient of the corresponding operating condition is reduced. If the radio block center data interaction rate is lower than the compatibility requirement, the trigger intensity superposition method of the multi-information coupling failure scenario is optimized.

7. The method according to claim 1, characterized in that, Verification of the runtime response data and the interaction status data includes: From the running response data and the interaction status data, feature parameters associated with the target test condition are extracted. The feature parameters include data time sequence characteristics, state change characteristics and abnormal fluctuation characteristics. The data time-series features, state change features, and abnormal fluctuation features are compared with the preset working condition response standard feature vector to obtain the corresponding feature matching degree values. By combining abnormal response source analysis, the root cause of the difference data with feature matching degree values ​​lower than the preset threshold is located, and it is determined whether the difference is caused by abnormal response logic of the vehicle system or abnormal data transmission, thus forming an abnormal source analysis result. Based on the feature matching degree value and the anomaly tracing result, it is determined whether the response behavior of the vehicle system in the target test condition meets the preset rule requirements.

8. A positioning test device for freight trains, characterized in that, The device includes: The acquisition module is used to acquire the satellite positioning information of the freight train, the departure information input by the driver, the identification and message information of the first group of physical transponders, and the track installation position information of the first group of physical transponders. It verifies the validity of each piece of information, obtains the validity status of each piece of information, and combines the validity status of each piece of information to form a validity status combination result. The generation module is used to generate a set of test scenarios based on the combined results of the validity states, the scenario dimension hierarchical rules, the working condition probability weighting strategy, and the anomaly coupling rules. The testing module is used to determine and adjust the triggering timing and intensity of the target test condition based on the test scenario set and the real-time status parameters of the freight train operation, so as to simulate the abnormal and normal states of the target test condition. The results analysis module is used to collect the operational response data of the vehicle system and the interaction status data between the vehicle system and the radio block center during the target test condition simulation process. The module verifies the operational response data and the interaction status data to determine whether the response behavior of the vehicle system in the target test condition meets the rule requirements and generates test results.

9. A storage medium, characterized in that, The storage medium includes a stored program, wherein, when the program is executed, it controls the device containing the storage medium to perform the freight train positioning test method as described in any one of claims 1-7.

10. An electronic device, characterized in that, The device includes at least one processor, at least one memory connected to the processor, and a bus; wherein the processor and the memory communicate with each other through the bus; the processor is used to call program instructions in the memory to execute the freight train positioning test method as described in any one of claims 1-7.

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