Agricultural machinery driver operator examination equipment, system and method based on Beidou positioning

Abstract

The present invention discloses equipment, systems, and methods for testing agricultural machinery operators based on Beidou positioning, belonging to the technical field of driving test technology. The system includes a satellite positioning antenna, a mobile station, a satellite base station, a satellite, a driver test data acquisition module, and a test center platform. The equipment also includes a satellite positioning antenna, a mobile station, a satellite base station, a satellite, a driver test data acquisition module, and a test center platform. The present invention uses satellite positioning and mobile data to monitor the position of agricultural machinery in real time. It combines driving behavior monitoring data with theoretical knowledge test data to comprehensively analyze the driving operation safety prediction index to assess the driver's operating safety and predict the safety of their future operations. This achieves a comprehensive assessment of the actual operating ability of agricultural machinery operators, solving the problem of incomplete assessment of the actual operating ability of agricultural machinery operators in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of driving test technology, and in particular to agricultural machinery driving operator test equipment, systems and methods based on Beidou positioning. Background Art

[0002] With the advancement of agricultural modernization and mechanization, agricultural production has become increasingly dependent on agricultural machinery. Especially in the context of large-scale mechanized operations, agricultural machinery operating techniques and driver safety awareness have become increasingly important. The skill level of agricultural machinery drivers not only affects operational efficiency but also directly impacts farmland safety and the sustainable development of agricultural production. To cope with increasingly complex operational requirements and ensure production safety, agricultural machinery driver training and examinations must keep pace with the times, gradually transitioning to information-based, digital, and intelligent systems.

[0003] Modern agricultural machinery driving test systems have begun to use computerized management, virtual simulation technology and intelligent evaluation methods, which can not only more accurately evaluate the driver's operating ability, but also optimize the training process and improve the quality of training through data.

[0004] For example, the invention patent with announcement number CN102360460B discloses a driver test supervision system, which includes: a test equipment verification system and a test equipment networking system. The verification system includes an authorization module, the networking system includes a test supervision module, the authorization module includes a management authorization module, a device feature extraction module, and a networking authorization module. The device feature extraction module extracts the feature parameters of the device and verifies the management authorization module. After success, the extracted device feature parameters are synchronously saved in the networking authorization module; the supervision module includes a networking comparison module and a call data recording module. The networking comparison module reads the feature parameters saved in the networking authorization module and compares the test equipment. After consistency, the test equipment calls the candidate information and writes the test results. The comparison module synchronously saves the call data in the call data recording module.

[0005] For example, the invention patent with announcement number CN106934740B discloses a driver test assessment method and system, including: a test terminal installed on a vehicle collects the candidate's identity information, vehicle location and vehicle equipment status information, and the test terminal determines whether the driver's test can be started based on the vehicle location and vehicle equipment status information; when the test terminal determines that the driver's test can be started, it sends a start test request carrying the candidate's identity information to the background server, and after the background server verifies the candidate's identity information, it sends a start test instruction to the test terminal.

[0006] However, existing technologies, including the above-mentioned technologies, have at least the following technical problems: Although the basic operating ability of candidates can be evaluated through their test scores, there are some significant limitations. The test results usually only reflect the performance of the candidates in a specific test situation, that is, they can only show the surface scores and lack a comprehensive assessment of the candidates' actual comprehensive abilities. This evaluation method cannot accurately reveal the degree of mastery of the candidates' various knowledge points, especially the assessment of some practical operating skills and emergency handling capabilities is not comprehensive enough. In summary, the existing technology has the problem of incomplete assessment of the actual operating ability of agricultural machinery drivers and operators. Summary of the Invention

[0007] In view of the above-mentioned problems, the purpose of the present invention is to provide an agricultural machinery driver operator examination device, system and method based on Beidou positioning, which can comprehensively evaluate the actual operating ability of agricultural machinery drivers.

[0008] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0009] Agricultural machinery driver and operator examination equipment based on Beidou positioning, including: agricultural machinery driver and operator examination equipment, special examination equipment, paperless examination system and electronic pile examination instrument;

[0010] Agricultural machinery driver operator examination equipment, used to monitor the driving behavior of agricultural machinery drivers while taking tests using special equipment for the test;

[0011] Special testing equipment, used to provide a testing driving environment for agricultural machinery operators;

[0012] Paperless examination system, used for conducting paperless computer examination of driving operators’ theoretical knowledge;

[0013] The electronic pile tester is used to test site driving operation skills and field operation driving operation skills.

[0014] The Beidou-based agricultural machinery driver and operator examination system is applied to the above-mentioned Beidou-based agricultural machinery driver and operator examination equipment, including a satellite positioning antenna, a mobile station, a satellite base station, a satellite, a driver and operator examination data acquisition module, and an examination center platform;

[0015] Satellite positioning antenna, used to calibrate the position of agricultural machinery;

[0016] Mobile station, used to measure the movement data of satellite positioning antenna;

[0017] Satellite base station, used to collect movement data from satellite positioning antennas on mobile stations and send the movement data to satellites;

[0018] Satellite, used to receive mobile data from satellite base stations and send the mobile data to the test center platform;

[0019] A driver test data acquisition module is used to acquire driver test data, obtain driver behavior monitoring data through agricultural machinery driver test equipment, and obtain theoretical knowledge test data through a paperless test system. The driver behavior monitoring data and theoretical knowledge test data are recorded as driver test data, and the driver test data is sent to the test center platform;

[0020] The examination center platform is used to receive driver examination data and mobile data sent from satellites. It is also used to analyze the driving operation safety prediction index based on the driver examination data and mobile data. The driving operation safety prediction index is used to estimate the safety level of the driver when he or she drives agricultural machinery next time.

[0021] Preferably, the test center platform further includes: a failure item detection module, a travel trajectory recognition module, an alarm prompt module, and a test result output module;

[0022] The unqualified item detection module is used to detect the test vehicle's stall, pole collision, line failure, and number of forward and reverse movements;

[0023] Travel trajectory recognition module, used to identify the location and travel status of the test vehicle;

[0024] An alarm prompt module is used to issue an alarm prompt to the agricultural machinery driver through audio-visual mode;

[0025] The test result output module is used to display, store and print the test results.

[0026] Preferably, the specific method of obtaining the driving operation safety estimation index is:

[0027] Based on the theoretical knowledge test data in the driver's test data, the theoretical knowledge safety index is analyzed. The theoretical knowledge safety index is used to reflect the driver's mastery of the theory.

[0028] Analyze the driving behavior safety index based on the driving operation behavior monitoring data and movement data in the driver's test data. The driving behavior safety index is used to reflect the driver's mastery of driving operations;

[0029] The influencing factors of theoretical knowledge safety index and driving behavior safety index on driving operation safety estimation index were obtained through objective weighting method.

[0030] According to the theoretical knowledge safety index, driving behavior safety index and influencing factors, the driving operation safety estimation index is analyzed through the driving operation safety estimation index formula.

[0031] Preferably, the driving operation safety prediction index formula is specifically:

[0032] ;

[0033] Where AHYI is the driving operation safety estimation index, e is the natural constant, LI is the theoretical knowledge safety index, JI is the driving behavior safety index, is the impact factor of LI on AHYI, is the impact factor of JI on AHYI.

[0034] Preferably, the specific method for obtaining the theoretical knowledge security index is:

[0035] Extract theoretical knowledge test scores, total number of incorrect test questions, difficulty level of incorrect test questions, total test question answering time, and mapping relationship between test questions and knowledge points from theoretical knowledge test data of driving operator test data;

[0036] The coverage of test questions and knowledge points is obtained based on the mapping relationship between test questions and knowledge points;

[0037] Obtain the impact factor of each data of theoretical knowledge test data on the theoretical knowledge security index through objective weighting method;

[0038] According to the theoretical knowledge test data and its influencing factors, the theoretical knowledge safety index is analyzed using the theoretical knowledge safety index formula.

[0039] Preferably, the theoretical knowledge safety index formula is:

[0040] ;

[0041] Where LI is the theoretical knowledge security index, MG is the theoretical knowledge test score, WT is the total number of wrong test questions, is the difficulty level of the i-th wrong question, i is the wrong question number, , DT is the total time for answering the test questions, NF is the coverage of the test knowledge points, tanh is the hyperbolic tangent function, and ln is the natural logarithm function.

[0042] Preferably, the specific method for obtaining the driving behavior safety index is:

[0043] Obtaining driving operation behavior monitoring data, driving operation behavior monitoring auxiliary data, and movement data from the driving operator test data;

[0044] Extract the acceleration and steering angular velocity of agricultural machinery based on the driving operation behavior monitoring data;

[0045] Extract the driving path offset distance and line-sticking time based on mobile data;

[0046] The weights of the agricultural machinery acceleration, agricultural machinery steering angular velocity, driving path offset distance and line-sticking time for the driving safety index are obtained according to the objective weighting method;

[0047] The driving behavior safety index is analyzed using the driving behavior safety index formula based on the agricultural machinery acceleration, agricultural machinery steering angular velocity, driving path offset distance, line-sticking time and their weights.

[0048] Preferably, the driving behavior safety index formula is:

[0049] ;

[0050] Where JI is the driving behavior safety index, AN is the acceleration of agricultural machinery, is the average acceleration of the agricultural machinery, WN is the steering angular velocity of the agricultural machinery, is the average steering angular velocity of the agricultural machinery, is the driving path offset distance, is the average offset distance of the driving path, The length of time it takes to stick to the line. is the average line-sticking time, is the weight of agricultural machinery acceleration to JI, is the weight of the agricultural machinery steering angular velocity for JI, is the weight of the driving path offset distance for JI, The weight of the line-sticking time for JI.

[0051] The agricultural machinery driver operator examination method based on Beidou positioning is applied to the above-mentioned agricultural machinery driver operator examination system based on Beidou positioning, and includes the following steps:

[0052] Calibrate the position of agricultural machinery through satellite positioning antenna;

[0053] Measuring the movement data of satellite positioning antennas through mobile stations;

[0054] The satellite base station collects the movement data of the satellite positioning antenna on the mobile station and sends the movement data to the satellite;

[0055] Receive mobile data from satellite base stations via satellite and send the mobile data to the test center platform;

[0056] Acquire driving operator test data through the driving operator test data acquisition module, acquire driving operation behavior monitoring data through the agricultural machinery driving operator test equipment, acquire theoretical knowledge test data through the paperless test system, record the driving operation behavior monitoring data and theoretical knowledge test data as driving operator test data, and send the driving operator test data to the test center platform;

[0057] The test center platform receives the driver's test data and the mobile data sent by satellite, and also analyzes the driving operation safety estimation index based on the driver's test data and the mobile data. The driving operation safety estimation index is used to estimate the safety level of the driver when he drives the agricultural machinery next time.

[0058] The beneficial effects of the present invention are:

[0059] The present invention combines Beidou satellite positioning technology with a driving operation behavior monitoring system to collect the operating data and movement trajectory of agricultural machinery drivers in real time, thereby deriving a driving operation safety prediction index for agricultural machinery drivers, thereby achieving a comprehensive assessment of the actual operating ability of agricultural machinery drivers and operators, effectively solving the problem of incomplete assessment of the actual operating ability of agricultural machinery drivers and operators in the existing technology.

[0060] The present invention combines theoretical knowledge test scores, the total number of incorrect test questions, the difficulty level of incorrect test questions, the total time taken to answer test questions, and the mapping relationship between test questions and knowledge points to obtain a theoretical knowledge safety index to comprehensively analyze the driver's mastery of theoretical knowledge, thereby achieving a quantitative assessment of the theoretical knowledge safety awareness of agricultural machinery drivers and effectively identifying their weak links.

[0061] The present invention comprehensively analyzes driving operation behavior monitoring data, movement data and related influencing factors to accurately calculate the driving behavior safety index, thereby achieving a comprehensive assessment of the agricultural machinery driver's behavior, identifying and quantifying their unsafe operations, and providing a basis for skill improvement, safety awareness improvement and safety management, effectively reducing potential risks and improving the overall operational safety level. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 This is a structural diagram of the agricultural machinery driver operator examination equipment based on Beidou positioning in Example 1;

[0063] Figure 2 This is a structural diagram of the agricultural machinery driver operator examination system based on Beidou positioning in Example 2;

[0064] Figure 3 This is a flow chart of the agricultural machinery driver operator examination method based on Beidou positioning in Example 3. DETAILED DESCRIPTION

[0065] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0066] This embodiment solves the problem of incomplete assessment of the actual operating ability of agricultural machinery drivers and operators in the existing technology by providing agricultural machinery driver operator examination equipment, systems and methods based on Beidou positioning. It monitors the position of agricultural machinery in real time through satellite positioning and mobile data, combines driving operation behavior monitoring data with theoretical knowledge examination data, and comprehensively analyzes the driving operation safety prediction index to evaluate the driver's operating safety and predict the safety of his future operations, thereby achieving a comprehensive assessment of the actual operating ability of agricultural machinery drivers and operators.

[0067] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0068] Example 1:

[0069] The first embodiment of the present invention provides an agricultural machinery driver operator examination device based on Beidou positioning, such as Figure 1 As shown, the equipment includes: agricultural machinery driver operator examination equipment, special examination equipment, paperless examination system and electronic pole test instrument; agricultural machinery driver operator examination equipment is used to monitor the driving operation behavior of agricultural machinery driver operators when using special examination equipment for examination; special examination equipment is used to provide a test driving environment for agricultural machinery driver operators, including providing a real driving environment and simulating various field operation scenes; the paperless examination system is used to provide computerized support for theoretical knowledge examinations and conduct paperless computer examinations of the driver operators' theoretical knowledge; the electronic pole test instrument is used to test field driving operation skills and field operation driving operation skills, and record and provide real-time feedback on the operator's driving performance, including precise control, steering, parking and other aspects.

[0070] Agricultural machinery driver operator examination equipment, etc. can be directly implemented by using relevant equipment, machinery, systems, and pile testers in the known technology. Similarly, the remaining components of the structure that are not described in detail in this application can directly adopt the known technology.

[0071] Example 2:

[0072] Another embodiment of the present invention provides an agricultural machinery driver operator examination system based on Beidou positioning, which is applied to agricultural machinery driver operator examination equipment based on Beidou positioning, such as Figure 2As shown, the system includes: a satellite positioning antenna, a mobile station, a satellite base station, a satellite, a driver operator test data acquisition module and an examination center platform; the satellite positioning antenna is used to calibrate the position of agricultural machinery; the mobile station is used to measure the movement data of the satellite positioning antenna; the satellite base station is used to collect the movement data of the satellite positioning antenna on the mobile station and send the movement data to the satellite; the satellite is used to receive the movement data of the satellite base station and send the movement data to the examination center platform; the driver operator test data acquisition module is used to acquire the driver operator test data, acquire the driving operation behavior monitoring data through the agricultural machinery driver operator test equipment, acquire the theoretical knowledge test data through the paperless test system, record the driving operation behavior monitoring data and the theoretical knowledge test data as the driver operator test data, and send the driver operator test data to the examination center platform; the examination center platform is used to receive the driver operator test data, receive the movement data sent by the satellite, and also to analyze the driving operation safety prediction index based on the driver operator test data and the movement data. The driving operation safety prediction index is used to estimate the safety level of the driver operator when he drives the agricultural machinery next time.

[0073] The examination center platform also includes: an unqualified item detection module, a travel trajectory identification module, an alarm prompt module, and an examination result output module; the unqualified item detection module is used to monitor and record safety hazards or irregular operations in the agricultural machinery examination process in real time, and detect the number of times the examination vehicle stalls, hits the pole, goes out of line, and moves forward and backward; the travel trajectory identification module is used to track and identify the location and travel status of the examination vehicle in real time through the Beidou positioning system, and accurately record the vehicle's movement trajectory, including whether it deviates from the predetermined route, driving speed, steering angle and other information; the alarm prompt module is used to monitor the safety behavior of the driver in real time during the examination. Once the system detects irregular operation or dangerous behavior (such as stalling, collision, abnormal acceleration, etc.), it will immediately issue a warning through audio-visual prompts to remind the driver to correct it in time; the examination result output module is used to output the examination results and related data (such as operation errors, score, trajectory data, etc.) after comprehensive analysis, and provides storage and printing functions to facilitate subsequent data viewing, archiving and report generation.

[0074] The specific method of obtaining the driving operation safety prediction index is as follows: based on the theoretical knowledge test data in the driving operator test data, the theoretical knowledge safety index is analyzed, and the theoretical knowledge safety index is used to reflect the driver's mastery of the theory; based on the driving operation behavior monitoring data and movement data in the driving operator test data, the driving behavior safety index is analyzed, and the driving behavior safety index is used to reflect the driver's mastery of driving operations; the influencing factors of the theoretical knowledge safety index and the driving behavior safety index on the driving operation safety prediction index are obtained through the objective weighting method; according to the theoretical knowledge safety index, the driving behavior safety index and the influencing factors, the driving operation safety prediction index is analyzed through the driving operation safety prediction index formula.

[0075] In this embodiment, the test center platform not only analyzes driver behavior based on test data and real-time satellite positioning data, but also comprehensively generates a driving safety assessment index. By analyzing each driver's operating data and historical records, the test center platform can provide personalized safety assessments and recommendations for each driver, more accurately identifying each candidate's weaknesses and helping them improve their skills in a targeted manner.

[0076] The driving operation safety prediction index formula is as follows:

[0077] ;

[0078] Where AHYI is the driving operation safety estimation index, e is the natural constant, LI is the theoretical knowledge safety index, JI is the driving behavior safety index, is the impact factor of LI on AHYI, is the impact factor of JI on AHYI.

[0079] For example, LI is 0.98, JI is 0.52, is 0.5, When it is 0.5, AHYI is 0.57. The higher the driving operation safety prediction index, the safer the next driving operation will be. Conversely, the lower the driving operation safety prediction index, the less safe the next driving operation will be.

[0080] The specific method for obtaining the theoretical knowledge safety index is as follows: extract the theoretical knowledge test scores, the total number of incorrect test questions, the difficulty level of incorrect test questions, the total time for answering test questions, and the mapping relationship between test questions and knowledge points from the theoretical knowledge test data of the driving operator test data; derive the test question knowledge point coverage based on the mapping relationship between test questions and knowledge points; obtain the influence factors of each data of the theoretical knowledge test data on the theoretical knowledge safety index through the objective weighting method; and analyze the theoretical knowledge safety index through the theoretical knowledge safety index formula based on the theoretical knowledge test data and its influencing factors.

[0081] In this embodiment, the theoretical knowledge safety index not only provides a more comprehensive and objective assessment of theoretical knowledge, but also quantitatively identifies drivers' weaknesses in different knowledge areas, providing data support for developing personalized training plans. This assessment effectively improves agricultural machinery drivers' awareness of safe operations, reduces operational risks caused by insufficient theoretical knowledge, and lays a solid foundation for future practical safety.

[0082] The theoretical knowledge safety index formula is:

[0083] ;

[0084] Where LI is the theoretical knowledge security index, MG is the theoretical knowledge test score, WT is the total number of wrong test questions, is the difficulty level of the i-th wrong question, i is the wrong question number, , DT is the total time for answering the test questions, and NF is the coverage of the test knowledge points.

[0085] For example, MG is 92, WT is 4, is 1, is 2, is 4, When the theoretical knowledge safety index is 4, the DT is 0.7h, and the NF is 0.45, the LI is 0.98. A higher theoretical knowledge safety index indicates that the agricultural machinery driver has a more proficient grasp of theoretical knowledge, and thus will be safer the next time they drive agricultural machinery. Conversely, a lower theoretical knowledge safety index indicates that the agricultural machinery driver is less proficient in theoretical knowledge, and thus will be less safe the next time they drive agricultural machinery.

[0086] The specific method for obtaining the driving behavior safety index is as follows: obtain the driving operation behavior monitoring data, driving operation behavior monitoring auxiliary data and mobile data from the driving operator test data; extract the agricultural machinery acceleration and agricultural machinery steering angular velocity based on the driving operation behavior monitoring data; extract the driving path offset distance and the time of sticking to the line based on the mobile data; obtain the weights of the agricultural machinery acceleration, agricultural machinery steering angular velocity, driving path offset distance and the time of sticking to the line for the driving safety index respectively according to the objective weighting method; analyze the driving behavior safety index through the driving behavior safety index formula based on the agricultural machinery acceleration, agricultural machinery steering angular velocity, driving path offset distance and the time of sticking to the line and their weights.

[0087] In this embodiment, the Driving Behavior Safety Index provides a comprehensive driving behavior assessment, identifying specific unsafe behaviors during operation and providing data-driven guidance for improving driver skills and safety awareness. By accurately quantifying the relationship between driving behavior and safety, it can help drivers identify operational areas that require improvement, helping them avoid potential risks and accidents in subsequent driving. Furthermore, the Driving Behavior Safety Index can provide effective data support to regulatory authorities, helping them develop more precise safety management measures and improve the overall safety level of agricultural machinery driving operations.

[0088] The driving behavior safety index formula is:

[0089] ;

[0090] Where JI is the driving behavior safety index, AN is the acceleration of agricultural machinery, is the average acceleration of the agricultural machinery, WN is the steering angular velocity of the agricultural machinery, is the average steering angular velocity of the agricultural machinery, is the driving path offset distance, is the average offset distance of the driving path, The length of time it takes to stick to the line. is the average line-sticking time, is the weight of agricultural machinery acceleration to JI, is the weight of the agricultural machinery steering angular velocity for JI, is the weight of the driving path offset distance for JI, The weight of the line-sticking time for JI.

[0091] For example, AN is 1.8 , 1.4 , WN is 1.5 , 1.2 , 0.22m, 0.3m, 12 minutes, 5min, is 0.2, is 0.2, is 0.2, When the driving behavior safety index is 0.3, the JI is 0.52. The higher the driving behavior safety index, the safer the driving behavior. Conversely, the lower the driving behavior safety index, the less safe the driving behavior.

[0092] Example 3:

[0093] The third embodiment of the present invention provides an agricultural machinery driving operator examination method based on Beidou positioning, which is applied to an agricultural machinery driving operator examination system based on Beidou positioning, such as Figure 3 As shown, the method includes the following steps: calibrating the position of the agricultural machinery through a satellite positioning antenna; measuring the movement data of the satellite positioning antenna through a mobile station; collecting the movement data of the satellite positioning antenna on the mobile station through a satellite base station, and sending the movement data to the satellite; receiving the movement data of the satellite base station through the satellite, and sending the movement data to the examination center platform; obtaining the driving operator test data through the driving operator test data acquisition module, obtaining the driving operation behavior monitoring data through the agricultural machinery driving operator test equipment, obtaining the theoretical knowledge test data through the paperless test system, recording the driving operation behavior monitoring data and the theoretical knowledge test data as the driving operator test data, and sending the driving operator test data to the examination center platform; receiving the driving operator test data through the examination center platform, receiving the movement data sent by the satellite, and analyzing the driving operation safety prediction index based on the driving operator test data and the movement data, and the driving operation safety prediction index is used to estimate the safety level of the driver when the driver operates the agricultural machinery next time.

[0094] In this embodiment, based on the driver's actual operating performance and historical data, a driving safety prediction index can be used to predict the driver's safety risks in future driving operations. This not only provides a scientific assessment of the driver's operating habits and potential risks, but also helps training institutions, regulatory authorities, and drivers themselves identify weaknesses in their operations, allowing them to take proactive measures to adjust and improve, thereby effectively reducing safety hazards in future operations.

[0095] In summary, the embodiment of the present application combines Beidou satellite positioning technology with a driving operation behavior monitoring system to collect the operation data and movement trajectory of agricultural machinery drivers in real time, thereby deriving the driving operation safety prediction index of the agricultural machinery driver, and thus achieving a comprehensive assessment of the actual operating ability of the agricultural machinery driver.

Claims

1. The agricultural machinery driver operator examination system based on Beidou positioning is characterized by: The examination equipment includes agricultural machinery driver and operator examination equipment, special examination equipment, paperless examination system and electronic pile examination instrument; Agricultural machinery driver operator examination equipment, used to monitor the driving behavior of agricultural machinery drivers while taking tests using special equipment for the test; Special testing equipment, used to provide a testing driving environment for agricultural machinery operators; Paperless examination system, used for conducting paperless computer examination of driving operators’ theoretical knowledge; Electronic pile tester, used to test site driving operation skills and field operation driving operation skills; The examination system includes satellite positioning antenna, mobile station, satellite base station, satellite, driver operator examination data acquisition module and examination center platform; Satellite positioning antenna, used to calibrate the position of agricultural machinery; Mobile station, used to measure the movement data of satellite positioning antenna; Satellite base station, used to collect movement data from satellite positioning antennas on mobile stations and send the movement data to satellites; Satellite, used to receive mobile data from satellite base stations and send the mobile data to the test center platform; A driver test data acquisition module is used to acquire driver test data, obtain driver behavior monitoring data through agricultural machinery driver test equipment, and obtain theoretical knowledge test data through a paperless test system. The driver behavior monitoring data and theoretical knowledge test data are recorded as driver test data, and the driver test data is sent to the test center platform; The examination center platform is used to receive driver examination data and mobile data sent from satellites. It is also used to analyze the driving operation safety prediction index based on the driver examination data and mobile data. The driving operation safety prediction index is used to estimate the safety level of the driver when he or she drives agricultural machinery next time.

2. The agricultural machinery driver operator examination system based on Beidou positioning according to claim 1 is characterized in that: The test center platform also includes: unqualified item detection module, travel trajectory recognition module, alarm prompt module, and test result output module; The unqualified item detection module is used to detect the test vehicle's stall, pole collision, line failure, and number of forward and reverse movements; Travel trajectory recognition module, used to identify the location and travel status of the test vehicle; An alarm prompt module is used to issue an alarm prompt to the agricultural machinery driver through audio-visual mode; The test result output module is used to display, store and print the test results.

3. The agricultural machinery driver operator examination system based on Beidou positioning according to claim 1 is characterized in that: The specific method for obtaining the driving operation safety estimation index is as follows: Based on the theoretical knowledge test data in the driver's test data, the theoretical knowledge safety index is analyzed. The theoretical knowledge safety index is used to reflect the driver's mastery of the theory. Analyze the driving behavior safety index based on the driving operation behavior monitoring data and movement data in the driver's test data. The driving behavior safety index is used to reflect the driver's mastery of driving operations; The influencing factors of theoretical knowledge safety index and driving behavior safety index on driving operation safety estimation index were obtained through objective weighting method. According to the theoretical knowledge safety index, driving behavior safety index and influencing factors, the driving operation safety estimation index is analyzed through the driving operation safety estimation index formula.

4. The agricultural machinery driver operator examination system based on Beidou positioning according to claim 3 is characterized in that: The driving operation safety prediction index formula is as follows: ； Where AHYI is the driving operation safety estimation index, e is the natural constant, LI is the theoretical knowledge safety index, JI is the driving behavior safety index, is the impact factor of LI on AHYI, is the impact factor of JI on AHYI.

5. The agricultural machinery driver operator examination system based on Beidou positioning according to claim 3 is characterized in that: The specific method for obtaining the theoretical knowledge security index is: Extract theoretical knowledge test scores, total number of incorrect test questions, difficulty level of incorrect test questions, total test question answering time, and mapping relationship between test questions and knowledge points from theoretical knowledge test data of driving operator test data; The coverage of test questions and knowledge points is obtained based on the mapping relationship between test questions and knowledge points; Obtain the impact factor of each data of theoretical knowledge test data on the theoretical knowledge security index through objective weighting method; According to the theoretical knowledge test data and its influencing factors, the theoretical knowledge safety index is analyzed using the theoretical knowledge safety index formula.

6. The agricultural machinery driver operator examination system based on Beidou positioning according to claim 5, characterized in that: The theoretical knowledge safety index formula is: ； Where LI is the theoretical knowledge security index, MG is the theoretical knowledge test score, WT is the total number of wrong test questions, is the difficulty level of the i-th wrong question, i is the wrong question number, , DT is the total time for answering the test questions, and NF is the coverage of the test knowledge points.

7. The agricultural machinery driver operator examination system based on Beidou positioning according to claim 3 is characterized in that: The specific method for obtaining the driving behavior safety index is as follows: Obtaining driving operation behavior monitoring data, driving operation behavior monitoring auxiliary data, and movement data from the driving operator test data; Extract the acceleration and steering angular velocity of agricultural machinery based on the driving operation behavior monitoring data; Extract the driving path offset distance and line-sticking time based on mobile data; The weights of the agricultural machinery acceleration, agricultural machinery steering angular velocity, driving path offset distance and line-sticking time for the driving safety index are obtained according to the objective weighting method; The driving behavior safety index is analyzed using the driving behavior safety index formula based on the agricultural machinery acceleration, agricultural machinery steering angular velocity, driving path offset distance, line-sticking time and their weights.

8. The agricultural machinery driver operator examination system based on Beidou positioning according to claim 5, characterized in that: The driving behavior safety index formula is: ； Where JI is the driving behavior safety index, AN is the acceleration of agricultural machinery, is the average acceleration of the agricultural machinery, WN is the steering angular velocity of the agricultural machinery, is the average steering angular velocity of the agricultural machinery, is the driving path offset distance, is the average offset distance of the driving path, The length of time it takes to stick to the line. is the average line-sticking time, is the weight of agricultural machinery acceleration to JI, is the weight of the agricultural machinery steering angular velocity for JI, is the weight of the driving path offset distance for JI, The weight of the line-sticking time for JI.

9. A method for testing agricultural machinery drivers and operators based on Beidou positioning, applied to the agricultural machinery driver and operator testing system based on Beidou positioning according to any one of claims 1 to 8, characterized in that: The following steps are involved: Calibrate the position of agricultural machinery through satellite positioning antenna; Measuring the movement data of satellite positioning antennas through mobile stations; The satellite base station collects the movement data of the satellite positioning antenna on the mobile station and sends the movement data to the satellite; Receive mobile data from satellite base stations via satellite and send the mobile data to the test center platform; Acquire driving operator test data through the driving operator test data acquisition module, acquire driving operation behavior monitoring data through the agricultural machinery driving operator test equipment, acquire theoretical knowledge test data through the paperless test system, record the driving operation behavior monitoring data and theoretical knowledge test data as driving operator test data, and send the driving operator test data to the test center platform; The test center platform receives the driver's test data and the mobile data sent by satellite, and also analyzes the driving operation safety estimation index based on the driver's test data and the mobile data. The driving operation safety estimation index is used to estimate the safety level of the driver when he drives the agricultural machinery next time.

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