An automated test system for manned-unmanned platform collaboration

Abstract

The present application belongs to the field of automation testing technology, and specifically relates to an automatic testing system for manned-unmanned platform cooperation. A testing process configuration module allows users to flexibly configure tasks and subtasks, and ensures smooth execution of testing tasks according to a predetermined process by setting start nodes and end nodes of the tasks. The system can automatically execute testing tasks and give a reliability score of the final testing result by comprehensively evaluating the reliability of data sources, the quality of sub-process execution and network conditions. The present application provides two reliability calculation methods: the principle of the wooden barrel and weighted calculation, and flexibly selects the most suitable algorithm for task result evaluation according to different testing scenarios. The principle of the wooden barrel determines the reliability of the overall task according to the reliability of the worst sub-process, while the weighted calculation gives different weights according to the importance of the sub-processes, and more finely evaluates the reliability of the task.

Description

Technical Field

[0001] This invention belongs to the field of automated testing technology, specifically relating to an automated testing system for collaborative testing of manned and unmanned platforms, aiming to achieve high efficiency, automation, and reliability assessment optimization in multi-platform collaborative testing processes. Background Technology

[0002] With the rapid development of intelligent and unmanned technologies, the functional requirements for collaborative work between manned and unmanned platforms are becoming increasingly complex, placing ever higher demands on testing systems. Existing traditional testing methods primarily rely on manual operation and simple automation tools, which suffer from excessive manual intervention, low efficiency, and limited data analysis capabilities. These methods struggle to meet the demands of multi-platform testing for efficiency, intelligence, and reliability assessment, particularly in multi-node collaborative work and complex scenario simulation. Therefore, there is a need to provide an automated testing system for collaborative work between manned and unmanned platforms, which, through modular design and reliability assessment, improves testing efficiency and result accuracy. Summary of the Invention

[0003] (a) Technical problems to be solved The technical problem to be solved by this invention is: how to achieve high efficiency, automation and reliability assessment optimization of multi-platform collaborative testing processes.

[0004] (II) Technical Solution To address the aforementioned technical problems, this invention provides an automated testing system for collaborative manned and unmanned platforms, the automated testing system comprising a status monitoring module, a testing module, and a configuration management module; The testing module is used to execute automated tests and collect key data in real time during the testing process. The key data includes the start and end timestamps of the task, as well as the timestamp records of the execution of each key sub-process. The testing module is not only responsible for in-depth analysis of the key data, but also for calculating the reaction time difference of the test task based on the start and end timestamps of the task. By evaluating the reliability of the key data and combining it with the performance indicators of each sub-process, the testing module comprehensively calculates the overall reliability score of the test task, thereby providing data support for subsequent task decisions. The configuration management module is used to configure the protocol of signal data parsing rules and manage the sub-processes of test tasks. The configuration management module configures different types of test tasks by setting relevant parameters of the test tasks, including node information and device type, and manages each sub-process of the test tasks. The status monitoring module is used to monitor various data in the testing system in real time, including platform operating status parameters and type parameters. Through high-precision timestamps, the status monitoring module can accurately record the execution sequence of each key sub-process within the testing task, providing real-time data support for subsequent evaluation and analysis. The status monitoring module provides a data foundation for subsequent decision-making.

[0005] The node information set by the configuration management module includes the start node and end node information of the task.

[0006] The workflow of the testing system is as follows: Step 1: First, configure the data status, including protocol information. By configuring different protocol types, vehicle information, and channel information parameters, ensure that the data can be transmitted and parsed accurately and reliably throughout the entire test process. Step 2: Configure the test process, including the execution flow of test tasks and their subtasks. The core is defining the start and end node information of the tasks. By configuring the start and end node information, the test system can clearly define the start conditions and end criteria of the test tasks, thereby ensuring that the test process proceeds according to the predetermined steps and logical order. The start node of the task indicates the initial conditions when the test starts, while the end node marks the completion of the task execution, ensuring the controllability and efficiency of the entire test process. Step 3: Perform automated testing. Based on the task information in the pre-configured test process, automatically execute various test tasks. Step 4: Conduct a reliability assessment of the test results. After the test task is completed, the test system evaluates the platform credibility of the data source, network latency, and the execution effect of key sub-processes. Finally, based on the evaluation results, the reliability of the entire test task is calculated to ensure the accuracy and credibility of the test results. Step 5: Display test results: Display the calculated reliability value of the test results on the page, and provide corresponding reliability prompts according to different test tasks.

[0007] In step 4, the reliability assessment of the test results involves the data reliability hysteresis value H. r Calculations are made based on the credibility of the platform from which the data originates. With network latency (Unit: ms) Calculation: ; in, , These are the weights for platform credibility and network latency, respectively, and the weight parameters satisfy... .

[0008] In step 4, the reliability evaluation of the test results involves the reliability values ​​of the execution effect of key sub-processes. The reliability values ​​of the execution effect of key sub-processes are affected by both network factors and the execution results of each sub-process. In order to comprehensively consider these two factors, two evaluation methods are adopted: the barrel principle and weighted calculation.

[0009] In step 4, the evaluation method of the "barrel principle" is based on the idea of ​​"shortest plank", that is, in multiple sub-processes, the test system takes the lowest reliability score as the reliability of the sub-process execution result of the overall task. The evaluation formula is as follows: Assuming there are n sub-processes, the execution reliability of each sub-process i is... Values ​​range from 0 to 1; based on network quality factor. This indicates the impact of network latency and bandwidth on task execution, ranging from 0 to 1, where 0 represents poor and 1 represents excellent. , Indicates network latency; reliability value of the execution result of critical subprocesses. .

[0010] In step 4, the weighted evaluation method is to comprehensively score each sub-process based on its importance (weight) and network quality, thus more flexibly reflecting the contribution of each sub-process to the overall task reliability; the weight t of each sub-process... i Based on their criticality to the overall test task, sub-processes with higher weights have a greater impact on the final reliability score; assuming there are n sub-processes, and the execution reliability value of each sub-process is... Values ​​range from 0 to 1, corresponding to weights of 0 and 1. The network quality factor is ; Reliability values ​​of the execution results of key sub-processes: .

[0011] The reliability algorithm for test results is calculated based on the reliability of the execution results of key sub-processes and the entropy value of data reliability: ;in This is the reliable value of the execution result of the key sub-process. Select the appropriate method according to the actual needs and substitute the corresponding calculation result value. , These are the weights of the execution result reliability value and the data reliability hysteresis value of the key sub-process, respectively, and the weight parameters satisfy... .

[0012] Among them, when using the barrel principle as an evaluation method, the aforementioned Using R t1 The value; When using a weighted evaluation method, the aforementioned Using R t2 The value of .

[0013] The architecture of the testing system is as follows: (1) Data layer: used to store protocol data and configuration test task data information; (2) Business layer: including status monitoring module, test module and configuration management module; the status monitoring module processes the status information of protocol data, determines whether the node is online and whether there is any abnormality; the test module performs automated testing and evaluates the reliability of the test results; the configuration management module includes data status configuration and test task and sub-process configuration, and provides configuration input and management functions for test information and process information. (3) Presentation layer: The presentation layer consists of status monitoring, testing and configuration management. It displays the status information of the test through the page and provides the function of inputting and displaying interface information.

[0014] (III) Beneficial Effects Compared with existing technologies, this invention provides an automated testing system for collaborative manned and unmanned platforms, including a status monitoring module, a testing module, and a configuration management module. The test process configuration module allows users to flexibly configure tasks and their subtasks, ensuring the smooth execution of test tasks according to a predetermined process by setting start and end nodes. The system can automatically execute test tasks and comprehensively evaluate and provide a reliability score for the final test results by analyzing the reliability of data sources, the quality of sub-process execution, and network conditions. This invention provides two reliability calculation methods: the "weakest link" principle and weighted calculation, allowing for flexible selection of the most suitable algorithm for task result evaluation in different testing scenarios. The "weakest link" principle determines the overall task reliability based on the reliability of the worst sub-process, while weighted calculation assigns different weights to sub-processes based on their importance, providing a more refined evaluation of task reliability. Attached Figure Description

[0015] Figure 1 This is a functional composition diagram of the system of the present invention.

[0016] Figure 2 This is a flowchart of the system operation of the present invention.

[0017] Figure 3 This is a system architecture diagram of the present invention. Detailed Implementation

[0018] To make the objectives, contents, and advantages of the present invention clearer, the specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples.

[0019] This invention proposes an automated testing system for collaborative testing of manned and unmanned platforms. The system consists of three main modules: a status monitoring module, a testing and experimentation module, and a configuration management module. The configuration management module is mainly responsible for configuring the protocol of signal data parsing rules and managing the sub-processes of test tasks. The testing and experimentation module executes automated tests and collects key data in real time during the testing process. The status monitoring module is responsible for monitoring various data in the system in real time. After the test task is completed, the system performs a reliability assessment of the results, judging and evaluating the reliability of the data source and the execution effect of the sub-processes. Finally, based on the assessment results, the reliability of the entire test task is calculated to ensure the accuracy and credibility of the test results.

[0020] To address the aforementioned technical problems, this invention provides an automated testing system for collaborative manned and unmanned platforms, the automated testing system comprising a status monitoring module, a testing module, and a configuration management module; The testing module is used to execute automated tests and collect key data in real time during the testing process. The key data includes the start and end timestamps of the task, as well as the timestamp records of the execution of each key sub-process. The testing module is not only responsible for in-depth analysis of the key data, but also for calculating the reaction time difference of the test task based on the start and end timestamps of the task. By evaluating the reliability of the key data and combining it with the performance indicators of each sub-process, the testing module comprehensively calculates the overall reliability score of the test task, thereby providing data support for subsequent task decisions. The configuration management module is used to configure the protocol of signal data parsing rules and manage the sub-processes of test tasks. The configuration management module configures different types of test tasks by setting relevant parameters of the test tasks, including node information and device type, and manages each sub-process of the test tasks. The status monitoring module is used to monitor various data in the testing system in real time, including platform operating status parameters and type parameters. Through high-precision timestamps, the status monitoring module can accurately record the execution sequence of each key sub-process within the testing task, providing real-time data support for subsequent evaluation and analysis. The status monitoring module provides a data foundation for subsequent decision-making.

[0021] The node information set by the configuration management module includes the start node and end node information of the task.

[0022] The workflow of the testing system is as follows: Step 1: First, configure the data status, including protocol information. By configuring different protocol types, vehicle information, and channel information parameters, ensure that the data can be transmitted and parsed accurately and reliably throughout the entire test process. Step 2: Configure the test process, including the execution flow of test tasks and their subtasks. The core is defining the start and end node information of the tasks. By configuring the start and end node information, the test system can clearly define the start conditions and end criteria of the test tasks, thereby ensuring that the test process proceeds according to the predetermined steps and logical order. The start node of the task indicates the initial conditions when the test starts, while the end node marks the completion of the task execution, ensuring the controllability and efficiency of the entire test process. Step 3: Perform automated testing. Based on the task information in the pre-configured test process, automatically execute various test tasks. Step 4: Conduct a reliability assessment of the test results. After the test task is completed, the test system evaluates the platform credibility of the data source, network latency, and the execution effect of key sub-processes. Finally, based on the evaluation results, the reliability of the entire test task is calculated to ensure the accuracy and credibility of the test results. Step 5: Display test results: Display the calculated reliability value of the test results on the page, and provide corresponding reliability prompts according to different test tasks.

[0023] In step 4, the reliability assessment of the test results involves the data reliability hysteresis value H. r Calculations are made based on the credibility of the platform from which the data originates. With network latency (Unit: ms) Calculation: ; in, , These are the weights for platform credibility and network latency, respectively, and the weight parameters satisfy... .

[0024] In step 4, the reliability evaluation of the test results involves the reliability values ​​of the execution effect of key sub-processes. The reliability values ​​of the execution effect of key sub-processes are affected by both network factors and the execution results of each sub-process. In order to comprehensively consider these two factors, two evaluation methods are adopted: the barrel principle and weighted calculation.

[0025] In step 4, the evaluation method of the "barrel principle" is based on the idea of ​​"shortest plank", that is, in multiple sub-processes, the test system takes the lowest reliability score as the reliability of the sub-process execution result of the overall task. The evaluation formula is as follows: Assuming there are n sub-processes, the execution reliability of each sub-process i is... Values ​​range from 0 to 1; based on network quality factor. This indicates the impact of network latency and bandwidth on task execution, ranging from 0 to 1, where 0 represents poor and 1 represents excellent. , Indicates network latency; reliability value of the execution result of critical subprocesses. .

[0026] In step 4, the weighted evaluation method is to comprehensively score each sub-process based on its importance (weight) and network quality, thus more flexibly reflecting the contribution of each sub-process to the overall task reliability; the weight t of each sub-process... i Based on their criticality to the overall test task, sub-processes with higher weights have a greater impact on the final reliability score; assuming there are n sub-processes, and the execution reliability value of each sub-process is... Values ​​range from 0 to 1, corresponding to weights of 0 and 1. The network quality factor is ; Reliability values ​​of the execution results of key sub-processes: .

[0027] The reliability algorithm for test results is calculated based on the reliability of the execution results of key sub-processes and the entropy value of data reliability: ;in This is the reliable value of the execution result of the key sub-process. Select the appropriate method according to the actual needs and substitute the corresponding calculation result value. , These are the weights of the execution result reliability value and the data reliability hysteresis value of the key sub-process, respectively, and the weight parameters satisfy... .

[0028] Among them, when using the barrel principle as an evaluation method, the aforementioned Using R t1 The value; When using a weighted evaluation method, the aforementioned Using R t2 The value of .

[0029] The architecture of the testing system is as follows: (1) Data layer: used to store protocol data and configuration test task data information; (2) Business layer: including status monitoring module, test module and configuration management module; the status monitoring module processes the status information of protocol data, determines whether the node is online and whether there is any abnormality; the test module performs automated testing and evaluates the reliability of the test results; the configuration management module includes data status configuration and test task and sub-process configuration, and provides configuration input and management functions for test information and process information. (3) Presentation layer: The presentation layer consists of status monitoring, testing and configuration management. It displays the status information of the test through the page and provides the function of inputting and displaying interface information.

[0030] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. An automated testing system for collaborative testing of manned and unmanned platforms, characterized in that, The automated testing system includes a status monitoring module, a testing module, and a configuration management module; The testing module is used to execute automated tests and collect key data in real time during the testing process. The key data includes the start and end timestamps of the task, as well as the timestamp records of the execution of each key sub-process. The testing module is not only responsible for in-depth analysis of the key data, but also for calculating the reaction time difference of the test task based on the start and end timestamps of the task. By evaluating the reliability of the key data and combining it with the performance indicators of each sub-process, the testing module comprehensively calculates the overall reliability score of the test task, thereby providing data support for subsequent task decisions. The configuration management module is used to configure the protocol of signal data parsing rules and manage the sub-processes of test tasks. The configuration management module configures different types of test tasks by setting relevant parameters of the test tasks, including node information and device type, and manages each sub-process of the test tasks. The status monitoring module is used to monitor various data in the test system in real time, including platform operating status parameters and type parameters; With high-precision timestamps, the status monitoring module can accurately record the execution sequence of each key sub-process within the test task, providing real-time data support for subsequent evaluation and analysis. The status monitoring module provides a data foundation for subsequent decision-making.

2. The automated testing system for collaborative testing of manned and unmanned platforms as described in claim 1, characterized in that, The node information set by the configuration management module includes the start node and end node information of the task.

3. The automated testing system for collaborative testing of manned and unmanned platforms as described in claim 1, characterized in that, The workflow of the testing system is as follows: Step 1: First, configure the data status, including protocol information. By configuring different protocol types, vehicle information, and channel information parameters, ensure that the data can be transmitted and parsed accurately and reliably throughout the entire test process. Step 2: Configure the test process, including the execution flow of test tasks and their subtasks. The core is defining the start and end node information of the tasks. By configuring the start and end node information, the test system can clearly define the start conditions and end criteria of the test tasks, thereby ensuring that the test process proceeds according to the predetermined steps and logical order. The start node of the task indicates the initial conditions when the test starts, while the end node marks the completion of the task execution, ensuring the controllability and efficiency of the entire test process. Step 3: Perform automated testing. Based on the task information in the pre-configured test process, automatically execute various test tasks. Step 4: Conduct a reliability assessment of the test results. After the test task is completed, the test system evaluates the platform credibility of the data source, network latency, and the execution effect of key sub-processes. Finally, based on the evaluation results, the reliability of the entire test task is calculated to ensure the accuracy and credibility of the test results. Step 5: Display test results: Display the calculated reliability value of the test results on the page, and provide corresponding reliability prompts according to different test tasks.

4. The automated testing system for collaborative manned and unmanned platforms as described in claim 3, characterized in that, In step 4, the reliability assessment of the test results involves the data reliability retracement value H. r Calculations are made based on the credibility of the platform from which the data originates. With network latency calculate: ; in, , These are the weights for platform credibility and network latency, respectively, and the weight parameters satisfy... .

5. The automated testing system for collaborative testing of manned and unmanned platforms as described in claim 4, characterized in that, In step 4, the reliability evaluation of the test results involves the reliability values ​​of the execution effect of key sub-processes. The reliability values ​​of the execution effect of key sub-processes are affected by both network factors and the execution results of each sub-process. In order to comprehensively consider these two factors, two evaluation methods are adopted: the barrel principle and weighted calculation.

6. The automated testing system for collaborative testing of manned and unmanned platforms as described in claim 5, characterized in that, In step 4, the evaluation method of the "barrel principle" is based on the idea of ​​"shortest plank", that is, in multiple sub-processes, the test system takes the lowest reliability score as the reliability of the sub-process execution result of the overall task. The evaluation formula is as follows: Assuming there are n sub-processes, the execution reliability of each sub-process i is... Values ​​range from 0 to 1; based on network quality factor. This indicates the impact of network latency and bandwidth on task execution, ranging from 0 to 1, where 0 represents poor and 1 represents excellent. , Indicates network latency; Reliability value of the execution result of the key sub-process .

7. The automated testing system for collaborative manned and unmanned platforms as described in claim 6, characterized in that, In step 4, the weighted evaluation method is to comprehensively score each sub-process based on its importance (i.e., weight) and network quality, to more flexibly reflect the contribution of each sub-process to the overall task reliability; the weight t of each sub-process... i Based on their criticality to the overall test task, sub-processes with higher weights have a greater impact on the final reliability score; assuming there are n sub-processes, and the execution reliability value of each sub-process is... Values ​​range from 0 to 1, with corresponding weights of 0 and 1. The network quality factor is ; Reliability values ​​of the execution results of key sub-processes: 。 8. The automated testing system for collaborative manned and unmanned platforms as described in claim 7, characterized in that, The test result reliability algorithm calculates the reliability based on the execution result reliability of key sub-processes and the data reliability hysteresis value: ;in This is the reliable value of the execution result of the key sub-process. Select the appropriate method according to the actual needs and substitute the corresponding calculation result value. , These are the weights of the execution result reliability value and the data reliability hysteresis value of the key sub-process, respectively, and the weight parameters satisfy... .

9. The automated testing system for collaborative testing of manned and unmanned platforms as described in claim 8, characterized in that, When using the barrel principle for evaluation, the aforementioned Using R t1 The value; When using a weighted evaluation method, the aforementioned Using R t2 The value of .

10. The automated testing system for collaborative manned and unmanned platforms as described in claim 9, characterized in that, The architecture of the testing system is as follows: (1) Data layer: used to store protocol data and configuration test task data information; (2) Business layer: including status monitoring module, test module and configuration management module; the status monitoring module processes the status information of protocol data, and determines whether the node is online and whether there is any abnormality; The testing module performs automated testing and assesses the reliability of the test results; the configuration management module includes data status configuration and test task and sub-process configuration, providing configuration input and management functions for test information and process information. (3) Presentation layer: The presentation layer consists of status monitoring, testing and configuration management. It displays the status information of the test through the page and provides the function of inputting and displaying interface information.

Images