Vehicle-mounted central control performance test method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention relates to the technical field of vehicles, and discloses a vehicle-mounted central control performance test method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring vehicle behavior data, external scene data and user use data; constructing a self-vehicle behavior model based on the pre-processed self-vehicle behavior data; constructing an external scene model based on the preprocessed external scene data; constructing a user portrait based on the preprocessed user usage data; and generating a vehicle-mounted central control performance test task based on the vehicle behavior model, the external scene model and the user portrait so as to complete the test of the vehicle-mounted central control performance. According to the method, the vehicle behavior data, the external scene data and the user use data are combined to generate the vehicle-mounted central control performance test task, so that the real use scene of the user can be effectively simulated, the comprehensiveness of the test is improved, and the test accuracy is improved.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, and in particular to a method, apparatus, electronic device, and storage medium for testing the performance of an in-vehicle central control system. Background Technology

[0002] Currently, in-vehicle central control system performance testing mostly focuses on the performance indicators of single applications, such as cold / warm start time and operational smoothness. However, these tests are primarily conducted on test benches, lacking real or simulated user scenarios compared to actual user driving. Furthermore, the applications are completely decoupled during testing, while real users typically use multiple applications simultaneously. Therefore, central control system performance testing may fail to accurately identify problems encountered by users during actual use. Summary of the Invention

[0003] The purpose of this invention is to provide a method, device, electronic device, and storage medium for testing the performance of in-vehicle central control systems, so as to at least solve the problems of incomplete testing of in-vehicle central control system performance and the lack of fit between the testing environment and real-world vehicle usage scenarios, thereby improving the comprehensiveness and accuracy of the test.

[0004] To address the aforementioned technical problems, in a first aspect, the present invention provides a method for testing the performance of an in-vehicle central control system, comprising at least:

[0005] Acquire vehicle behavior data, external scenario data, and user usage data;

[0006] A vehicle behavior model is constructed based on the preprocessed vehicle behavior data.

[0007] An external scene model is constructed based on the preprocessed external scene data;

[0008] A user profile is constructed based on the preprocessed user usage data;

[0009] Based on the vehicle behavior model, the external scene model, and the user profile, a vehicle central control performance test task is generated to complete the test of the vehicle central control performance.

[0010] Optionally, constructing a vehicle behavior model based on the preprocessed vehicle behavior data specifically includes:

[0011] Perform preprocessing operations on the vehicle behavior data to generate at least standard vehicle data;

[0012] The standard autonomous vehicle data is classified based on the autonomous vehicle behavior data category to decompose the standard autonomous vehicle data into at least multiple autonomous vehicle data modules.

[0013] The autonomous vehicle behavior model is constructed based on at least all of the aforementioned autonomous vehicle data modules.

[0014] Optionally, constructing an external scene model based on the preprocessed external scene data specifically includes:

[0015] Perform preprocessing operations on the external scene data to generate at least standard scene data;

[0016] The external scene model is constructed based at least on the standard scene data.

[0017] Optionally, the step of constructing a user profile based on the preprocessed user usage data specifically includes:

[0018] Perform preprocessing operations on the user data to generate at least standard user data;

[0019] Extract user usage information of the in-vehicle central control application from the standard user data to at least determine the user's usage frequency and habits of the in-vehicle central control application;

[0020] User profiles are constructed based on the frequency of use and the usage habits.

[0021] Optionally, the step of generating an in-vehicle central control performance test task based on the vehicle behavior model, the external scene model, and the user profile to complete the test of the in-vehicle central control performance specifically includes:

[0022] Based on the user profile, the vehicle behavior chain is obtained through the vehicle behavior model;

[0023] Based on the user profile, the test scenario is obtained through the external scenario model;

[0024] Based on the vehicle behavior chain and the test scenario, an in-vehicle central control performance test task is generated to complete the test of the in-vehicle central control performance.

[0025] Optionally, after generating the in-vehicle central control performance test task based on the vehicle behavior model, the external scene model, and the user profile to complete the test of the in-vehicle central control performance, the method further includes:

[0026] Based on the test results of the vehicle central control system performance, a test result report is generated and uploaded to the tester via a preset communication method.

[0027] Optionally, the test result report may include at least one of the following: application startup time, resource usage, memory management, application smoothness, and network performance.

[0028] Secondly, the present invention also provides an in-vehicle central control performance testing device, comprising at least:

[0029] The information acquisition module is used to acquire vehicle behavior data, external scene data, and user usage data.

[0030] The first processing module is used to construct a vehicle behavior model based on the preprocessed vehicle behavior data.

[0031] The second processing module is used to construct an external scene model based on the preprocessed external scene data.

[0032] The third processing module is used to construct a user profile based on the preprocessed user usage data.

[0033] The performance testing module is used to generate in-vehicle central control performance testing tasks based on the vehicle behavior model, the external scene model, and the user profile, so as to complete the testing of the in-vehicle central control performance.

[0034] Thirdly, the present invention also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program executable on the processor, characterized in that the processor executes the program to implement the steps in the vehicle central control performance testing method according to any one of the first aspects.

[0035] Fourthly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the steps in the vehicle central control performance testing method according to any one of the first aspects.

[0036] The technical solution provided by this invention first acquires vehicle behavior data, external scene data, and user usage data; second, it constructs a vehicle behavior model based on the preprocessed vehicle behavior data; third, it constructs an external scene model based on the preprocessed external scene data; then, it constructs a user profile based on the preprocessed user usage data; finally, it generates an in-vehicle central control performance test task based on the vehicle behavior model, external scene model, and user profile to complete the test of the in-vehicle central control performance.

[0037] Therefore, this invention, on the one hand, combines vehicle behavior data, external scene data, and user usage data to generate in-vehicle central control performance test tasks, effectively simulating real-world user scenarios, thus improving the comprehensiveness and accuracy of the test. On the other hand, by constructing vehicle behavior models and external scene models, this invention provides substantial data support for subsequent test task generation, improving testing efficiency and reducing testing costs. Attached Figure Description

[0038] Figure 1 This is a flowchart of a vehicle central control performance testing method provided by an embodiment of the present invention;

[0039] Figure 2 This is a flowchart of another in-vehicle central control performance testing method provided by an embodiment of the present invention;

[0040] Figure 3 This is a schematic diagram of the structure of an in-vehicle central control performance testing device provided in an embodiment of the present invention;

[0041] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0043] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to limit the application. The singular forms “a,” “said,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0044] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0045] It should be understood that although the terms first, second, third, etc., may be used in the embodiments of this application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, first may also be referred to as second without departing from the scope of the embodiments of this application, and similarly, second may also be referred to as first.

[0046] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”

[0047] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that an article or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such an article or device. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or device that includes said element.

[0048] It should be noted that any symbols and / or numbers present in the specification that are not marked in the accompanying drawings are not reference numerals.

[0049] Figure 1 This is a flowchart of a vehicle central control performance testing method provided by an embodiment of the present invention. This embodiment is applicable to at least various vehicle central control performance testing scenarios. The vehicle central control performance testing method can be, but is not limited to, executed by the vehicle central control performance testing device in this embodiment of the present invention as the execution subject. This execution subject can be implemented in software and / or hardware. Figure 1 As shown, the in-vehicle central control system performance testing method includes at least the following steps:

[0050] S1. Acquire vehicle behavior data, external scene data, and user usage data.

[0051] The vehicle behavior data can include user operation data and vehicle status data during vehicle use. Examples include power status, vehicle speed status, and the status of the four doors and two hoods (i.e., the four doors, engine hood, and trunk lid). Power status can be ACC, ON, OFF, or CRANK (voltage drop at startup). Vehicle speed status can be the vehicle speed and acceleration status during user use. Vehicle speed can be used to simulate urban congestion, high-speed cruising, and rapid acceleration / deceleration. Acceleration status reflects driving smoothness. It is known that opening the four doors and two hoods can trigger changes in system load (such as audio switching or screen brightness adjustment).

[0052] External scene data can include static environmental data, dynamic traffic data, climate environmental data, and network environmental data. Static environmental data can include overpasses, tunnels, and underground parking garages. Dynamic traffic data can include instances of vehicles cutting in front, vehicles following behind, traffic light recognition, and navigation lane changes. Climate environmental data can include weather conditions, such as rain or sunshine. Network environmental data can include network status.

[0053] User usage data can include user operation information for various apps within the vehicle's central control system, such as usage frequency, dwell time, operation path, and usage timestamp. The usage timestamp indicates the exact time the user used the app, such as when a user opened the navigation app at 8:00 AM. User usage data can be obtained through vehicle logs, user surveys, and other methods.

[0054] S2. Construct a vehicle behavior model based on the preprocessed vehicle behavior data.

[0055] The preprocessing here can involve removing user error data, erroneous data, etc., from the vehicle behavior data. In this embodiment, the vehicle behavior model can be any general-purpose large model available on the market, such as a ByteDance large model. When training the vehicle behavior model, the collected vehicle behavior data and user profiles need to be input as training data into the model so that it can associate features between the user profiles and the vehicle behavior data. In subsequent use, only the user profile needs to be used as input data, and the vehicle behavior model can output a series of vehicle behavior data related to the user profile.

[0056] S3. Construct an external scene model based on the preprocessed external scene data.

[0057] This preprocessing can involve removing obviously unreasonable or erroneous data from the external scene data. The external scene data can also be any general-purpose large model available on the market, such as a ByteDance large model. When training the external scene model, the collected external scene data and user profiles need to be input as training data. This allows the model to correlate features between the user profiles and the external scene data. In subsequent use, only the user profile needs to be input data, and the external scene model can output a series of external scene data related to the user profile.

[0058] S4. Build user profiles based on preprocessed user usage data.

[0059] One user profile can refer to a user.

[0060] S5. Generate in-vehicle central control performance test tasks based on the vehicle behavior model, external scene model, and user profile to complete the test of in-vehicle central control performance.

[0061] The in-vehicle central control performance test task can be a set of instruction information for a series of test tasks, which may include information such as scenario description, perception task, target threshold, user unacceptability level, test scenario example, data collection method, and remarks. The perception task can be the task indicator that needs to be acquired or judged under the scenario description. The target threshold can be understood as the optimal range. The data collection method can be the data collection means for the perception task. Remarks can be precautions.

[0062] The technical solution provided in this embodiment first acquires vehicle behavior data, external scene data, and user usage data; second, it constructs a vehicle behavior model based on the preprocessed vehicle behavior data; third, it constructs an external scene model based on the preprocessed external scene data; then, it constructs a user profile based on the preprocessed user usage data; finally, it generates an in-vehicle central control performance test task based on the vehicle behavior model, external scene model, and user profile to complete the test of the in-vehicle central control performance.

[0063] Therefore, this embodiment, on the one hand, combines vehicle behavior data, external scene data, and user usage data to generate in-vehicle central control performance test tasks, effectively simulating real-world user scenarios, thus improving the comprehensiveness and accuracy of the test. On the other hand, by constructing vehicle behavior models and external scene models, this embodiment provides substantial data support for subsequent test task generation, improving testing efficiency and reducing testing costs.

[0064] Based on the above embodiments or implementation methods Figure 2 This is a flowchart of another in-vehicle central control performance testing method provided by an embodiment of the present invention. This embodiment is based on the above embodiment with additions. Figure 2 As shown, the in-vehicle central control system performance testing method includes at least the following steps:

[0065] S1. Acquire vehicle behavior data, external scene data, and user usage data.

[0066] S21. Perform preprocessing operations on the vehicle behavior data to generate at least standard vehicle data.

[0067] S22. Perform a classification operation on the standard vehicle data based on the vehicle behavior data category, so as to decompose the standard vehicle data into at least multiple vehicle data modules.

[0068] Among them, the autonomous vehicle behavior data category is used to classify autonomous vehicle behavior data. The autonomous vehicle behavior data category can include user operation category (such as user shifting gear lever, steering wheel, etc.), system feedback category, vehicle system load status category, etc.

[0069] S23. Construct a vehicle behavior model based on at least all vehicle data modules.

[0070] It is understandable that one user operation category can correspond to one vehicle data module. This embodiment uses a modular model structure to make the maintenance of the vehicle behavior model more convenient. In some scenarios, if a certain type of user operation or system feedback data needs to be optimized or expanded (such as adding a new gear operation mode), only the corresponding vehicle data module needs to be adjusted, without modifying the entire model, effectively reducing the model iteration cost. When using the model, it can flexibly combine the data generated by each module to make the output results closer to actual driving scenarios.

[0071] S31. Perform preprocessing operations on the external scene data to generate at least standard scene data.

[0072] S32. At least build an external scene model based on standard scene data.

[0073] S41. Perform preprocessing operations on user data to generate at least standard user data.

[0074] S42. Extract user usage information of in-vehicle central control applications from standard user data to at least determine the user's usage frequency and habits of in-vehicle central control applications.

[0075] Among them, usage frequency can be the frequency with which a user uses the in-vehicle central control application within a preset time period, and usage habits can be the time a user uses the in-vehicle central control application, or in which scenarios a user habitually opens a specific in-vehicle central control application.

[0076] S43. Build user profiles based on usage frequency and usage habits.

[0077] Table 1 is a user profile data table provided in this embodiment, as shown in Table 1.

[0078] Table 1

[0079]

[0080] S51. Obtain the vehicle behavior chain based on the user profile and the vehicle behavior model.

[0081] The autonomous vehicle behavior chain can be a task list that sorts a series of autonomous vehicle behavior data related to the user profile based on time sequence. For example, first open application A, then open application B a few seconds later, and then exit application A a few minutes later.

[0082] S52. Obtain test scenarios based on user profiles and external scenario models.

[0083] The test scenarios can be environmental data related to the user profile. For example, if the user profile is a ride-hailing driver, the test scenarios configured for them can be early morning, low temperature, long driving time, etc.

[0084] S53. Generate in-vehicle central control performance test tasks based on the vehicle behavior chain and test scenario to complete the test of in-vehicle central control performance.

[0085] The process for testing the performance of the vehicle's central control system can be as follows:

[0086] P01, Scenario Description: During the morning rush hour, after a cold start, immediately open the navigation app to go to work; Perception Task: Navigation cold start time; Target Threshold: No more than 2.5s; User Unacceptability Level: More than 4s; Test Scenario Example: After being stationary at -10°C for eight hours, the engine is started, and then the navigation app is accessed; Data Acquisition Method: Camera and CAN timestamp; Remarks: Includes AGPS download.

[0087] P02, Scenario Description: Slide to find the nearest gas station list; Perception Task: Average frame rate of list sliding; Target Threshold: Not less than 55fps; User Unacceptable Level: Less than 40fps; Test Scenario Example: 50 POI list, slide at a constant speed for 2 screens; Acquisition Method: Screen recording and image analysis; Note: Frame drop ≤ 2.

[0088] P03, Scenario Description: Music continues to play at the tunnel exit; Perception Task: Music interruption duration in weak network conditions; Target Threshold: 0s; User Unacceptability Level: 3s; Test Scenario Example: Network drops to 128kbps / 500ms RTT for 20s; Acquisition Method: Audio loopback and network packet capture; Note: Allow one 0.5s buffer.

[0089] P04, Scenario Description: Say "Call Zhang San" after voice wake-up; Perception Task: Response time of voice wake-up to interface; Target Threshold: No more than 800ms; User Unacceptability Level: 105s; Test Scenario Example: 60dB air conditioning noise, car windows closed; Data Acquisition Method: Microphone trigger and screen brightness sampling; Remarks: Includes ASR first packet return.

[0090] P05, Scenario Description: Receiving a WeChat call while navigating; Perception Task: Navigation stuttering and frame rate drop; Target Threshold: Frame rate drop ≤ 5fps and drop time ≤ 1s; User Unacceptability: 2s stuttering; Test Scenario Example: Navigation, Bluetooth call, and WeChat voice call running concurrently; Data Acquisition Method: Screen recording and CPU / GPU sampling; Remarks: Record whether location is lost.

[0091] P06, Scenario Description: Continuous driving for 2 hours in high summer temperatures; Perception Task: Memory growth after 2 hours; Target Threshold: Growth rate not greater than 10%; User Unacceptability: Growth rate greater than 20%; Test Scenario Example: 8℃ environmental chamber, 4 rounds of cyclical commuting script; Data Collection Method: Temperature and memory monitoring software; Note: Memory will be restored after restart.

[0092] P07, Scenario Description: When starting a vehicle in the underground parking garage, it automatically connects to Wi-Fi; Perception Task: First Wi-Fi connection in the underground parking garage; Target Threshold: Connection latency no more than 10 seconds; User Unacceptable Level: Connection latency greater than 20 seconds; Test Scenario Example: Underground parking garage Wi-Fi signal -70 dBm, high DHCP latency; Data Acquisition Method: Network logs and packet capture; Remarks: Includes Portal authentication.

[0093] P08, Scenario Description: One-click exit of reversing camera; Perception Task: Homepage response latency when reversing camera exits; Target Threshold: Latency not greater than 500ms; User Unacceptable Level: Connection latency greater than 1s; Test Scenario Example: In R gear and shift to N gear, record the homepage appearance time; Acquisition Method: Camera; Note: Black frames are prohibited.

[0094] S6. Based on the test results of the vehicle central control performance, generate a test result report and upload the test result report to the tester through a preset communication method.

[0095] The preset communication method can be email, SMS, or other similar methods. In one specific implementation, the test result report may optionally include at least one of the following: application startup time, resource usage, memory management, application smoothness, and network performance.

[0096] The technical solution provided in this embodiment first acquires vehicle behavior data, external scene data, and user usage data. Further, it performs preprocessing operations on the vehicle behavior data to generate at least standard vehicle data. Further, it performs classification operations on the standard vehicle data based on vehicle behavior data categories to decompose the standard vehicle data into at least multiple vehicle data modules. Further, it constructs a vehicle behavior model based on at least all vehicle data modules. Further, it performs preprocessing operations on the external scene data to generate at least standard scene data. Further, it constructs an external scene model based on at least the standard scene data. Further, it performs preprocessing operations on the user usage data to generate at least standard user data. Further, it extracts user usage information for in-vehicle central control applications from the standard user data to determine at least the user's usage frequency and habits for the in-vehicle central control applications. Further, it constructs a user profile based on the usage frequency and habits. Further, it obtains the vehicle behavior chain based on the user profile and the vehicle behavior model. Further, it obtains test scenarios based on the user profile and the external scene model. Furthermore, based on the vehicle behavior chain and test scenario, an in-vehicle central control performance test task is generated to complete the test of the in-vehicle central control performance. Finally, based on the test results of the in-vehicle central control performance, a test result report is generated and uploaded to the testers through a preset communication method.

[0097] Therefore, this embodiment, on the one hand, combines vehicle behavior data, external scene data, and user usage data to generate in-vehicle central control performance test tasks, effectively simulating real-world user scenarios, thus improving the comprehensiveness and accuracy of the test. On the other hand, by constructing vehicle behavior models and external scene models, this embodiment provides substantial data support for subsequent test task generation, improving testing efficiency and reducing testing costs.

[0098] Figure 3 This is a schematic diagram of the structure of an in-vehicle central control performance testing device provided in an embodiment of the present invention. This embodiment is applicable to at least various in-vehicle central control performance testing scenarios, and the in-vehicle central control performance testing device can be implemented using software and / or hardware. Figure 3 As shown, the in-vehicle central control performance testing device includes at least:

[0099] The information acquisition module 110 is used to acquire vehicle behavior data, external scene data, and user usage data.

[0100] The first processing module 120 is used to construct a vehicle behavior model based on the preprocessed vehicle behavior data.

[0101] The second processing module 130 is used to construct an external scene model based on the preprocessed external scene data.

[0102] The third processing module 140 is used to build user profiles based on preprocessed user usage data.

[0103] The performance testing module 150 is used to generate in-vehicle central control performance test tasks based on the vehicle behavior model, external scene model and user profile, so as to complete the test of the in-vehicle central control performance.

[0104] Optionally, the first processing module 120 is specifically used for:

[0105] Perform preprocessing operations on the vehicle behavior data to generate at least standard vehicle data; and perform classification operations on the standard vehicle data based on the vehicle behavior data categories to decompose the standard vehicle data into at least multiple vehicle data modules; and construct a vehicle behavior model based at least on all vehicle data modules.

[0106] Optionally, the second processing module 130 is specifically used for:

[0107] Perform preprocessing operations on the external scene data to generate at least standard scene data; and construct an external scene model based at least on the standard scene data.

[0108] Optionally, the third processing module 140 is specifically used for:

[0109] Perform preprocessing operations on user data to generate at least standard user data; extract user usage information of in-vehicle central control applications from the standard user data to at least determine the user's usage frequency and habits of in-vehicle central control applications; and construct user profiles based on usage frequency and habits.

[0110] Optionally, the performance testing module 150 is specifically used for:

[0111] Based on user profiles, a vehicle behavior chain is obtained through a vehicle behavior model; and based on user profiles, a test scenario is obtained through an external scenario model; and based on the vehicle behavior chain and the test scenario, an in-vehicle central control performance test task is generated to complete the test of the in-vehicle central control performance.

[0112] Optionally, it also includes:

[0113] The report upload module 160 is used to generate a test result report based on the test results of the vehicle central control performance and upload the test result report to the tester through a preset communication method.

[0114] Optionally, the test results report should include at least one of the following: application startup time, resource usage, memory management, application smoothness, and network performance.

[0115] The technical solution provided in this embodiment first acquires vehicle behavior data, external scene data, and user usage data through an information acquisition module. Further, a first processing module constructs a vehicle behavior model based on the preprocessed vehicle behavior data. Further, a second processing module constructs an external scene model based on the preprocessed external scene data. Further, a third processing module constructs a user profile based on the preprocessed user usage data. Finally, a performance testing module generates an in-vehicle central control performance test task based on the vehicle behavior model, external scene model, and user profile to complete the testing of the in-vehicle central control performance.

[0116] Therefore, this embodiment, on the one hand, combines vehicle behavior data, external scene data, and user usage data to generate in-vehicle central control performance test tasks, effectively simulating real-world user scenarios, thus improving the comprehensiveness and accuracy of the test. On the other hand, by constructing vehicle behavior models and external scene models, this embodiment provides substantial data support for subsequent test task generation, improving testing efficiency and reducing testing costs.

[0117] This embodiment provides an electronic device. Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. See also: Figure 4The electronic device 1000 includes a processor 1001 and a memory 1002. The memory 1002 stores computer-readable instructions. When the computer-readable instructions are executed by the processor 1001, the steps in any of the above-described vehicle central control performance testing methods are performed. Through the above technical solution, the processor 1001 and the memory 1002 are interconnected and communicate with each other via a communication bus and / or other forms of connection mechanisms (not shown). The memory 1002 stores a processor-executable computer program. When the electronic device 1000 is running, the processor 1001 executes the computer program to perform the vehicle central control performance testing method in any of the optional implementations of the above embodiments, to at least achieve the following functions: acquiring vehicle behavior data, external scene data, and user usage data; constructing a vehicle behavior model based on preprocessed vehicle behavior data; constructing an external scene model based on preprocessed external scene data; constructing a user profile based on preprocessed user usage data; and generating a vehicle central control performance testing task based on the vehicle behavior model, external scene model, and user profile to complete the testing of the vehicle central control performance.

[0118] This embodiment provides a computer-readable storage medium storing a computer program thereon. When executed by a processor, the program implements the vehicle central control performance testing method provided in all embodiments of this application: acquiring vehicle behavior data, external scene data, and user usage data; constructing a vehicle behavior model based on preprocessed vehicle behavior data; constructing an external scene model based on preprocessed external scene data; constructing a user profile based on preprocessed user usage data; and generating a vehicle central control performance testing task based on the vehicle behavior model, external scene model, and user profile to complete the testing of vehicle central control performance.

[0119] Any combination of one or more computer-readable media may be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0120] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including—but not limited to—electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of transmitting, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0121] The program code contained on a computer-readable medium may be transmitted using any suitable medium, including—but not limited to—wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0122] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, and C++—as well as conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0123] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for testing the performance of an in-vehicle central control system, characterized in that, At least including: Acquire vehicle behavior data, external scenario data, and user usage data; A vehicle behavior model is constructed based on the preprocessed vehicle behavior data. An external scene model is constructed based on the preprocessed external scene data; A user profile is constructed based on the preprocessed user usage data; Based on the vehicle behavior model, the external scene model, and the user profile, a vehicle central control performance test task is generated to complete the test of the vehicle central control performance.

2. The vehicle central control performance testing method according to claim 1, characterized in that, The construction of the vehicle behavior model based on the preprocessed vehicle behavior data specifically includes: Perform preprocessing operations on the vehicle behavior data to generate at least standard vehicle data; The standard autonomous vehicle data is classified based on the autonomous vehicle behavior data category to decompose the standard autonomous vehicle data into at least multiple autonomous vehicle data modules. The autonomous vehicle behavior model is constructed based on at least all of the aforementioned autonomous vehicle data modules.

3. The vehicle central control performance testing method according to claim 1, characterized in that, The construction of the external scene model based on the preprocessed external scene data specifically includes: Perform preprocessing operations on the external scene data to generate at least standard scene data; The external scene model is constructed based at least on the standard scene data.

4. The vehicle central control performance testing method according to claim 1, characterized in that, The process of constructing a user profile based on the preprocessed user usage data specifically includes: Perform preprocessing operations on the user data to generate at least standard user data; Extract user usage information of the in-vehicle central control application from the standard user data to at least determine the user's usage frequency and habits of the in-vehicle central control application; User profiles are constructed based on the frequency of use and the usage habits.

5. The vehicle central control performance testing method according to claim 1, characterized in that, The process of generating in-vehicle central control performance test tasks based on the vehicle behavior model, the external scene model, and the user profile to complete the testing of in-vehicle central control performance specifically includes: Based on the user profile, the vehicle behavior chain is obtained through the vehicle behavior model; Based on the user profile, the test scenario is obtained through the external scenario model; Based on the vehicle behavior chain and the test scenario, an in-vehicle central control performance test task is generated to complete the test of the in-vehicle central control performance.

6. The vehicle central control performance testing method according to claim 1, characterized in that, After generating the in-vehicle central control performance test task based on the vehicle behavior model, the external scene model, and the user profile to complete the test of the in-vehicle central control performance, the method further includes: Based on the test results of the vehicle central control system performance, a test result report is generated and uploaded to the tester via a preset communication method.

7. The vehicle central control performance testing method according to claim 1, characterized in that, The test result report shall include at least one of the following: application startup time, resource usage, memory management, application smoothness, and network performance.

8. A vehicle-mounted central control performance testing device, characterized in that, At least including: The information acquisition module is used to acquire vehicle behavior data, external scene data, and user usage data. The first processing module is used to construct a vehicle behavior model based on the preprocessed vehicle behavior data. The second processing module is used to construct an external scene model based on the preprocessed external scene data. The third processing module is used to construct a user profile based on the preprocessed user usage data. The performance testing module is used to generate in-vehicle central control performance testing tasks based on the vehicle behavior model, the external scene model, and the user profile, so as to complete the testing of the in-vehicle central control performance.

9. An electronic device comprising a memory and a processor, the memory storing a computer program executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the vehicle central control performance testing method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps in the vehicle central control performance testing method according to any one of claims 1 to 7.

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