Automobile instrument lamp position function priority display test method and terminal

Abstract

The invention discloses an automobile instrument lamp position function priority display test method and terminal, and belongs to the technical field of automobile instruments, and the method comprises the steps: obtaining a test case, and simulating a test scene through virtual instrument panel simulation software; respectively executing automobile instrument lamp position function priority display test scenes according to the test cases, acquiring a plurality of test result images, preprocessing the plurality of test result images, and respectively analyzing test results through an optimal machine learning model. According to the method and the device, various types of indicator lights on the instrument panel of the vehicle need to be displayed according to a certain priority rule, so that a driver can quickly notice the most important information, and the driving safety and the user experience are improved.

Description

Technical Field

[0001] The invention discloses a method and a terminal for displaying and testing the priority of a light position function of an automobile instrument, and belongs to the technical field of automobile instruments. Background Art

[0002] As the number of ECUs (Electronic Control Units, also known as "driving computers", "on-board computers", etc.) and the number of lines of code on cars are increasing day by day, the complexity of the entire automotive system is also increasing, and the instrument system and the central control system are also divided into independent control systems and integrated partition control systems. Functional safety has become an issue that cannot be ignored. When users use their vehicles, various fault icons often appear, but users rarely understand the meaning of these icons. Except for car model designers or maintenance personnel who often repair cars, the meaning of common icons is very necessary for users' driving safety. Otherwise, we continue to drive when the fault light is on, which not only damages our vehicles, but also poses a great risk to user safety.

[0003] Since the vehicle fault lights are complicated and have priority processing, users will not understand the display logic behind them even after purchasing the vehicle. During the test process, testers need to match the requirements of the requirements when testing a fault light or display light, which not only increases the cost and time of the project operation, but also requires designers to understand the cause of the problem after knowing the fault. After this fault phenomenon occurs, the workload for both testers and designers is huge, and there is currently no automated method to complete this work. Summary of the invention

[0004] In view of the defects of the prior art, the present invention proposes a method and terminal for testing the functional priority display of automobile instrument light positions, so as to solve the display priority management problem of indicator lights in an automobile instrument panel display system.

[0005] The technical solution of the present invention is as follows:

[0006] According to a first aspect of an embodiment of the present invention, a function priority display test method is provided, comprising:

[0007] Obtain test cases and use virtual dashboard simulation software to simulate test scenarios;

[0008] According to the test cases, the automobile instrument light function priority display test scenarios are respectively executed to obtain multiple test result images, and the multiple test result images are preprocessed to analyze the test results respectively through the optimal machine learning model.

[0009] Preferably, before obtaining the test case, the method further includes:

[0010] Obtain historical images of automobile instrument light positions when activated, and perform preprocessing and data annotation on them to obtain an automobile instrument light position training dataset;

[0011] Construct a machine learning model, and use the automobile instrument light position training data set to train the machine learning model to obtain the optimal machine learning model.

[0012] Preferably, the test cases include: common indicator light display, functional safety light display and test scenarios.

[0013] Preferably, the common indicator light display includes at least: vehicle speed display, gear position indication, turn signal, fuel level indication and charging status, and the functional safety light display includes at least: seat belt unfastened indicator light, brake system fault light, door ajar warning light and engine fault light.

[0014] Preferably, the test scenarios include: displaying only common indicator lights, displaying several common indicator lights and functional safety lights at the same time, displaying functional safety lights when all common indicator light positions are occupied, and displaying high-priority functional safety lights and low-priority common indicator lights at the same time.

[0015] Preferably, the simulating the test scenario using the virtual instrument panel simulation software includes: using the virtual instrument panel simulation software to set different light states through an API or a control interface, and checking display priority.

[0016] Preferably, the preprocessing includes: cropping and adjusting the image according to the instrument panel area, identifying and segmenting the area of ​​each indicator light to obtain a plurality of light position area images.

[0017] Preferably, the data labeling includes: marking the correct light position status for each light position area image.

[0018] Preferably, the step of using the automobile instrument light position training data set to train the machine learning model to obtain the best machine learning model includes:

[0019] The images of multiple light areas with correct light status marks are set as the input of the machine learning model, and the indicator light status and indicator light type are set as the output of the machine learning model to train the machine learning model and obtain the optimal machine learning model.

[0020] According to a second aspect of an embodiment of the present invention, a terminal is provided, including:

[0021] one or more processors;

[0022] a memory for storing the one or more processor-executable instructions;

[0023] Wherein, the one or more processors are configured to:

[0024] Execute the method described in the first aspect of the embodiment of the present invention.

[0025] According to a third aspect of an embodiment of the present invention, a non-transitory computer-readable storage medium is provided. When instructions in the storage medium are executed by a processor of a terminal, the terminal is enabled to execute the method described in the first aspect of the embodiment of the present invention.

[0026] According to a fourth aspect of an embodiment of the present invention, an application product is provided. When the application product is running on a terminal, the terminal executes the method described in the first aspect of the embodiment of the present invention.

[0027] The beneficial effects of the present invention are:

[0028] The present invention provides a method and a terminal for testing the functional priority display of automobile instrument light positions. The method obtains test cases, uses virtual instrument panel simulation software to simulate test scenarios, executes automobile instrument light functional priority display test scenarios respectively according to the test cases, obtains multiple test result images, pre-processes the multiple test result images, and analyzes the test results respectively through an optimal machine learning model, so that various types of indicator lights on the vehicle's instrument panel need to be displayed according to certain priority rules, so as to ensure that the driver can quickly notice the most important information, thereby improving driving safety and user experience.

[0029] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 The present invention is a flow chart showing a method for testing the priority display of a vehicle instrument light function according to an exemplary embodiment.

[0031] Figure 2 The present invention is a schematic block diagram of a terminal structure according to an exemplary embodiment. DETAILED DESCRIPTION

[0032] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] In the description of the present invention, it should be noted that the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside", etc. indicate directions or positional relationships based on the directions or positional relationships shown in the accompanying drawings. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction. Therefore, they cannot be understood as limitations on the present invention.

[0034] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0035] An embodiment of the present invention provides a method for testing the priority display of a vehicle instrument light function. The method is implemented by a terminal, which may be a desktop computer or a notebook computer, etc. The terminal at least includes a CPU, etc.

[0036] Embodiment 1

[0037] Figure 1 The present invention is a flow chart of a method for testing the priority display of a vehicle instrument light position function according to an exemplary embodiment. The method is used in a terminal and includes the following steps:

[0038] Step 101, obtain test cases and use virtual dashboard simulation software to simulate test scenarios. The specific contents are as follows:

[0039] Before obtaining the test case, this embodiment also includes the following steps:

[0040] Obtain historical images of vehicle instrument light positions when activated, preprocess and annotate them to obtain a vehicle instrument light position training dataset. Build a machine learning model, and use the vehicle instrument light position training dataset to train the machine learning model to obtain the best machine learning model.

[0041] The historical images of automobile instrument lights activated include: taking images of different commonly used indicator lights when activated, and marking the display position of each light (for example, fuel level light, turn signal, handbrake light, etc.) and images of various functional safety lights when they are on. The preprocessing step is to crop and adjust the collected original image according to the dashboard area to ensure that only the light area of ​​the dashboard is retained, reduce interference information, and segment the area of ​​each indicator light to ensure that the position of each indicator light can be accurately located. Data annotation: Mark the correct light status (on / off) for each collected training image, and mark which are commonly used indicator lights and which are functional safety lights.

[0042] The brightness and color information of each light area is then extracted through the machine learning model. By analyzing the pixel changes (brightness changes and color changes) in the image, it is determined whether the light is in an activated state. Common indicator lights usually have fixed colors and brightness (such as red for the fuel level light and yellow for the turn signal light), and these features can be extracted through the color histogram analysis of the image. Functional safety lights usually have different colors and display modes (such as red or yellow flashing lights), so features can also be extracted in a similar way. Then, the images of multiple light areas with the correct light status marked are set as the input of the machine learning model, and the indicator light status and indicator light type are set as the output of the machine learning model to train the machine learning model to obtain the best machine learning model.

[0043] Get test cases, which include: common indicator light display, functional safety light display and test scenarios, where:

[0044] Common indicator lights include at least: vehicle speed display, gear position indicator, turn signal, fuel level indicator and charging status;

[0045] Functional safety lights include at least: seat belt unfastened indicator light, brake system fault light, door ajar warning light and engine fault light;

[0046] The test scenarios include: displaying only common indicator lights, displaying several common indicator lights and functional safety lights at the same time, displaying functional safety lights when all common indicator light positions are occupied, and displaying high-priority functional safety lights and low-priority common indicator lights at the same time.

[0047] Use virtual dashboard simulation software to simulate test scenarios, including: Use virtual dashboard simulation software, select software that supports dashboard simulation, such as CANoe, dSPACE and other tools, or custom simulation software developed based on vehicle-mounted systems. Set different light states through API or control interface, API interface configuration: Write control scripts to activate different indicator lights through the software's API interface (such as RESTfulAPI, TCP / IP interface, etc.) or programming control interface. Light position activation instructions: Each indicator light (common indicator light and functional safety light) needs to have clear activation and shutdown instructions, and support batch activation to simulate complex scenarios.

[0048] Display status monitoring: Set the monitoring function to record the display status (on / off) of each light and the order of the light positions in real time.

[0049] Check the display priority and priority rule configuration: Configure the priority rules of the light positions according to your needs, ensure that the commonly used indicator lights have a higher display priority, and the functional safety lights will use the D1 position for polling display when there is no free position. In this way, by displaying the relationship between the light position and the priority, you can see whether the display light position meets the priority definition.

[0050] Step 102, respectively executing the automobile instrument light position function priority display test scenes according to the test case, obtaining multiple test result images, preprocessing the multiple test result images, and respectively analyzing the test results through the optimal machine learning model. The specific steps are as follows:

[0051] According to the test cases, the car instrument light position function priority display test scenarios are executed respectively, and the specific contents are as follows:

[0052] 1. Execute the display of only common indicators: Activate the common indicators and observe the dashboard display to ensure that all common indicators are displayed correctly and no functional safety lights are displayed. According to the functions and corresponding signals in the test scenario, use the model to judge whether all common indicators are displayed by the display light positions on the screen.

[0053] 2. Execute simultaneous display of several common indicator lights and functional safety lights: Activate some common indicator lights and a small number of functional safety lights. Confirm that the common indicator lights are displayed first, and the functional safety lights are displayed only when the common indicator lights are idle. According to the functions and corresponding signals in the test scenario, use the display light position on the screen to judge with the model whether the functional safety lights are displayed only when the common indicator lights are idle.

[0054] 3. Execute the display of functional safety lights while all common indicator positions are occupied: Activate all common indicator positions and simulate the activation of functional safety lights. Ensure that the functional safety lights are polled and displayed using the D1 position. According to the functions and corresponding signals in the test scenario, use the model to judge through the display light positions on the screen to see whether the functional safety lights are only polled at the D1 position, and the common lights are normally displayed at the common light positions and are not polled at the D1 position.

[0055] 4. Execute the simultaneous display of high-priority functional safety lights and low-priority common indicators: Activate a high-priority functional safety light and a low-priority common indicator. Confirm that the high-priority functional safety light is displayed first or covers the low-priority common indicator. Use the display light position on the screen, the model and priority definition to determine whether the high-priority indicator lights are normally covered when different priority indicators are displayed.

[0056] Acquire multiple test result images, preprocess the multiple test result images, and analyze the test results separately through the best machine learning model. The above preprocessing is to crop and adjust the original image collected according to the dashboard area to ensure that only the light area of ​​the dashboard is retained, reduce interference information, and segment the area of ​​each indicator light to ensure that the position of each indicator light can be accurately located. The best machine learning model analyzes the test results separately and displays any abnormalities or unexpected behaviors found. If it is found that the priority display does not meet the set rules, feedback the problem to the development team and suggest improvements.

[0057] Embodiment 2

[0058] Figure 2 2 is a block diagram of a terminal provided in an embodiment of the present application, and the terminal may be a terminal in the above embodiment. The terminal 200 may be a portable mobile terminal, such as a smart phone or a tablet computer. The terminal 200 may also be referred to as a user equipment, a portable terminal, or other names.

[0059] Typically, the terminal 200 includes a processor 201 and a memory 202 .

[0060] The processor 201 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 201 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), and PLA (Programmable Logic Array). The processor 201 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 201 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 201 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0061] The memory 202 may include one or more computer-readable storage media, which may be tangible and non-transitory. The memory 202 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 202 is used to store at least one instruction, which is used to be executed by the processor 201 to implement a vehicle instrument light position function priority display test method provided in this application.

[0062] In some embodiments, the terminal 200 may further include: a peripheral device interface 203 and at least one peripheral device. Specifically, the peripheral device includes: at least one of a radio frequency circuit 204 , a touch display screen 205 , a camera 206 , an audio circuit 207 , a positioning component 208 and a power supply 209 .

[0063] The peripheral device interface 203 may be used to connect at least one peripheral device related to I / O (Input / Output) to the processor 201 and the memory 202. In some embodiments, the processor 201, the memory 202, and the peripheral device interface 203 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 201, the memory 202, and the peripheral device interface 203 may be implemented on a separate chip or circuit board, which is not limited in this embodiment.

[0064] The radio frequency circuit 204 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 204 communicates with the communication network and other communication devices through electromagnetic signals. The radio frequency circuit 204 converts the electrical signal into an electromagnetic signal for transmission, or converts the received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 204 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, etc. The radio frequency circuit 204 can communicate with other terminals through at least one wireless communication protocol. The wireless communication protocol includes but is not limited to: the World Wide Web, a metropolitan area network, an intranet, various generations of mobile communication networks (2G, 3G, 4G and 5G), a wireless local area network and / or a WiFi (Wireless Fidelity) network. In some embodiments, the radio frequency circuit 204 may also include circuits related to NFC (Near Field Communication), which is not limited in this application.

[0065] The touch display screen 205 is used to display the UI (User Interface). The UI may include graphics, text, icons, videos and any combination thereof. The touch display screen 205 also has the ability to collect touch signals on the surface or above the surface of the touch display screen 205. The touch signal can be input to the processor 201 as a control signal for processing. The touch display screen 205 is used to provide virtual buttons and / or virtual keyboards, also known as soft buttons and / or soft keyboards. In some embodiments, the touch display screen 205 can be one, and the front panel of the terminal 200 is set; in other embodiments, the touch display screen 205 can be at least two, which are respectively set on different surfaces of the terminal 200 or are folded; in some other embodiments, the touch display screen 205 can be a flexible display screen, which is set on the curved surface or folded surface of the terminal 200. Even, the touch display screen 205 can also be set to a non-rectangular irregular shape, that is, a special-shaped screen. The touch display screen 205 can be made of materials such as LCD (Liquid Crystal Display) and OLED (Organic Light-Emitting Diode).

[0066] The camera assembly 206 is used to capture images or videos. Optionally, the camera assembly 206 includes a front camera and a rear camera. Typically, the front camera is used to realize video calls or selfies, and the rear camera is used to realize the shooting of photos or videos. In some embodiments, there are at least two rear cameras, which are any one of a main camera, a depth of field camera, and a wide-angle camera, so as to realize the fusion of the main camera and the depth of field camera to realize the background blur function, and the fusion of the main camera and the wide-angle camera to realize panoramic shooting and VR (Virtual Reality) shooting functions. In some embodiments, the camera assembly 206 may also include a flash. The flash can be a monochrome temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm light flash and a cold light flash, which can be used for light compensation at different color temperatures.

[0067] The audio circuit 207 is used to provide an audio interface between the user and the terminal 200. The audio circuit 207 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, and convert the sound waves into electrical signals and input them into the processor 201 for processing, or input them into the radio frequency circuit 204 to achieve voice communication. For the purpose of stereo acquisition or noise reduction, there may be multiple microphones, which are respectively arranged at different parts of the terminal 200. The microphone may also be an array microphone or an omnidirectional acquisition microphone. The speaker is used to convert the electrical signal from the processor 201 or the radio frequency circuit 204 into sound waves. The speaker may be a traditional film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can not only convert the electrical signal into sound waves audible to humans, but also convert the electrical signal into sound waves inaudible to humans for purposes such as ranging. In some embodiments, the audio circuit 207 may also include a headphone jack.

[0068] The positioning component 208 is used to locate the current geographical location of the terminal 200 to implement navigation or LBS (Location Based Service).

[0069] The power supply 209 is used to power various components in the terminal 200. The power supply 209 can be an alternating current, a direct current, a disposable battery, or a rechargeable battery. When the power supply 209 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery charged through a wired line, and a wireless rechargeable battery is a battery charged through a wireless coil. The rechargeable battery can also be used to support fast charging technology.

[0070] In some embodiments, the terminal 200 further includes one or more sensors 210 , including but not limited to: an acceleration sensor 211 , a gyroscope sensor 212 , a pressure sensor 213 , a fingerprint sensor 214 , an optical sensor 215 , and a proximity sensor 216 .

[0071] The acceleration sensor 211 can detect the magnitude of acceleration on the three coordinate axes of the coordinate system established by the terminal 200. For example, the acceleration sensor 211 can be used to detect the components of gravity acceleration on the three coordinate axes. The processor 201 can control the touch display screen 205 to display the user interface in a horizontal view or a vertical view according to the gravity acceleration signal collected by the acceleration sensor 211. The acceleration sensor 211 can also be used for collecting game or user motion data.

[0072] The gyro sensor 212 can detect the body direction and rotation angle of the terminal 200. The gyro sensor 212 can cooperate with the acceleration sensor 211 to collect the user's 3D (3 Dimensions) action on the terminal 200. The processor 201 can implement the following functions based on the data collected by the gyro sensor 212: motion sensing (such as changing the UI according to the user's tilt operation), image stabilization during shooting, game control, and inertial navigation.

[0073] The pressure sensor 213 can be set in the side frame of the terminal 200 and / or the lower layer of the touch display screen 205. When the pressure sensor 213 is set in the side frame of the terminal 200, it can detect the user's holding signal of the terminal 200, and perform left and right hand recognition or shortcut operation according to the holding signal. When the pressure sensor 213 is set in the lower layer of the touch display screen 205, it can control the operability control on the UI interface according to the user's pressure operation on the touch display screen 205. The operability control includes at least one of a button control, a scroll bar control, an icon control, and a menu control.

[0074] The fingerprint sensor 214 is used to collect the user's fingerprint to identify the user's identity based on the collected fingerprint. When the user's identity is identified as a trusted identity, the processor 201 authorizes the user to perform relevant sensitive operations, including unlocking the screen, viewing encrypted information, downloading software, paying, and changing settings. The fingerprint sensor 214 can be set on the front, back, or side of the terminal 200. When a physical button or a manufacturer logo is set on the terminal 200, the fingerprint sensor 214 can be integrated with the physical button or the manufacturer logo.

[0075] The optical sensor 215 is used to collect the ambient light intensity. In one embodiment, the processor 201 can control the display brightness of the touch display screen 205 according to the ambient light intensity collected by the optical sensor 215. Specifically, when the ambient light intensity is high, the display brightness of the touch display screen 205 is increased; when the ambient light intensity is low, the display brightness of the touch display screen 205 is reduced. In another embodiment, the processor 201 can also dynamically adjust the shooting parameters of the camera assembly 206 according to the ambient light intensity collected by the optical sensor 215.

[0076] The proximity sensor 216, also called a distance sensor, is usually arranged on the front of the terminal 200. The proximity sensor 216 is used to collect the distance between the user and the front of the terminal 200. In one embodiment, when the proximity sensor 216 detects that the distance between the user and the front of the terminal 200 is gradually decreasing, the processor 201 controls the touch display screen 205 to switch from the screen-on state to the screen-off state; when the proximity sensor 216 detects that the distance between the user and the front of the terminal 200 is gradually increasing, the processor 201 controls the touch display screen 205 to switch from the screen-off state to the screen-on state.

[0077] Those skilled in the art will understand that Figure 2 The structure shown in the figure does not constitute a limitation on the terminal 200, and the terminal 200 may include more or less components than those shown in the figure, or combine some components, or adopt a different component arrangement.

[0078] Embodiment 3

[0079] In an exemplary embodiment, a computer-readable storage medium is also provided, on which a computer program is stored. When the program is executed by a processor, a method for displaying a priority display of a function of a vehicle instrument light position is implemented as provided in all the inventive embodiments of the present application.

[0080] Any combination of one or more computer-readable media may be used. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device, or device.

[0081] Computer-readable signal media may include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0082] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0083] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0084] Embodiment 4

[0085] In an exemplary embodiment, an application product is also provided, including one or more instructions, which can be executed by the processor 201 of the above-mentioned device to complete the above-mentioned automobile instrument light position function priority display test method.

[0086] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and the embodiments. It can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily realized. Therefore, without departing from the general concept defined by the claims and equivalent scope, the present invention is not limited to the specific details and the illustrations shown and described here.

Claims

1. A function priority display test method, characterized in that: include: Obtain test cases and use virtual dashboard simulation software to simulate test scenarios; According to the test cases, the automobile instrument light function priority display test scenarios are respectively executed to obtain multiple test result images, and the multiple test result images are preprocessed to analyze the test results respectively through the optimal machine learning model.

2. A function priority display test method according to claim 1, characterized in that: Before obtaining the test case, it also includes: Obtain historical images of automobile instrument light positions when activated, and perform preprocessing and data annotation on them to obtain an automobile instrument light position training dataset; Construct a machine learning model, and use the automobile instrument light position training data set to train the machine learning model to obtain the optimal machine learning model.

3. A function priority display test method according to claim 2, characterized in that: The test cases include: common indicator light display, functional safety light display and test scenarios.

4. A function priority display test method according to claim 3, characterized in that: The commonly used indicator lights include at least vehicle speed display, gear position indicator, turn signal, fuel level indicator and charging status; the functional safety light displays include at least seat belt unfastened indicator light, brake system fault light, door open warning light and engine fault light.

5. A function priority display test method according to claim 3, characterized in that: The test scenarios include: displaying only common indicator lights, displaying several common indicator lights and functional safety lights at the same time, displaying functional safety lights when all common indicator light positions are occupied, and displaying high-priority functional safety lights and low-priority common indicator lights at the same time.

6. A function priority display test method according to claim 2, characterized in that: The use of the virtual instrument panel simulation software to simulate the test scenario includes: using the virtual instrument panel simulation software to set different light states through an API or a control interface, and checking display priority.

7. A function priority display test method according to claim 6, characterized in that: The preprocessing includes: cutting and adjusting the image according to the instrument panel area, identifying and segmenting the area of ​​each indicator light to obtain multiple light position area images.

8. A function priority display test method according to claim 6, characterized in that: The data labeling includes: marking the correct light position status for each light position area image.

9. A function priority display test method according to claim 7, characterized in that: The method of using the automobile instrument light position training data set to train the machine learning model to obtain the best machine learning model includes: The images of multiple light areas with correct light status marks are set as the input of the machine learning model, and the indicator light status and indicator light type are set as the output of the machine learning model to train the machine learning model and obtain the optimal machine learning model.

10. A terminal, characterized in that: include: one or more processors; a memory for storing the one or more processor-executable instructions; Wherein, the one or more processors are configured to: Execute a wind noise prediction method based on an artificial neural network as described in any one of claims 1 to 9.

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