Intelligent head-up display method and system adaptive to multiple scenes and electronic equipment

Abstract

The invention discloses a self-adaptive multi-scene intelligent head-up display method and system and electronic equipment, and relates to the field of vehicle-mounted display, and the method comprises an environment sensing module which is used for collecting external environment information, and the external environment information comprises weather, illumination, road types and traffic flow; the user information acquisition module is used for acquiring user personalized information, and the user personalized information comprises vision ability and type data, driving habit preference data and seat position state data; the scene recognition module is used for receiving the external environment information collected by the environment sensing module and recognizing a current driving scene according to a preset algorithm; wherein the scene recognition module is in data connection with the user information acquisition module; the display control module is in data connection with the scene recognition module and the user information acquisition module; and the data storage module is in data connection with the user information acquisition module, the scene recognition module, the display control module and the interaction control module.

Description

Technical Field

[0001] This application relates to the field of vehicle-mounted displays, and more particularly to an adaptive multi-scenario intelligent head-up display method, an adaptive multi-scenario intelligent head-up display system, electronic devices, storage media, and vehicles. Background Technology

[0002] Head-up display (HUD) technology projects key information about the vehicle's operation onto the driver's line of sight, eliminating the need to look down at the instrument panel and thus improving driving safety and ease of operation. However, existing HUDs have several shortcomings: First, the displayed content and parameters are relatively fixed, making it impossible to flexibly adjust to different usage scenarios (such as city driving, highway driving, night driving, and rainy driving). This results in irrelevant or unclear information in certain situations, affecting user experience and safety. Second, the interaction methods are limited, mostly supporting only simple steering wheel buttons or soft buttons on the central control screen, failing to meet users' needs for quick and convenient interaction in complex scenarios. Third, there is a lack of support for personalized user needs, failing to optimize the display based on factors such as different users' vision and driving habits.

[0003] Therefore, there is a need for an adaptive intelligent head-up display solution that can optimize scene recognition, display strategies, and interaction methods. Summary of the Invention

[0004] The purpose of this invention is to provide an adaptive multi-scenario intelligent head-up display method, an adaptive multi-scenario intelligent head-up display system, an electronic device, a storage medium, and a vehicle. It addresses at least the problem of fixed HUD display content and parameters, which cannot be flexibly adjusted according to different usage scenarios, leading to irrelevant or unclear display of key information in certain scenarios, affecting user experience and safety. It also addresses the problem of limited interaction methods, mostly supporting only simple steering wheel buttons or soft buttons on the central control screen, which fails to meet users' needs for fast and convenient interaction in complex scenarios. Furthermore, it addresses the technical problem of lacking support for personalized user needs and failing to optimize displays based on factors such as different users' vision and driving habits.

[0005] This invention provides the following solution:

[0006] According to a first aspect of the present invention, an adaptive multi-scene intelligent head-up display system is provided, comprising:

[0007] The system includes an environmental perception module, a user information collection module, a scene recognition module, a display control module, an interactive control module, and a data storage module.

[0008] The environmental perception module is used to collect external environmental information, including weather, lighting, road type, and traffic flow.

[0009] The user information collection module is used to obtain personalized user information, including visual ability and type data, driving habit preference data, and seat position status data.

[0010] Generate user demand information based on user personalization information;

[0011] The scene recognition module is used to receive external environment information collected by the environment perception module and identify the current driving scene according to a preset algorithm;

[0012] The display control module is used to adjust the display content and display parameters of the head-up display based on the current driving scenario identified by the scene recognition module and the personalized user information obtained by the user information collection module.

[0013] The interactive control module is used to provide diverse interaction methods according to the current driving scenario and user needs, and supports the customization of interaction methods.

[0014] The data storage module is used to store historical data of environmental information, personalized data of user needs, result data of scene recognition, and head-up display capability data formed by system configuration.

[0015] The scene recognition module is connected to the user information collection module.

[0016] The display control module is connected to the scene recognition module and the user information collection module via data connection.

[0017] The data storage module is connected to the user information collection module, scene recognition module, display control module, and interactive control module.

[0018] Furthermore, the environmental perception module includes:

[0019] Cameras, light sensors, rain sensors, and millimeter-wave radar collect information such as weather, lighting, road type, and traffic flow.

[0020] Among them, the camera is used to analyze the quantity and content information of road signs, vehicles and pedestrians, dynamic and static information through a preset image recognition algorithm, and to determine the road type, traffic flow and congestion status.

[0021] A light sensor is used to detect the intensity of light in the external environment;

[0022] Based on the corresponding clock information, generate recognition information for nighttime scenes;

[0023] Rain sensors are used to detect rainfall and determine whether the current location is in a rainy weather scenario;

[0024] Millimeter-wave radar is used to detect the distance between the vehicle and other vehicles / obstacles in front, as well as the relative speed between the vehicle and other vehicles, assisting cameras in judging traffic flow and congestion status.

[0025] Furthermore, the user information collection module includes:

[0026] Personalized user information can be obtained through at least one of the following methods: manual input by the user, interaction with the vehicle seat memory system, or interaction with the vehicle account system.

[0027] The manual input by the user includes data on visual ability and type;

[0028] Interaction with the vehicle seat memory system includes acquiring seat position status data and adjustment process data;

[0029] Interaction with the vehicle account system includes synchronizing driving history and assisting in the generation of driving habit preference data.

[0030] Furthermore, the scene recognition module includes:

[0031] The scene recognition module identifies the current driving scenarios, including urban road driving scenarios, highway driving scenarios, nighttime driving scenarios, and rainy driving scenarios.

[0032] Based on user needs in urban road driving scenarios, highway driving scenarios, night driving scenarios, and rainy driving scenarios, weighted information is generated that relates to the user's driving ability, traffic safety risks, and personalized needs.

[0033] Furthermore, the display control module includes:

[0034] In urban driving scenarios, the priority of raising the HUD to display vehicle speed, traffic light status, and turn prompts at the upcoming intersection should be increased.

[0035] Reduce the navigation map display scale to the preset scale and adjust the brightness to the median value adjustable by the device;

[0036] The HUD display image is corrected based on the user's vision ability and type data; the user's vision ability and type data includes myopia, hyperopia, and degree of myopia.

[0037] This also includes nighttime highway driving scenarios;

[0038] In nighttime highway driving scenarios, reduce the HUD display brightness to below the device's adjustable median and enhance contrast;

[0039] Highlight vehicle speed, distance to other vehicles, and distance to service areas;

[0040] Add nighttime safety alerts to the display;

[0041] Driving habit preference data includes user vehicle speed preference data;

[0042] Based on the user's vehicle speed preference data, the HUD highlights a comparison between the current vehicle speed and the preferred value.

[0043] Furthermore, the interactive control module includes:

[0044] Based on the collection of external environment information, the acquisition of user personalized information, and the generation of user demand information based on user personalized information, the current scenario is classified as a normal scenario or an emergency scenario.

[0045] Customize the parameters of the interactive control module for emergency scenarios;

[0046] The parameters of the custom interactive control module include: presetting high-priority semantics on the voice interaction end, presetting high-priority gestures on the visual recognition end, and setting high-priority buttons on the button end;

[0047] It also includes setting corresponding HUD display strategies based on preset high-priority semantics on the voice interaction end, preset high-priority gestures on the visual recognition end, and set high-priority buttons on the button end;

[0048] Based on the collection of external environmental information, the acquisition of personalized user information, and the generation of user demand information based on the personalized user information, it can be determined whether the current situation is an emergency.

[0049] If so, then capture the trigger commands from the voice interaction terminal, the visual recognition terminal, and / or the button terminal;

[0050] Based on the captured trigger command, the corresponding HUD display strategy is activated.

[0051] Furthermore, the data storage module includes:

[0052] Data optimization is performed based on historical environmental data, personalized user demand data, scene recognition results, and head-up display capability data generated by system configuration.

[0053] Data optimization includes scene recognition optimization, display strategy optimization, and interaction method optimization;

[0054] Scene recognition optimization includes improving the false recognition rate in nighttime scenes;

[0055] Display strategy optimization includes prioritizing the display of information content on the HUD;

[0056] Interaction method optimization includes optimizing the parameters of the interaction control module based on high-frequency and high-efficiency interaction methods.

[0057] According to a second aspect of the present invention, an adaptive multi-scene intelligent head-up display method is provided, based on an adaptive multi-scene intelligent head-up display system, the adaptive multi-scene intelligent head-up display method comprising:

[0058] S1. Information Acquisition: The environmental perception module collects external environmental information in real time at a preset frequency;

[0059] Based on the user's login status after boarding, the user information collection module completes the acquisition of the user's personalized information.

[0060] This includes obtaining personalized information about users in both logged-in and logged-out states;

[0061] S2, Scene Recognition: The scene recognition module receives real-time data from the environment perception module, performs scene determination once at a preset time interval, and outputs the current driving scene type and confidence information;

[0062] S3. Display Adjustment: During the preset time period after scene confirmation, the display control module calls the preset display parameter library to adjust the HUD display content and parameters according to the scene type and user's personalized information.

[0063] S4. Interaction Selection: The interaction control module loads the corresponding set of interaction methods according to the current scene type, and monitors user interaction operations at the same time;

[0064] If the user triggers custom settings, the user will be taken to the interaction method customization interface.

[0065] S5. Data storage and analysis: The data storage module stores the data generated in steps S1-S4 in real time, and the data analysis unit performs data optimization according to a preset cycle; the optimized parameters are synchronized to the scene recognition module, display control module and interactive control module.

[0066] According to a third aspect of the present invention, an electronic device is provided, comprising: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus;

[0067] The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of an adaptive multi-scene intelligent head-up display method.

[0068] According to a fourth aspect of the present invention, a computer-readable storage medium is provided storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of an adaptive multi-scene intelligent head-up display method.

[0069] According to a fifth aspect of the present invention, a vehicle is provided, comprising:

[0070] Electronic devices, steps for implementing an adaptive multi-scenario intelligent head-up display method;

[0071] The processor runs a program, and when the program runs, it executes the steps of an adaptive multi-scenario intelligent head-up display method based on data output from electronic devices.

[0072] Storage medium for storing programs that, when running, execute steps of an adaptive multi-scenario intelligent head-up display method based on data output from an electronic device.

[0073] The above solution achieves the following beneficial technical effects:

[0074] This application uses environmental perception and scene recognition to match the HUD display content and interaction methods with the current scene, thereby improving the practicality and security in different scenarios.

[0075] This application improves user experience by adjusting display and interaction based on personalized user information to meet the needs of different users.

[0076] This application offers diverse interaction methods and customizable settings, facilitating quick user operation and enhancing driving safety.

[0077] This application can optimize system performance through data storage and analysis functions. As usage time increases, scene recognition, display, and interaction adjustments become more accurate, thereby improving the level of intelligence. Attached Figure Description

[0078] Figure 1 This is a flowchart of an adaptive multi-scene intelligent head-up display method provided by one or more embodiments of the present invention.

[0079] Figure 2 This is a structural diagram of an adaptive multi-scene intelligent head-up display system provided by one or more embodiments of the present invention.

[0080] Figure 3 This is a schematic diagram of the HUD display state provided in a specific embodiment of the present invention. Figure 1 .

[0081] Figure 4 This is a schematic diagram of the HUD display state provided in a specific embodiment of the present invention. Figure 2 .

[0082] Figure 5 This is a schematic diagram of the HUD display state provided in a specific embodiment of the present invention. Figure 3 .

[0083] Figure 6This is a block diagram of an electronic device structure for an adaptive multi-scene intelligent head-up display method provided by one or more embodiments of the present invention. Detailed Implementation

[0084] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0085] Figure 2 This is a structural diagram of an adaptive multi-scene intelligent head-up display system provided by one or more embodiments of the present invention.

[0086] like Figure 2 The adaptive multi-scene intelligent head-up display system shown includes:

[0087] The system includes an environmental perception module, a user information collection module, a scene recognition module, a display control module, an interactive control module, and a data storage module.

[0088] The environmental perception module is used to collect external environmental information, including weather, lighting, road type, and traffic flow.

[0089] The user information collection module is used to obtain personalized user information, including visual ability and type data, driving habit preference data, and seat position status data.

[0090] Generate user demand information based on user personalization information;

[0091] The scene recognition module is used to receive external environment information collected by the environment perception module and identify the current driving scene according to a preset algorithm;

[0092] The display control module is used to adjust the display content and display parameters of the head-up display based on the current driving scenario identified by the scene recognition module and the personalized user information obtained by the user information collection module.

[0093] The interactive control module is used to provide diverse interaction methods according to the current driving scenario and user needs, and supports the customization of interaction methods.

[0094] The data storage module is used to store historical data of environmental information, personalized data of user needs, result data of scene recognition, and head-up display capability data formed by system configuration.

[0095] The scene recognition module is connected to the user information collection module.

[0096] The display control module is connected to the scene recognition module and the user information collection module via data connection.

[0097] The data storage module is connected to the user information collection module, scene recognition module, display control module, and interactive control module.

[0098] Specifically, in one embodiment, an adaptive multi-scenario intelligent head-up display system is disclosed, comprising the following modules:

[0099] 1. Environmental Perception Module: This module uses cameras, light sensors, rain sensors, millimeter-wave radar, etc., to collect information such as weather, lighting conditions, road type, and traffic flow. For example, cameras use image recognition algorithms to analyze road signs, vehicles, and pedestrians to determine road type and traffic flow; light sensors detect light intensity; rain sensors determine rainy weather; and millimeter-wave radar detects vehicle distance and speed to assist in judging traffic conditions.

[0100] 2. User Information Collection Module: This module collects information such as vision data (myopia / astigmatism), driving habits (speed preference, navigation preference), and seat position by users through manual input or interaction with the vehicle seat memory and account system.

[0101] 3. Scene Recognition Module: Receives environmental perception information and uses preset algorithms to identify scenes. For example, it determines nighttime / rainy day based on lighting and rainfall, road type based on road signs and features, and congestion level based on traffic flow.

[0102] 4. Display Control Module: Adjusts display content and parameters based on scene and user information. Reduces brightness and enhances oncoming vehicle headlight alerts at night; increases contrast and displays safety prompts in rainy weather; corrects images based on vision; and adjusts information priority (such as vehicle speed and navigation display mode) according to driving habits.

[0103] 5. Interactive Control Module: Provides diverse interactions based on scenarios and user needs. Normal scenarios support voice, gesture, and button interactions; emergency situations prioritize voice interaction (e.g., voice command response during collision warnings); custom gesture / voice commands are also supported.

[0104] 6. Data storage module: Stores historical environment information, user data, scene recognition results, and configuration data for system analysis and optimization.

[0105] In this embodiment, the environment perception module includes:

[0106] Cameras, light sensors, rain sensors, and millimeter-wave radar collect information such as weather, lighting, road type, and traffic flow.

[0107] Among them, the camera is used to analyze the quantity and content information of road signs, vehicles and pedestrians, dynamic and static information through a preset image recognition algorithm, and to determine the road type, traffic flow and congestion status.

[0108] A light sensor is used to detect the intensity of light in the external environment;

[0109] Based on the corresponding clock information, generate recognition information for nighttime scenes;

[0110] Rain sensors are used to detect rainfall and determine whether the current location is in a rainy weather scenario;

[0111] Millimeter-wave radar is used to detect the distance between the vehicle and other vehicles / obstacles in front, as well as the relative speed between the vehicle and other vehicles, assisting cameras in judging traffic flow and congestion status.

[0112] Specifically, the environmental perception modules of multiple vehicles upload the collected environmental information to the cloud system, and through unified large model analysis, obtain the environmental perception information of the current vehicle location.

[0113] In this embodiment, the user information collection module includes:

[0114] Personalized user information can be obtained through at least one of the following methods: manual input by the user, interaction with the vehicle seat memory system, or interaction with the vehicle account system.

[0115] The manual input by the user includes data on visual ability and type;

[0116] Interaction with the vehicle seat memory system includes acquiring seat position status data and adjustment process data;

[0117] Interaction with the vehicle account system includes synchronizing driving history and assisting in the generation of driving habit preference data.

[0118] Specifically, driving habit preference data is tailored to specific user identities. Driving habit preference data is obtained by using larger-scale historical data to reduce random interference.

[0119] By acquiring seat position status data and adjustment process data, driving habit preferences can be more reliably identified and marked.

[0120] In this embodiment, the scene recognition module includes:

[0121] The scene recognition module identifies the current driving scenarios, including urban road driving scenarios, highway driving scenarios, nighttime driving scenarios, and rainy driving scenarios.

[0122] Based on user needs in urban road driving scenarios, highway driving scenarios, night driving scenarios, and rainy driving scenarios, weighted information is generated that relates to the user's driving ability, traffic safety risks, and personalized needs.

[0123] Specifically, users' driving abilities differ in urban driving scenarios, highway driving scenarios, nighttime driving scenarios, and rainy driving scenarios, leading to different user needs and inherently personalized differences. These personalized differences can be used to adjust the common strategies in the HUD display, manifested as different weights. For example, some users have poor eyesight, exhibiting myopia, requiring refractive error correction on the HUD in highway driving scenarios. However, myopic users typically wear glasses; therefore, they prefer not to wear glasses while driving, resulting in a relative shift in personalized weight towards refractive error correction compared to other users.

[0124] In this embodiment, the display control module includes:

[0125] In urban driving scenarios, the priority of raising the HUD to display vehicle speed, traffic light status, and turn prompts at the upcoming intersection should be increased.

[0126] Reduce the navigation map display scale to the preset scale and adjust the brightness to the median value adjustable by the device;

[0127] The HUD display image is corrected based on the user's vision ability and type data; the user's vision ability and type data includes myopia, hyperopia, and degree of myopia.

[0128] This also includes nighttime highway driving scenarios;

[0129] In nighttime highway driving scenarios, reduce the HUD display brightness to below the device's adjustable median and enhance contrast;

[0130] Highlight vehicle speed, distance to other vehicles, and distance to service areas;

[0131] Add nighttime safety alerts to the display;

[0132] Driving habit preference data includes user vehicle speed preference data;

[0133] Based on the user's vehicle speed preference data, the HUD highlights a comparison between the current vehicle speed and the preferred value.

[0134] Specifically, in urban driving scenarios, there are many intersections and restricted roads, and turning is easily affected by green belts. Therefore, raising the priority of displaying vehicle speed, traffic light status, and turning prompts at upcoming intersections on the HUD is crucial. Correspondingly, other needs are not as strong.

[0135] In nighttime highway driving scenarios, characterized by high speeds and low illumination, it's easy to miss servers and exceed speed limits. Therefore, the HUD should prominently display vehicle speed, distance warnings, and service area distances. However, an overly bright HUD can significantly impact visual perception. Therefore, the HUD display brightness should be reduced to below the device's adjustable median, and contrast should be enhanced.

[0136] In this embodiment, the interactive control module includes:

[0137] Based on the collection of external environment information, the acquisition of user personalized information, and the generation of user demand information based on user personalized information, the current scenario is classified as a normal scenario or an emergency scenario.

[0138] Customize the parameters of the interactive control module for emergency scenarios;

[0139] The parameters of the custom interactive control module include: presetting high-priority semantics on the voice interaction end, presetting high-priority gestures on the visual recognition end, and setting high-priority buttons on the button end;

[0140] It also includes setting corresponding HUD display strategies based on preset high-priority semantics on the voice interaction end, preset high-priority gestures on the visual recognition end, and set high-priority buttons on the button end;

[0141] Based on the collection of external environmental information, the acquisition of personalized user information, and the generation of user demand information based on the personalized user information, it can be determined whether the current situation is an emergency.

[0142] If so, then capture the trigger commands from the voice interaction terminal, the visual recognition terminal, and / or the button terminal;

[0143] Based on the captured trigger command, the corresponding HUD display strategy is activated.

[0144] Specifically, in emergency scenarios, the complex multi-turn interaction process is difficult to handle, requiring rapid and accurate prioritization of the most important information. Interaction input terminals are set up on the voice interaction end, the visual recognition end, and / or the button end to reduce the difficulty of data input, while corresponding preset HUD display strategies are activated. The HUD display strategy is usually relative to the specific emergency scenario type. For example, in an emergency scenario of running out of fuel on a highway, service areas are the top priority; missing one could lead to breakdowns. The HUD abandons other displays, only showing the fuel consumption status and the distance to an example service area, such as converting it into a comparison chart of fuel consumption and remaining distance per unit distance, assisting the user in reaching a service area or gas station by appropriately reducing speed.

[0145] In this embodiment, the data storage module includes:

[0146] Data optimization is performed based on historical environmental data, personalized user demand data, scene recognition results, and head-up display capability data generated by system configuration.

[0147] Data optimization includes scene recognition optimization, display strategy optimization, and interaction method optimization;

[0148] Scene recognition optimization includes improving the false recognition rate in nighttime scenes;

[0149] Display strategy optimization includes prioritizing the display of information content on the HUD;

[0150] Interaction method optimization includes optimizing the parameters of the interaction control module based on high-frequency and high-efficiency interaction methods.

[0151] Specifically, light sensors monitor light levels, but darkness, overcast skies, and tunnels weaken the light signal. Other recognition methods are used to reduce the false positive rate in nighttime scenes. For example, a clock-based approach can assist in defining low-light environments. The information displayed on the HUD varies depending on the scene, but when more subtle scene differences exist, due to the limited display area and user attention, further priority optimization is needed to ensure that the displayed content is most relevant to the current scene.

[0152] Some interaction methods require multiple rounds to produce results, resulting in low efficiency. Other content requires multiple rounds of interaction for confirmation; otherwise, accurate locking is difficult. Although the steps are cumbersome, these are high-frequency interaction methods. Interaction control module parameters can be optimized based on high-frequency and high-efficiency interactions, or vice versa. Furthermore, the specific interaction method should be selected for optimization based on the specific scenario. For example, at high speeds, hands need to firmly grip the steering wheel, resulting in high-frequency and efficient interaction signals from steering wheel buttons, making it a viable optimization method. Voice interaction, however, is affected by environmental factors and user attention, making it less comfortable for users. In high-speed scenarios, voice interaction frequency is low, or users may have strong accents, leading to low efficiency; therefore, voice interaction can be considered a secondary option.

[0153] Figure 1 This is a flowchart of an adaptive multi-scene intelligent head-up display method provided by one or more embodiments of the present invention.

[0154] like Figure 1 The adaptive multi-scene intelligent head-up display method shown is based on an adaptive multi-scene intelligent head-up display system. The adaptive multi-scene intelligent head-up display method includes:

[0155] S1. Information Acquisition: The environmental perception module collects external environmental information in real time at a preset frequency;

[0156] Based on the user's login status after boarding, the user information collection module completes the acquisition of the user's personalized information.

[0157] This includes obtaining personalized information about users in both logged-in and logged-out states;

[0158] S2, Scene Recognition: The scene recognition module receives real-time data from the environment perception module, performs scene determination once at a preset time interval, and outputs the current driving scene type and confidence information;

[0159] S3. Display Adjustment: During the preset time period after scene confirmation, the display control module calls the preset display parameter library to adjust the HUD display content and parameters according to the scene type and user's personalized information.

[0160] S4. Interaction Selection: The interaction control module loads the corresponding set of interaction methods according to the current scene type, and monitors user interaction operations at the same time;

[0161] If the user triggers custom settings, the user will be taken to the interaction method customization interface.

[0162] S5. Data storage and analysis: The data storage module stores the data generated in steps S1-S4 in real time, and the data analysis unit performs data optimization according to a preset cycle; the optimized parameters are synchronized to the scene recognition module, display control module and interactive control module.

[0163] Specifically, in one embodiment, based on an adaptive multi-scenario intelligent head-up display system, the method includes the following steps:

[0164] 1. Information Collection: The environmental perception module collects external environmental information in real time, and the user information collection module obtains personalized user information.

[0165] 2. Scene Recognition: The scene recognition module uses algorithms to identify the current scene based on environmental information.

[0166] 3. Display Adjustment: The display control module adjusts the HUD display content and parameters according to the scene and user information.

[0167] 4. Interaction Selection: The interaction control module selects the appropriate interaction method based on the scenario and user needs, and provides custom settings options.

[0168] 5. Data storage and analysis: Store relevant data and analyze it regularly to optimize scene recognition algorithms, display strategies, and interaction methods.

[0169] It is worth noting that although this system / device only discloses the aforementioned environmental perception module, user information collection module, scene recognition module, display control module, interactive control module, and data storage module, this does not mean that this system / device is limited to the aforementioned basic functional modules. Rather, what this invention intends to express is that, based on the aforementioned basic functional modules, those skilled in the art can arbitrarily add one or more functional modules in combination with existing technology to form an infinite number of embodiments or technical solutions. In other words, this system is open rather than closed. The fact that this embodiment only discloses a few basic functional modules should not lead to the conclusion that the scope of protection of the claims of this invention is limited to the aforementioned disclosed basic functional modules.

[0170] In one specific embodiment, a HUD display control method for urban road driving scenarios is disclosed:

[0171] Environmental perception: The camera recognizes that there are dense buildings on both sides of the road, many intersections, and heavy traffic, and the light sensor detects normal light intensity.

[0172] Scene recognition: The scene is identified as an urban road scene.

[0173] Display Control: The HUD prioritizes displaying vehicle speed, traffic light status, and turn signals at upcoming intersections; it reduces the navigation map display scale and adjusts the brightness to a suitable level; the displayed image is corrected based on the user's nearsightedness. (e.g.) Figure 3 , 5 As shown, the display focuses on vehicle speed, traffic light status, and turn signal at the upcoming intersection.

[0174] Interactive control: Provides voice interaction (such as checking gas stations) and gesture interaction (switching displayed content) to reduce driving distraction.

[0175] Data storage: Records scene recognition results, display and interaction settings for subsequent optimization.

[0176] In another specific embodiment, a HUD display control for a nighttime highway driving scenario is disclosed:

[0177] Environmental perception: The light sensor detected extremely low light intensity, the camera recognized that the road was straight and the distance between vehicles was large, and the millimeter-wave radar detected that the vehicle speed was relatively fast.

[0178] Scene recognition: The scene is determined to be a nighttime highway scene.

[0179] Display control: Reduce HUD display brightness, enhance contrast, highlight vehicle speed, distance reminders, and service area distance, and add nighttime safety prompts; based on the user's preset speed preference, prominently display a comparison between the current speed and the preferred value. (e.g.) Figure 3 As shown, the display emphasizes vehicle speed and distance reminders.

[0180] Interactive control: Primarily uses voice interaction (such as adjusting vehicle speed settings and querying navigation) to ensure ease of operation.

[0181] Data storage: Record relevant data to provide a basis for system optimization.

[0182] Figure 6 This is a block diagram of an electronic device structure for an adaptive multi-scene intelligent head-up display method provided by one or more embodiments of the present invention.

[0183] like Figure 6 As shown, this application provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0184] The memory stores a computer program that, when executed by the processor, causes the processor to perform steps of an adaptive multi-scene intelligent head-up display method.

[0185] This application also provides a computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of an adaptive multi-scene intelligent head-up display method.

[0186] This application also provides a vehicle, including:

[0187] Electronic devices, steps for implementing an adaptive multi-scenario intelligent head-up display method;

[0188] The processor runs a program, and when the program runs, it executes the steps of an adaptive multi-scenario intelligent head-up display method based on data output from electronic devices.

[0189] Storage medium for storing programs that, when running, execute steps of an adaptive multi-scenario intelligent head-up display method based on data output from an electronic device.

[0190] The communication bus mentioned in the above electronic devices can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not indicate that there is only one bus or one type of bus.

[0191] The electronic device comprises a hardware layer, an operating system layer running on top of the hardware layer, and an application layer running on the operating system. The hardware layer includes hardware such as a central processing unit (CPU), a memory management unit (MMU), and memory. The operating system can be any one or more computer operating systems that control the electronic device through processes, such as Linux, Unix, Android, iOS, or Windows. Furthermore, in this embodiment of the invention, the electronic device can be a smartphone, tablet computer, or other handheld device, or a desktop computer, portable computer, or other electronic device; there is no particular limitation in this embodiment.

[0192] In this embodiment of the invention, the executing entity for electronic device control can be an electronic device itself, or a functional module within an electronic device capable of calling and executing a program. The electronic device can obtain the firmware corresponding to the storage medium. This firmware is provided by the supplier, and different storage media may have the same or different firmware; no limitation is made here. After obtaining the firmware corresponding to the storage medium, the electronic device can write this firmware into the storage medium; specifically, it burns the firmware corresponding to the storage medium into the storage medium. The process of burning the firmware into the storage medium can be implemented using existing technology, and will not be elaborated upon in this embodiment of the invention.

[0193] Electronic devices can also obtain reset commands corresponding to the storage media. The reset commands corresponding to the storage media are provided by the supplier. The reset commands corresponding to different storage media can be the same or different, and no restrictions are imposed here.

[0194] At this time, the storage medium of the electronic device is a storage medium on which the corresponding firmware has been written. The electronic device can respond to the reset command corresponding to the storage medium on which the corresponding firmware has been written, thereby resetting the storage medium on which the corresponding firmware has been written according to the reset command. The process of resetting the storage medium according to the reset command can be implemented by existing technology and will not be described in detail in this embodiment of the invention.

[0195] For ease of description, the above devices are described separately by function as various units and modules. Of course, in implementing this application, the functions of each unit and module can be implemented in one or more software and / or hardware.

[0196] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the meaning consistent with their meaning in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined.

[0197] For the sake of simplicity, the method embodiments are described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0198] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0199] 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. An adaptive multi-scenario intelligent head-up display system, characterized in that, The adaptive multi-scene intelligent head-up display system comprises: An environment perception module, a user information acquisition module, a scene recognition module, a display control module, an interactive control module, and a data storage module; The environment perception module is configured to collect external environment information, which includes weather, illumination, road type, and traffic flow; The user information acquisition module is configured to obtain user personalized information, which includes visual ability and type data, driving habit preference data, and seat position state data; User demand information is generated according to the user personalized information; The scene recognition module is configured to receive the external environment information collected by the environment perception module and recognize the current driving scene according to a preset algorithm; The display control module is configured to adjust the display content and display parameters of the head-up display according to the current driving scene recognized by the scene recognition module and the user personalized information obtained by the user information acquisition module; The interactive control module is configured to provide diversified interactive modes according to the current driving scene and user demand, and support custom setting of the interactive modes; The data storage module is configured to store historical data of environment information, user personalized data of user demand information, result data of scene recognition, and head-up display capability data formed by system configuration; The scene recognition module is in data connection with the user information acquisition module; The display control module is in data connection with the scene recognition module and the user information acquisition module; The data storage module is in data connection with the user information acquisition module, the scene recognition module, the display control module, and the interactive control module.

2. The adaptive multi-scenario intelligent head-up display system of claim 1, wherein, The environment perception module comprises: A camera, a light sensor, a rain sensor, and a millimeter wave radar, which are configured to collect information such as weather, illumination, road type, and traffic flow; The camera is configured to analyze road signs, dynamic and static quantity information and content information of vehicles and pedestrians, judge the road type, traffic flow, and congestion state by using a preset image recognition algorithm; The light sensor is configured to detect the illumination intensity of the external environment; The clock information is used to generate the recognition information of the night scene; The rain sensor is configured to detect the rainfall state to determine whether the current location is a rainy scene; The millimeter wave radar is configured to detect the distance between the vehicle and the front vehicle / obstacle and the relative driving speed of the vehicle, and assist the camera in judging the traffic flow and congestion state.

3. The adaptive multi-scenario intelligent head-up display system of claim 1, wherein, The user information acquisition module comprises: The user personalized information is obtained by at least one of the following ways: user manual input, interaction with the vehicle seat memory system, and interaction with the vehicle account system; The user manual input includes visual ability and type data; The interaction with the vehicle seat memory system includes obtaining seat position state data and adjustment process data; The interaction with the vehicle account system includes synchronizing driving history to assist in generating driving habit preference data.

4. The adaptive multi-scenario intelligent head-up display system of claim 1, wherein, The scene recognition module comprises: The current driving scene recognized by the scene recognition module includes an urban road driving scene, an expressway driving scene, a night driving scene, and a rainy driving scene; Corresponding to the user demand in the urban road driving scene, the highway driving scene, the night driving scene and the rainy day driving scene, the weight information associated with the user driving ability, the traffic safety risk and the personalized demand is generated.

5. The adaptive multi-scenario intelligent head-up display system of claim 1, wherein, The display control module comprises: In the urban road driving scene, the priority of the HUD display speed, traffic signal state, front intersection turning prompt information is raised; The navigation map display scale is reduced to a preset scale state and the brightness is adjusted to the middle number adjustable by the device; According to the user vision ability and type data, the HUD display image is corrected; the user vision ability and type data include myopia, hyperopia and degree; It also includes the night highway driving scene; In the night highway driving scene, the HUD display brightness is reduced below the middle number adjustable by the device and the contrast is enhanced; The vehicle speed, vehicle distance reminder and service area distance are highlighted; The display of night safety prompt information is increased; The driving habit preference data includes user vehicle speed preference data; According to the user vehicle speed preference data, the contrast between the current vehicle speed and the preference value is highlighted on the HUD.

6. The adaptive multi-scenario intelligent head-up display system of claim 1, wherein, The interaction control module comprises: According to the collected external environment information, the obtained user personalized information and the user demand information generated according to the user personalized information, it is judged whether the current scene belongs to a normal scene or an emergency scene; Customize the parameters of the interaction control module corresponding to the emergency scene; The parameters of the interaction control module include preset high priority semantics in the voice interaction end, preset high priority gestures in the visual recognition end and high priority keys in the key end; It also includes setting the corresponding HUD display strategy according to the preset high priority semantics in the voice interaction end, the preset high priority gestures in the visual recognition end and the high priority keys in the key end; According to the collected external environment information, the obtained user personalized information and the user demand information generated according to the user personalized information, it is judged whether the current scene belongs to a normal scene or an emergency scene; If yes, the trigger instruction of the voice interaction end, the visual recognition end or / and the key end is captured; According to the captured trigger instruction, the corresponding HUD display strategy is started.

7. The adaptive multi-scenario intelligent head-up display system of claim 1, wherein, The data storage module comprises: According to the historical data of the environment information, the user personalized data of the user demand information, the result data of the scene recognition and the head-up display ability data formed by the system configuration, the data optimization is carried out; Data optimization includes scene recognition optimization, display strategy optimization and interaction mode optimization; Scene recognition optimization includes optimization of night scene misjudgment rate; Display strategy optimization includes priority optimization of information content display on the HUD; Interaction mode optimization includes optimization of the interaction control module parameters based on high frequency and high efficiency interaction mode screening.

8. An adaptive multi-scenario intelligent head-up display method based on the adaptive multi-scenario intelligent head-up display system of any one of claims 1-7, characterized in that, The adaptive multi-scene intelligent head-up display method comprises: S1, information collection: the environment perception module collects external environment information in real time at a preset frequency; According to the user login state after the user gets on the vehicle, the user information collection module completes the acquisition of user personalized information; It includes user personalized information acquisition in the same user login and non-login state; S2, scene recognition: the scene recognition module receives real-time data of the environment perception module, performs scene determination once per preset time interval, and outputs the current driving scene type and confidence information; S3, display adjustment: the display control module adjusts the HUD display content and parameters according to the scene type and user personalized information during the preset time period after the scene confirmation; S4, interactive selection: the interactive control module loads the corresponding interactive mode set according to the current scene type, and monitors the user interaction operation; If the user triggers the custom setting, the interactive mode custom interface is entered; S5, data storage and analysis: the data storage module stores the data generated in steps S1-S4 in real time, and the data analysis unit performs data optimization at a preset period; the optimized parameters are synchronized to the scene recognition module, the display control module and the interactive control module.

9. An electronic device, comprising: It comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus. The memory stores a computer program which, when executed by the processor, causes the processor to perform the steps of the adaptive multi-scene intelligent head-up display method according to claim 8. The memory stores a computer program executable by the electronic device, which causes the electronic device to perform the steps of the adaptive multi-scene intelligent head-up display method according to claim 8 when the computer program runs on the electronic device.

10. A computer-readable storage medium, characterized in that, ​

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