Display method of vehicle screen, vehicle, electronic device, and computer program

Abstract

The embodiment of the specification provides a display method of a vehicle screen, relates to the technical field of intelligent cockpits, and achieves digital description of a current driving situation by acquiring environment perception data of the vehicle in a driving scene; then, the degree of attention demand of a driver is configured based on the environment perception data to obtain driving situation tension, so as to convert the fuzzy attention demand into a quantifiable index; then, the gaze area of the driver to multiple screens is determined to determine the gaze area priority of each screen, so as to realize spatial positioning of visual attention; then, preset rendering parameters corresponding to the driving situation tension are determined and adjusted according to the gaze area priority to obtain target rendering parameters, so as to achieve dynamic adaptation of a rendering strategy to the situation tension and the attention priority; finally, a rendering operation is performed based on the target rendering parameters to display content on each screen, so as to guarantee the integrity of the display of key content in the vehicle and improve the safety of vehicle driving.

Description

Technical Field

[0001] This specification relates to the field of intelligent cockpit technology, specifically to vehicle screen display technology in the field of vehicle technology, and more specifically, to a vehicle screen display method, vehicle, electronic device, and computer program. Background Technology

[0002] With the trend of multi-screen development in smart cockpits, it has become common for multiple screens, such as the instrument panel, central control screen, and passenger screen, to work simultaneously, placing higher demands on the computing power and power consumption management of in-vehicle graphics processors. The general need in this technological field is to minimize the overall system's energy consumption and heat generation while ensuring clear and smooth display of driving safety-related content, thereby extending driving range and improving user experience.

[0003] Generally, a fixed combination of rendering parameters is used for display in multi-screen collaborative display processes. However, in complex driving scenarios, a fixed rendering process may cause the display of key driving content to be missing or delayed due to excessive load on the graphics processor, affecting the safety of vehicle driving. Summary of the Invention

[0004] This specification provides an embodiment of a vehicle screen display method, a vehicle, an electronic device, and a computer program to improve vehicle driving safety.

[0005] To achieve the above technical objectives, the embodiments of this specification provide the following technical solutions: Firstly, one embodiment of this specification provides a method for displaying a vehicle screen, comprising: Acquire environmental perception data of the vehicle in the driving scenario; Based on the environmental perception data, the driver's attention needs in the driving scenario are configured with features to obtain the driving situation tension of the driving scenario. Determine the driver's gaze area for multiple screens configured in the vehicle, and determine the gaze area priority for each screen based on the gaze area. Determine the preset rendering parameters corresponding to the driving situation tension, and adjust the preset rendering parameters according to the gaze area priority to obtain the target rendering parameters corresponding to each screen; Rendering operations are performed based on the target rendering parameters to display content on each screen in the vehicle.

[0006] Optionally, in one possible implementation, acquiring the vehicle's environmental perception data in the driving scenario includes: Acquire vehicle driving data in the driving scenario; Eye tracking is performed on the driver to obtain eye tracking data; Obtain the navigation data of the vehicle in the driving scenario; The vehicle driving data, the eye-tracking data, and the navigation data are aligned based on timestamps to obtain the environmental perception data.

[0007] In this implementation, real-time perception of vehicle dynamic behavior is achieved by acquiring vehicle driving data; simultaneously, eye tracking data is obtained by tracking the driver's gaze, enabling precise capture of the driver's attention distribution; navigation data of the vehicle in the driving scenario is then acquired to predict the complexity of the road ahead; finally, vehicle driving data, eye tracking data, and navigation data are aligned based on timestamps to obtain environmental perception data, achieving the fusion of three sources of information: vehicle status, driver status, and road environment, thereby improving the comprehensiveness and robustness of contextual perception.

[0008] Optionally, in one possible implementation, the step of configuring features based on the environmental perception data to determine the driver's attention needs in the driving scenario, in order to obtain the driving situation tension of the driving scenario, includes: Obtain a preset dimension related to the degree of attention demand in the driving scenario. The preset dimension is configured based on internal and external factors. The internal factors include at least one of vehicle speed parameters and attention parameters. The external factors include at least one of vehicle distance parameters and road condition parameters. Obtain the weight matrix corresponding to the driving scenario; The internal factors and / or external factors are weighted and fused based on the weight matrix to obtain the target feature value; The driving situation tension of the driving scenario is determined by comparing threshold intervals based on the target feature values.

[0009] In this implementation, a preset dimension related to the degree of attention demand is obtained. This dimension includes internal and external factors such as vehicle speed parameters, attention parameters, vehicle distance parameters, and road condition parameters, enabling a structured analysis of key factors affecting the driver's cognitive load. Then, a weight matrix corresponding to the driving scenario is obtained to achieve differentiated expression of the importance of each factor under different scenarios. Next, based on the weight matrix, internal and external factors are weighted and fused to obtain target feature values, realizing the numerical transformation of multi-dimensional heterogeneous data into a single continuous scalar. Finally, threshold interval comparisons are performed based on the target feature values ​​to determine the driving situation tension, thereby discretizing continuous values ​​into operable tension levels and improving decision-making efficiency.

[0010] Optionally, in one possible implementation, the step of comparing threshold intervals based on the target feature value to determine the driving situation tension of the driving scenario includes: The target feature value is compared with a preset interval threshold. If the target feature value is in the hysteresis interval, the configuration duration for detecting the tension of the driving situation is determined, and the hysteresis interval is configured based on the boundary value of the preset interval threshold. If the configuration duration meets the preset conditions, then the tension level corresponding to the hysteresis interval is determined as the driving situation tension of the driving scenario.

[0011] In this implementation, the initial determination of the tension level is achieved by comparing the target feature value with a preset interval threshold. If the target feature value is in the hysteresis interval, the configuration duration of the driving situation tension is detected. This hysteresis interval is configured based on the threshold boundary value to introduce a decision dead zone near the boundary to suppress noise fluctuations. If the configuration duration meets the preset conditions, the tension level corresponding to the hysteresis interval is determined as the driving situation tension level, realizing a delayed confirmation mechanism for level switching, improving the stability of rendering parameter adjustment, and preventing frequent image quality oscillations.

[0012] Optionally, in one possible implementation, determining the preset rendering parameters corresponding to the driving situation tension and adjusting the preset rendering parameters according to the gaze region priority to obtain the target rendering parameters corresponding to each screen includes: Determine the preset rendering parameters corresponding to the tension level of the driving situation; The gaze region and non-gaze region are determined based on the gaze region priority. Determine the function type corresponding to the gaze region; Based on the function type corresponding to the gaze area and the driving situation tension, the preset rendering parameters corresponding to the gaze area are improved to obtain the target rendering parameters for each screen.

[0013] In this implementation, preset rendering parameters corresponding to the driving situation's tension are determined to quickly anchor the basic image quality level of each screen. Then, the gaze area and non-gaze area are determined according to the gaze area priority to achieve accurate spatial segmentation of the driver's visual attention range. Next, the function type corresponding to the gaze area is determined to identify the criticality of different screen tasks. Then, based on the function type of the gaze area and the driving situation's tension, the preset rendering parameters corresponding to the gaze area are improved to obtain the target rendering parameters, achieving a two-layer adjustment of the basic situation level and gaze enhancement. This ensures safety while improving user experience and achieving energy saving in non-gaze areas.

[0014] Optionally, in one possible implementation, the method further includes: Based on the target rendering parameters, the predicted information of the graphics processor for the vehicle configuration is estimated; Obtain the load information of the graphics processor; If the predicted information exceeds the safe capacity compared to the load information, the parameters are adjusted according to the gaze region priority to reduce the target rendering parameters.

[0015] In this implementation, after generating the target rendering parameters, the predicted information of the graphics processor is estimated based on the target rendering parameters to achieve predictive calculation of the graphics processor load; then, the real-time load information of the graphics processor is obtained to achieve immediate perception of the actual operating status of the hardware; if the predicted information exceeds the safe capacity compared with the load information, the parameters are adjusted according to the priority of the gaze area to reduce the target rendering parameters, thereby achieving the overload protection process of priority arbitration and active load reduction, preventing the graphics processor from overloaded or overheated, and ensuring the stability of critical information rendering and driving safety in high-load scenarios.

[0016] Optionally, in one possible implementation, the method further includes: Monitoring data for each screen is collected based on a preset cycle. Based on the monitoring data, determine the execution achievement parameters, load parameters, and power consumption parameters; Feedback signals are obtained by comparing the execution achievement parameters, the load parameters, and the power consumption parameters with the adjustment strategy; The target rendering parameters are adjusted based on the feedback signal.

[0017] In this implementation, monitoring data from each screen is collected at a preset period to achieve real-time quantitative feedback on the rendering effect of the execution layer. Then, the execution achievement parameters, load parameters, and power consumption parameters are determined based on the monitoring data, achieving an abstract transformation from the original monitoring values ​​to evaluation indicators. Next, the execution achievement parameters, load parameters, and power consumption parameters are compared with the adjustment strategy to obtain feedback signals, thereby triggering the adaptive rules. Finally, the target rendering parameters are adjusted based on the feedback signals to achieve closed-loop adaptive optimization, continuously correcting subsequent decisions to adapt to factors such as hardware aging and changes in ambient temperature, thereby improving the robustness and energy efficiency of the system under different operating conditions.

[0018] Secondly, one embodiment of this specification provides a display device for a vehicle screen, comprising: The acquisition unit is used to acquire environmental perception data of the vehicle in the driving scenario; The processing unit is used to configure features based on the environmental perception data to determine the driver's attention needs in the driving scenario, so as to obtain the driving situation tension of the driving scenario. The processing unit is further configured to determine the driver's gaze area on multiple screens configured in the vehicle, so as to determine the gaze area priority corresponding to each screen through the gaze area. The processing unit is further configured to determine the preset rendering parameters corresponding to the driving situation tension, and adjust the preset rendering parameters according to the gaze area priority to obtain the target rendering parameters corresponding to each screen. The display unit is used to perform rendering operations based on the target rendering parameters in order to display content on each screen in the vehicle.

[0019] Thirdly, one embodiment of this specification also provides a vehicle screen display system, including sensors and a vehicle controller, wherein the sensors are used to collect vehicle-related data; and the vehicle controller is used to execute the vehicle screen display method as described in the first aspect or any possible implementation thereof.

[0020] Fourthly, one embodiment of this specification also provides a vehicle, the vehicle comprising: a memory for storing executable program code; and a processor for calling and running the executable program code from the memory, causing the vehicle to execute the vehicle screen display method in the first aspect or any possible implementation of the first aspect.

[0021] Fifthly, one embodiment of this specification also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the vehicle screen display method described above.

[0022] Sixthly, embodiments of this specification provide a computer program product or computer program, the computer program product including a computer program that can be stored in a computer-readable storage medium or in the cloud; the processor of the computer device reads the computer program, and when the processor executes the computer program, it implements the steps of the above-described vehicle screen display method.

[0023] As can be seen from the above technical solution, the vehicle screen display method provided in this specification acquires environmental perception data of the vehicle in the driving scenario to achieve a digital description of the current driving situation; then, based on the environmental perception data, it performs feature configuration on the driver's attention needs to obtain the driving situation tension, thereby transforming the vague attention needs into quantifiable indicators; next, it determines the driver's gaze areas on multiple screens to determine the priority of each screen's gaze area, thereby achieving spatial positioning of visual attention; then, it determines the preset rendering parameters corresponding to the driving situation tension and adjusts them according to the gaze area priority to obtain the target rendering parameters, achieving dynamic adaptation of the rendering strategy with the situation tension and attention priority; finally, it executes rendering operations based on the target rendering parameters to display content on each screen, achieving safety-first, on-demand, multi-screen fine-grained control, ensuring the integrity of the display of key content in the vehicle, and improving the safety of vehicle driving. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments or prior art of this specification, the drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this specification. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0025] Figure 1 This is a schematic diagram illustrating the application environment of a vehicle screen display method provided as one embodiment of this specification.

[0026] Figure 2 This is a flowchart illustrating a method for displaying a vehicle screen according to one embodiment of this specification.

[0027] Figure 3 This is a schematic diagram of an execution flow provided for one embodiment of this specification.

[0028] Figure 4 This is a schematic diagram of another execution flow provided for one embodiment of this specification.

[0029] Figure 5 This is a schematic diagram of another execution flow provided for one embodiment of this specification.

[0030] Figure 6 This is a schematic diagram of another execution flow provided for one embodiment of this specification.

[0031] Figure 7 This is a schematic diagram of another execution flow provided for one embodiment of this specification.

[0032] Figure 8This is a schematic diagram of the functional modules of a vehicle screen display device provided in one embodiment of this specification.

[0033] Figure 9 This is a structural schematic diagram of a vehicle provided for one embodiment of this specification. Detailed Implementation

[0034] Unless otherwise defined, the technical or scientific terms used in the embodiments of this specification shall have the ordinary meaning understood by one of ordinary skill in the art to which this specification pertains. The terms "first," "second," and similar terms used in the embodiments of this specification do not indicate any order, quantity, or importance, but are merely used to avoid confusion of constituent elements.

[0035] Unless the context otherwise requires, throughout this specification, "a plurality of" means "at least two," and "including" is interpreted as open-ended or encompassing, that is, "including, but not limited to." In the description of this specification, terms such as "one embodiment," "some embodiments," "exemplary embodiment," "example," "specific example," or "some examples" are intended to indicate that a particular feature, structure, material, or characteristic associated with that embodiment or example is included in at least one embodiment or example of this specification. The illustrative representations of the above terms do not necessarily refer to the same embodiment or example.

[0036] The technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this specification.

[0037] With the trend of multi-screen development in smart cockpits, it has become common for multiple screens, such as the instrument panel, central control screen, and passenger screen, to work simultaneously, placing higher demands on the computing power and power consumption management of in-vehicle graphics processors. The general need in this technological field is to minimize the overall system's energy consumption and heat generation while ensuring clear and smooth display of driving safety-related content, thereby extending driving range and improving user experience.

[0038] Generally, a fixed combination of rendering parameters is used for display in multi-screen collaborative display processes. However, in complex driving scenarios, a fixed rendering process may cause the display of key driving content to be missing or delayed due to excessive load on the graphics processor, affecting the safety of vehicle driving.

[0039] To address the aforementioned problems, this specification provides a display system for a vehicle screen, and the display method for the vehicle screen provided in this specification is applied to the display system. This display system constructs a quantitative model of driving situation tension through multi-source data fusion, identifies the priority of gaze areas using eye-tracking technology, and achieves coordinated adjustment of frame rate and resolution across multiple screens based on a dynamic rendering parameter mapping table.

[0040] Specifically, the display system of the vehicle screen may include a system composed of... Figure 1 The system comprises a client 110, a server 120, and a vehicle 130, forming an operating environment. The client 110 communicates with the server 120 via a network. The client 110 is wirelessly connected to the vehicle 130. The vehicle 130 communicates with the server 120 via a network connection. The client 110 can be an electronic device with network access capabilities. Specifically, for example, the client 110 can be a desktop computer, tablet, laptop, smartphone, digital assistant, smart wearable device, shopping guide terminal, television, smart speaker, microphone, etc. Smart wearable devices include, but are not limited to, smart bracelets, smartwatches, smart glasses, smart helmets, smart necklaces, etc. Alternatively, the client 110 can also be software that can run on the electronic device. The server 120 can be an electronic device with certain computing power. It can have a network communication module, processor, and memory, etc. Of course, the server 120 can also refer to software running on the electronic device. The server 120 can also be a distributed server, which can be a system with multiple processors, memory, network communication modules, etc., operating collaboratively. Alternatively, the server 120 can also be a cluster formed by several servers 120. Alternatively, with the development of science and technology, server 120 could also be a new technological means capable of realizing the corresponding functions of the implementation method described in the manual. For example, it could be a new form of "server" based on quantum computing.

[0041] Specifically, when displaying an interface within a vehicle using the aforementioned display system, the system acquires environmental perception data of the vehicle in the driving scenario to achieve a digital description of the current driving situation. Then, based on the environmental perception data, it configures features to assess the driver's attention needs to obtain the driving situation's tension, transforming vague attention needs into quantifiable indicators. Next, it determines the driver's gaze areas on multiple screens to establish the priority of each screen's gaze area, achieving spatial localization of visual attention. Then, it determines preset rendering parameters corresponding to the driving situation's tension and adjusts them according to the gaze area priority to obtain target rendering parameters, achieving dynamic adaptation of the rendering strategy to the situation's tension and attention priority. Finally, it executes rendering operations based on the target rendering parameters to display content on each screen, achieving safety-first, on-demand, and refined multi-screen control, ensuring the integrity of key content displayed within the vehicle, and improving vehicle driving safety.

[0042] Based on the above concept, this specification provides a method for displaying a vehicle screen. The method for displaying a vehicle screen provided in this specification will be described exemplarily below with reference to the accompanying drawings.

[0043] To be applied Figure 1 Taking a vehicle as an example, this specification provides illustrative examples of some implementation methods for displaying the vehicle screen, such as... Figure 2 As shown, Figure 2 This is a flowchart illustrating a method for displaying a vehicle screen according to one embodiment of this specification; the method includes: 201. Obtain environmental perception data of the vehicle in the driving scenario.

[0044] In this embodiment, environmental perception data refers to a collection of multi-source information collected by vehicle sensors, cameras, and navigation systems that reflects the vehicle's status, driver behavior, and external road environment in the current driving scenario. Specifically, it includes vehicle driving data such as vehicle speed and steering angular velocity, eye-tracking data such as driver's gaze direction and gaze duration, and navigation data such as intersection complexity and distance to the next navigation action. Environmental perception data provides the raw input for subsequent calculations of driving situation tension.

[0045] Specifically, environmental perception data is used to quantify the driver's attention requirements in a driving scenario. The following section explains the conversion process in conjunction with the system's functional divisions, such as... Figure 3 As shown, Figure 3This diagram illustrates an execution flow for one embodiment of this specification. It shows a perception / quantization / decision / execution architecture for the dynamic display adjustment process across multiple vehicle screens. First, at the perception layer, ADAS perceives road conditions, DMS perceives driver status, and navigation information; a multi-source data collector aggregates this data to generate raw perception data. Next, at the quantization layer, contextual features are extracted from the data, driving situation stress (DSS) is calculated, and four levels (L1-L4) are defined. Then, at the decision layer, the DSS level is combined with the gaze area recognition results to generate rendering parameters for each screen via a rendering parameter mapping table; instructions are then issued by the multi-screen coordinator. Finally, at the execution layer, the rendering control modules for the instrument panel, central control screen, and passenger-side screen receive the parameters; the GPU resource monitoring module uniformly allocates resources and feeds back resource usage to the decision layer, forming a closed-loop control system to achieve dynamic adaptation of in-vehicle multi-screen rendering resources based on driving context.

[0046] In one possible scenario, environmental perception data can include vehicle driving data, eye-tracking data, and navigation data. First, vehicle driving data in the driving scenario is acquired, which can be collected through vehicle sensors such as speed sensors, turn signals, and lights. Then, the driver's eye is tracked to obtain eye-tracking data, for example, through a camera or other vision devices. Navigation data in the driving scenario is also acquired. Finally, the vehicle driving data, eye-tracking data, and navigation data are aligned based on timestamps to obtain the environmental perception data.

[0047] Specifically, regarding the above-mentioned multi-source data collection process, such as... Figure 4 As shown, Figure 4 This diagram illustrates another execution flow for one embodiment of this specification. It shows a data acquisition and preprocessing process that begins with multi-source driving data. Raw data is first collected from three input sources: output signals from the Advanced Driver Assistance System (ADAS) (vehicle speed, following distance, distance to other vehicles, lane markings), output signals from the Driver Monitoring System (DMS) (eye gaze coordinates, gaze duration, blink frequency), and navigation signals (intersection distance, road type, traffic flow). Data preprocessing is then performed through timestamp alignment, coordinate system unification, and outlier filtering to eliminate temporal and format differences between data points. Finally, aligned feature vectors are generated, providing standardized input for subsequent model calculations.

[0048] It is understandable that the above data collection process is applied to Figure 3 The processing logic of the perception layer shown is the multi-source context data acquisition, which is responsible for collecting core input data and providing the original basis for context quantification.

[0049] For example, inputs include raw signals from vehicle sensors, cameras, and navigation systems.

[0050] Output: Aligned multi-source feature vectors.

[0051] ADAS signals: vehicle speed (0-200km / h), headway (0-5s), steering angular velocity (° / s).

[0052] DMS signal: The driver's line of sight is projected onto the screen as x, y, gaze duration (ms), and scan rate (Hz).

[0053] Navigation signals: distance to the next navigation action (m), intersection complexity (simple / complex), road class.

[0054] The above description of multi-source data is an example. The specific data composition and driving process can vary from the above example and are not limited here.

[0055] As can be seen, this embodiment acquires vehicle driving data through vehicle sensors to achieve real-time perception of vehicle dynamic behavior; at the same time, it tracks the driver's gaze through a camera to obtain gaze tracking data, thereby accurately capturing the driver's attention distribution; then it acquires navigation data of the vehicle in the driving scenario to predict the complexity of the road ahead; and finally, it aligns the vehicle driving data, gaze tracking data, and navigation data based on timestamps to obtain environmental perception data, achieving the fusion of three sources of information: vehicle status, driver status, and road environment, thereby improving the comprehensiveness and robustness of contextual perception.

[0056] 202. Based on environmental perception data, feature configuration is performed on the driver's attention needs in driving scenarios to obtain the driving situation tension.

[0057] In this embodiment, the quantification of the driving situation's tension using environmental perception data is essentially a description of the level of attention required. The level of attention required refers to the level of cognitive resources a driver is required to invest to ensure driving safety in a specific driving scenario. This level is determined by multiple factors, including vehicle speed, following distance, road complexity, and the driver's current state of distraction. A higher level of attention required indicates a stronger reliance on the driver's focus on the road and their actions, resulting in fewer cognitive resources available for non-driving tasks.

[0058] Correspondingly, Driving Situation Stress (DSS) is a comprehensive index calculated based on environmental perception data, which quantitatively represents the degree to which the current driving scenario occupies the driver's cognitive resources. Its value ranges from 0 to 1 and is divided into multiple stress levels by comparison with a threshold. This index integrates factors such as vehicle speed, following urgency, navigation operation complexity, and attention distraction; a higher value indicates a more stressful driving situation and a higher demand on the driver's attention.

[0059] In one possible scenario, the quantitative representation of driving situation tension can be based on the vectorized representation of multi-source data. That is, firstly, a preset dimension associated with the degree of attention required in the driving scenario is obtained; then, a weight matrix corresponding to the driving scenario is obtained; and internal and / or external factors are weighted and fused based on the weight matrix to obtain target feature values; then, threshold intervals are compared based on the target feature values ​​to determine the driving situation tension of the driving scenario.

[0060] The preset dimension is configured based on internal and external factors. The internal factors include at least one of vehicle speed parameters and attention parameters, and the external factors include at least one of vehicle distance parameters and road condition parameters. That is, the vectorization process can be based on a combination of one or more of the above factors.

[0061] Understandably, internal factors refer to the characteristic dimensions used to describe the state of the vehicle and the driver when calculating the stress of a driving situation. These mainly include vehicle speed parameters and attention parameters. Vehicle speed parameters reflect the speed of the vehicle's movement, while attention parameters, based on eye-tracking data, reflect the proportion of time the driver's gaze is off the road or the rate at which the driver scans the screen. Together, they characterize the cognitive load originating from within the vehicle and from the driver themselves in a driving scenario.

[0062] Correspondingly, external factors refer to the characteristic dimensions used to describe the external environment in which the vehicle is located when calculating the stress of a driving situation. These mainly include distance parameters and road condition parameters. Distance parameters reflect the urgency of following the vehicle ahead based on the distance to the vehicle in front, while road condition parameters reflect the difficulty of road tasks such as intersection complexity and distance to the next action based on navigation data. Together, they characterize the cognitive load originating from the external environment in a driving scenario.

[0063] As can be seen, this embodiment obtains a preset dimension related to the degree of attention demand, including internal and external factors such as vehicle speed parameters, attention parameters, vehicle distance parameters, and road condition parameters, to achieve a structured analysis of key factors affecting the driver's cognitive load. Then, it obtains a weight matrix corresponding to the driving scenario to achieve a differentiated expression of the importance of each factor under different scenarios. Next, it performs weighted fusion of internal and external factors based on the weight matrix to obtain the target feature value, realizing the numerical transformation of multi-dimensional heterogeneous data into a single continuous scalar. Finally, it compares threshold intervals based on the target feature value to determine the driving situation tension, thereby discretizing continuous values ​​into an operable tension level and improving decision-making efficiency.

[0064] In another possible scenario, the determination of driving situation tension can be based on the hit rate of an interval threshold. To avoid frequent level jumps, a switching hysteresis interval is set. First, the target feature value is compared with a preset interval threshold. If the target feature value is within the hysteresis interval, the configuration duration of the driving situation tension is detected. The hysteresis interval is configured based on the boundary value of the preset interval threshold. If the configuration duration meets preset conditions, the tension level corresponding to the hysteresis interval is determined as the driving situation tension of the driving scenario. For example, a switching hysteresis interval of ±0.05 can be set, and the level maintenance time must exceed 200ms (preset condition).

[0065] As can be seen, this embodiment achieves a preliminary determination of the tension level by comparing the target feature value with a preset interval threshold. If the target feature value is in the hysteresis interval, the configuration duration of the driving situation tension is detected. This hysteresis interval is configured based on the threshold boundary value to introduce a decision dead zone near the boundary to suppress noise fluctuations. If the configuration duration meets the preset conditions, the tension level corresponding to the hysteresis interval is determined as the driving situation tension, realizing a delayed confirmation mechanism for level switching, improving the stability of rendering parameter adjustment, and preventing frequent image quality oscillations.

[0066] Combining the above quantification process of driving situation tension, we can obtain Figure 5 The execution flow shown is as follows: Figure 5 This diagram illustrates another execution flow for one embodiment of this specification. It shows the calculation process for the Driving Situation Stress Level (DSS). First, input features are extracted from vehicle speed, road conditions, navigation, and driver dimensions, and converted into normalized vehicle speed factors, following urgency factors, operational complexity factors, and attention distraction factors, respectively. Then, each factor is linearly weighted and summed using weight matrices W1-W4, with nonlinear compensation optimization applied to the result. Finally, after threshold judgment and hysteresis processing, stable L1-L4 levels of Driving Situation Stress (DSS) are output, achieving a quantitative classification of driving risk and complexity.

[0067] Specifically, the calculation process of the DSS level is applied to Figure 3 the quantization layer of the architecture shown, that is, the calculation of driving situation tension, which is used to fuse multi-source features into a single quantization index, that is, driving situation tension (DSS), and is divided into four levels.

[0068] Exemplarily, the following calculation process can be obtained: Input: Aligned multi-source feature vectors.

[0069] Output: DSS index (0 - 1) and corresponding level (L1 - L4).

[0070] Quantization rule (feature processing process of preset dimensions): For internal factors, including vehicle speed factor (vehicle speed parameter, F_speed), for example, vehicle speed < 30km / h: F_speed = 0.3 (low speed, flexible operation); while 30 ≤ vehicle speed ≤ 80km / h: F_speed = 0.6 (medium speed, stable control required); vehicle speed > 80km / h: F_speed = 0.9 (high speed, high response requirement). And the attention distraction factor (attention parameter, F_distraction), which can calculate the proportion of the duration when the driver's line of sight leaves the road based on DMS: distraction proportion < 10%: F_distraction = 0.2; 10% ≤ distraction proportion < 30%: F_distraction = 0.5; distraction proportion ≥ 30%: F_distraction = 0.9.

[0071] For external factors, including following vehicle urgency factor (vehicle distance parameter, F_follow), which is calculated based on the time - to - collision TTC of the preceding vehicle: TTC > 3s: F_follow = 0.2 (sufficient safety distance); 1s < TTC ≤ 3s: F_follow = 0.6 (attention required); TTC ≤ 1s: F_follow = 1.0 (emergency state). And the operation complexity factor (road condition parameter, F_navi). For example, straight or simple road condition: F_navi = 0.2; turning at ordinary intersections: F_navi = 0.5; complex interchange / ramp: F_navi = 0.8; when the distance to the navigation action < 100m, F_navi = 1.0. <00​​​​​​​​​​​​ The weight configuration is as follows: w1=0.25, w2=0.30, w3=0.25, w4=0.20. This is just an example, and the specific weight values ​​can be dynamically adjusted according to the actual scenario.

[0073] After obtaining the comprehensive DSS, i.e., the driving situation tension level, the level can be divided according to the interval to which the data belongs. The specific division rules are shown in Table 1.

[0074] Table 1: Rules for Classifying Driving Situation Stress Levels by DSS In addition, to avoid frequent level changes, the hysteresis processing in the above embodiments can be adopted, that is, setting a switching hysteresis interval (±0.05) and the level maintenance time needs to exceed 200ms.

[0075] 203. Determine the driver's gaze area for multiple screens in the vehicle configuration, and determine the gaze area priority for each screen based on the gaze area.

[0076] In this embodiment, the Gaze Priority Zone (GPZ) refers to the order in which different screens or different areas within a screen are allocated rendering resources, determined based on the driver's gaze tracking data. When the driver's gaze is projected onto a screen, that screen is marked as the gaze area and enjoys a higher priority, while screens that are not gazed at have a lower priority. In addition, when multiple screens are gazed at simultaneously or when resource arbitration is required, a basic priority order among the instrument panel screen, the central control screen, and the passenger screen can be preset.

[0077] Specifically, the process of determining the priority of each screen's gaze area based on the gaze region can begin with acquiring and mapping gaze tracking data. This involves using an infrared or visible light camera in the driver monitoring system to capture the driver's facial image and eye features in real time. The driver's gaze direction vector in three-dimensional space is then calculated using the pupil-corneal reflection method or a three-dimensional gaze estimation model. This gaze vector is then spatially transformed using the pre-calibrated physical coordinate systems of the various displays (instrument panel, center console, passenger screen, and rear screen) within the cockpit to obtain the projected coordinates of the gaze on each screen plane. If the projected coordinates fall within the boundary of a screen's display area, that screen is determined to be the driver's current gaze screen. If the projected coordinates fall within the boundaries of multiple screens or outside all screen boundaries, a unique gaze screen is determined according to preset rules (such as the longest gaze duration or proximity to the screen center), or it is marked as a non-gaze area.

[0078] Next, the priority of the gaze area is quantified and assigned. That is, after determining the screen the driver is currently looking at, the system assigns that screen the highest gaze area priority. Furthermore, to handle multi-screen resource contention scenarios, the system pre-sets basic priority weights for screen types: for example, the instrument panel displays safety-critical information such as vehicle speed and warnings, and has the highest basic priority; the central control screen displays navigation and vehicle settings, and has the next highest basic priority; the passenger-side screen and rear-seat screens display entertainment information, and have the lowest basic priority. If the driver is currently looking at the central control screen, its final priority is equal to the sum of its gaze priority and its medium basic priority, higher than the pure basic priority of an unviewed instrument panel screen, but lower than the instrument panel screen's priority when it is being viewed. Through this combined assignment method, the system can temporarily increase the resource allocation weight of a non-safety-critical screen when the driver actively focuses on it, while maintaining basic protection for the instrument panel screen.

[0079] This process then outputs the gaze region priority. Each screen corresponds to a gaze region priority value, ranging from, for example, 0 to 1. The priority of a gazed screen is greater than 0.8, the priority of an ungazed instrument panel screen is no less than 0.5, and the priority of an ungazed entertainment screen is less than 0.3. This priority value serves as a key basis for subsequent adjustments to rendering parameters: when generating target rendering parameters, the system determines whether to increase the preset rendering parameters based on the priority (e.g., increasing the frame rate to 60fps if the priority is greater than 0.8), and determines the order of degradation during multi-screen resource conflict arbitration (the screen with the lowest priority is degraded first). Through this execution process, a clear spatial attention guide is provided for rendering scheduling.

[0080] 204. Determine the preset rendering parameters corresponding to the tension level of the driving situation, and adjust the preset rendering parameters according to the priority of the gaze area to obtain the target rendering parameters corresponding to each screen.

[0081] In this embodiment, the preset rendering parameters are a rendering parameter mapping table, a set of rules used to map the DSS index to parameters such as frame rate, resolution, and brightness for each screen. Specifically, it is a pre-calibrated and stored baseline image quality configuration for each screen without considering the priority of the gaze area, for each driving situation's tension level. This includes parameters such as frame rate, resolution, and brightness. The preset rendering parameters provide a basic mapping from tension level to rendering output; for example, the passenger screen uses a lower frame rate at low tension levels, while the instrument panel screen maintains a high frame rate at high tension levels.

[0082] Correspondingly, target rendering parameters refer to the actual image quality configuration obtained by making targeted adjustments based on the priority of the gaze region, based on the preset rendering parameters, and finally sent to the image processor for execution. Target rendering parameters increase the parameters of the gaze region to improve rendering quality, while maintaining or further reducing the parameters of the non-gaze region, thereby achieving on-demand allocation.

[0083] Specifically, the process of determining the target rendering parameters can begin by first determining the preset rendering parameters corresponding to the driving situation tension; then determining the gaze area and non-gaze area based on the gaze area priority; and determining the function type corresponding to the gaze area; and then, based on the function type corresponding to the gaze area and the driving situation tension, improving the preset rendering parameters corresponding to the gaze area to obtain the target rendering parameters for each screen.

[0084] For example, firstly, preset rendering parameters corresponding to the driving situation's tension are determined. Then, based on the priority of the gaze area, the driver's current gaze area and non-gaze area are determined, and the function type of the gaze area is further identified (e.g., navigation map display area, instrument speed display area, or entertainment content display area). Based on this function type and the current driving situation's tension, the preset rendering parameters corresponding to the gaze area are increased (e.g., increasing the frame rate from 30fps to 60fps), generating target rendering parameters for each screen. This mechanism ensures that key information areas that the driver focuses on during tense driving scenarios receive higher rendering quality, while non-gaze areas maintain lower rendering parameters, prioritizing the smooth display of safety-related content without increasing the overall GPU load.

[0085] In one possible scenario, referring to the example above, we can obtain... Figure 6 The execution flow shown is as follows: Figure 6 This diagram illustrates another execution flow for one embodiment of this specification. It shows the rendering parameter decision-making process. This process dynamically generates a rendering strategy based on the DSS level and driver status. First, using the DSS level, gaze coordinates, and feedback data as input, it calculates the intersection points of the gaze with each screen, determines the gazed screen, and assigns priority weights to complete gaze region identification. Then, it looks up basic rendering parameters such as frame rate, resolution, and brightness based on the DSS level, and performs differentiated enhancements for gazed screens (instrument screen maintained / enhanced, central control screen partially upgraded) and non-gazed screens (parameter downgraded). Finally, it summarizes the GPU resources required for the target parameters of each screen and compares them with the feedback GPU load threshold. If the threshold is exceeded, unified arbitration is performed; otherwise, the target rendering parameters for each screen are directly issued.

[0086] Specifically, the above process can be applied to Figure 3The decision layer shown is used for rendering parameter mapping and multi-screen collaborative scheduling. That is, based on the driving situation tension (DSS), the driver's gaze area, and the GPU load status fed back by the execution layer, it dynamically generates the optimal rendering parameters for each display screen and handles resource competition between multiple screens.

[0087] For example, for the decision-making layer, its inputs include: DSS level (L1~L4); the projection coordinates of the driver's line of sight on the screen (from DMS); the current rendering status of each screen (frame rate, resolution, brightness); and execution layer feedback data: GPU real-time load (%), actual frame rate compliance rate of each screen, and chip temperature.

[0088] The output includes: target rendering parameters for each screen (frame rate, resolution, brightness); resource conflict arbitration results (degradation scheme when the GPU is overloaded).

[0089] Specifically, the gaze area identification process involves projecting the gaze vector output by the DMS onto the physical coordinate system of each display screen in the cockpit to determine the screen the driver is currently looking at. If the gaze falls outside the screen, it is marked as "unfocused screen".

[0090] The system can also configure attention priority weights: instrument panel screen > central control screen > passenger screen, which is used to favor subsequent resource allocation, i.e., to increase the priority weight of safety-related screens.

[0091] In addition, for the invocation of preset rendering parameters, i.e. the basic parameter mapping process, the basic rendering parameters of each screen can be obtained from a predefined mapping table based on the DSS level (see Table 2). The mapping table is generated based on a large amount of calibration data, taking into account both security and energy-saving requirements.

[0092] Table 2: Basic Rendering Parameter Mapping Table Furthermore, for gaze region enhancement, which is the process of improving the preset rendering parameters corresponding to the gaze region based on the function type and driving situation tension, the following example can be obtained: When DSS≥L3 and the driver is looking at the central control screen, local high-quality rendering is applied to the gaze area (such as the navigation map display area) (the frame rate is increased to 60fps, and the resolution remains the original), while the non-gaze area is still executed according to the basic parameters.

[0093] If the driver is looking at the instrument panel, regardless of the DSS level, the instrument panel will maintain the highest image quality (60fps / native / 100%).

[0094] If you are looking at the passenger screen (which usually happens when the car is parked or the passenger is operating the system), the passenger screen will be rendered according to the L1 standard, while the central control screen can be downgraded appropriately.

[0095] As can be seen, this embodiment achieves rapid anchoring of the basic image quality level of each screen by determining the preset rendering parameters corresponding to the driving situation tension; then, it determines the gaze area and non-gaze area according to the gaze area priority, achieving accurate spatial segmentation of the driver's visual attention range; next, it determines the function type corresponding to the gaze area, realizing the identification of the task criticality of different screens; then, based on the function type of the gaze area and the driving situation tension, it enhances the preset rendering parameters corresponding to the gaze area to obtain the target rendering parameters, achieving a two-layer adjustment of the basic situation level and gaze enhancement, improving user experience while ensuring safety and achieving energy saving in non-gaze areas.

[0096] In another possible scenario, considering that multi-screen collaborative display requires GPU support, resource shortages may occur. In this case, the predicted information of the vehicle's graphics processor configuration can be estimated based on the target rendering parameters; then, the graphics processor load information can be obtained; if the predicted information exceeds the safe capacity compared to the load information, the parameters can be adjusted according to the priority of the gaze area to reduce the target rendering parameters.

[0097] Specifically, determining the safe capacity involves estimating the required GPU computing power based on the target parameters of each screen and comparing it with real-time GPU load and temperature data fed back from the execution layer. For example, if the estimated resource requirement exceeds the GPU capacity threshold (e.g., 85%), or the temperature exceeds the safe limit, an arbitration mechanism is initiated to adjust the parameters.

[0098] The parameter adjustment process prioritizes keeping the rendering parameters of the instrument panel unchanged; secondly, it maintains the image quality of the viewing area of ​​the central control screen while reducing the parameters of the non-viewing area or the non-viewing screen.

[0099] Furthermore, if the limits are still exceeded, the frame rate or resolution of the non-focused areas of the passenger screen and the central control screen will be reduced sequentially. The arbitration result and the target parameters will then be sent to the execution layer.

[0100] As can be seen, after generating the target rendering parameters, this embodiment estimates the graphics processor's load based on the target rendering parameters, thereby achieving predictive calculation of the graphics processor's load. Then, it obtains the real-time load information of the graphics processor to achieve immediate perception of the actual operating status of the hardware. If the predicted information exceeds the safe capacity compared to the load information, the parameters are adjusted according to the priority of the gaze area to reduce the target rendering parameters, thereby achieving an overload protection process of priority arbitration and active load reduction, preventing the graphics processor from overloading or overheating, and ensuring the stability of critical information rendering and driving safety in high-load scenarios.

[0101] 205. Perform rendering operations based on the target rendering parameters to display content on each screen in the vehicle.

[0102] In this embodiment, rendering based on target rendering parameters means sending parameters such as frame rate, resolution, and brightness, determined after mapping situational tension levels and adjusting gaze area priority, to the image processor. The image processor then configures the rendering pipeline according to the parameters corresponding to each screen, generates the display frame buffer content for each screen, and outputs it to the corresponding physical display screen for refresh display through the display interface. This process ensures that the instrument panel, central control screen, passenger-side screen, and rear screen each operate independently according to the final optimized rendering parameters. The screen in the gaze area receives higher rendering quality, while screens in non-gaze areas or low-tension scenarios operate at lower frame rates or resolutions. This ensures the visibility of key information in front of the driver and at the gaze point while reducing the unnecessary computational load on the graphics processor and overall power consumption.

[0103] In addition, since the parameter configuration may deviate from the actual display process due to hardware status, real-time monitoring and feedback can be performed. This involves collecting monitoring data for each screen based on a preset period; then determining the execution achievement parameters, load parameters, and power consumption parameters based on the monitoring data; and obtaining feedback signals by comparing the execution achievement parameters, load parameters, and power consumption parameters with the adjustment strategy; and finally adjusting the target rendering parameters based on the feedback signals.

[0104] Specifically, the monitoring and feedback process is as follows: Figure 7 As shown, Figure 7 This diagram illustrates another execution flow for one embodiment of this specification. The diagram shows the execution layer and closed-loop feedback process, which is the execution closed loop of in-vehicle multi-screen rendering. After receiving rendering parameters for each screen from the decision layer, the rendering control modules of the instrument panel, central control screen, and passenger-side screen execute rendering commands respectively. Simultaneously, the GPU resource monitoring module uniformly allocates hardware resources and monitors resource usage in real time. The monitoring data is returned to the decision layer in the form of "resource usage feedback," enabling dynamic adjustment of the rendering strategy and ensuring stable adaptation between multi-screen rendering and GPU load.

[0105] This execution process is applied to Figure 3 The execution layer shown is used for rendering control and effect feedback. It is used to convert the parameter instructions of the decision layer into actual screen rendering control and monitor the execution effect in real time, forming a closed-loop feedback, which allows the decision layer to dynamically optimize subsequent decisions.

[0106] For example, the inputs to the execution layer include: rendering parameters for each screen target (frame rate, resolution, brightness); and the arbitrated resource allocation scheme (optional).

[0107] The output includes: the actual rendered image of each screen; feedback data packets: GPU load (%), actual frame rate of each screen, frame rate compliance rate, chip temperature, and estimated power consumption.

[0108] Specifically, regarding the monitoring and feedback process, i.e., the feedback closed-loop mechanism, the execution layer collects monitoring data at fixed intervals (e.g., 100ms), packages it into feedback data packets, and sends them to the decision-making layer. In the next round of decision-making, the decision-making layer uses the feedback data to adjust subsequent scheduling; that is, the adjustment strategy includes: If the GPU load continues to approach the threshold, the decision-making level will tighten the leniency of resource arbitration (for example, lowering the "resource usage threshold" from 85% to 80%) to proactively prevent overload.

[0109] If the frame rate of a screen falls below 95% (the target frame rate has not been consistently achieved), the decision-making team will reassess the parameter mapping of that screen and, if necessary, reduce its target frame rate in exchange for stability.

[0110] If the temperature is too high, the decision-makers will prioritize implementing aggressive energy-saving strategies such as pausing rendering on the passenger screen until the temperature drops.

[0111] Through this feedback loop, the system achieves configuration from open-loop commands to closed-loop adaptive configuration, ensuring a balance between safety and performance under various operating conditions.

[0112] As can be seen, this embodiment achieves real-time quantitative feedback on the rendering effect of the execution layer by collecting monitoring data from each screen based on a preset cycle. Then, it determines the execution achievement parameters, load parameters, and power consumption parameters based on the monitoring data, achieving an abstract transformation from the original monitoring values ​​to evaluation indicators. Next, it obtains feedback signals by comparing the execution achievement parameters, load parameters, and power consumption parameters with the adjustment strategy, realizing the conditional triggering of adaptive rules. Finally, it adjusts the target rendering parameters based on the feedback signals, achieving closed-loop adaptive optimization, continuously correcting subsequent decisions to adapt to factors such as hardware aging and changes in ambient temperature, improving the system's robustness and energy efficiency under different operating conditions. This solves the contradiction between high performance and low power consumption in intelligent cockpit multi-screen display systems. By deeply coupling driving scenarios, driver attention, and display rendering, it achieves fine-grained GPU resource scheduling with safety priority on demand, maximizing energy efficiency while ensuring driving safety.

[0113] In summary, the above embodiments utilize driving scenario-driven rendering decisions, taking the tension of the driving scenario as the core basis for display rendering, thus ensuring that safety requirements determine image quality allocation. Furthermore, it achieves enhanced priority for gaze areas, meaning that by combining DMS eye tracking, higher rendering quality is given to the screen area currently being focused on by the driver, while energy is saved on non-gaze areas. It also implements multi-screen collaborative resource pooling, treating GPU computing power as a global resource and dynamically allocating it across screens, prioritizing safety-critical displays. Finally, it implements a refined hierarchical strategy, based on four DSS levels and gaze priority, enabling multi-dimensional collaborative adjustment of frame rate (60 / 45 / 30 / 15fps), resolution, and brightness.

[0114] In one possible scenario, the technical effects comparison shown in Table 3 can be obtained by adopting the steps of the above embodiments.

[0115] Table 3: Comparison of Technical Effects of This Embodiment Accordingly, by adopting the steps of the above embodiments, the differences in the vehicle display process in typical driving scenarios can be obtained as shown in Table 4 below.

[0116] Table 4: Comparison of Typical Scene Effects As can be seen from the table above, the comparative effects of this solution and the traditional solution are summarized in four typical driving scenarios: In the L1 low-stress scenario of high-speed cruising, the traditional solution wastes power by making the passenger screen run at 60fps, while this solution saves energy by reducing the frame rate of the passenger screen and maintaining smooth map display on the central control screen; In the L3 high-stress scenario of complex intersections, the traditional solution maintains the original image quality in full screen, causing GPU overheating, while this solution pauses rendering on the passenger screen and provides high image quality for the area of ​​focus on the central control screen; In the L2 medium-stress scenario of congested driving, the traditional solution maintains a high refresh rate on the instrument panel, but the information content is simple, resulting in wasted resources, while this solution appropriately reduces the frame rate of the instrument panel to extend battery life; In the nighttime driving scenario, the traditional solution has a fixed screen brightness that is glaring, while this solution adaptively adjusts the brightness according to the situation, balancing comfort and energy saving. Overall, this solution achieves refined rendering based on stress level and attention in all scenarios, resolving the contradiction between energy waste and safety experience.

[0117] Therefore, this embodiment realizes the process of intelligent cockpit display system from fixed image quality to situational adaptation through driving situation tension measurement model, gaze area priority recognition, and multi-screen collaborative rendering scheduling. It maximizes energy saving effect while ensuring driving safety and realizes refined energy consumption management of intelligent cockpit.

[0118] In summary, this embodiment acquires environmental perception data of the vehicle in a driving scenario to achieve a digital description of the current driving situation. Then, based on the environmental perception data, it configures features to determine the driver's attention needs to obtain the driving situation tension, thus transforming vague attention needs into quantifiable indicators. Next, it determines the driver's gaze areas on multiple screens to establish the priority of each screen's gaze area, achieving spatial localization of visual attention. Then, it determines the preset rendering parameters corresponding to the driving situation tension and adjusts them according to the gaze area priority to obtain the target rendering parameters, achieving dynamic adaptation of the rendering strategy to the situation tension and attention priority. Finally, it executes rendering operations based on the target rendering parameters to display content on each screen, achieving safety-first, on-demand, and refined multi-screen control, ensuring the integrity of key content displayed in the vehicle, and improving vehicle driving safety.

[0119] It should be noted that the various embodiments described in this specification emphasize the parts that differ from other embodiments, and the embodiments can be explained by comparison with each other. Any combination of the various embodiments described in this specification based on general technical knowledge is covered within the scope of this specification.

[0120] In one exemplary embodiment of this specification, a display device 800 for a vehicle screen is also provided, such as... Figure 8 As shown, Figure 8 A functional block diagram of a vehicle screen display device provided in one embodiment of this specification, the display device 800 including: The acquisition unit 801 is used to acquire environmental perception data of the vehicle in the driving scenario; The processing unit 802 is used to configure features based on the environmental perception data to determine the driver's attention needs in the driving scenario, so as to obtain the driving situation tension of the driving scenario. The processing unit 802 is further configured to determine the driver's gaze area on multiple screens configured in the vehicle, so as to determine the gaze area priority corresponding to each screen through the gaze area. The processing unit 802 is further configured to determine the preset rendering parameters corresponding to the driving situation tension, and adjust the preset rendering parameters according to the gaze area priority to obtain the target rendering parameters corresponding to each screen. Display unit 803 is used to perform rendering operations based on the target rendering parameters in order to display content on each screen in the vehicle.

[0121] Optionally, in one possible embodiment, the acquisition unit 801 is specifically used to acquire vehicle driving data in the driving scenario; The acquisition unit 801 is specifically used to perform eye tracking on the driver in order to obtain eye tracking data; The acquisition unit 801 is specifically used to acquire navigation data of the vehicle in the driving scenario; The acquisition unit 801 is specifically used to align the vehicle driving data, the eye tracking data, and the navigation data based on timestamps to obtain the environmental perception data.

[0122] Optionally, in one possible embodiment, the processing unit 802 is specifically used to obtain a preset dimension associated with the degree of attention demand in the driving scenario. The preset dimension is configured based on internal factors and external factors. The internal factors include at least one of vehicle speed parameters and attention parameters, and the external factors include at least one of vehicle distance parameters and road condition parameters. The processing unit 802 is specifically used to obtain the weight matrix corresponding to the driving scenario; The processing unit 802 is specifically used to perform weighted fusion of the internal factors and / or the external factors based on the weight matrix to obtain the target feature value; The processing unit 802 is specifically used to perform threshold range comparison based on the target feature value in order to determine the driving situation tension of the driving scenario.

[0123] Optionally, in one possible embodiment, the processing unit 802 is specifically used to compare the target feature value with a preset interval threshold. The processing unit 802 is specifically used to detect the configuration duration of driving situation tension if the target feature value is in the hysteresis interval, wherein the hysteresis interval is configured based on the boundary value of the preset interval threshold. The processing unit 802 is specifically used to determine the tension level corresponding to the hysteresis interval as the driving situation tension level of the driving scenario if the configuration duration meets the preset conditions.

[0124] Optionally, in one possible embodiment, the processing unit 802 is specifically used to determine preset rendering parameters corresponding to the driving situation tension. The processing unit 802 is specifically used to determine the gaze region and non-gaze region according to the gaze region priority. The processing unit 802 is specifically used to determine the function type corresponding to the gaze region; The processing unit 802 is specifically used to improve the preset rendering parameters corresponding to the gaze area based on the function type corresponding to the gaze area and the driving situation tension, so as to obtain the target rendering parameters corresponding to each screen.

[0125] Optionally, in one possible embodiment, the processing unit 802 is specifically used to estimate the graphics processor's prediction information for the vehicle configuration based on the target rendering parameters. The processing unit 802 is specifically used to obtain the load information of the graphics processor; The processing unit 802 is specifically used to adjust the parameters according to the gaze region priority if the prediction information exceeds the safe capacity compared to the load information, so as to reduce the target rendering parameters.

[0126] Optionally, in one possible embodiment, the processing unit 802 is specifically used to collect monitoring data corresponding to each screen based on a preset period. The processing unit 802 is specifically used to determine the execution achievement parameters, load parameters, and power consumption parameters based on the monitoring data. The processing unit 802 is specifically used to obtain a feedback signal by comparing the execution achievement parameters, the load parameters, and the power consumption parameters with the adjustment strategy; The processing unit 802 is specifically used to adjust the target rendering parameters based on the feedback signal.

[0127] Specifically, in this embodiment, the acquisition unit, processing unit, and display unit can correspond to physical components. For example, the processing unit can be a processing module such as a CPU, GPU, or FPGA, while the display unit can be a display module such as a screen at different locations on the vehicle. The specific physical component can be any component or combination of components with the above functions. The specific method depends on the actual scenario and is not limited here.

[0128] The aforementioned display device acquires environmental perception data of the vehicle in a driving scenario to achieve a digital description of the current driving situation. Then, based on the environmental perception data, it configures features to determine the driver's attention needs to obtain the driving situation tension, thus transforming vague attention needs into quantifiable indicators. Next, it determines the driver's gaze areas on multiple screens to establish the priority of each screen's gaze area, achieving spatial positioning of visual attention. Then, it determines the preset rendering parameters corresponding to the driving situation tension and adjusts them according to the gaze area priority to obtain the target rendering parameters, achieving dynamic adaptation of the rendering strategy to the situation tension and attention priority. Finally, it executes rendering operations based on the target rendering parameters to display content on each screen, achieving safety-first, on-demand, and refined multi-screen control, ensuring the integrity of key content displayed in the vehicle, and improving vehicle driving safety.

[0129] Specific limitations regarding the display device of the vehicle screen can be found in the limitations regarding the display method of the vehicle screen above, and will not be repeated here. Each unit module in the aforementioned vehicle screen display device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0130] In addition, in one exemplary embodiment of this specification, a vehicle is also provided, such as Figure 9 As shown, Figure 9 This is a structural schematic diagram of a vehicle provided for one embodiment of this specification.

[0131] For example, vehicle 900 and Figure 1 Vehicle 130 in the text refers to the same vehicle.

[0132] For example, such as Figure 9 As shown, the vehicle 900 includes a memory 910 and a processor 920, wherein the memory 910 stores executable program code 930, and the processor 920 is used to call and execute the executable program code 930 to perform a method for displaying a vehicle screen.

[0133] For example, the memory 910 can be used to store related programs of the vehicle screen display method provided in the embodiments of this application; the processor 920 can call the related programs of the vehicle screen display method stored in the memory 910 to execute the vehicle screen display method of the embodiments of this application; for example, acquiring environmental perception data of the vehicle in a driving scenario; configuring features based on the environmental perception data to determine the driver's attention needs in the driving scenario to obtain the driving situation tension; determining the driver's gaze areas for multiple screens configured in the vehicle, so as to determine the gaze area priority corresponding to each screen through the gaze areas; determining the preset rendering parameters corresponding to the driving situation tension, and adjusting the preset rendering parameters according to the gaze area priority to obtain the target rendering parameters corresponding to each screen; and performing rendering operations based on the target rendering parameters to display content on each screen in the vehicle.

[0134] This embodiment can divide the device into functional modules based on the above method example. For example, each module can correspond to a separate function, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods.

[0135] When each functional module is divided according to its corresponding function, the device may further include an acquisition module, a prediction module, a determination module, and an output module. It should be noted that all relevant content regarding the steps involved in the above method embodiments can be referenced to the functional descriptions of the corresponding functional modules, and will not be repeated here.

[0136] It should be understood that the device provided in this embodiment is used to execute the above-described method for displaying a vehicle screen, and therefore can achieve the same effect as the above-described implementation method.

[0137] When using an integrated unit, the device may include a processing module and a storage module. When the device is applied to a vehicle, the processing module can be used to control and manage the vehicle's movements. The storage module can be used to support the vehicle in executing program code, etc.

[0138] The processing module may be a processor or a controller, which can implement or execute various exemplary logic blocks, modules, and circuits as disclosed in this application. The processor may also be a combination of computing functions, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and microprocessors, etc., and the storage module may be a memory.

[0139] In addition, the device provided in the embodiments of this application may specifically be a chip, component or module. The chip may include a connected processor and a memory. The memory is used to store instructions. When the processor calls and executes the instructions, the chip can execute a vehicle screen display method provided in the above embodiments.

[0140] This application also provides a computer-readable storage medium storing computer program code, which, when executed on a computer, causes the computer to perform the aforementioned method steps to implement the vehicle screen display method provided in the above embodiments. The computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, Digital Video Discs (DVDs), Compact Disc Read-Only Memory (CD-ROMs), microdrives, and magneto-optical disks, read-only memory (ROMs), random access memory (RAMs), erasable programmable read-only memory (EPROMs), electrically erasable programmable read-only memory (EEPROMs), dynamic random access memory (DRAMs), video random access memory (VRAMs), flash memory devices, magnetic cards or optical cards, nanosystems (including molecular memory ICs), or any type of media or device suitable for storing instructions and / or data.

[0141] This application also provides a computer program product that, when run on a computer, causes the computer to perform the aforementioned related steps to implement the vehicle screen display method provided in the above embodiments.

[0142] The vehicle, computer-readable storage medium, computer program product or chip provided in this application are all used to execute the corresponding methods provided above. Therefore, the beneficial effects that can be achieved can be referred to the beneficial effects of the corresponding methods provided above, and will not be repeated here.

[0143] Through the above description of the embodiments, those skilled in the art will understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0144] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0145] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0146] The embodiments described above are merely illustrative of several implementation methods outlined in this specification. While the descriptions are specific and detailed, they should not be construed as limiting the scope of the solutions provided in this specification. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this specification, and these all fall within the scope of protection of this specification. Therefore, the scope of protection for this patent should be determined by the appended claims.

Claims

1. A display method for a vehicle screen, characterized in that, include: Acquire environmental perception data of the vehicle in the driving scenario; Based on the environmental perception data, the driver's attention needs in the driving scenario are configured with features to obtain the driving situation tension of the driving scenario. Determine the driver's gaze area for multiple screens configured in the vehicle, and determine the gaze area priority for each screen based on the gaze area. Determine the preset rendering parameters corresponding to the driving situation tension, and adjust the preset rendering parameters according to the gaze area priority to obtain the target rendering parameters corresponding to each screen; Rendering operations are performed based on the target rendering parameters to display content on each screen in the vehicle.

2. The method according to claim 1, characterized in that, The acquisition of environmental perception data of the vehicle in the driving scenario includes: Acquire vehicle driving data in the driving scenario; Eye tracking is performed on the driver to obtain eye tracking data; Obtain the navigation data of the vehicle in the driving scenario; The vehicle driving data, the eye-tracking data, and the navigation data are aligned based on timestamps to obtain the environmental perception data.

3. The method according to claim 1, characterized in that, The step of configuring features based on the environmental perception data to assess the driver's attention needs in the driving scenario, in order to obtain the driving situation tension level of the driving scenario, includes: Obtain a preset dimension related to the degree of attention demand in the driving scenario. The preset dimension is configured based on internal and external factors. The internal factors include at least one of vehicle speed parameters and attention parameters. The external factors include at least one of vehicle distance parameters and road condition parameters. Obtain the weight matrix corresponding to the driving scenario; The internal factors and / or external factors are weighted and fused based on the weight matrix to obtain the target feature value; The driving situation tension of the driving scenario is determined by comparing threshold intervals based on the target feature values.

4. The method according to claim 3, characterized in that, The step of comparing threshold intervals based on the target feature value to determine the driving situation tension of the driving scenario includes: The target feature value is compared with a preset interval threshold. If the target feature value is in the hysteresis interval, the configuration duration for detecting the tension of the driving situation is determined, and the hysteresis interval is configured based on the boundary value of the preset interval threshold. If the configuration duration meets the preset conditions, then the tension level corresponding to the hysteresis interval is determined as the driving situation tension of the driving scenario.

5. The method according to claim 1, characterized in that, The process of determining preset rendering parameters corresponding to the driving situation tension and adjusting these preset rendering parameters according to the gaze region priority to obtain target rendering parameters for each screen includes: Determine the preset rendering parameters corresponding to the tension level of the driving situation; The gaze region and non-gaze region are determined based on the gaze region priority. Determine the function type corresponding to the gaze region; Based on the function type corresponding to the gaze area and the driving situation tension, the preset rendering parameters corresponding to the gaze area are improved to obtain the target rendering parameters for each screen.

6. The method according to claim 5, characterized in that, The method further includes: Based on the target rendering parameters, the predicted information of the graphics processor for the vehicle configuration is estimated; Obtain the load information of the graphics processor; If the predicted information exceeds the safe capacity compared to the load information, the parameters are adjusted according to the gaze region priority to reduce the target rendering parameters.

7. The method according to any one of claims 1-6, characterized in that, The method further includes: Monitoring data for each screen is collected based on a preset cycle. Based on the monitoring data, determine the execution achievement parameters, load parameters, and power consumption parameters; Feedback signals are obtained by comparing the execution achievement parameters, the load parameters, and the power consumption parameters with the adjustment strategy; The target rendering parameters are adjusted based on the feedback signal.

8. A vehicle, characterized in that, The vehicles include: Memory, used to store executable program code; A processor is configured to call and run the executable program code from the memory, causing the vehicle to perform the vehicle screen display method as described in any one of claims 1 to 7.

9. An electronic device, characterized in that, The device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the display method of the vehicle screen according to any one of claims 1 to 7.

10. A computer program product, characterized in that, include: A computer program, when executed by a processor, implements the display method of the vehicle screen according to any one of claims 1 to 7.

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