A car intelligent roof lamp with natural sky light effect simulation, a control method and a control system

Abstract

This application relates to the field of automotive interior lighting control technology, specifically to an intelligent automotive dome light with simulated natural sky lighting effects, a control method, and a control system, comprising: constructing a sky scene feature library using a sky lighting effect measurement method; setting the scene corresponding to the vehicle's location as the measured sky scene; obtaining scene representation factors corresponding to the measured sky scene; sequentially calculating the feature similarity between the scene representation factors and each environment matching factor in the sky scene feature library; determining the target visual parameters corresponding to the scene representation factors based on feature similarity; setting the sampling frequency of each typical sky scene in the sky scene feature library; defining the sky scene attribution rules corresponding to the scene representation factors; matching the typical sky scenes corresponding to the scene representation factors; matching the sampling frequency of the measured sky scenes; and mapping the target visual parameters to the corresponding basic lighting driving parameters.

Description

Technical Field

[0001] This application relates to the field of automotive interior lighting control technology, specifically to an intelligent automotive dome light with simulated natural sky lighting effects, a control method, and a control system. Background Technology

[0002] As a core lighting component of automotive interiors, car roof lights are primarily installed at the front of the car's roof, providing basic lighting and assisting with reading, and are an important part of the driving and riding experience. Currently, most car roof lights on the market use traditional single-color white LEDs as their light source, and their control methods are limited to basic on / off control and simple brightness adjustment. The control logic is simple, the adjustment dimensions are singular, and the overall control system is designed only to "meet basic lighting needs," without considering the visual experience and emotional needs of drivers and passengers, nor does it have any control design related to simulating natural light effects. This makes them unable to adapt to the current trend of automotive interiors moving towards intelligence, comfort, and personalization.

[0003] Specifically, existing methods for controlling automotive dome lights have the following significant drawbacks: Firstly, the light effect control dimension is lacking. Existing control methods can only achieve the on / off switching and brightness adjustment of white light, without the control logic of color, color temperature, and spectral distribution. The core issue is that existing dome lights all use a single white LED light source, and the supporting control circuit is only designed with basic on / off and constant current voltage regulation modules. There is no control logic architecture for multi-color light source driving, dynamic color temperature adjustment, and spectral adaptation. Furthermore, a visual parameter system that characterizes the light effect of the natural sky has not been established. As a result, it is impossible to accurately control the color, color temperature, and spectral distribution of the light effect. Consequently, it is impossible to simulate the light effect characteristics of the natural sky at different times, such as warm orange at sunrise, blue at noon, and warm red at sunset. When the dome light is lit, it is only in the form of a single white light, resulting in a rigid and monotonous visual experience. It cannot create an immersive lighting environment that is close to nature for the occupants of the vehicle, nor can it match the emotional state of the occupants through changes in the color and brightness of the light effect, making it difficult to realize the emotional regulation and soothing value of the light effect. Secondly, the control method has a low level of intelligence. Existing dome lights are mostly controlled directly through physical switches, without dedicated intelligent control modules and scene matching algorithms. They cannot adaptively adjust the light effect based on external weather, time, ambient light, and other information, nor do they have preset natural sky scene light effect control modes. The core reason is that existing dome lights do not integrate dedicated intelligent control modules, environmental perception modules, and network communication modules. They lack corresponding scene matching algorithms and preset light effect mode control programs, and only use simple physical switches to control the power supply. They cannot collect environmental information such as external weather, time, and ambient light in real time, nor can they adaptively adjust and match the light effect based on environmental information. At the same time, there are no preset light effect control modes for natural sky scenes such as sunrise, sunset, and clear sky. The entire process relies on manual operation by drivers and passengers, which not only has poor flexibility in adapting to different usage scenarios, but also greatly reduces the convenience of daily operation. Thirdly, the light adjustment lacks smooth transition control. Existing control methods lack smooth transition control logic for light parameters when adjusting brightness or switching on / off, which easily leads to sudden changes in light. Furthermore, traditional dome lights lack targeted optical control, and direct viewing of the light-emitting surface can easily cause glare, causing eye discomfort for drivers and passengers, and may even distract the driver, affecting driving safety. The core reason is that existing control methods do not have a gradient smoothing adjustment algorithm for light parameters and lack logic to constrain the rate of change of lighting drive parameters. When adjusting brightness or switching on / off, the lighting drive parameters will undergo a step change, resulting in sudden changes in parameters such as brightness and color temperature. In addition, traditional dome lights lack coordinated control logic for optical control. The light source emits light directly without softening or scattering control design. The light is directly shone without effective optical processing, and direct viewing of the light-emitting surface can easily produce strong glare, which can cause visual fatigue and obvious discomfort for drivers and passengers, and may also distract the driver during driving, creating a driving safety hazard. Meanwhile, with the development of automotive intelligent technology, the needs of drivers and passengers for in-vehicle lighting have shifted from simple illumination to a combination of comfort and emotional value. The demand for automotive dome lights capable of simulating natural sky light effects and achieving intelligent control is increasingly urgent. However, existing automotive dome light control methods, due to the aforementioned shortcomings, cannot achieve accurate simulation and intelligent control of natural sky light effects, becoming a key issue restricting the development of intelligent automotive interior lighting. Therefore, we propose an intelligent automotive dome light with natural sky light effect simulation, a control method, and a control system. Summary of the Invention

[0004] The purpose of this application is to solve the problems of existing automotive dome light control methods, such as lack of light effect control dimension, low level of intelligence, lack of smooth transition in light adjustment which easily produces glare, inability to simulate natural sky light effect, lack of emotional value, poor adaptability and ease of operation, and potential driving safety hazards.

[0005] To achieve the above objectives, this application provides an intelligent car roof light with simulated natural sky light effects, including a lamp body, a touch switch panel, a PCB board, a full-color lamp board, a diffuser, a condenser, a mask, a full-spectrum LED, a reflector, and a control module circuit. The lamp body is an integral hollow load-bearing shell. The diffuser plate is fastened to the inside of the lamp body by screwing. The control module circuit adopts a snap-fit ​​structure to form a two-way tight fit with the diffuser plate and the inner wall of the lamp body. The diffuser plate and the control module circuit are tightly connected by limiting, and the control module circuit and the diffuser plate are internally arranged in the same layer. The full-color LED panel and the concentrator are screwed together to form an integrated optical light source assembly, and the full-spectrum LED and the reflector are screwed together to form another integrated optical light source assembly. The two integrated components of the full-color light panel and the condenser, and the full-spectrum LED and the reflector are fixedly installed inside the lamp body with screws and located below the diffuser. The PCB board is integrated inside the lamp body. The mask adapter fits over the front opening on the outside of the lamp body. The touch switch panel is tightly attached to the outer surface of the mask. The PCB board is electrically connected to the control module circuit, the full-color lamp board, and the full-spectrum LED, providing power supply and signal transmission channels for each electronic component. The control module circuit is also electrically connected to the touch switch panel.

[0006] A smart car roof light with simulated natural sky lighting effects includes: A sky scene feature library is constructed using the sky light effect measurement method. The sky scene feature library contains multiple typical sky scenes, and each typical sky scene is configured with multiple fixed environmental matching factors and benchmark visual parameters. When the vehicle's location is set, the corresponding scene is the measured sky scene, and the scene representation factor corresponding to the measured sky scene is obtained; Calculate the feature similarity between the scene representation factor and each environment matching factor in the sky scene feature library in turn; Determine the target visual parameters corresponding to the scene representation factors based on feature similarity; Set the sampling frequency for each typical sky scene in the sky scene feature library; define the sky scene attribution rules corresponding to the scene representation factors, match the typical sky scenes corresponding to the scene representation factors, and match the sampling frequency of the measured sky scenes; Establish a mapping relationship between baseline visual parameters and basic lighting driving parameters in the sky scene feature library, and map the target visual parameters to the corresponding basic lighting driving parameters based on the mapping relationship. Specifically, the baseline visual parameters... With basic lighting drive parameters The mapping relationship between them is as follows: ,in This is a conversion function from visual parameters to driving parameters.

[0007] As a further improvement to this technical solution, the sky scene feature library contains multiple typical sky scenes, each of which is configured with multiple fixed environment matching factors and baseline visual parameters. Specifically, the... In a typical sky scene, the first Environmental matching factors as follows: ; No. A typical sky scene, and environmental matching factors. The corresponding number A benchmark visual parameter as follows: ; in: m, This represents the total number of typical sky scenes; , This represents the total number of environmental matching factors and baseline visual parameters, with a one-to-one correspondence between the environmental matching factors and the baseline visual parameters. Environmental matching factor The total number of environmental features; As a reference visual parameter The total number of medium luminous efficacy features; = Environmental matching factor In a typical sky scene Next, the Quantitative identifiers corresponding to environmental characteristics Typical sky scene The Middle The original values ​​of the environmental features; For the first The weight coefficients of each environmental feature are given, and the sum of the weight coefficients of all environmental features is 1.

[0008] As a further improvement to this technical solution, the method for measuring sky light effect is as follows: Multi-dimensional field measurements of the real sky light environment were conducted under different geographical locations, time periods, and meteorological conditions, and environmental characteristics were recorded simultaneously. The collected continuous environmental features are divided into several typical sky scenes according to clustering rules. Stable and discriminative environmental matching factors are extracted for each typical sky scene. The benchmark visual parameters that are compatible with them are calibrated through in-vehicle light effect matching experiments. Finally, a sky scene feature library containing typical sky scenes, environmental matching factors, and benchmark visual parameters is formed. The clustering rule is as follows: based on the key features of the sky light environment, calculate the scene similarity between different scenes, judge the fit of scene features, classify scenes with small feature differences into the same category, and classify scenes with large feature differences into different categories.

[0009] As a further improvement to this technical solution, the scene representation factor Matching factors with the environment The feature similarity between them is as follows: ; in, = Scene characterization factor The vector magnitude, Environmental matching factor The vector magnitude.

[0010] As a further improvement to this technical solution, the scene representation factor Corresponding target visual parameters for: If scene characterization factor Matching factors with the environment Feature similarity between In this case, the environment matching factor is directly retrieved from the sky scene feature library. Corresponding baseline visual parameters As a scene representation factor Target visual parameters ; If scene characterization factor If the similarity between the scene and all environmental matching factors in the sky scene feature library is not equal to 1, then the scene representation factor is retrieved. The feature with the highest similarity to all environmental matching factors, and the adjacent environmental matching factors Environmental matching factor ; Bilinear interpolation was used to evaluate the environmental matching factor. Environmental matching factor Corresponding baseline visual parameters Reference visual parameters Perform bilinear interpolation to obtain the scene representation factor. Corresponding target visual parameters: ; in: This is the difference weight.

[0011] As a further improvement to this technical solution, the typical sky scene is defined. corresponding sampling frequency : With typical sky scenes Using all environmental matching factors as constraints, retrieve typical sky scenes. All environmental matching factors Based on mapping all environmental matching factors Corresponding basic lighting drive parameters Analyze all basic lighting driving parameters in sequence Adjustment time between Select the maximum adjustment duration As a typical sky scene Corresponding minimum sampling frequency ; Calculate typical sky scenes All environmental matching factors Corresponding dimensional dynamic features ; Based on typical sky scenes minimum sampling frequency Dimensional dynamic features Set typical sky scenes corresponding sampling frequency ,in This is the adaptive adjustment coefficient.

[0012] As a further improvement to this technical solution, the basic lighting driving parameters To basic lighting drive parameters Adjustment duration between as follows: Basic lighting drive parameters Basic lighting drive parameters Each includes different driving dimensions; Calculate the single-dimensional adjustment duration between different driving dimensions sequentially: ; in, , Basic lighting drive parameters Basic lighting drive parameters The Middle One driving dimension; For the first The maximum safe rate of change allowed for each driving parameter is limited by hardware constraints and visual comfort thresholds. Select basic lighting drive parameters Basic lighting drive parameters The maximum adjustment duration among all driving dimensions is used as the basic lighting driving parameter. Basic lighting drive parameters Adjustment duration between: ; in, For all driving dimensions Maximum value operation To traverse all driving dimensions.

[0013] As a further improvement to this technical solution, the sky scene attribution rule is as follows: If scene characterization factor Matching factors with the environment Feature similarity between Then the scene representation factor Equal to environmental matching factor Scene representation factor Simultaneously matches typical sky scenes ; If scene characterization factor Matching factors with the environment Feature similarity between But scene representation factors The scene representation factor is the one with the highest feature similarity to two environment matching factors, and the two environment matching factors are adjacent. Match the typical sky scenes corresponding to the two environmental matching factors mentioned above, namely: Scene representation factor Matching factors with the environment The environmental matching factors have the highest similarity in feature dimensions, and adjacent environmental matching factors... Environmental matching factor Both are in typical sky scenes When, then the scene representation factor Matching typical sky scenes .

[0014] A smart roof light control system for automobiles with simulated natural sky lighting effects includes: The feature library construction module uses the sky light effect measurement method to construct a sky scene feature library. The sky scene feature library contains multiple typical sky scenes, and each typical sky scene is configured with multiple fixed environmental matching factors and benchmark visual parameters. The target visual parameter matching module sets the scene corresponding to the vehicle's location as the measured sky scene and obtains the scene representation factor corresponding to the measured sky scene. Calculate the feature similarity between the scene representation factor and each environment matching factor in the sky scene feature library in turn; Determine the target visual parameters corresponding to the scene representation factors based on feature similarity; The sampling frequency setting module sets the sampling frequency for each typical sky scene in the sky scene feature library; defines the sky scene attribution rules corresponding to the scene representation factors; matches the typical sky scenes corresponding to the scene representation factors; and matches the sampling frequency of the measured sky scenes. The lighting driving parameter mapping module establishes a mapping relationship between the baseline visual parameters and the basic lighting driving parameters in the sky scene feature library, and maps the target visual parameters to the corresponding basic lighting driving parameters based on the mapping relationship.

[0015] Compared with the prior art, the beneficial effects of this application are as follows: This invention relates to a smart car roof light with simulated natural sky lighting effects, its control method, and its control system. By constructing a multi-dimensional lighting effect control architecture encompassing color, color temperature, and spectral distribution, and integrating a full-color LED panel and full-spectrum LEDs with collaborative driving logic, a sky scene feature library is established, and a precise mapping conversion function between baseline visual parameters and lighting driving parameters is constructed. This collaborative mechanism works in conjunction with the hardware components: the full-color LED panel, full-spectrum LEDs, and a condenser. The lighting effect control architecture provides multi-dimensional adjustment support for the driving parameter output, the sky scene feature library provides standardized templates for extracting visual parameters of natural sky lighting effects, and the mapping conversion function achieves precise conversion from visual parameters to hardware driving parameters. This collaborative link transforms natural sky lighting effect characteristics into hardware-executable driving commands, driving the full-color LED panel and full-spectrum LEDs to precisely and collaboratively emit light. This overcomes the limitations of existing control methods that can only achieve white light on / off and brightness adjustment, thus recreating the natural sky lighting effects of different times of day and weather, such as sunrise, sunset, and blue skies. This creates an immersive lighting environment that closely resembles nature for drivers and passengers, while also providing emotional regulation and relaxation through dynamic changes in color and brightness.

[0016] In addition to the purposes, features, and advantages described above, this application has other purposes, features, and advantages. A further detailed description of this application will be provided below with reference to the figures.

[0017] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the principle of an intelligent sky effect car roof light provided in this application; Figure 2 This is a schematic diagram of the arrangement of an intelligent sky-effect car roof light provided in this application; Figure 3 This is a schematic diagram of a smart sky-effect car roof light structure provided in this application; Figure 4 This is a longitudinal sectional view of an intelligent sky-effect car roof light provided in this application; Figure 5 This is a cross-sectional view of an intelligent sky-effect car roof light provided in this application; Figure 6 This is an exploded view of an intelligent sky-effect car roof light provided in this application; Figure 7 This is a schematic diagram of the working steps of this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] A smart car roof light with simulated natural sky light effects includes a lamp body, a touch switch panel, a PCB board, a full-color lamp board, a diffuser, a condenser, a mask, a full-spectrum LED, a reflector, and a control module circuit. refer to Figure 4 As shown, the lamp body is an integral hollow load-bearing shell. The diffuser plate is fastened to the inside of the lamp body by screwing. The control module circuit adopts a snap-fit ​​structure to form a two-way tight fit with the diffuser plate and the inner wall of the lamp body. The diffuser plate and the control module circuit are connected by a limiting tight connection, and the control module circuit and the diffuser plate are internally arranged in the same layer. refer to Figure 5 and Figure 6 As shown, the internal structure is described in detail, visually presenting the technical details, specifically: The full-color LED panel and condenser are screwed together to form an integrated optical light source assembly, while the full-spectrum LED and reflector are screwed together to form another integrated optical light source assembly. The two integrated components of the full-color light panel and the condenser, and the full-spectrum LED and the reflector are fixed inside the lamp body with screws and located below the diffuser. The PCB board is integrated inside the lamp body, the mask adapter fits over the front opening of the outside of the lamp body, and the touch switch panel is tightly attached to the outer surface of the mask. The PCB board is electrically connected to the control module circuit, the full-color lamp board, and the full-spectrum LED, providing power supply and signal transmission channels for each electronic component. The control module circuit is also electrically connected to the touch switch panel. After the user touch command received by the touch switch panel is converted into an electrical signal, it is parsed and processed by the control module circuit, and then transmitted to the full-color lamp board and the full-spectrum LED through the PCB board, forming a complete electrical control and signal transmission. The principles underlying each of the above components are as follows: refer to Figure 2 and Figure 3 As shown, the lamp body serves as the structural support and protective foundation for the overall dome light, providing precise installation and positioning space for all hardware components, ensuring the relative stability of each component, while also adapting to the installation requirements of the car roof, achieving seamless integration with the interior, and providing physical protection for all internal hardware. Touch switch panel: The core component of human-computer interaction, it receives touch operation commands from users (such as left reading light switch, lighting switch and other human-computer interaction components), and transmits the commands to the control module circuit to realize the user's personalized control of the overhead light effect; PCB (Printed Circuit Board): It forms the basis for the circuit connection of all electronic components of the ceiling light, builds the power supply and signal transmission channels, realizes the transmission of electrical signals and power between the control module circuit, full-color light board, full-spectrum LED, and touch switch panel, and is the circuit skeleton for the collaborative work of electronic components. Full-color light panel: The core color light source of the ceiling light, which can output mixed light of red, green and blue. By adjusting the brightness and ratio of the three colors, it can simulate the color changes of different natural skies such as sunrise, sunset and blue sky, and achieve color gradient of light effect; refer to Figure 1 As shown, the diffuser plate is the core optical control component of the overhead light. It is made of PMMA material mixed with nanoscale materials. Utilizing the Rayleigh scattering principle, it softens the incident light from the full-color light panel and full-spectrum LEDs, eliminating glare. At the same time, it achieves color layering and gradation in different areas, restoring the diffused light effect of the natural sky and avoiding visual discomfort caused by looking directly at the light source. Concentrator: An optical component for full-color light panels, it focuses, shapes, and directionally constrains the light emitted by the full-color light panels, ensuring that the light is directed onto the diffuser, improving the concentration and utilization efficiency of the light, and preventing the light from being scattered irregularly; The mask, made of nanomaterials, serves as the outer protective layer and secondary light-softening component for the overhead light, protecting the internal diffuser plate, light source, and other hardware from dust. Full-spectrum LED: Supplements the natural spectrum of the ceiling light with a light source, outputting full-spectrum light that is close to natural light, making up for the lack of spectrum in the full-color light panel, enhancing the realism and visual comfort of the sky lighting effect, and at the same time assisting in adjusting the overall brightness of the light effect; Reflector: An optical component for full-spectrum LEDs, it reflects and focuses the light emitted by the full-spectrum LEDs, guiding the light evenly toward the diffuser plate to ensure uniform coverage of the full-spectrum light and further enhance the naturalness of the light effect; Control module circuit: This is the core control component of the ceiling light, integrating drive, communication, and control algorithms. It can receive user commands from the touch switch panel and precisely control the working parameters (brightness, color, current, etc.) of the full-color light panel and full-spectrum LEDs. At the same time, it can link with environmental sensors and network modules to achieve intelligent adaptive adjustment of light effect and ensure smooth transition of light effect.

[0022] refer to Figure 7 As shown, a method for controlling a car's intelligent roof light with simulated natural sky lighting effects includes: A sky scene feature library was constructed using the sky light effect measurement method. The sky scene feature library contains multiple typical sky scenes, and each typical sky scene is configured with multiple fixed environmental matching factors and benchmark visual parameters. When the vehicle's location is set, the corresponding scene is the measured sky scene, and the scene representation factor corresponding to the measured sky scene is obtained; Calculate the feature similarity between the scene representation factor and each environment matching factor in the sky scene feature library in turn; Determine the target visual parameters corresponding to the scene representation factors based on feature similarity; Set the sampling frequency for each typical sky scene in the sky scene feature library; define the sky scene attribution rules corresponding to the scene representation factors, match the typical sky scenes corresponding to the scene representation factors, and match the sampling frequency of the measured sky scenes; Establish a mapping relationship between the baseline visual parameters and the basic lighting driving parameters in the sky scene feature library, and map the target visual parameters to the corresponding basic lighting driving parameters based on the mapping relationship; In a method for controlling a car smart roof light with natural sky light effect simulation, the system can also receive manual adjustment commands from the user. The adjustment commands are transmitted to the control module circuit via electrical connection. After the control module circuit parses the commands, it accurately selects a typical sky scene that matches the commands from a preset sky scene feature library, providing a target scene basis for subsequent light effect adjustment. The above-mentioned method for controlling a car smart roof light with simulated natural sky lighting effects is further detailed below: A sky scene feature library was constructed using a sky lighting effect measurement method. This library contains multiple typical sky scenes, each with corresponding fixed environmental matching factors and baseline visual parameters. In a typical sky scene, the first Environmental matching factors as follows: ; No. A typical sky scene, and environmental matching factors. The corresponding number A benchmark visual parameter as follows: ; in: m, This represents the total number of typical sky scenes; , This represents the total number of environmental matching factors and baseline visual parameters, with a one-to-one correspondence between the environmental matching factors and the baseline visual parameters. Environmental matching factor The total number of environmental features; As a reference visual parameter The total number of medium luminous efficacy features; = Environmental matching factor In a typical sky scene Next, the Quantitative identifiers corresponding to environmental characteristics Typical sky scene The Middle The original values ​​of the environmental features; For the first The weight coefficients of all environmental features are set, and the sum of the weight coefficients of all environmental features is 1. These are used to distinguish the similarity of corresponding environmental matching factors in different typical sky scenes. Thus, environmental features can be used to differentiate the similarity of environmental matching factors. The distribution differences among different typical sky scenes were determined; the greater the distribution difference, the more significant the environmental characteristics. The more critical the scene classification, the better; specifically, this involves collecting environmental features from all typical sky scenes. The original set of values; computational environment characteristics Variance across different scenarios: The larger the variance, the more significant the difference in feature distribution across scenarios, and the stronger the discriminative power; the variance of all environmental features is normalized to obtain weight coefficients. ; Specifically, the above-mentioned benchmark visual parameters Specifically, this involves: building typical sky scenes. Subsequently, typical sky scenes were detected and collected using testing instruments such as spectroradiometers and luminance meters. The system uses multiple light effect features, including parameters such as color coordinates, brightness values, and gradient values, which are arranged in a fixed order to form a baseline visual parameter. ; The specific working principle of the sky light effect measurement method is as follows: Multi-dimensional measurements of the real sky light environment are collected under different regions, time periods, and meteorological conditions. Simultaneously, environmental features such as light intensity, color temperature, spectral distribution, sky brightness gradient, and environmental reflection characteristics are recorded. The collected continuous environmental features are divided into several typical sky scenes according to clustering rules. Stable and discriminative environmental matching factors are extracted for each typical sky scene. The benchmark visual parameters that are compatible with it are calibrated through in-vehicle light effect matching experiments. Finally, a sky scene feature library containing typical sky scenes, environmental matching factors, and benchmark visual parameters is formed. When collecting continuous environmental features to form environmental matching factors, the collection method is the same as that used during normal vehicle operation. The working principle is as follows: using the actual lighting environment under normal vehicle operation as the collection benchmark, the same collection parameters, collection frequency and collection range as during daily driving are used to simultaneously collect core environmental features such as sky light intensity, color temperature and spectral distribution. During the collection process, the actual scene conditions during vehicle operation are strictly followed, without adding extra collection procedures or changing collection specifications, to ensure that the collected continuous environmental features can truly reflect the actual sky light environment encountered during vehicle operation. Then, based on these real and effective collection data, environmental matching factors are extracted to ensure that the environmental matching factors are highly consistent with the actual light effect environment during normal vehicle operation. The clustering rules are as follows: based on key features of the sky light environment (such as light intensity, color temperature, spectral distribution, etc., i.e., multi-dimensional data collected in the previous field measurements), clustering is based on the scene similarity between different scenes (which can be calculated using metrics such as Euclidean distance and cosine similarity) to determine the fit of scene features. Scenes with small feature differences are grouped into the same category, while scenes with large feature differences are divided into different categories. The scene similarity calculation is based on the environmental features measured in the previous field measurements to ensure that the clustering results are consistent with the features of the real sky light environment. At the same time, combined with the actual needs of vehicle lighting, corresponding baseline visual parameters and adjustment rules are matched for each clustered scene, so that each typical sky scene after clustering can correspond to a clear environmental matching factor and baseline visual parameters. The specific differences in the features of the above scenarios are as follows: Based on previously measured key features of the sky lighting environment (illuminance, color temperature, spectral distribution, sky brightness gradient, etc.), scene similarity values ​​are obtained through quantitative calculations using Euclidean distance and cosine similarity. A preset threshold (e.g., 0.95) is then experimentally calibrated to classify the magnitude of feature differences. If the feature differences are small (classified into the same category), and the scene similarity value of two sky scenes is less than the preset threshold, they are judged to have small feature differences. If the feature differences are large (classified into different categories), and the scene similarity value of two sky scenes is greater than or equal to the preset threshold, they are judged to have small feature differences.

[0023] The following is a specific example of the sky light effect measurement method: Since the natural sky light effects are characterized by continuous and gradual changes, it is not necessary to collect all light effect states. Therefore, multiple typical sky scenes that can simulate real atmospheric scattering, light intensity and light angle are built by using weather type as the clustering dimension. Specifically, the clustering dimension refers to using meteorological type as the sole clustering dimension. Based on atmospheric scattering mechanisms, light intensity characteristics, and the essential similarity of overall visual effects, continuously changing sky lighting effects are divided into multiple cluster categories. Within the same cluster category, typical sky scenes exhibit consistent lighting effect generation mechanisms and similar visual characteristics in their environmental matching factors. Specifically: A consistent light effect generation mechanism refers to the fact that all environmental matching factors within the same typical sky scene have identical physical principles regarding light generation, atmospheric scattering, and light field propagation. The formation mechanism of the light effect is essentially the same, with only gradient differences in parameters such as illumination angle and intensity, rather than a fundamental change in the mechanism. Taking clear sky clustering as an example: The sunrise in the morning, the blue sky at noon, and the sunset in the evening all follow the same light effect mechanism of direct sunlight combined with Rayleigh scattering by atmospheric molecules, and the light source type, scattering mode, and light field structure are completely consistent; Taking clustering on cloudy and rainy days as an example: there is only the light effect mechanism of thick cloud cover combined with uniform diffused light throughout the space, with no directional direct light and a unified scattering pattern; Similar visual features refer to the overall light and color style, brightness distribution, gradual transition rules, and visual texture of all baseline visual parameters within the same typical sky scene, which are highly similar due to the consistent light effect generation mechanism. The visual differences are only gradual changes in degree, not abrupt changes in type. Taking the clear sky cluster as an example again: multiple baseline visual parameters are all transparent, have a clear direction of illumination, and have a natural blue / warm white color tone. Only the color temperature and brightness are different, and the visual base is highly similar. Taking clustering on rainy days as an example: multiple baseline visual parameters are all soft, without contrast between light and dark, and have an overall uniform grayish-white visual characteristic, resulting in a highly consistent visual experience; Because the light effect generation mechanism is completely uniform and the visual feature baseline is very similar within the same typical sky scene, when constructing a typical sky scene, only single variables such as solar altitude angle, light intensity, and light source color temperature are adjusted in a linear fashion with equal steps. There are no sudden changes in the light effect mechanism or parameter jumps. Based on this, the encoded environmental matching factors and the baseline visual parameters extracted by the instrument will show a continuous and equally spaced change pattern in sync with the linearly adjusted variables. Ultimately, this results in uniform feature distances between the environmental matching factors and baseline visual parameters of the same typical sky scene, with an overall continuous gradient arrangement. For example, consider the clear sky weather clustering: The gradient of environmental matching factors is uniform: the clear sky cluster includes three typical sky scenes: sunrise in the morning, blue sky at noon, and sunset in the evening. Only the solar altitude angle and time period are used as variables. The solar altitude angle changes symmetrically and uniformly according to "15°-30° (morning) → 60°-90° (noon) → 15°-30° (evening)", and the time period progresses linearly according to "morning → noon → evening". The adjustment range and step size are completely consistent, so that the feature distance of environmental matching factors is equal. Uniform gradient of baseline visual parameters: On a uniform sunny day directional scattering optical substrate, only the light source angle, color temperature and illuminance are linearly adjusted. The color coordinates transition uniformly from warm orange in the morning (x≈0.45, y≈0.38) to bright blue at noon (x≈0.31, y≈0.32), and then to orange-red in the evening (x≈0.48, y≈0.37). The brightness value rises and falls uniformly in the order of "350cd / m²→800cd / m²→350cd / m²". The gradient value changes synchronously with a fixed step size, without abrupt changes or gaps. Finally, the environmental matching factor and the baseline visual parameter feature distance are uniformly spaced and arranged in a continuous gradient.

[0024] The scene where the vehicle's location is set is the actual measured sky scene. ; When obtaining the vehicle's location, the original values ​​of multiple environmental features are obtained. The original values ​​are encoded again using the weight coefficients of each environmental feature to obtain the measured sky scene at the vehicle's location. Corresponding scene representation factor (Scene Representation Factor) and scene representation factors (When each encoded environmental feature corresponds to a 1, indicating the vehicle's location, multiple codes are obtained for each environmental feature; all subsequent codes are determined by the number of times they are obtained.) Calculate scene representation factors sequentially The feature similarity between the scene and each environment matching factor in the sky scene feature library, if the scene representation factor Matching factors with the environment Feature similarity between When, it indicates the scene representation factor. Matching factors with the environment Completely identical, directly retrieve environment matching factors from the sky scene feature library. Corresponding baseline visual parameters As a scene representation factor Target visual parameters ; If scene characterization factor If the similarity between the scene representation factor and all environmental matching factors in the sky scene feature library is not equal to 1, then the scene representation factor is considered to be... No environment matching factor was found in the sky scene feature library. Furthermore, since the environment matching factor and visual parameters for the same typical sky scene in the sky scene feature library both exhibit a continuous gradient distribution, the scene representation factor was retrieved. The feature with the highest similarity to all environmental matching factors, and the adjacent environmental matching factors Environmental matching factor ; Bilinear interpolation was used to evaluate the environmental matching factor. Environmental matching factor Corresponding baseline visual parameters Reference visual parameters Perform bilinear interpolation to obtain the scene representation factor. Corresponding target visual parameters ; Feature similarity Specifically as follows: ; in, = Scene characterization factor The vector magnitude, Environmental matching factor The vector magnitude; Target visual parameters in bilinear interpolation Specifically as follows: ; in: Weights are based on differences; During normal vehicle operation, the external sky environment undergoes continuous and dynamic changes depending on the vehicle's geographical location, time, and weather conditions. To ensure that the in-vehicle lighting effect can accurately and smoothly adjust in sync with the changing trends of the actual sky environment, it is necessary to first determine the sampling frequency that matches the real-time sky environment during vehicle operation, and then obtain the measured sky scene based on the corresponding sampling frequency. Scene representation factors at different time points And based on scene representation factors Further analysis of the target visual parameters at different time points Finally, the corresponding basic lighting driving parameters are determined sequentially. To achieve smooth and precise synchronization of the vehicle's interior lighting effects with continuous changes in the actual sky environment, each typical sky scene in the sky scene feature library is pre-defined. corresponding sampling frequency ; Define scene representation factors The corresponding sky scene attribution rules are used to match scene representation factors. Corresponding typical sky scene ; After matching, bind to a typical sky scene. Corresponding sampling frequency Compared with the actual sky scene Used to employ sampling frequency while the vehicle is in motion. Collect subsequent scene representation factors , The scene representation factors collected at the current time point are then mapped to the corresponding basic lighting driving parameters to adjust the in-vehicle lights in a timely manner. The specific rules for assigning ownership of sky scenes are as follows: If scene characterization factor Matching factors with the environment Feature similarity between Then the scene representation factor Equal to environmental matching factor Scene representation factor Simultaneously matches typical sky scenes ; If scene characterization factor Matching factors with the environment Feature similarity between But scene representation factors The scene representation factor is the one with the highest feature similarity to two environment matching factors, and the two environment matching factors are adjacent. Match the typical sky scenes corresponding to the two environmental matching factors mentioned above, namely: Scene representation factor Matching factors with the environment The environmental matching factors have the highest similarity in feature dimensions, and adjacent environmental matching factors... Environmental matching factor Both are in typical sky scenes When, then the scene representation factor Matching typical sky scenes ; Set typical sky scenes corresponding sampling frequency The specific working principle is as follows: Determine the actual sky scene during normal vehicle operation. Equivalent to a typical sky scene Subsequently, constrained by the continuous and gradual changes in the actual sky lighting environment, the measured sky scenes were continuously acquired. Multiple scene representation factors typically do not undergo abrupt changes across clustering dimensions; that is, scene variations are constrained to the measured sky scene. Internally, there is no need to reserve extra adjustment redundancy for cross-dimensional switching; In addition, sampling frequency is used After collecting scene characterization factors at different time points, it is necessary to dynamically output corresponding basic lighting driving parameters based on the changes in adjacent scene characterization factors to achieve real-time matching and smooth transition between in-vehicle lighting and the measured sky scene; however, if the sampling frequency is... Too high a sampling frequency may cause new parameter updates to be triggered before the lighting adjustment is complete, resulting in flickering or interrupted transitions; if the sampling frequency is too high... If the light is too low, it will not be able to respond to changes in the scene in a timely manner, resulting in a disconnect between the lighting and the actual environment; Therefore, a typical sky scene is set. corresponding sampling frequency At that time, with typical sky scenes Using all environmental matching factors as constraints, retrieve typical sky scenes. All environmental matching factors Based on mapping all environmental matching factors Corresponding basic lighting drive parameters Analyze all basic lighting driving parameters in sequence Adjustment duration between Select the maximum adjustment duration As a typical sky scene Corresponding minimum sampling frequency This ensures that any driving parameter can be smoothly adjusted within a single sampling interval; Calculate typical sky scenes All environmental matching factors Corresponding dimensional dynamic features (Including but not limited to characteristics such as distribution density and rate of environmental change): For typical sky scenes All environmental matching factors First, feature dimensions such as distribution density, environmental change rate, feature dispersion, extreme value distribution, and feature correlation are extracted. Then, each feature dimension is standardized and normalized to eliminate the differences in dimensionality and numerical range between different feature dimensions, mapping each feature dimension to a unified interval. Next, a preset weight is assigned based on the contribution of each feature dimension to the dynamics of scene lighting effects. Finally, the standardized feature dimensions are weighted and summed according to their weights to obtain a dimensional dynamic feature that comprehensively represents the dynamic complexity of scene lighting effects. This feature fully integrates dynamic information such as the clustering, rate of change, dispersion, frequency of extreme lighting effects, and collaborative changes between features of lighting effects in the scene. It can accurately quantify the strength of scene dynamics and provide a unified quantitative basis for subsequent adaptive adjustment of sampling frequency. When extracting the feature dimensions such as distribution density, environmental change rate, feature dispersion, extreme value distribution, and feature correlation, conventional technical means in this field are used. The relevant calculation and implementation methods are well known to those skilled in the art and will not be elaborated on here. Ultimately, based on typical sky scenes minimum sampling frequency Dimensional dynamic features Set typical sky scenes corresponding sampling frequency ,in This is the adaptive adjustment coefficient; The adjustment duration is specifically as follows: in the same typical sky scene Within, from any basic lighting drive parameter Gradual adjustment to another basic lighting drive parameter To ensure flicker-free and seamless lighting, and for comfortable human vision, the minimum time window required for the hardware driver (LEDPWM duty cycle, drive current, etc.) to complete a full transition is specified. Specific basic lighting drive parameters To basic lighting drive parameters Adjustment duration between as follows: Basic lighting drive parameters Basic lighting drive parameters Each includes different driving dimensions, which are specifically determined by the actual control type of the vehicle lighting hardware (such as the duty cycle of RGB three-color LED pulse width modulation, full-spectrum LED driving current, etc.), and all driving dimensions correspond one-to-one. Calculate the single-dimensional adjustment duration between different driving dimensions sequentially: ; in, , Basic lighting drive parameters Basic lighting drive parameters The Middle One driving dimension; For the first The maximum safe rate of change of the driving parameters is constrained by two factors: First, there is a hardware limitation, namely the maximum parameter step value that the LED driver circuit, PWM controller and other hardware can withstand per second. Exceeding this limit will cause damage to the device or abnormal response. Second, the visual comfort threshold, which is the limit of human eye perception of changes in light. Exceeding this threshold will cause the eye to perceive flickering and abrupt changes, leading to visual fatigue. Select basic lighting drive parameters Basic lighting drive parameters The maximum adjustment duration among all driving dimensions is used as the basic lighting driving parameter. Basic lighting drive parameters Adjustment duration between: ; in, For all driving dimensions Maximum value operation To traverse all driving dimensions; By selecting the maximum adjustment duration As a typical sky scene Corresponding minimum sampling frequency It can ensure typical sky scenes The adjustment between any two sets of basic lighting driving parameters can be completed within a sampling interval with a smooth transition without flicker or jump, so that the change of the interior lighting effect in the same scene always meets the visual comfort requirements of the human eye, while ensuring the real-time synchronization and consistency of the lighting effect with the actual sky environment. Hardware limitations and visual comfort thresholds can be determined using calibration experiments, specifically: Hardware limitations were determined through hardware parameter calibration experiments. The parameter amplitudes were gradually adjusted for each driving dimension to calibrate the minimum step size, maximum safe step value, and corresponding maximum safe rate of change for the driving circuit to be stably executed. The visual comfort threshold was determined through human visual perception experiments. The maximum rate of change of light effect that the human eye cannot perceive was tested and statistically analyzed under typical in-vehicle lighting conditions. Establish a mapping relationship between baseline visual parameters in the sky scene feature library and basic lighting driving parameters (including RGB three-color LED pulse width modulation duty cycle, full-spectrum LED driving current, etc.). Specific baseline visual parameters... With basic lighting drive parameters The mapping relationship between them is as follows: ; in, This is a function for converting visual parameters to driving parameters; Map target visual parameters based on mapping relationship For the corresponding basic lighting drive parameters Ultimately, through the aforementioned basic lighting driving parameters To control the lighting effects inside the vehicle; Transformation function Synchronization can be determined using a calibration experiment method. Specifically, in a standardized testing environment, benchmark visual parameters (such as color temperature, brightness, and spectral distribution) are used as the target luminous efficacy index. By iteratively adjusting the basic lighting driving parameters (RGB three-color LED pulse width modulation duty cycle, full-spectrum LED driving current, etc.), the actual luminous efficacy output by the lighting hardware is precisely matched with the target visual parameters. Multiple sets of calibration sample pairs of visual parameters and driving parameters are collected. Then, through data fitting or model training, the discrete sample pairs are transformed into a generalizable continuous transformation function, achieving a precise mapping from the visual perception dimension to the hardware control dimension, while ensuring that the driving parameters are within the hardware safety constraints. The detailed working steps are as follows: First, a standard test environment consistent with the actual use scenario of the vehicle is set up, and the vehicle lighting hardware module, high-precision optical measurement equipment and control and acquisition system are deployed and the equipment is calibrated. Based on the sky scene feature library, visual parameter sample points covering typical lighting effects across the entire range are preset. Then, the driving parameters are iteratively adjusted for each visual parameter sample. Light effect indicators are collected and output in real time and compared with target parameters. When the error reaches the standard, the corresponding driving parameters are recorded to form a calibration sample pair. All sample pairs are preprocessed by screening, outlier removal, and normalization. Then, based on the preprocessed samples, a transformation function is obtained by modeling using methods such as multinomial fitting, neural network training, or lookup table interpolation. Select a verification sample to test the accuracy of the transformation function. If the error exceeds the limit, supplement the sample or adjust the model parameters until the requirements are met.

[0025] Although this application 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 of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A car intelligent roof lamp with natural sky light effect simulation, characterized in that, Includes lamp body, touch switch panel, PCB board, full-color lamp board, diffuser, condenser, mask, full-spectrum LED, reflector, and control module circuit; The lamp body is an integral hollow load-bearing shell. The diffuser plate is fastened to the inside of the lamp body by screwing. The control module circuit adopts a snap-fit ​​structure to form a two-way tight fit with the diffuser plate and the inner wall of the lamp body. The diffuser plate and the control module circuit are tightly connected by limiting, and the control module circuit and the diffuser plate are internally arranged in the same layer. The full-color LED panel and the concentrator are screwed together to form an integrated optical light source assembly, and the full-spectrum LED and the reflector are screwed together to form another integrated optical light source assembly. The two integrated components of the full-color light panel and the condenser, and the full-spectrum LED and the reflector are fixedly installed inside the lamp body with screws and located below the diffuser. The PCB board is integrated inside the lamp body. The mask adapter fits over the front opening on the outside of the lamp body. The touch switch panel is tightly attached to the outer surface of the mask. The PCB board is electrically connected to the control module circuit, the full-color lamp board, and the full-spectrum LED, providing power supply and signal transmission channels for each electronic component. The control module circuit is also electrically connected to the touch switch panel.

2. A control method of the smart roof lamp with natural sky light effect simulation, the control method controls the smart roof lamp with natural sky light effect simulation according to claim 1, characterized in that, include: A sky scene feature library is constructed using the sky light effect measurement method. The sky scene feature library contains multiple typical sky scenes, and each typical sky scene is configured with multiple fixed environmental matching factors and benchmark visual parameters. When the vehicle's location is set, the corresponding scene is the measured sky scene, and the scene representation factor corresponding to the measured sky scene is obtained; Calculate the feature similarity between the scene representation factor and each environment matching factor in the sky scene feature library in turn; Determine the target visual parameters corresponding to the scene representation factors based on feature similarity; Set the sampling frequency for each typical sky scene in the sky scene feature library; Define the sky scene attribution rules corresponding to the scene representation factors, match the typical sky scenes corresponding to the scene representation factors, and match the sampling frequency of the measured sky scenes; A mapping relationship between a reference visual parameter and a basic lighting driving parameter in a sky scene feature library is established, and a target visual parameter is mapped to a corresponding basic lighting driving parameter according to the mapping relationship. The mapping relationship between the reference visual parameter and the basic lighting driving parameter is as follows: is a conversion function of the visual parameter to the driving parameter.​​​ 3. The method of claim 2, wherein the method further comprises: determining a position of the sun; determining a position of the moon; determining a position of the sun and the moon relative to the vehicle; and determining a position of the sun and the moon relative to the vehicle. The sky scene feature library includes a plurality of typical sky scenes, each of which is configured with a plurality of fixed environment matching factors and reference visual parameters. under the first environment matching factor as follows: ； As follows:​​​​ ； in: m, is the total number of typical sky scenes; , is the total number of environment matching factors and reference visual parameters corresponding to each other one by one. environment matching factor total number of environment features; reference visual parameter total number of mid light effect features; = Environmental matching factor In a typical sky scene Next, the Quantitative identifiers corresponding to environmental characteristics Typical sky scene The Middle The original values ​​of the environmental features; For the first The weight coefficients of each environmental feature are given, and the sum of the weight coefficients of all environmental features is 1.

4. The method of claim 3, wherein the method further comprises: The method for measuring sky light effects is as follows: Multi-dimensional field measurements of the real sky light environment were conducted under different geographical locations, time periods, and meteorological conditions, and environmental characteristics were recorded simultaneously. The collected continuous environmental features are divided into several typical sky scenes according to clustering rules. Stable and discriminative environmental matching factors are extracted for each typical sky scene. The benchmark visual parameters that are compatible with them are calibrated through in-vehicle light effect matching experiments. Finally, a sky scene feature library containing typical sky scenes, environmental matching factors, and benchmark visual parameters is formed. The clustering rule is as follows: based on the key features of the sky light environment, calculate the scene similarity between different scenes, judge the fit of scene features, classify scenes with small feature differences into the same category, and classify scenes with large feature differences into different categories.

5. The method of claim 4, wherein the method further comprises: The scene characterization factor and the environmental matching factor The feature similarity between the scene characterization factor and the environmental matching factor is as follows: ； wherein = the vector norm of the scene characterization factor = the vector norm of the scene characterization factor = the vector norm of the scene characterization factor = the vector norm of the environment matching factor = the vector norm of the environment matching factor 6. The vehicle intelligent roof lamp control method with natural sky light effect simulation according to claim 5, characterized in that: The scene characterization factor Corresponding target visual parameter Is: If scene characterization factor Matching factors with the environment Feature similarity between In this case, the environment matching factor is directly retrieved from the sky scene feature library. Corresponding baseline visual parameters As a scene representation factor Target visual parameters ; If the scene characteristic factor If the similarity between the scene characteristic factor and all environment matching factors in the sky scene characteristic library is not equal to 1, the scene characteristic factor is called out The feature similarity between the scene characteristic factor and all environment matching factors is the largest, and the adjacent environment matching factor , the environment matching factor ; The environment matching factor is obtained by bilinear interpolation The environment matching factor The corresponding reference visual parameter The reference visual parameter The scene representation factor is obtained by bilinear interpolation The corresponding target visual parameter: ； wherein: is the difference weight.

7. The method of claim 3, wherein the method further comprises: determining a position of the sun; determining a position of the moon; determining a position of the sun and the moon relative to the vehicle; and determining a position of the sun and the moon relative to the vehicle. Define the typical sky scene. corresponding sampling frequency : With typical sky scenes Using all environmental matching factors as constraints, retrieve typical sky scenes. All environmental matching factors Based on mapping all environmental matching factors Corresponding basic lighting drive parameters Analyze all basic lighting driving parameters in sequence Adjustment duration between Select the maximum adjustment duration As a typical sky scene Corresponding minimum sampling frequency ; Computing a typical sky scene All environment matching factors Corresponding dimensional dynamic characteristics ; According to the typical sky scene a minimum sampling frequency , dimension dynamic characteristics , set the typical sky scene corresponding sampling frequency , wherein is an adaptive adjustment coefficient.

8. The method of claim 7, wherein the method further comprises: determining a position of the sun; determining a position of the moon; determining a position of the sun and the moon relative to the vehicle; and determining a position of the sun and the moon relative to the vehicle. The base lighting drive parameter To the base lighting drive parameter The adjustment duration As follows: Basic lighting drive parameters Basic lighting drive parameters Each includes different driving dimensions; Calculate the single-dimensional adjustment duration between different driving dimensions sequentially: ； in, , Basic lighting drive parameters Basic lighting drive parameters The Middle One driving dimension; The maximum safe rate of change allowed for the first drive parameter, constrained by hardware limits, visual comfort thresholds. Selecting a base lighting drive parameter , the base lighting drive parameter corresponding to the maximum value of the adjustment duration in all drive dimensions as the base lighting drive parameter , the base lighting drive parameter the adjustment duration between ； wherein, for all driving dimensions max operation, for all driving dimensions.

9. The method of claim 8, wherein the method further comprises: determining a position of the sun; determining a position of the moon; determining a position of the sun and the moon relative to the vehicle; and determining a position of the sun and the moon relative to the vehicle. The specific rules for attributing the sky scene are as follows: If scene characterization factor Matching factors with the environment Feature similarity between Then the scene representation factor Equal to environmental matching factor Scene representation factor Simultaneously matches typical sky scenes ; If scene characterization factor Matching factors with the environment Feature similarity between But scene representation factors The scene representation factor is the one with the highest feature similarity to two environment matching factors, and the two environment matching factors are adjacent. Match the typical sky scenes corresponding to the two environmental matching factors mentioned above, namely: Scene representation factor Matching factors with the environment The environmental matching factors have the highest similarity in feature dimensions, and adjacent environmental matching factors... Environmental matching factor Both are in typical sky scenes When, then the scene representation factor Matching typical sky scenes .

10. A control system for an intelligent car roof light with simulated natural sky lighting effects, wherein the system is applied to the control method for an intelligent car roof light with simulated natural sky lighting effects as described in claim 2, characterized in that, include: The feature library construction module uses the sky light effect measurement method to construct a sky scene feature library. The sky scene feature library contains multiple typical sky scenes, and each typical sky scene is configured with multiple fixed environmental matching factors and benchmark visual parameters. The target visual parameter matching module sets the scene corresponding to the vehicle's location as the measured sky scene and obtains the scene representation factor corresponding to the measured sky scene. Calculate the feature similarity between the scene representation factor and each environment matching factor in the sky scene feature library in turn; Determine the target visual parameters corresponding to the scene representation factors based on feature similarity; The sampling frequency setting module allows you to set the sampling frequency for each typical sky scene in the sky scene feature library. Define the sky scene attribution rules corresponding to the scene representation factors, match the typical sky scenes corresponding to the scene representation factors, and match the sampling frequency of the measured sky scenes; The lighting driving parameter mapping module establishes a mapping relationship between the baseline visual parameters and the basic lighting driving parameters in the sky scene feature library, and maps the target visual parameters to the corresponding basic lighting driving parameters based on the mapping relationship.

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