Cabin atmosphere lighting control method and device
By acquiring and integrating multi-dimensional cockpit parameters to generate comprehensive status information and control cockpit ambient lighting, the system addresses the shortcomings of existing systems in terms of intelligence and personalization, achieving intelligent and personalized cockpit ambient lighting and enhancing the driving experience and safety.
Patent Information
- Application Number
- CN202511177939.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-21
- Publication Date
- 2025-11-28
AI Technical Summary
Existing cabin ambient lighting systems cannot sense ambient light and the status of occupants in real time, resulting in a gap between the lighting effect and actual needs. They lack intelligence and personalization, and lack in-depth analysis of driver visual attention and vehicle driving status, making it difficult to provide safe and intelligent lighting solutions.
By acquiring a multi-dimensional set of cabin parameters, including ambient light data, personnel status data, driver physiological data, and vehicle driving parameters, preprocessing and feature extraction are performed. A weighted fusion algorithm is used to generate comprehensive status information, and a hierarchical decision-making mechanism is used to control the cabin ambient lighting device to achieve intelligent and personalized lighting adjustment.
It enables intelligent and personalized cabin ambient lighting, improving the driving experience and passenger comfort, and enhancing safety and intelligence.
Smart Images
Figure CN121038034A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of intelligent cockpit technology, and in particular to a method and device for controlling cabin ambient lighting. Background Technology
[0002] With the development of intelligent and personalized vehicles, cabin ambient lighting systems are attracting increasing attention from consumers. Good cabin ambient lighting not only enhances the driving experience but also creates a comfortable and pleasant riding environment for passengers. However, existing cabin ambient lighting systems can only adjust the light according to preset patterns, failing to perceive changes in ambient light and the status of occupants in real time. This results in a gap between the lighting effect and actual needs, and insufficient intelligence and personalization. Furthermore, existing systems lack analysis of driver visual attention and deep integration of vehicle driving status, making it difficult to provide safer and more intelligent lighting solutions. Summary of the Invention
[0003] This invention provides a cabin ambient lighting control method and device, aiming to overcome the deficiencies in the prior art, realize intelligent and personalized cabin ambient lighting, and improve product competitiveness.
[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows: This invention provides a method for controlling cabin ambient lighting, comprising: S1. Obtain a multi-dimensional parameter set for the cockpit, which includes at least ambient light data, personnel status data, driver physiological data, and vehicle driving parameters. S2. Preprocess and extract features from the multidimensional parameter set to generate a feature vector set; S3. The feature vector set is fused using a weighted fusion algorithm to output comprehensive state information; S4. Generate target lighting parameters based on the hierarchical decision-making mechanism of the comprehensive state information; S5. Control the cabin ambient lighting device according to the target lighting parameters.
[0005] Specifically, step S4 includes: S41. When the driver's fatigue characteristic value F>0.6 and the vehicle speed V>30km / h, activate the first lighting mode; otherwise, proceed to the next step. S42. When the vehicle is turning, activate the second lighting mode; otherwise, proceed to the next step. S43. Determine the base brightness and base color temperature based on the normalized ambient light intensity and vehicle speed; S44. Adjust the base brightness and base color temperature based on normalized human emotion parameters and normalized temperature to determine the target brightness and target color temperature.
[0006] Specifically, the parameters corresponding to the first lighting mode are: color temperature H=0°, saturation S=100%, and brightness L. tired =L max *[1+sin(2π×0.3t)] / 2, where L max The maximum brightness of the lighting system is represented by t, which is a time parameter. The second lighting mode is: If the steering angle satisfies 0.1≤|θ norm If |≤0.3, then the ambient lighting parameters are: chromaticity H=30°, luminance L turn =L max *(0.4+0.2×θ norm (1-k) v *V norm ), where k v It is the vehicle speed suppression coefficient, which can be calibrated experimentally, for example, 0.6; If the steering angle satisfies |θ norm If |>0.3, then L turn =L t-1 L t-1 The brightness value at the last moment.
[0007] Specifically, the base brightness is determined according to the following formula:
[0008] Among them, L min For the system's minimum brightness, L max For maximum brightness, ω E ,、ω S Let w be the weighting coefficient. E +w S =1,k E is the ambient light response gain coefficient; p is the vehicle speed response index of brightness; The base color temperature is determined according to the following formula:
[0009] Among them, C min For the system's minimum color temperature, C max For maximum color temperature, δ E δ S Let be the weighting coefficients, satisfying δ E +δ S =1,j E is the ambient light color temperature saturation coefficient, and q is the vehicle speed response index of the color temperature.
[0010] Specifically, step 44 includes: Step 4401: Calculate the first brightness adjustment amount based on the normalized human emotion parameters; Step 4402: Calculate the first color temperature adjustment amount based on the normalized human emotion parameters; Step 4403: Calculate the second brightness adjustment amount based on the normalized temperature; Step 4404: Calculate the second color temperature adjustment amount based on the normalized temperature; Step 4405: Calculate the target brightness and target color temperature based on the base brightness and base color temperature, the first brightness adjustment amount, the second brightness adjustment amount, the first color temperature adjustment amount, and the second color temperature adjustment amount.
[0011] Specifically, the first brightness adjustment amount is calculated according to the following formula: ΔL M = α M × M norm × ΔL max Where, α M ΔL is the proportionality coefficient for emotion regulation. max M represents the maximum brightness adjustment range. norm A normalized sentiment index; The first color temperature adjustment amount is calculated according to the following formula: ΔC M = -β M × M norm × ΔC max Where, β M ΔC is the proportionality coefficient for emotion regulation. max This represents the maximum adjustment range for color temperature.
[0012] Specifically, the second brightness adjustment amount is calculated according to the following formula: ΔL T = -α T × (T norm - 0.5) × 2 × ΔL max Where, α T T is the temperature regulation proportional coefficient. norm For normalized temperature, ΔL max This represents the maximum brightness adjustment range; The second color temperature adjustment amount is calculated according to the following formula: ΔC T = β T × (T norm - 0.5) × 2 × ΔC max Where, β T ΔC is the temperature regulation proportional coefficient.max This represents the maximum adjustment range for color temperature.
[0013] Specifically, the target brightness is calculated according to the following formula: L = L base + ΔL M + ΔL T And if L <L min Then L = L min If L>L max Then L = L max ; The target color temperature is calculated according to the following formula: C = C base + ΔC M + ΔC T And if C <C min Then C = C min If C>C max Then C = C max .
[0014] Specifically, the preset rule is as follows: L s =0.2*L+0.8*L t-1 C s =0.2*C+0.8*C t-1 Among them, L s For the smoothed target brightness, C s For the smoothed target color temperature, L t-1 C represents the brightness at the previous moment. t-1 This indicates the color temperature at the previous moment.
[0015] Another aspect of the present invention provides a cabin ambient lighting control device, comprising: The data fusion and processing module, as well as the ambient light acquisition module, cockpit state perception module, driver attention analysis module, vehicle state perception module, and adaptive control module connected thereto, and also include a lighting execution module connected to the adaptive control module; The ambient light acquisition module is used to acquire ambient light intensity parameters inside the cockpit; The cockpit status sensing module is used to sense the emotional state of the people in the cockpit and the temperature parameters of the cockpit. The driver attention analysis module is used to analyze driver fatigue level parameters; The vehicle status perception module is used to acquire the vehicle's speed and steering angle; The data fusion processing module is used to fuse and process the data collected by the ambient light acquisition module, the cockpit state perception module, the driver attention analysis module and the vehicle state perception module, and output comprehensive state information. The adaptive control module is used to generate target lighting parameters based on the hierarchical decision-making mechanism of the comprehensive state information; The lighting execution module is used to adjust the cabin ambient lighting based on the control signal generated by the target lighting parameters.
[0016] The beneficial effects of this invention are as follows: This invention obtains a multi-dimensional parameter set of the cockpit, generates a feature vector set based on the multi-dimensional parameter set, then uses a weighted fusion algorithm to fuse the feature vector set, outputs comprehensive state information, and finally generates target lighting parameters based on the hierarchical decision-making mechanism of the comprehensive state information to control the cockpit ambient lighting device, thereby realizing intelligent and personalized cockpit ambient lighting and improving the competitiveness of the product. Attached Figure Description
[0017] Figure 1 This is a flowchart illustrating the cabin ambient lighting control method of the present invention; Figure 2 This is a structural schematic diagram of the cabin ambient lighting control device of the present invention. Detailed Implementation
[0018] The embodiments of the present invention are described in detail below with reference to the accompanying drawings. The drawings are for reference and illustration only and do not constitute a limitation on the scope of patent protection of the present invention.
[0019] In the process described in the specification, claims, or drawings of this invention, each step is numbered (e.g., step 10, 20, etc.). These numbers are used only to distinguish the steps and do not represent any execution order. It should be noted that the terms "first," "second," etc., used herein are only for distinguishing the objects being described and do not represent a chronological order, nor do they indicate that "first," "second," etc., are different types.
[0020] Example 1 like Figure 1 As shown, this embodiment provides a cabin ambient lighting control method, including: S1. Obtain a multi-dimensional parameter set for the cockpit, which includes at least ambient light data, personnel status data, driver physiological data, and vehicle driving parameters.
[0021] In this embodiment, step S1 includes: S11. Obtain ambient light intensity parameters for different areas within the cockpit; S12. Obtain the emotional and temperature parameters of the people in the cabin; S13. Obtain driver fatigue level parameters; S14. Obtain vehicle speed and steering angle parameters.
[0022] S2. Preprocess and extract features from the multidimensional parameter set to generate a feature vector set.
[0023] In this embodiment, step S2 includes: S21. The multidimensional parameter set is denoised, filtered, and normalized to generate a normalized parameter set.
[0024] For example, the normalized ambient light intensity E norm for:
[0025] Among them, E min =0lx,E max =10 5 lx.
[0026] Normalized vehicle speed V norm for:
[0027] Among them, V max It is determined based on the specific vehicle's maximum speed limit.
[0028] Normalized steering angle θ norm for:
[0029] Where, θ max =540°.
[0030] Normalized temperature T norm for:
[0031] Among them, T min T max You can set it yourself according to your actual needs, for example, T min =10℃, T max =40℃.
[0032] The normalized sentiment index M∈[0,1] (0=negative, 1=positive).
[0033] The normalized fatigue index F∈[0,1] (0=awake, 1=severely fatigued).
[0034] S22. Extract target feature information from the normalized parameter set to generate a feature vector set.
[0035] The target feature information includes: ambient light intensity, human emotional characteristics, cabin temperature characteristics, driver fatigue characteristics, vehicle speed characteristics, and steering angle characteristics.
[0036] S3. The feature vector set is fused using a weighted fusion algorithm to output comprehensive state information.
[0037] S4. Generate target lighting parameters based on the hierarchical decision-making mechanism of the comprehensive state information.
[0038] In this embodiment, step S4 includes: S41. When the driver's fatigue characteristic value F>0.6 and the vehicle speed V>30km / h, activate the first lighting mode; otherwise, proceed to the next step.
[0039] In this embodiment, the parameters corresponding to the first lighting mode are: color temperature H=0°, saturation S=100%, and brightness L. tired =L max *[1+sin(2π×0.3t)] / 2, where L max Let be the maximum brightness of the lighting system, and t be the time parameter.
[0040] S42. When the vehicle is turning, activate the second lighting mode; otherwise, proceed to the next step.
[0041] In this embodiment, the second lighting mode is: If the steering angle satisfies 0.1≤|θ norm If |≤0.3, then the ambient lighting parameters are: chromaticity H=30°, luminance L turn =L max *(0.4+0.2×θ norm (1-k) v *V norm ), where k v It is the vehicle speed suppression coefficient, which can be calibrated experimentally, for example, 0.6; If the steering angle satisfies |θ norm If |>0.3, then L turn =L t-1 L t-1 The brightness value at the last moment.
[0042] S43, Based on the normalized ambient light intensity E norm and vehicle speed V norm Determine the basic brightness L base With base color temperature C base ; In this embodiment, the basic brightness L base Determined according to the following formula:
[0043] Among them, L min For the system's minimum brightness, L max For maximum brightness, ω E ,、ω S Let w be the weighting coefficient. E +w S =1,k E is the ambient light response gain coefficient; p is the vehicle speed response index of brightness.
[0044] In this embodiment, ω E =0.7, ω S =0.3.
[0045] k E The optimal value can be determined through human factors engineering experiments based on the Weber-Fechner law, with a range of 5-15. In this embodiment, k E =9.
[0046] The value of P ranges from 0.5 ≤ p ≤ 2.0. In this embodiment, p = 1.35.
[0047] In this embodiment, the base color temperature C base Determined according to the following formula:
[0048] Among them, C min For the system's minimum color temperature, C max For maximum color temperature, δ E δ S Let be the weighting coefficients, satisfying δ E +δ S =1,j E is the ambient light color temperature saturation coefficient, and q is the vehicle speed response index of the color temperature.
[0049] In this embodiment, C min =2700K (representing warm colors), C max =6500K (representing a cool color).
[0050] In this embodiment, δ E =0.6, δ S =0.4.
[0051] j E The value range is 0.05 ≤ j E ≤ 0.8, in this embodiment j E Take 0.25.
[0052] In this embodiment, q=1.28.
[0053] S44, Based on normalized human emotion parameter M and normalized temperature T relative to baseline brightness L base With base color temperature C base Adjustments are made to determine the target brightness L and target color temperature C.
[0054] In this embodiment, step 44 includes: Step 4401: Calculate the first brightness adjustment amount ΔL based on the normalized human emotion parameter M. M .
[0055] In this embodiment, the first brightness adjustment amount ΔL M Calculate using the following formula: ΔL M = α M × M norm × ΔL max Where, α M The proportionality coefficient for emotion regulation can be determined experimentally (e.g., p). L = 0.4); ΔL max Maximum brightness adjustment range (e.g., ΔL) max =20% × (L max - L min )); M norm This is a normalized sentiment index.
[0056] Step 4402: Calculate the first color temperature adjustment amount ΔC based on the normalized human emotion parameter M. M .
[0057] In this embodiment, the first color temperature adjustment amount ΔC M Calculate using the following formula: ΔC M = -β M × M norm × ΔC max Where, β M This is the proportionality coefficient for emotion regulation, which can be calibrated experimentally (e.g., 0.5); ΔC max This represents the maximum adjustment range for color temperature (e.g., 500K).
[0058] From this formula, we can see that as the emotional parameter M increases, ΔC... M When the value is negative, the color temperature decreases, resulting in warmer ambient lighting; when the emotion parameter M decreases, ΔC... M A positive value indicates a higher color temperature, resulting in a cooler ambient light.
[0059] Step 4403: Based on the normalized temperature T norm Calculate the second brightness adjustment amount ΔLT .
[0060] In this embodiment, the second brightness adjustment amount ΔL T Calculate using the following formula: ΔL T = -α T × (T norm - 0.5) × 2 × ΔL max Where, α T This is the temperature regulation proportionality coefficient, which can be calibrated experimentally (e.g., 0.2); T norm Normalized temperature; ΔL max This represents the maximum brightness adjustment range.
[0061] Step 4404: Based on the normalized temperature T norm Calculate the second color temperature adjustment amount ΔC T .
[0062] In this embodiment, the second color temperature adjustment amount ΔC T Calculate using the following formula: ΔC T = β T × (T norm - 0.5) × 2 × ΔC max Where, β T This is the temperature regulation proportionality coefficient, which can be calibrated experimentally (e.g., 0.6), ΔC max This represents the maximum adjustment range for color temperature (e.g., 500K).
[0063] Step 4405: Based on the aforementioned basic brightness L base With base color temperature C base First brightness adjustment amount ΔL M Second brightness adjustment amount ΔL T First color temperature adjustment amount ΔC M Second color temperature adjustment amount ΔC T Calculate the target brightness L and target color temperature C.
[0064] In this embodiment, the target brightness L is calculated according to the following formula: L = L base + ΔL M + ΔL T And if L <L min Then L = L min If L>L max Then L = L max .
[0065] In this embodiment, the target color temperature C is calculated according to the following formula: C = C base + ΔC M + ΔC T And if C <C min Then C = C min If C>C max Then C = C max .
[0066] S45. Smooth the target brightness L and target color temperature C according to preset rules.
[0067] In this embodiment, the preset rule is: L s =0.2*L+0.8*L t-1 C s =0.2*C+0.8*C t-1 Among them, L s For the smoothed target brightness, C s For the smoothed target color temperature, L t-1 C represents the brightness at the previous moment. t-1 This indicates the color temperature at the previous moment.
[0068] S5. Control the cabin ambient lighting device according to the target lighting parameters.
[0069] Based on the determined lighting parameters, corresponding control signals are generated to adjust the working status of the corresponding LED light groups.
[0070] Example 2 like Figure 2 As shown, this embodiment provides a cabin ambient lighting control device, including: The data fusion and processing module, as well as the ambient light acquisition module, cockpit state perception module, driver attention analysis module, vehicle state perception module, and adaptive control module connected thereto, and also include a lighting execution module connected to the adaptive control module; The ambient light acquisition module is used to acquire ambient light intensity parameters inside the cockpit; In practical implementation, the ambient light acquisition module is an internal ambient light sensor installed inside the cabin. It can use a combination of various sensors, including sensors installed on the dashboard, ceiling, or inside the doors, to acquire ambient light data for different areas inside the cabin.
[0071] The cockpit status sensing module is used to sense the emotional state of the people in the cockpit and the temperature parameters of the cockpit. In practical implementation, the cockpit status perception module includes a camera, a microphone, and a temperature sensor; The camera can be a 1080P wide-angle camera, installed in a suitable location inside the cabin (such as the center of the ceiling), and uses image recognition technology to obtain the emotional state of the people inside the vehicle; The microphones can be high-sensitivity microphones, which can be installed on both sides of the ceiling to collect sound signals inside the cockpit and determine the emotional state of the people through voice recognition technology; Temperature sensors can be installed inside the center console to detect the temperature inside the cabin.
[0072] The driver attention analysis module is used to analyze driver fatigue level parameters; In practical implementation, the driver attention analysis module includes: an eye-tracking camera and a physiological signal sensor; Eye-tracking cameras, which can use near-infrared LEDs and high-speed CMOS image sensors, can be mounted above the dashboard to track the driver's eye movements and determine the driver's level of fatigue. The physiological signal sensors include a heart rate sensor and a respiratory rate sensor. The heart rate sensor can be a photoelectric reflective heart rate monitoring device, installed on the steering wheel; the respiratory rate sensor can be a piezoresistive sensor, installed inside the seat back, used to detect the driver's breathing rate. By analyzing the collected physiological signals, the driver's fatigue level can be determined.
[0073] The vehicle status perception module is used to acquire the vehicle's speed and steering angle.
[0074] The data fusion processing module is used to fuse and process the data collected by the ambient light acquisition module, the cockpit state perception module, the driver attention analysis module and the vehicle state perception module, and output comprehensive state information. In specific implementation, the data fusion processing module includes: a data preprocessing unit, a feature extraction unit, and a data fusion unit; the data preprocessing unit performs noise reduction, filtering, and normalization processing on the collected raw data; the feature extraction unit extracts feature information from the preprocessed data to generate a feature vector set; the data fusion unit uses a weighted fusion algorithm to fuse the feature vector set and output comprehensive status information.
[0075] The adaptive control module is used to generate target lighting parameters based on a hierarchical decision-making mechanism of the comprehensive state information.
[0076] The lighting execution module is used to adjust the cabin ambient lighting based on the control signal generated by the target lighting parameters. In practical implementation, the lighting execution module includes several LED light groups and a driving circuit. The LED light groups are installed in different positions in the cabin, such as the dashboard, roof, doors, seats, and footwell. The driving circuit drives the LED light groups to work according to the control signal, so as to adjust the color, brightness, and dynamic effects of the light.
[0077] In particular, the LED lights around the dashboard and in the driver's line of sight use high color rendering LEDs to improve the visibility of important information; while the LED lights in the footwell and inside the doors use low-brightness, warm-toned LEDs to provide soft ambient lighting.
[0078] The driving circuit uses a PWM driver chip to generate PWM signals with different duty cycles according to the control signal, which drive the LED light group to work and realize the adjustment of light color, brightness and dynamic effects.
[0079] The working process of the cabin ambient lighting device described in this embodiment is as shown in the cabin ambient lighting method described in Embodiment 1, and will not be repeated here.
[0080] The above-disclosed embodiments are merely preferred embodiments of the present invention and should not be construed as limiting the scope of protection of the present invention. Therefore, any equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.
Claims
1. A method for controlling cabin ambient lighting, characterized in that, include: S1. Obtain a multi-dimensional parameter set for the cockpit, which includes at least ambient light data, personnel status data, driver physiological data, and vehicle driving parameters. S2. Preprocess and extract features from the multidimensional parameter set to generate a feature vector set; S3. The feature vector set is fused using a weighted fusion algorithm to output comprehensive state information; S4. Generate target lighting parameters based on the hierarchical decision-making mechanism of the comprehensive state information; S5. Control the cabin ambient lighting device according to the target lighting parameters.
2. The cabin ambient lighting control method according to claim 1, characterized in that, Step S4 includes: S41. When the driver's fatigue characteristic value F>0.6 and the vehicle speed V>30km / h, activate the first lighting mode; otherwise, proceed to the next step. S42. When the vehicle is turning, activate the second lighting mode; otherwise, proceed to the next step. S43. Determine the base brightness and base color temperature based on the normalized ambient light intensity and vehicle speed; S44. Adjust the base brightness and base color temperature based on normalized human emotion parameters and normalized temperature to determine the target brightness and target color temperature.
3. The cabin ambient lighting control method according to claim 2, characterized in that, The parameters corresponding to the first lighting mode are: color temperature H=0°, saturation S=100%, brightness L. tired =L max *[1+sin(2π×0.3t)] / 2, where L max Let be the maximum brightness of the lighting system, and t be the time parameter. The second lighting mode is: If the steering angle satisfies 0.1≤|θ norm If |≤0.3, then the ambient lighting parameters are: chromaticity H=30°, luminance L turn =L max *(0.4+0.2×θ norm (1-k) v *V norm ), where k v It is the vehicle speed suppression coefficient, which can be calibrated experimentally, for example, 0.6; If the steering angle satisfies |θ norm If |>0.3, then L turn =L t-1 L t-1 The brightness value at the last moment.
4. The cabin ambient lighting control method according to claim 2, characterized in that, The base brightness is determined according to the following formula: Among them, L min For the system's minimum brightness, L max For maximum brightness, ω E ,、ω S Let w be the weighting coefficient. E +w S =1,k E is the ambient light response gain coefficient; p is the vehicle speed response index of brightness; The base color temperature is determined according to the following formula: Among them, C min For the system's minimum color temperature, C max For maximum color temperature, δ E δ S Let be the weighting coefficients, satisfying δ E +δ S =1,j E is the ambient light color temperature saturation coefficient, and q is the vehicle speed response index of the color temperature.
5. The cabin ambient lighting control method according to claim 2, characterized in that, Step 44 includes: Step 4401: Calculate the first brightness adjustment amount based on the normalized human emotion parameters; Step 4402: Calculate the first color temperature adjustment amount based on the normalized human emotion parameters; Step 4403: Calculate the second brightness adjustment amount based on the normalized temperature; Step 4404: Calculate the second color temperature adjustment amount based on the normalized temperature; Step 4405: Calculate the target brightness and target color temperature based on the base brightness and base color temperature, the first brightness adjustment amount, the second brightness adjustment amount, the first color temperature adjustment amount, and the second color temperature adjustment amount.
6. The cabin ambient lighting control method according to claim 5, characterized in that, The first brightness adjustment amount is calculated according to the following formula: ΔL M = a M × M norm × ΔL max Where, α M ΔL is the proportionality coefficient for emotion regulation. max M represents the maximum brightness adjustment range. norm A normalized sentiment index; The first color temperature adjustment amount is calculated according to the following formula: ΔC M = - β M × M norm × ΔC max Where, β M ΔC is the proportionality coefficient for emotion regulation. max This represents the maximum adjustment range for color temperature.
7. The cabin ambient lighting control method according to claim 6, characterized in that, The second brightness adjustment amount is calculated according to the following formula: ΔL T = - a T × (T norm - 0.5) × 2 × ΔL max Where, α T T is the temperature regulation proportional coefficient. norm For normalized temperature, ΔL max This represents the maximum brightness adjustment range; The second color temperature adjustment amount is calculated according to the following formula: ΔC T = β T × (T norm - 0.5) × 2 × ΔC max Where, β T ΔC is the temperature regulation proportional coefficient. max This represents the maximum adjustment range for color temperature.
8. The cabin ambient lighting control method according to claim 7, characterized in that, The target brightness is calculated according to the following formula: L = L base + ΔL M + ΔL T And if L < L min Then L = L min If L > L max Then L = L max ; The target color temperature is calculated according to the following formula: C = C base + ΔC M + ΔC T And if C < C min Then C = C min If C > C max Then C = C max .
9. The cabin ambient lighting control method according to claim 8, characterized in that, The preset rule is as follows: L s =0.2*L+0.8*L t-1 C s =0.2*C+0.8*C t-1 Among them, L s For the smoothed target brightness, C s For the smoothed target color temperature, L t-1 C represents the brightness at the previous moment. t-1 This indicates the color temperature at the previous moment.
10. A cabin ambient lighting control device, characterized in that, include: The data fusion and processing module, as well as the ambient light acquisition module, cockpit state perception module, driver attention analysis module, vehicle state perception module, and adaptive control module connected thereto, also includes a lighting execution module connected to the adaptive control module; The ambient light acquisition module is used to acquire ambient light intensity parameters inside the cockpit; The cockpit status sensing module is used to sense the emotional state of the people in the cockpit and the temperature parameters of the cockpit. The driver attention analysis module is used to analyze driver fatigue level parameters; The vehicle status perception module is used to acquire the vehicle's speed and steering angle; The data fusion processing module is used to fuse and process the data collected by the ambient light acquisition module, the cockpit state perception module, the driver attention analysis module and the vehicle state perception module, and output comprehensive state information. The adaptive control module is used to generate target lighting parameters based on the hierarchical decision-making mechanism of the comprehensive state information; The lighting execution module is used to adjust the cabin ambient lighting based on the control signal generated by the target lighting parameters.