Micro LED pixel vehicle lamp multi-zone control method and system, and vehicle

Abstract

The application discloses a kind of MicroLED pixel car light multi-zone control method, system and vehicle, wherein, method includes: based on LED junction temperature and environmental visibility determines temperature correction coefficient and fog scattering correction coefficient;With the same correction coefficient product, simultaneously correct basic transition bandwidth and basic optical coupling matrix;In the case where the pixel adjacency coupling topology, coupling kernel shape and coupling radius are kept unchanged, form fixed space structure, dynamic amplitude scaling real-time optical coupling model;Based on demarcation line distance and real-time transition bandwidth, continuously fuse illumination mask and projection mask;Then using the real-time optical coupling matrix calculates neighborhood light leakage and implements feedforward cancellation, finally generates PWM drive frame. Directly control pixel car light using vehicle speed, road and target perception information, output composite light field matched with current state under urban road, meeting, pedestrian crossing, rain and fog and fault working condition.

Description

Technical Field

[0001] This invention relates to the field of vehicle lighting control technology, specifically to a multi-zone control method, system, and vehicle for MicroLED pixel vehicle lights. Background Technology

[0002] Pixelated headlights can achieve adaptive high or low beam illumination, anti-glare for oncoming vehicles, pedestrian illumination, and road surface projection on the same light-emitting module by independently dimming the array of pixels. As the number of pixels increases, the lighting and projection functions need to share limited pixels, drive power, and computing resources, and their partition boundaries will also change with vehicle speed, road type, and oncoming traffic participants.

[0003] Existing control methods typically allocate pixels to lighting and projection based on preset areas or fixed ratios. When road risks or third-party glare conditions change, fixed partitioning can hardly simultaneously meet the requirements of basic lighting safety, projection graphic integrity, and anti-glare; if pixel assignment is switched directly between adjacent frames, it is also easy to cause brightness jumps, boundary jitter, or perceptible flicker at the boundary.

[0004] Furthermore, MicroLED arrays and their front-end optical systems suffer from inter-pixel light leakage, lens vignetting, and inconsistent pixel emission. Changes in LED junction temperature can alter the divergence characteristics of the emitted light field, and rain and fog can exacerbate scattering during propagation. When a fixed transition band and a fixed crosstalk compensation coefficient are used, calibration results under normal temperature and sunny conditions are insufficient to cover high temperature, low temperature, rain, and fog conditions, potentially causing boundary blurring, road surface halo, or a grayish projected image.

[0005] Solving these problems is now a top priority. Summary of the Invention

[0006] To address the above technical problems, this invention provides a method, system, and vehicle for multi-zone control of MicroLED pixel vehicle lights.

[0007] The technical solution is as follows:

[0008] The first aspect of this application relates to a multi-zone control method for MicroLED pixel automotive lights, comprising the following steps:

[0009] Power-on initialization of static calibration parameters, which include at least a pixel-far-field angle mapping table. Basic optical coupling matrix Width of basic transition zone Gamma correction curve and PWM mapping table;

[0010] Periodically obtain the LED junction temperature of the MicroLED array The visibility level Vis of the vehicle's external environment, based on the LED junction temperature. Determine the temperature correction factor The fog scattering correction factor is determined based on the visibility level Vis. And based on the fundamental optical coupling matrix Width of basic transition zone Temperature correction factor and fog scattering correction coefficient Determine the real-time transition band width and real-time optical coupling matrix ; wherein, the width of the real-time transition band and real-time optical coupling matrix Each will be subject to amplitude limiting.

[0011] Obtain vehicle speed and the set of targets in front of the vehicle. Based on road information, determine the target set. Each target unit Corresponding target collision risk coefficient and third-party glare coefficient Based on the maximum target collision risk coefficient Vehicle speed characteristic function Road type characteristics and maximum third-party glare coefficient Calculate the overall risk value The third-party glare coefficient The negative adjustment term is used in the overall risk value. Calculation;

[0012] The comprehensive risk value Mapped to lighting weights and projection weights and in lighting weight Lower bound constraint, minimum projected pixel area Under constraints and MicroLED array hardware constraints, multiple candidate boundary lines are generated to divide the lighting functional area and the projection interaction area. From the candidate boundary lines that satisfy the hardware constraints, the one corresponding to the current comprehensive risk value is selected. The original dividing line and the original boundary line The boundary line is obtained by performing boundary smoothing filtering. ;

[0013] According to the dividing line and real-time transition band width The MicroLED array is divided into non-overlapping lighting functional areas. Projection Interactive Area and transition pixel band ;

[0014] Pixels are allocated according to the priority order of basic ADB lighting, auxiliary lighting, safety projection, and comfort projection, based on the overall risk value. Exceeding the first risk threshold At that time, all comfortable projection pixels are reclaimed, and the projection interaction area shrinks. The boundary, in the comprehensive risk value Exceeding the second risk threshold At that time, redundant pixels of the safe projection are recycled, and the minimum pixel area of ​​the projection is retained. When an extremely high-risk oncoming vehicle or pedestrian target is detected at close range, the projection interaction area will be cleared. And its pixels are included in the lighting functional area. ;

[0015] Generate illumination sub-partition masks respectively and projection sub-partition mask ;

[0016] For each MicroLED pixel, first calculate the MicroLED pixel's position relative to the boundary line pixel by pixel. distance And according to the real-time transition band width Construction with distance Continuously changing transitional mixing weights According to the transition mixing weight For the illumination sub-partition mask and projection sub-partition mask The base target brightness is obtained by fusion. Then, based on the real-time optical coupling matrix and the set of neighboring pixels of the MicroLED pixel Calculate neighboring pixels The light leakage component of the MicroLED pixel, and from the basic target brightness After subtracting the light leakage component, the driving range is limited to obtain the pixel normalized output brightness. ;

[0017] First, normalize the output brightness of the pixel according to the Gamma correction curve. Brightness correction is performed, and then bit width mapping is performed according to the PWM mapping table to generate a PWM drive frame for driving the output drive light field of the MicroLED array.

[0018] The above-mentioned multi-zone control method for MicroLED pixel automotive lights determines temperature correction coefficients and fog scattering correction coefficients based on LED junction temperature and ambient visibility. The basic transition band width and basic optical coupling matrix are simultaneously corrected using the product of the same correction coefficients. While maintaining the pixel adjacency coupling topology, coupling kernel shape, and coupling radius, a real-time optical coupling model with a fixed spatial structure and dynamic amplitude scaling is formed. The illumination mask and projection mask are continuously fused based on the boundary distance and real-time transition band width. Then, the real-time optical coupling matrix is ​​used to calculate neighborhood light leakage and implement feedforward cancellation, finally generating a PWM drive frame. Therefore, this method updates the real-time transition band width and real-time optical coupling matrix synchronously with the same temperature correction coefficient and fog scattering correction coefficient, and connects risk-driven partitioning, distance field continuous fusion and neighborhood light leakage feedforward cancellation into a complete control chain, enabling lighting and projection to share pixels under dynamic road conditions, while reducing boundary jumps, crosstalk diffusion and image graying. This allows the pixel headlights to be directly controlled using vehicle speed, road and target perception information, and outputs a composite light field that matches the current state under urban roads, oncoming traffic, pedestrian crossings, rain, fog and fault conditions.

[0019] In some implementations, the real-time optical coupling matrix Determined according to the following formula:

[0020] ;

[0021] Among them, the basic optical coupling matrix The value range is [0, 0.15], temperature correction coefficient. The value range is [0.8, 1.6], which is the fog scattering correction coefficient. The value range is [1.0, 1.8], and the real-time optical coupling matrix is... The individual coupling weights are capped to [0, 0.24].

[0022] The real-time transition band width Determined according to the following formula:

[0023] ;

[0024] Among them, the width of the basic transition zone The value range is [3,8], and the real-time transition band width Wreal is limited to [2,12] pixels.

[0025] The above design uses scalar product to correct the basic optical coupling weights and the basic transition band width, and clamps them to the effective range respectively. This reduces the computational cost of dynamic convolution kernel reconstruction while keeping the coupling position and coupling radius unchanged, and avoids overcompensation or excessively wide transition bands caused by extreme temperature and fog combinations.

[0026] In some implementations, the target set This includes the target's horizontal angle, vertical angle, physical distance to the target, and target status;

[0027] For each target after data association, an independent Kalman filter instance is established, employing a constant angular velocity model for the state vector and a direct angle observation model for the observation vector, based on the vehicle speed. Target physical distance and target state Solving for dimensionless gain The noise matrix of the real-time adaptive process is obtained as follows:

[0028] ;

[0029] in, The reference process noise matrix;

[0030] Utilizing LED junction temperature Ambient lighting Visibility level (Vis), target physical distance Target state structure Solving for dimensionless gain The real-time adaptive observation noise matrix is ​​obtained as follows:

[0031] ;

[0032] in, The reference observation noise matrix;

[0033] The noise matrix of the real-time adaptive process and real-time adaptive observation noise matrix Substituting the values ​​into the Kalman filter iterative calculation, the optimal target motion state in the current frame is obtained. Then, the state transition matrix is ​​used to extrapolate outwards and predict the target's horizontal angle for the next 1 to 2 frames. And predicted vertical angle To determine the set of anti-glare protection pixels corresponding to the target and the original boundary line. .

[0034] By adopting the above design, an independent constant angular velocity Kalman filter instance is established for each target, and the process noise and observation noise are adaptively adjusted according to vehicle motion, target distance and environmental conditions. This can obtain a relatively stable future angle prediction when sensing jitter or short-term occlusion, and form an anti-glare protection pixel set in advance.

[0035] In some implementations, the illumination sub-partition mask ADB anti-glare base mask Lateral horizontal brightness attenuation function The composite yields:

[0036] ;

[0037] The predicted level angle is obtained based on Kalman prediction. And predicted vertical angle Pixels located within the target anti-glare protection pixel set The ADB anti-glare base mask The value in the middle is set to 0, and the rest are set to 1;

[0038] The lateral horizontal brightness attenuation function A piecewise linear attenuation method is used in the horizontal direction to gradually reduce the maximum allowable output brightness of the lateral pixels far from the center of the light field:

[0039] ;

[0040] in, For pixels Horizontal pixel coordinates, The horizontal pixel coordinates of the center of the light field. The main lighting area is half the width of the flat area. This is the lateral attenuation termination boundary;

[0041] The projection sub-partition mask The original grayscale image from the upper-level interactive graphics. The result is obtained by inputting the optical uniformity correction lookup table.

[0042] By combining the ADB hard occlusion mask with the lateral horizontal brightness soft attenuation, strong light can be shut off in the target protection area, and large-angle lateral stray light can be limited in the unoccluded area. Applying a uniform correction lookup table to the projected grayscale can compensate for pixel differences and vignetting, and improve the consistency of projected grayscale.

[0043] In some implementations, the comprehensive risk value Determined according to the following formula:

[0044] ;

[0045] in, All are pre-defined risk weight coefficients, with values ​​ranging from [0.1, 1.0].

[0046] The comprehensive risk value Mapping to satisfy Lighting weight and projection weights and make the lighting weight satisfy:

[0047] ;

[0048] in, Based on the basic lighting weight, it is the lighting weight. The lower limit.

[0049] By adopting the above design, collision risk, vehicle speed, and road type are used as positive adjustment factors for lighting resources, while third-party glare is used as a negative adjustment factor. Furthermore, lower and upper limits for lighting weights are set, so that the comprehensive risk value is used as a pixel scheduling indicator rather than a physical probability, thus forming a clear control direction between safe lighting and glare suppression.

[0050] In some implementations, the dividing line The determination includes the following steps:

[0051] Calculate lighting safety scores for each of the multiple candidate zoning schemes. Projection completeness and third-party glare loss ,by To maximize overall benefits, To minimize glare loss, candidate partitioning schemes that do not meet the preset MicroLED driving constraints and minimum projected area constraints are eliminated. The Pareto optimal solution set is then selected based on the comprehensive risk value. Select the original boundary line. ;

[0052] The original boundary line is defined according to the following formula. Perform boundary smoothing filtering to obtain the smoothed boundary line. :

[0053] ;

[0054] in, These are the boundary filter coefficients. Indicates the boundary line of the previous frame;

[0055] And, satisfy This limits the movement of the boundary line between adjacent frames to a preset maximum movement limit per boundary frame. Within.

[0056] By adopting the above design, through hardware constraint screening, Pareto non-dominated solution selection, inter-frame low-pass filtering, and single-frame maximum motion limit, the selected boundary line takes into account lighting safety, projection integrity, and glare loss, and reduces the possibility of the boundary jumping rapidly with perceived noise.

[0057] In some implementations, the dividing line To the projection interaction area Real-time transition band width on one side Within the range, the transition mixing weight satisfy:

[0058] ;

[0059] This indicates that the current pixel is output entirely using the illumination sub-partition mask. This indicates that the current pixel is output entirely using the projected sub-partition mask. The weights change continuously and monotonically within the interval [0,1] to achieve a smooth transition.

[0060] Through transitional blending weights Fusion lighting sub-partition mask and projection sub-partition mask The base target brightness, without considering pixel optical crosstalk, was calculated. :

[0061] ;

[0062] in, This is the global brightness equalization gain coefficient;

[0063] The pixel normalized output brightness The formula for calculation is:

[0064] ;

[0065] in, The real-time adaptive optical coupling coefficient is used to represent the neighboring pixels. For the current pixel The weight of light leakage intensity; The lower limit truncation is used to ensure that the pixel output brightness is physically achievable and to avoid negative brightness values ​​under strong crosstalk conditions.

[0066] By adopting the above design, the illumination mask and projection mask are continuously fused within the transition pixel band using raised cosine distance weights. Then, neighboring light leakage is subtracted according to real-time coupling weights and upper and lower limits are truncated, resulting in continuous, non-negative pixel brightness that can be achieved by the driving circuit.

[0067] In some implementations, the fault condition detection is also performed in parallel, including:

[0068] In the event of a Level 1 fault involving a short-term perceived frame drop, the pixel normalization output brightness of the previous frame is frozen. The dividing line between the previous frame and the previous frame ;

[0069] In the event of a Level 2 fault (permanent failure of the camera or radar), clear the projection interaction area. And only retain the illumination sub-partition mask. Calculation;

[0070] When a Level 3 fault occurs, such as algorithm overflow or MicroLED hardware failure, the execution of the MicroLED pixel headlight multi-zone control method is stopped, and the pre-stored fixed low beam basic light pattern or fixed high beam basic light pattern is output.

[0071] The above design employs a three-level fault strategy to handle short-term frame drops, continuous failure of critical sensors, and severe algorithm or hardware failures. This allows the system to progressively degrade from freezing the previous valid output and retaining only safety lighting to a fixed basic light pattern, thus avoiding the continued execution of unreliable complex projections and compensations under fault conditions.

[0072] The second aspect of this application relates to a multi-zone control system for MicroLED pixel automotive lights, comprising:

[0073] Independently dimmable MicroLED array;

[0074] Temperature sensor, used to acquire LED junction temperature of MicroLED array. ;

[0075] The environmental perception module is used to collect information for generating the visibility level Vis;

[0076] The target perception module is used to collect and generate a set of targets. Information;

[0077] Vehicle information interface, which is used to collect vehicle speed and road information;

[0078] The memory, which stores at least a pixel-far-field angle mapping table. Basic optical coupling matrix Width of basic transition zone Gamma correction curve, PWM mapping table, and computer program;

[0079] The processor, when executing the computer program, implements the above-described MicroLED pixel vehicle light multi-zone control method and outputs PWM drive frames to the MicroLED array.

[0080] The above-mentioned MicroLED pixel vehicle headlight multi-zone control system fully utilizes all the advantages of the aforementioned MicroLED pixel vehicle headlight multi-zone control method.

[0081] The third aspect of this application relates to a vehicle characterized by including the aforementioned MicroLED pixel headlight multi-zone control system.

[0082] Using the above vehicles, all the advantages of the aforementioned MicroLED pixel headlight multi-zone control method are realized. Attached Figure Description

[0083] Figure 1 This is a block diagram illustrating the principle of a multi-zone control method for MicroLED pixel automotive lights. Detailed Implementation

[0084] The present invention will be further described below with reference to the embodiments and accompanying drawings.

[0085] Example 1:

[0086] like Figure 1 As shown, a multi-zone control method for MicroLED pixel automotive lights includes the following steps:

[0087] S1. Initialize static calibration parameters after power-on.

[0088] After the vehicle or headlights are powered on, static parameter loading and data integrity verification are performed only once.

[0089] Static calibration parameters include:

[0090] (1) Pixel-far-field angle mapping table It is used to store pixel coordinates The corresponding coordinate system of the lamps specifies the horizontal and vertical emission angles, which are used to convert image pixel coordinates into target angles, preventing skewed projected graphics and offset illumination areas. ∈[0,1023], ∈[0,2047], horizontal exit angle Vertical exit angle .

[0091] (1) Basic optical coupling matrix This is the baseline coefficient for optical crosstalk between adjacent pixels under normal temperature and sunny conditions, serving as the basis for the crosstalk compensation algorithm. Matrix unit values: Where 0 represents no optical crosstalk and 0.15 represents the maximum light leakage of the pixel.

[0092] (2) Width of the base transition zone This refers to the standard pixel width of the transition pixel band between the lighting area and the projection area under normal temperature and sunny conditions. Value range: The industry default value is 6.

[0093] (3) The Gamma correction curve and PWM mapping table are obtained by fitting the driving PWM value with the actual luminous brightness based on LED photoelectric conversion tests. Gamma coefficient values ​​are as follows: PWM bit width: 8-bit, 12-bit, or 16-bit; the example uses 12-bit.

[0094] (4) Boundary filter coefficients It determines the optimal value by balancing boundary response speed and smoothing jitter based on vehicle testing on roads. Value range: .

[0095] (5) Maximum movement limit per frame at the boundary It is obtained through subjective visual testing and is used to avoid glaring effects from rapidly changing boundaries. Value range: ∈[1,4].

[0096] (6) First risk threshold Second risk threshold It classifies risk levels based on batch nighttime oncoming traffic and actual vehicle and pedestrian conditions. Value range: ∈[1.0,1.5]; ∈[2.0,2.5].

[0097] (7) Minimum pixel area of ​​projection It uses minimum resolution simulation calibration of projected graphics to ensure that warning graphics are recognizable. Value range: ∈[500,5000]

[0098] (8) Risk weighting coefficient It is obtained through fitting and calibration of a global risk function under multiple operating conditions. Value range: ∈[0.1,1.0].

[0099] S2, periodically collect dynamic information and perform fault detection in parallel.

[0100] Periodically obtain the LED junction temperature of the MicroLED array Visibility level (Vis) and ambient light of the vehicle's external environment Speed Target set .

[0101] The dynamic parameters updated in real time during each control cycle are as follows:

[0102] (1) Temperature correction factor Value range: The values ​​are based on LED optical calibration tests conducted in high and low temperature environmental chambers. When the LED chip heats up at high temperatures, the PN junction temperature rises, causing the light divergence angle to increase and the light diffusion to widen, expanding the illumination boundary. This necessitates narrowing the transition band and reducing coupling crosstalk, so the coefficient is greater than 1. At the extreme high temperature of 125℃, the divergence angle shift is the largest, with an upper limit of 1.6. At the low temperature of -40℃, the LED light converges, the beam narrows, and the boundary light transmission decreases, requiring amplified optical compensation, so the coefficient is less than 1; the lower limit of the extreme low temperature is 0.8. A value range of 0.8 to 1.6 can completely cover the beam shift across the entire operating temperature range of the vehicle headlight (-40℃ to 125℃). Exceeding this range will result in an excessively wide or narrow transition band, blurry edges in the projected image, or tonal gradations.

[0103] (2) Fog scattering correction coefficient Value range: The values ​​are based on fog chamber tests and multi-level visibility calibration in rainy weather. In fog-free, clear air with no scattering, light travels in a straight line, requiring no additional compensation; the baseline value is 1.0 (lower limit). In foggy or rainy weather, water vapor scatters light, blurring the illumination boundary and increasing the glare diffusion range; the lower the visibility, the stronger the scattering, requiring a wider transition buffer zone and enhanced brightness compensation. Vis=0 (dense fog) is the extreme condition, and the calibration yields a maximum compensation coefficient of 1.8; exceeding 1.8 will over-compress the projection and waste pixel resources. The lower limit of the value range does not start from 0: fog only exacerbates light scattering, does not weaken beam diffusion, and there is no need for negative correction.

[0104] (3) Real-time transition band width Value range: (Unit: Acorn), Value Basis: Balancing MicroLED hardware pixel size, human visual perception, and optical crosstalk suppression. Lower Limit 2 pixels: Minimum hardware buffer width. If the transition band is ≤1 pixel, the transition between light and dark boundaries is extremely steep, resulting in a clearly visible dividing line and flicker, making it impossible to eliminate crosstalk during lighting or projection. Upper Limit 12 pixels: Total pixel resource constraint. The transition band only serves as a buffer and does not participate in effective lighting or projection. A width exceeding 12 pixels will consume a large number of pixels, compressing the usable area for lighting and projection, and reducing the lighting field of view and the size of the projected image. The 2 to 12 pixel range can be used in conjunction with... , It adapts to various operating conditions, including temperature and fog.

[0105] (4) Real-time optical coupling matrix Value range: The value is based on the optical calibration of light leakage crosstalk between pixels. The lower limit is 0: Under ideal crosstalk-free conditions (sunny, normal temperature), the illumination pixels will not leak light into the projection area, and no coupling compensation is needed. The upper limit is 0.24: Under extreme high temperature and dense fog conditions, light leakage between pixels is most severe; 0.24 is the maximum crosstalk weight measured experimentally. The value represents the intensity of light leakage between adjacent pixels. Exceeding 0.24 will over-brighten the boundaries, causing road surface halos and glare; less than 0 results in no compensation, and the projection appears white and blurry.

[0106] (5) Vehicle speed The value range is 0-180km / h, and the value is based on the vehicle's VCU output, subject to regulatory restrictions. The lower limit is 0: for vehicles parked or idling at a standstill. The upper limit is 180km / h: the electronic speed limiter for passenger vehicles and the maximum legal speed limit on domestic roads; speeds exceeding 180km / h are considered extreme speeding conditions, and the algorithm will not be further optimized. The vehicle speed value is included in the overall risk value. Calculations show that the higher the vehicle speed, the higher the overall risk value. The higher the value, the more pixels are allocated to lighting.

[0107] (6) LED junction temperature Value range: -40℃ to 125℃, based on automotive-grade electronic device temperature standard AEC-Q102. -40℃: Minimum operating temperature for extremely cold starts in northern winters. 125℃: Maximum safe junction temperature for prolonged LED operation; exceeding this temperature will result in light decay and hardware burnout. This range represents a temperature correction factor. The input data source fully covers the entire operating temperature range of the module.

[0108] (7) Ambient lighting Value range: 0.01-100000 lux, based on data collected by a light sensor. Lower limit 0.01 lux: completely dark outdoor environment with no streetlights or other light sources at night. Upper limit 100000 lux: strong sunlight directly hitting the road surface at midday in summer. Risks associated with using ambient light for calculation: The human eye is less sensitive to glare under strong daylight, so the weight of glare is reduced; low light at night makes the eye more sensitive to glare, so the algorithm increases its anti-glare measures.

[0109] (8) Visibility level Vis, value range: 0-10, value basis: image algorithm extracts the contrast of distant scene, gray mean, and edge feature fusion to evaluate fog concentration, divides fog conditions into 11 integer levels from 0 to 10, without the need to calculate the precise physical visibility distance, reducing the computing power consumption of the controller; a hierarchical lookup table method is used to reduce the computing power consumption of the controller, which is used to match the fog scattering correction coefficient. It adaptively compensates for glare and projection blur caused by ambient light scattering in rain and fog. Level 0: Extremely dense fog with extremely poor visibility; Level 10: Clear skies with no fog. There are 11 levels in total, ranging from integers 0 to 10. The classification is simple and consumes little computing power. It linearly maps the fog correction coefficient without requiring complex floating-point calculations. Too many levels would increase computing power, while too few would result in insufficient correction accuracy.

[0110] (9) Target collision risk coefficient The value range is [0,1]. The value is based on a normalized evaluation metric to facilitate cross-sectional comparison and weighted calculation of multiple objectives. Lower limit 0: no risk; upper limit 1: maximum risk.

[0111] (10) Third-party glare coefficient Value range: [0,1], value basis: normalized evaluation quantity, to facilitate multi-target horizontal comparison and weighted calculation. Lower limit 0: no glare; upper limit 1: strongest glare.

[0112] (11) Target set It carries perception data of traffic targets ahead, has no fixed numerical range, and belongs to the set type variable. Target set The empty set represents the absence of any vehicles, pedestrians, or obstacles in front, and the target set. The maximum number of elements is 30. The forward-looking perception hardware synchronously identifies the upper limit of the target. More than 30 weak targets at a distance are directly filtered out to reduce computing power consumption.

[0113] (12) Overall risk value Value range: ∈[-0.5,3.0], value based on: multi-dimensional risk weighted normalization calibration. Lower limit -0.5: extremely low risk conditions, prioritize expanding the projection area; upper limit 3.0: high risk conditions, increase lighting weight, and clear the projection area.

[0114] (13) Lighting weight and projection weights Constraints need to be met .

[0115] (14) Global brightness equalization gain coefficient The value range is [1.0, 1.4], and the value is based on: transition zone brightness attenuation compensation and regulatory brightness upper limit constraints. Base value 1.0: indicates no compensation. That is, in normal temperature and sunny weather, the brightness attenuation in the transition zone is slight, and no brightening is needed. Upper limit value 1.4: In low temperature and dense fog, the light loss in the transition area is severe, requiring brightening to compensate for the dim image; the national standard GB4785 limits the maximum brightness of low beam headlights, and 1.4 is the maximum brightening factor without exceeding the regulatory brightness threshold. Because the transition zone only has brightness attenuation and no excess light, there is no need to reduce brightness, so values ​​less than 1 are not set.

[0116] Fault detection and subsequent normal algorithms are executed in parallel. When a change in fault level is detected, the fault policy can immediately override the output permissions of the normal algorithm.

[0117] Specifically, perform fault state detection in parallel:

[0118] In the event of a Level 1 fault involving a short-term perceived frame drop, the pixel normalization output brightness of the previous frame is frozen. The dividing line between the previous frame and the previous frame To prevent single-frame empty data from causing full array flicker; when the freeze time exceeds the preset threshold, it is upgraded to a level 2 fault.

[0119] In the event of a Level 2 fault (permanent failure of the camera or radar), clear the projection interaction area. And only retain the illumination sub-partition mask. The calculation can determine the real-time transition band width. The value is fixed to a reference value, and the coupling compensation gain is reduced to decrease output fluctuations caused by erroneous environmental parameters.

[0120] When a Level 3 fault occurs, such as algorithm overflow or MicroLED hardware failure, the execution of the MicroLED pixel headlight multi-zone control method is stopped, and the pre-stored fixed low beam basic light pattern or fixed high beam basic light pattern is output.

[0121] S3. Determine the environmental adaptive optics parameters.

[0122] Based on the preset boundary single-frame maximum movement limit LED junction temperature Determine the temperature correction factor The fog scattering correction coefficient is determined based on the preset boundary single-frame maximum movement limit and visibility level Vis. And based on the preset boundary single-frame maximum motion limit fundamental optical coupling matrix Width of basic transition zone Temperature correction factor and fog scattering correction coefficient Determine the real-time transition band width and real-time optical coupling matrix Real-time transition band width and real-time optical coupling matrix It is adaptable to all climate and temperature conditions and is used for subsequent optical field boundary smoothing and optical crosstalk compensation.

[0123] Real-time transition band width for the preset maximum single-frame movement limit at the boundary and real-time optical coupling matrix Amplitude limiting is implemented separately, employing an engineering equivalent modeling method with a fixed kernel spatial structure and dynamic amplitude scaling. This significantly reduces the real-time computing power overhead of the onboard controller while ensuring optical compensation accuracy. Details are as follows:

[0124] Real-time optical coupling matrix Determined according to the following formula:

[0125] ;

[0126] Regarding the above Amplitude limiting cutoff function, when hour, ,when hour, ,when hour, .

[0127] Among them, the basic optical coupling matrix The value range is [0, 0.15], which represents the inherent spatial distribution of optical crosstalk between MicroLED pixels, including inherent optical characteristics such as radius, coupling kernel shape, and basic light leakage weight, and remains constant during algorithm operation; temperature correction coefficient. The value range is [0.8, 1.6]; fog scattering correction coefficient The value range is [1.0, 1.8]; Real-time optical coupling matrix The individual coupling weights are capped to [0, 0.24].

[0128] Real-time transition band width Determined according to the following formula:

[0129] ;

[0130] Among them, the width of the basic transition zone The value range is [3,8], and the width of the basic transition zone is... It is the static reference pixel width under standard working conditions of normal temperature and clear skies, which is a fixed calibration constant of the system; the real-time transition band width Wreal is limited to [2,12] pixels.

[0131] Temperature correction factor Indicating internal optical changes in the light source: LED junction temperature The changes directly alter the chip's light emission divergence angle and beam energy distribution. Under high-temperature conditions, the LED's light emission divergence angle widens, the outward diffusion of the light field in a single pixel is enhanced, and the overall amplitude of native light leakage between pixels increases. Under low-temperature conditions, the beam converges, the light field concentration increases, and the overall crosstalk between pixels is weakened. Temperature changes only alter the overall leakage amplitude of the light emitted by the pixel and do not change the relationships determined by the MicroLED hardware structure; therefore, they do not change the spatial shape and coupling radius of the coupling core.

[0132] Fog scattering correction factor This describes the optical changes propagating from the air medium: In rainy or foggy weather, suspended aerosols in the air scatter light multiple times, causing the originally sharp illumination boundary to diffuse and spread. Macroscopically, this manifests as an overall increase in the boundary leakage intensity of the entire light field. Although atmospheric scattering physically exhibits spatial convolution broadening characteristics, within the effective field of view of vehicle low beam lighting, finite pixel resolution, and normal driving visibility range, the boundary blurring effect caused by fog can be equivalent to a proportional amplification of the coupling weights of all pixels; the relative crosstalk distribution characteristics between pixels remain stable, without the need to dynamically modify the shape of the coupling kernel function and the coupling radius.

[0133] In summary, although the physical mechanisms of the changes in internal light field divergence at the LED light source caused by temperature and the changes in external light scattering at the propagation end caused by rain, fog, and visibility differ, they both manifest as a uniform increase or decrease in optical leakage intensity across the entire system's operating range, while the spatial coupling topology remains unchanged. Therefore, this patent employs a scalar product unified correction model to achieve adaptive optical compensation under all operating conditions with extremely low computational power. Theoretically, The maximum value is 0.15. Maximum value 1.6 The maximum value is 1.8, and multiplying the three values ​​yields a theoretical extreme value of 0.432. However, in actual vehicle operation, extreme high temperatures of LEDs and dense fog are difficult to coexist; an excessively high coupling coefficient will cause excessive brightening of the boundaries, increased road surface halo, and induce additional glare, which does not meet the requirements of vehicle lighting regulations and visual comfort. Therefore, the algorithm introduces a truncation constraint. After obtaining the coupling coefficient through multiplication, upper and lower limit clamping is performed to ensure that the coupling weights of all pixels stably fall within the effective range of [0, 0.24].

[0134] The real-time transition band width output in this step Real-time optical coupling matrix This will serve as the real-time input parameter for subsequent light field fusion, crosstalk cancellation, and boundary smoothing algorithms.

[0135] S4. Multi-target prediction and anti-glare protection area generation.

[0136] target set This includes the target's horizontal angle, vertical angle, physical distance, and status. Target set. A single target unit within ;in, The target angle observation vector is derived from the pixel-far-field angle mapping table. The solution is obtained; The physical distance to the target; The target state structure.

[0137] Through the target set To complete multi-target data association, an independent Kalman filter instance is established for each target after data association. A constant angular velocity model for the state vector and a direct angle observation model for the observation vector are used, based on the vehicle speed. Target physical distance and target state Solving for dimensionless gain The noise matrix of the real-time adaptive process is obtained as follows:

[0138] ;

[0139] in, The reference process noise matrix;

[0140] Utilizing LED junction temperature Ambient lighting Visibility level (Vis), target physical distance Target state structure Solving for dimensionless gain The real-time adaptive observation noise matrix is ​​obtained. :

[0141] ;

[0142] in, The reference observation noise matrix;

[0143] The noise matrix of the real-time adaptive process and real-time adaptive observation noise matrix Substituting the values ​​into the Kalman filter iterative calculation, the optimal target motion state in the current frame is obtained. Then, the state transition matrix is ​​used to extrapolate outwards and predict the target's horizontal angle for the next 1 to 2 frames. And predicted vertical angle To determine the set of anti-glare protection pixels corresponding to the target and the original boundary line. .

[0144] (1) The constant angular velocity model is:

[0145] ;

[0146] , ;

[0147] in, For state vectors, Let k be the horizontal observation angle of the target at time k. Let k be the target's horizontal angular velocity. Let k be the vertical observation angle of the target at time k. Let k be the target's vertical angular velocity. The constant angular velocity state transition matrix, This is the noise vector at time k-1.

[0148] The process noise follows a Gaussian distribution: .

[0149] (2) The direct observation model of angle is:

[0150] ;

[0151] ;

[0152] in, For direct angle observation matrix, Let k be the noise vector observed at time k.

[0153] The observation noise follows a Gaussian distribution: .

[0154] It can increase with increasing vehicle speed, decreasing target distance, or sudden changes in motion state; It can increase as the temperature deviates from the baseline value, the ambient light is too low, the visibility decreases, the target distance increases, or the observation confidence decreases.

[0155] S5. Calculate the overall risk value and the weights for lighting and projection.

[0156] Calculate the overall risk value Used for dynamically allocating lighting weights and projection weights (satisfies constraints) This enables adaptive allocation of pixel resources between road lighting and ground projection.

[0157] Specifically, based on the maximum target collision risk coefficient Vehicle speed characteristic function Road type characteristics and maximum third-party glare coefficient Calculate the overall risk value Therefore, the overall risk value Determined according to the following formula:

[0158] ;

[0159] in, All are pre-defined risk weight coefficients, with values ​​ranging from [0.1, 1.0].

[0160] The collision risk coefficient is the highest among all targets; This indicates the collision risk posed by the target ahead. The higher the risk, the higher the overall index, and the algorithm tends to allocate more pixels for road lighting.

[0161] This is the vehicle speed characteristic function corresponding to the vehicle speed. This function is used to indicate that as vehicle speed increases, the driver's need for long-distance lighting visibility increases. The vehicle speed function increases monotonically, thus increasing the priority of lighting.

[0162] For road type features; This is used to indicate the baseline risk offset for different road types such as highways, urban roads, and rural roads.

[0163] The maximum glare coefficient for all targets. The higher the value, the stronger the glare effect of our lights on vehicles and pedestrians ahead. This is a glare constraint correction term, namely: third-party glare coefficient. The negative adjustment term is used in the overall risk value. The calculation shows that as glare intensity increases, When the value is reduced, the system automatically lowers the lighting weight and softens the light field boundary, actively suppressing strong light leakage and achieving anti-glare constraint; under conditions without significant glare, this effect is weak, ensuring normal lighting and projection functions.

[0164] For vehicle speed characteristic function Using piecewise linear form:

[0165] ;

[0166] according to Size mapping yields lighting weights Projection weights To ensure basic driving safety, the system sets a minimum lighting weight of 0.4, ensuring that at least 40% of pixels are always allocated for road lighting regardless of the operating conditions. In extremely high-risk conditions, the lighting weight reaches a maximum of 0.99, reserving only a very small percentage of pixels for auxiliary projection. satisfy:

[0167] ;

[0168] in, Based on the basic lighting weight, it is the lighting weight. The lower limit is set to ensure that the basic road lighting retains no less than the preset proportion of pixels under any normal operating conditions.

[0169] S6, candidate partition optimization, boundary smoothing, and hierarchical pixel allocation.

[0170] Comprehensive risk value Mapped to lighting weights and projection weights and in lighting weight Lower bound constraint, minimum projected pixel area Under constraints and MicroLED array hardware constraints, multiple candidate boundary lines are generated to divide the lighting functional area and the projection interaction area. From the candidate boundary lines that satisfy the hardware constraints, the one corresponding to the current comprehensive risk value is selected. The original dividing line and the original boundary line The boundary line is obtained by performing boundary smoothing filtering. According to the dividing line and real-time transition band width The MicroLED array is divided into non-overlapping lighting functional areas. Projection Interactive Area and transition pixel band .

[0171] Specifically, the dividing line The determination includes the following steps:

[0172] (1) First, establish standards: calculate the lighting safety score for each of the multiple candidate zoning schemes. Projection completeness and third-party glare loss Among them, lighting safety is divided into It can comprehensively consider basic lighting coverage, target visibility, and ADB protection compliance, as well as projection integrity. It can comprehensively consider the area retained in the graphic, the integrity rate of key strokes, and the usable grayscale range, as well as third-party glare loss analysis. It can integrate the light intensity and large-angle lateral output within the protected area.

[0173] (2) Generate multiple candidate partitioning schemes, and filter out candidate schemes that do not meet hardware constraints such as maximum PWM per pixel, total lamp power, local power density, minimum guarantee for basic lighting, minimum pixel area for projection, and single-frame computation time. To maximize overall benefits, To minimize the glare loss, the Pareto optimal solution set and the current overall risk value are obtained from the remaining solutions. Select an optimal original dividing line. .

[0174] (3) To reduce the jitter of the boundary line between adjacent frames, the original boundary line is adjusted according to the following formula. Perform boundary smoothing filtering to obtain the smoothed boundary line. :

[0175] ;

[0176] in, These are the boundary filter coefficients. Indicates the boundary line of the previous frame;

[0177] And, satisfy This limits the movement of the boundary line between adjacent frames to a preset maximum movement limit per boundary frame. Within.

[0178] According to the dividing line and real-time transition band width The entire pixel panel is cut to divide the MicroLED array into non-overlapping lighting functional areas. Projection Interactive Area and transition pixel band Among them, the lighting functional area Used for ADB adaptive lighting, projection interaction area Transition pixel band used for projecting graphics or warning signals onto the road surface, etc. To closely follow the dividing line and real-time transition band width The strip-shaped buffer pixels.

[0179] Furthermore, the lighting functional areas The projected area is divided into three sub-areas: main road lighting, oncoming vehicle glare and shielding sub-area, and pedestrian high-brightness supplementary lighting sub-area. It is divided into two sub-areas: a safety warning graphic sub-area and a welcome decorative light language sub-area. This allows for the simultaneous implementation of multiple lighting functions without interference.

[0180] Subsequently, pixels were allocated according to the priority of basic ADB lighting (minimum guarantee), auxiliary lighting (main road enhancement, pedestrian supplemental lighting, etc.), safety projection (for collision warning, lane indication, etc.), and comfort projection (for welcome or decorative lighting, etc.), based on the comprehensive risk value. Exceeding the first risk threshold At that time, all comfortable projection pixels are reclaimed, and the projection interaction area shrinks. The boundary, in the comprehensive risk value Exceeding the second risk threshold At that time, redundant pixels of the safe projection are recycled, and the minimum pixel area of ​​the projection is retained. When an extremely high-risk oncoming vehicle or pedestrian target is detected at close range, the projection interaction area will be cleared. And its pixels are included in the lighting functional area. .

[0181] S7. Generate illumination sub-partition mask and projection sub-partition mask .

[0182] By integrating ADB anti-glare rules and applying attenuation constraints to lateral brightness, third-party glare is reduced, and an illumination sub-zone mask is generated. ; An optical uniformity correction lookup table is superimposed on the grayscale image of the upper layer graphic, and the projection sub-partition mask is output. Pixel coordinates The row and column indices represent the MicroLED array. The mask value represents the maximum allowable output duty cycle or brightness coefficient of the corresponding pixel. 1 represents full brightness output, and 0 represents the pixel being off.

[0183] Specifically, illumination sub-partition mask ADB anti-glare base mask Lateral horizontal brightness attenuation function The composite yields:

[0184] ;

[0185] The predicted level angle is obtained based on Kalman prediction. And predicted vertical angle Pixels located within the target anti-glare protection pixel set ADB anti-glare base mask Set the value in the middle to 0 and the rest to 1; this completes the traditional anti-glare shading.

[0186] ;

[0187] Lateral horizontal brightness attenuation function (To suppress strong lateral light and reduce oncoming glare) A piecewise linear attenuation in the horizontal direction is used to gradually reduce the maximum allowable output brightness of lateral pixels far from the center of the light field.

[0188] ;

[0189] in, For pixels Horizontal pixel coordinates, The horizontal pixel coordinates of the center of the light field. Half width of the main lighting flat area (in pixels); Lateral attenuation within the interval remains constant, and the coefficient remains at 1. The lateral attenuation termination boundary (in pixels); Exceed After that, the decay ceased, and the base remained at 0.4. For example, =80 pixels, =160 pixels.

[0190] Through the above design, there is no attenuation in the central area; the brightness of lateral pixels away from the center gradually decreases, and the upper limit of brightness in the farthest lateral area is limited to 40% of the original value, preventing large-angle lateral light from directly hitting oncoming vehicles and pedestrians. Compared to traditional ADB which only performs "hard occlusion", this step also applies soft lateral brightness constraints in areas without target occlusion, reducing lateral stray light from the source and further suppressing third-party glare.

[0191] In this embodiment, the projection sub-partition mask The original grayscale image from the upper-level interactive graphics. The result is obtained by inputting the optical uniformity correction lookup table, i.e.:

[0192] ;

[0193] in, This is the original grayscale image of the upper-layer interactive graphics. This is an optical uniformity correction lookup table used to compensate for optical differences in LED arrays, lens vignetting, and inconsistent pixel emission.

[0194] An example of discrete calibration is shown below, where linear interpolation can be used between adjacent nodes.

[0195] Original grayscale Corrected projection sub-partition mask 0.00 0.00 0.20 0.24 0.40 0.46 0.60 0.65 0.80 0.83 1.00 1.00

[0196] Due to issues such as vignetting and uneven pixel emission in the front-end optical system of MicroLEDs, the actual brightness at the edges of the image is lower under the same input grayscale. Therefore, the original grayscale image of the upper-layer interactive graphics is used. The projection sub-partition mask is obtained by inputting the optical uniformity correction lookup table. This allows for a moderate increase in the grayscale of medium and low-level areas, compensating for optical losses and ultimately ensuring a uniform and consistent grayscale appearance of the road surface projection.

[0197] S8. Continuous transition fusion based on distance field.

[0198] For each MicroLED pixel, first calculate the relative position of that MicroLED pixel to the boundary line pixel by pixel. distance And based on the real-time transition band width Construction with distance Continuously changing transitional mixing weights According to the transition mixing weight Illumination sub-partition mask and projection sub-partition mask The base target brightness is obtained by fusion. .

[0199] Dividing line To the projection interaction area Real-time transition band width on one side Within the range, transitional mixed weights satisfy:

[0200] ;

[0201] For lighting functional areas , This indicates that the current pixel is output using the illumination sub-partition mask.

[0202] For the projection interaction area , This indicates that the current pixel is output using the projected sub-partition mask.

[0203] For the transition pixel band T, , The weights change continuously and monotonically within the interval [0,1] to achieve a smooth transition.

[0204] Then, through transitional blending weights Fusion lighting sub-partition mask and projection sub-partition mask The base target brightness, without considering pixel optical crosstalk, was calculated. :

[0205] ;

[0206] in, This is the global brightness equalization gain coefficient, with a value range of [0.8-1.2], used for uniform adjustment of the brightness of the entire light field.

[0207] Based on the real-time transition band width output from the previous steps A continuous and smooth blending weight is constructed using a raised cosine function. The boundary position fully adopts the illumination mask characteristics. As pixels move away from the boundary, the brightness weight gradually and smoothly transitions from the illumination mask to the projection mask; when the pixel distance is greater than... At this time, projection mask output is used entirely. This continuous weighting method does not require dynamic segmentation of pixel blocks, and can completely avoid brightness jumps and visual flicker caused by region switching.

[0208] S9, pixel-level optical crosstalk feedforward compensation.

[0209] According to the real-time optical coupling matrix and the set of neighboring pixels of the MicroLED pixel Calculate neighboring pixels The light leakage component of the MicroLED pixel, and from the basic target brightness After subtracting the light leakage component, the driving range is limited to obtain the pixel normalized output brightness. Pixel normalized output brightness The formula for calculation is:

[0210] ;

[0211] in, The real-time adaptive optical coupling coefficient is used to represent the neighboring pixels. For the current pixel The weight of light leakage intensity; The lower limit truncation is used to ensure that the pixel output brightness is physically achievable and to avoid negative brightness values ​​under strong crosstalk conditions.

[0212] Steps S8 and S9 employ a raised cosine window function to construct transition weights, which can completely eliminate abrupt changes in brightness and visual flicker caused by hard boundaries in lighting and projection; simultaneously, they rely on environmental adaptive parameters. This allows the transition band width to be dynamically and adaptively adjusted according to LED junction temperature and ambient visibility, adapting to all weather conditions. Due to inherent optical crosstalk in MicroLED arrays, light emitted from adjacent pixels leaks into each other, leading to widened light field boundaries and blurred images. This method, based on ideal fused brightness, accurately deducts the leaked light components from neighboring pixels, achieving pixel-level optical crosstalk feedforward compensation, effectively converging boundary blurring and improving light field clarity and boundary regularity. Non-negative truncation constraints ensure output stability under extreme conditions, resulting in continuous, smooth, and noise-free light field output across the entire frame. Specifically, the compensation in step S9 is feedforward compensation, and the neighbor summation uses the uncompensated base target brightness. This avoids recursive solutions between pixels. If hardware calibration indicates that its own pixels also have equivalent feedback terms, this can be achieved in the basic optical coupling matrix. It can be set separately or absorbed through global gain. Non-negative truncation prevents unattainable negative brightness under strong crosstalk conditions, and upper limit truncation prevents exceeding the maximum duty cycle.

[0213] S10, Gamma correction, PWM mapping, and light field output.

[0214] First, normalize the output brightness of the pixels according to the Gamma correction curve. Perform brightness correction:

[0215] ;

[0216] in, Normalize the output brightness for pixels , To be The normalized driving domain grayscale value after correction by the inverse Gamma correction curve has a range of [0,1]. This value is a normalized floating-point value and has not yet undergone hardware bit-width quantization.

[0217] Then, based on the PWM mapping table, bit width mapping is performed to generate a PWM drive frame for driving the output drive light field of the MicroLED array:

[0218] ;

[0219] in, It is a PWM drive frame, and its output range is 0-4095. The round function is used for rounding to the nearest integer. =8bit, 12bit or 16bit, 12bit is commonly used.

[0220] After completion, return to step S3. It should be noted that steps S2 and S3-S10 are performed in parallel.

[0221] The following are application examples under specific working conditions:

[0222] Parameter calibration: , , , The range of values ​​is .

[0223] : At speeds ≤30km / h, It is 0.2; At speeds between 30 and 120 km / h It increases linearly; At speeds ≥120km / h, The value is 1.

[0224] Application Example 1: Normal Urban Road Projection Conditions

[0225] The vehicle was traveling at 25 km / h on a city road with no oncoming vehicles or pedestrians in front; the LED junction temperature was 25℃ and Vis=10.

[0226] , ;

[0227] , ;

[0228] ;

[0229] Weight calculation:

[0230] ;

[0231] ;

[0232] ;

[0233] Control strategy: balanced allocation of lighting and projection resources; medium-width smooth transition band; unobstructed ADB mask with moderate lateral brightness attenuation; moderate crosstalk compensation; simultaneous output of basic road lighting and ground interactive projection, suitable for urban pedestrian and vehicle mixed traffic scenarios.

[0234] Application Example 2: Rapid Approach of Oncoming Vehicles

[0235] The vehicle is traveling at 60 km / h on a two-way road, with an oncoming vehicle rapidly approaching. The LED junction temperature is 25℃, and Vis=10.

[0236] High risk of glare;

[0237] ;

[0238] Weight calculation:

[0239] ;

[0240] ;

[0241] Control strategy: This brings about a significant negative adjustment, reducing overall risk and slightly increasing projection weight; the ADB mask sets zero occlusion for oncoming vehicle areas, further attenuating lateral brightness and suppressing stray light; the transition zone is smoothly blended, reducing direct strong light output and prioritizing glare suppression; projection is moderately retained for road marking interaction, but direct strong light on the opposite side is avoided.

[0242] Application Example 3: Pedestrian crossing the road

[0243] Speed The speed limit is 50 km / h; pedestrians are crossing the lane from the roadside; the LED junction temperature is 25℃, and Vis=10.

[0244] High collision risk ;

[0245] ;

[0246] Weight calculation:

[0247] ;

[0248] ;

[0249] Control strategy: Collision risk factors take precedence, lighting weight is significantly increased, and projection resources are compressed; ADB mask protects pedestrian areas from glare while enhancing the lighting output around pedestrians; sufficient lighting ensures target recognition; projection retains only a small amount of interactive information, and safety lighting is prioritized.

[0250] Application Example 4: High Temperature and Extremely Dense Fog Overlapping Conditions

[0251] LED junction temperature is high. Severe fog Speed The speed was 40 km / h, and there were no nearby targets.

[0252] ;

[0253] Original coupling coefficient product This triggers amplitude limiting.

[0254] ;

[0255] ;

[0256] ;

[0257] Weight calculation:

[0258] ;

[0259] Control strategy: The transition zone width is adaptively widened significantly, the light field boundary is extremely soft, and glare in fog is suppressed; the upper limit of the optical coupling coefficient is triggered to prevent over-compensation from causing image distortion; the crosstalk compensation intensity reaches the maximum value to offset the boundary diffusion caused by the increased pixel light leakage under high temperature; the side attenuation in foggy weather is continuous to reduce stray light scattered in the air; the lighting and projection weights are nearly balanced to take into account both the field of vision and road surface prompts.

[0260] Application Example 5: Partial Channel Failure and Degraded Operation Conditions

[0261] Condition 1:

[0262] Anomalies were detected in some MicroLED pixel channels, and the algorithm entered a fault degradation strategy.

[0263] Fixed constraint: Forced locking Limit the maximum projection weight ;

[0264] Fixed parameter freeze: Force clamp to reference value It no longer amplifies with temperature and humidity;

[0265] Coupling compensation strength halved To avoid compensatory instability.

[0266] Condition 2:

[0267] Driving at high speed V=100km / h, there is a vehicle ahead;

[0268] Original calculation ,theory Triggering a downgrade constraint, forcibly raising it to [a higher level]. .

[0269] Control strategy: Abandon dynamic adaptive adjustment and prioritize basic road lighting; compress projection function; fix transition bandwidth to reduce crosstalk compensation amplitude and avoid flickering caused by abnormal pixel superposition compensation; turn off complex graphic projection and retain only the simplest lighting ADB anti-glare function to meet the minimum safety requirements of regulations.

[0270] Example 2:

[0271] A multi-zone control system for MicroLED pixel automotive lights includes an independently dimmable MicroLED array, a temperature sensor, an environmental perception module, a target perception module, a vehicle information interface, a memory, and a processor. The temperature sensor is mounted on the light panel and is used to collect the LED junction temperature of the MicroLED array. The environmental perception module includes cameras and ambient light sensors, used to collect and generate visibility level (Vis) information. The target perception module fuses camera and radar outputs to collect and generate a target set. The vehicle information interface is used to collect vehicle speed and road information, and the memory stores at least a pixel-far-field angle mapping table. Basic optical coupling matrix Width of basic transition zone The processor executes the computer program, which includes a Gamma correction curve, a PWM mapping table, and a computer program, to implement the MicroLED pixel vehicle light multi-zone control method of Embodiment 1 and output PWM drive frames to the MicroLED array.

[0272] Example 3:

[0273] A vehicle is characterized by including the MicroLED pixel headlight multi-zone control system of Embodiment 2. The vehicle provides vehicle speed via a VCU and road and target information via a camera, radar, and a road recognition module.

[0274] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention. Those skilled in the art, under the guidance of the present invention, can make various similar representations without departing from the spirit and claims of the present invention, and such modifications all fall within the protection scope of the present invention.

Claims

1. A multi-zone control method for MicroLED pixel automotive lights, characterized in that, Includes the following steps: Power-on initialization of static calibration parameters, which include at least a pixel-far-field angle mapping table. Basic optical coupling matrix Width of basic transition zone Gamma correction curve and PWM mapping table; Periodically obtain the LED junction temperature of the MicroLED array The visibility level Vis of the vehicle's external environment, based on the LED junction temperature. Determine the temperature correction factor The fog scattering correction factor is determined based on the visibility level Vis. And based on the fundamental optical coupling matrix Width of basic transition zone Temperature correction factor and fog scattering correction coefficient Determine the real-time transition band width and real-time optical coupling matrix ; wherein, the width of the real-time transition band and real-time optical coupling matrix Each will be subject to amplitude limiting. Obtain vehicle speed and the set of targets in front of the vehicle. Based on road information, determine the target set. Each target unit Corresponding target collision risk coefficient and third-party glare coefficient Based on the maximum target collision risk coefficient Vehicle speed characteristic function Road type characteristics and maximum third-party glare coefficient Calculate the overall risk value The third-party glare coefficient The negative adjustment term is used in the overall risk value. Calculation; The comprehensive risk value Mapped to lighting weights and projection weights and in lighting weight Lower bound constraint, minimum projected pixel area Under constraints and MicroLED array hardware constraints, multiple candidate boundary lines are generated to divide the lighting functional area and the projection interaction area. From the candidate boundary lines that satisfy the hardware constraints, the one corresponding to the current comprehensive risk value is selected. The original dividing line and the original boundary line The boundary line is obtained by performing boundary smoothing filtering. ; According to the dividing line and real-time transition band width The MicroLED array is divided into non-overlapping lighting functional areas. Projection Interactive Area and transition pixel band ; Pixels are allocated according to the priority order of basic ADB lighting, auxiliary lighting, safety projection, and comfort projection, based on the overall risk value. Exceeding the first risk threshold At that time, all comfortable projection pixels are reclaimed, and the projection interaction area shrinks. The boundary, in the comprehensive risk value Exceeding the second risk threshold At that time, redundant pixels of the safe projection are recycled, and the minimum pixel area of ​​the projection is retained. When an extremely high-risk oncoming vehicle or pedestrian target is detected at close range, the projection interaction area will be cleared. And its pixels are included in the lighting functional area. ; Generate illumination sub-partition masks respectively and projection sub-partition mask ; For each MicroLED pixel, first calculate the MicroLED pixel's position relative to the boundary line pixel by pixel. distance And according to the real-time transition band width Construction with distance Continuously changing transitional mixing weights According to the transition mixing weight For the illumination sub-partition mask and projection sub-partition mask The base target brightness is obtained by fusion. Then, based on the real-time optical coupling matrix and the set of neighboring pixels of the MicroLED pixel Calculate neighboring pixels The light leakage component of the MicroLED pixel, and from the basic target brightness After subtracting the light leakage component, the driving range is limited to obtain the pixel normalized output brightness. ; First, normalize the output brightness of the pixel according to the Gamma correction curve. Brightness correction is performed, and then bit width mapping is performed according to the PWM mapping table to generate a PWM drive frame for driving the output drive light field of the MicroLED array.

2. The MicroLED pixel automotive lighting multi-zone control method according to claim 1, characterized in that, The real-time optical coupling matrix Determined according to the following formula: ； Among them, the basic optical coupling matrix The value range is [0, 0.15], temperature correction coefficient. The value range is [0.8, 1.6], which is the fog scattering correction coefficient. The value range is [1.0, 1.8], and the real-time optical coupling matrix is... The individual coupling weights are capped to [0, 0.24]. The real-time transition band width Determined according to the following formula: ； Among them, the width of the basic transition zone The value range is [3,8], and the real-time transition band width Wreal is limited to [2,12] pixels.

3. The multi-zone control method for MicroLED pixel automotive lights according to claim 1, characterized in that, The target set This includes the target's horizontal angle, vertical angle, physical distance to the target, and target status; For each target after data association, an independent Kalman filter instance is established, employing a constant angular velocity model for the state vector and a direct angle observation model for the observation vector, based on the vehicle speed. Target physical distance and target state Solving for dimensionless gain The noise matrix of the real-time adaptive process is obtained as follows: ； in, The reference process noise matrix; Utilizing LED junction temperature Ambient lighting Visibility level (Vis), target physical distance Target state structure Solving for dimensionless gain The real-time adaptive observation noise matrix is ​​obtained as follows: ； in, The reference observation noise matrix; The noise matrix of the real-time adaptive process and real-time adaptive observation noise matrix Substituting the values ​​into the Kalman filter iterative calculation, the optimal target motion state in the current frame is obtained. Then, the state transition matrix is ​​used to extrapolate outwards and predict the target's horizontal angle for the next 1 to 2 frames. And predicted vertical angle To determine the set of anti-glare protection pixels corresponding to the target and the original boundary line. .

4. The multi-zone control method for MicroLED pixel automotive lights according to claim 3, characterized in that, The illumination sub-partition mask ADB anti-glare base mask Lateral horizontal brightness attenuation function The composite yields: ； The predicted level angle is obtained based on Kalman prediction. And predicted vertical angle Pixels located within the target anti-glare protection pixel set The ADB anti-glare base mask The value in the middle is set to 0, and the rest are set to 1; The lateral horizontal brightness attenuation function A piecewise linear attenuation method is used in the horizontal direction to gradually reduce the maximum allowable output brightness of the lateral pixels far from the center of the light field: ； in, For pixels Horizontal pixel coordinates, The horizontal pixel coordinates of the center of the light field. The main lighting area is half the width of the flat area. This is the lateral attenuation termination boundary; The projection sub-partition mask The original grayscale image from the upper-level interactive graphics. The result is obtained by inputting the optical uniformity correction lookup table.

5. The multi-zone control method for MicroLED pixel automotive lights according to claim 1, characterized in that, The comprehensive risk value Determined according to the following formula: ； in, All are pre-defined risk weight coefficients, with values ​​ranging from [0.1, 1.0]. The comprehensive risk value Mapping to satisfy Lighting weight and projection weights and make the lighting weight satisfy: ； in, Based on the basic lighting weight, it is the lighting weight. The lower limit.

6. The multi-zone control method for MicroLED pixel automotive lights according to claim 5, characterized in that, The dividing line The determination includes the following steps: Calculate lighting safety scores for each of the multiple candidate zoning schemes. Projection completeness and third-party glare loss ,by To maximize overall benefits, To minimize glare loss, candidate partitioning schemes that do not meet the preset MicroLED driving constraints and minimum projected area constraints are eliminated. The Pareto optimal solution set is then selected based on the comprehensive risk value. Select the original boundary line. ; The original boundary line is defined according to the following formula. Perform boundary smoothing filtering to obtain the smoothed boundary line. : ； in, These are the boundary filter coefficients. Indicates the boundary line of the previous frame; And, satisfy This limits the movement of the boundary line between adjacent frames to a preset maximum movement limit per boundary frame. Within.

7. The multi-zone control method for MicroLED pixel automotive lights according to claim 1, characterized in that, The dividing line To the projection interaction area Real-time transition band width on one side Within the range, the transition mixing weight satisfy: ； This indicates that the current pixel is output entirely using the illumination sub-partition mask. This indicates that the current pixel is output entirely using the projected sub-partition mask. The weights change continuously and monotonically within the interval [0,1] to achieve a smooth transition. Through transitional blending weights Fusion lighting sub-partition mask and projection sub-partition mask The base target brightness, without considering pixel optical crosstalk, was calculated. : ； in, This is the global brightness equalization gain coefficient; The pixel normalized output brightness The formula for calculation is: ； in, The real-time adaptive optical coupling coefficient is used to represent the neighboring pixels. For the current pixel The weight of light leakage intensity; The lower limit truncation is used to ensure that the pixel output brightness is physically achievable and to avoid negative brightness values ​​under strong crosstalk conditions.

8. The multi-zone control method for MicroLED pixel automotive lights according to claim 1, characterized in that, It also includes parallel execution of fault state detection, including: In the event of a Level 1 fault involving a short-term perceived frame drop, the pixel normalization output brightness of the previous frame is frozen. The dividing line between the previous frame and the previous frame ; In the event of a Level 2 fault (permanent failure of the camera or radar), clear the projection interaction area. And only retain the illumination sub-partition mask. Calculation; When a Level 3 fault occurs, such as algorithm overflow or MicroLED hardware failure, the execution of the MicroLED pixel headlight multi-zone control method is stopped, and the pre-stored fixed low beam basic light pattern or fixed high beam basic light pattern is output.

9. A multi-zone control system for MicroLED pixel automotive lights, characterized in that, include: Independently dimmable MicroLED array; Temperature sensor, used to acquire LED junction temperature of MicroLED array. ; The environmental perception module is used to collect information for generating the visibility level Vis; The target perception module is used to collect and generate a set of targets. Information; Vehicle information interface, which is used to collect vehicle speed and road information; The memory, which stores at least a pixel-far-field angle mapping table. Basic optical coupling matrix Width of basic transition zone Gamma correction curve, PWM mapping table, and computer program; The processor, when executing the computer program, implements the MicroLED pixel vehicle light multi-zone control method according to any one of claims 1 to 8, and outputs PWM drive frames to the MicroLED array.

10. A vehicle, characterized in that, Including the MicroLED pixel vehicle light multi-zone control system as described in claim 9.

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