Optical information processing method of vehicle, vehicle and computer readable storage medium

Abstract

The embodiment of the invention provides an optical information processing method of a vehicle, the vehicle and a computer readable storage medium, and the method comprises the steps that light rays of the environment where the vehicle is located are detected to obtain optical information, the light rays are used for being incident to the eyes of a target object through an optical device, the optical device is a device allowing light transmittance to be adjusted, and the light information is obtained; the target object is in the vehicle; based on the light information, a dazzling risk index is determined, and the dazzling risk index is used for representing the degree of dazzling risk brought by the light to the target object; in response to the condition that the dazzling risk index is higher than a risk index threshold value, driving state information of the vehicle is obtained, and the driving state information is used for representing the state of driving parameters of the vehicle; mapping the driving state information and the light information by using a target model to obtain a target light transmittance; and adjusting the initial light transmittance of the optical device to the target light transmittance. The technical problem that the light information processing efficiency of the vehicle is low is solved.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and more specifically, to a method for processing optical information in a vehicle, a vehicle, and a computer-readable storage medium. Background Technology

[0002] Currently, in the process of vehicle light information processing, most vehicle-mounted adaptive anti-glare systems adjust based on only one factor: light intensity. This means that in complex driving environments (such as driving at high speed on sunny days, meeting oncoming traffic at night, or facing direct sunlight), the response of the vehicle-mounted adaptive anti-glare system may be insufficient or excessive, affecting the efficiency of light information processing.

[0003] In addition, some lower-end models or older anti-glare technologies still require drivers to manually adjust the sun visor or glasses, which not only increases the driver's workload but may also fail to respond in time in emergency situations, reducing the immediacy of light information processing.

[0004] Therefore, the technical problem of low efficiency in vehicle optical information processing still exists.

[0005] There is currently no good solution to the above problems. Summary of the Invention

[0006] This application provides a method for processing optical information in a vehicle, a vehicle, and a computer-readable storage medium to at least solve the technical problem of low efficiency in processing optical information in vehicles.

[0007] According to one aspect of the embodiments of this application, a method for processing light information of a vehicle is provided. The method may include: detecting light in the environment in which the vehicle is located to obtain light information, wherein the light is incident on the binoculars of a target object via an optical device, the optical device being a device that allows adjustment of light transmittance, and the target object being located within the vehicle; determining a glare risk index based on the light information, wherein the glare risk index represents the degree to which the light poses a glare risk to the target object; in response to the glare risk index being higher than a risk index threshold, acquiring vehicle driving state information, wherein the driving state information characterizes the state of the vehicle's driving parameters; mapping the driving state information and the light information using a target model to obtain a target transmittance, wherein the target model represents the rules for mapping the driving state information and the light information to the target transmittance; adjusting the initial transmittance of the optical device to the target transmittance, wherein after the light passes through the adjusted optical device, the glare risk index corresponding to the light is lower than or equal to the risk index threshold.

[0008] Furthermore, using the target model, the driving state information and light information are mapped to obtain the target transmittance, including: responding to the information value of the light information being within the information value range, using the target model to map the driving state information and light information to obtain the target transmittance range, wherein the target transmittance range corresponds to the information value range; within the target transmittance range, the target transmittance is determined.

[0009] Furthermore, the information value of the light information includes the light intensity of the light, the information value range includes the target light intensity range, and the target model includes a first target model. The first target model is used to represent the rules for mapping driving state information and light intensity to a target transmittance range. In response to the information value of the light information being within the information value range, the target model is used to map the driving state information and the light information to obtain the target transmittance range, including: in response to the light intensity being within the target light intensity range, the first target model is used to map the driving state information and the light intensity to obtain the target transmittance range.

[0010] Furthermore, the method further includes: determining a first initial model, wherein the first initial model is used to represent the mapping relationship between different initial illumination intensity ranges of light samples and different initial transmittance ranges of optical device samples; adjusting the initial illumination intensity range and initial transmittance range using illumination intensity samples and transmittance samples to obtain target illumination intensity range and target transmittance range, wherein, after a light sample with illumination intensity equal to the illumination intensity sample passes through an optical device sample with transmittance equal to the transmittance sample, the glare risk index corresponding to the light sample is lower than or equal to the risk index threshold, the initial illumination intensity range includes the target illumination intensity range, and the initial transmittance range includes the target transmittance range; and training a first target model using the target illumination intensity range and target transmittance range.

[0011] Furthermore, when the optical device is a windshield deployed on a vehicle, the information value of the light information also includes the incident angle of the light, the information value range includes a target incident angle range, and the target model includes a second target model. The second target model is used to represent the rule for mapping the driving state information and the incident angle to a target position range, and the target position range corresponds to the target incident angle range. The method further includes: in response to the incident angle being within the target incident angle range, using the second target model to map the driving state information and the incident angle to obtain the target position range; within the target position range, determining the target position, wherein the target position is used to represent the position to which the vehicle's sun visor needs to be adjusted; and adjusting the initial position of the sun visor to the target position, wherein the adjusted sun visor is used to block light for the target object.

[0012] Furthermore, the method also includes: determining a second initial model, wherein the second initial model is used to represent the mapping relationship between different initial incident angle ranges of light samples and different initial position ranges of sunshade samples; adjusting the initial incident angle range and initial position range using incident angle samples and position samples to obtain target incident angle range and target position range, wherein the light sample with incident angle is the incident angle sample is blocked by the sunshade sample with position is the position sample, the initial incident angle range includes the target incident angle range, and the initial position range includes the target position range; and training a second target model using the target incident angle range and target position range.

[0013] Furthermore, after adjusting the initial transmittance of the optical device to the target transmittance, the method further includes: using the target transmittance as a transmittance sample and the light information as a light information sample, adjusting the weights of the target model according to a weight adjustment strategy, wherein the weight adjustment strategy is used to represent the rules for adjusting the weights of the target model; and updating the original target model using the adjusted target model.

[0014] According to another aspect of the embodiments of this application, a vehicle optical information processing system is also provided, including: an optical information sensing device, a state sensing device, and a controller. The optical information sensing device is used to detect the light in the vehicle's environment to obtain optical information. The light is incident on the binoculars of a target object via an optical device, the optical device being a device that allows adjustment of light transmittance. The target object is located in the vehicle, and the optical device is either a windshield deployed on the vehicle or glasses worn by the target object. The controller is used to determine a glare risk index based on the optical information, wherein the glare risk index indicates that the light is from the target object. The degree of glare risk; a state perception device, used to acquire vehicle driving state information in response to a glare risk index exceeding a risk index threshold, wherein the driving state information is used to characterize the state of the vehicle's driving parameters; a controller, also used to map the driving state information and light information using a target model to obtain a target transmittance, wherein the target model is used to represent the rules for mapping the driving state information and light information to the target transmittance; adjusting the initial transmittance of the optical device to the target transmittance, wherein after the light passes through the adjusted optical device, the glare risk index corresponding to the light is lower than or equal to the risk index threshold.

[0015] According to another aspect of the embodiments of this application, a vehicle is also provided, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of this application when it runs.

[0016] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0017] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the methods of various embodiments of this application.

[0018] According to another aspect of the embodiments of this application, a computer program product is also provided, including a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods in various embodiments of this application.

[0019] According to another aspect of the embodiments of this application, a computer program is also provided, which, when executed by a processor, implements the methods of the various embodiments of this application.

[0020] In this embodiment, the light in the vehicle's environment is detected to obtain light information. The light is incident on the target object's binoculars via an optical device that allows adjustment of transmittance. The target object is located inside the vehicle. Based on the light information, a glare risk index is determined, representing the degree to which the light poses a glare risk to the target object. In response to the glare risk index exceeding a risk index threshold, the vehicle's driving status information is acquired, characterizing the state of the vehicle's driving parameters. A target model is used to map the driving status information and the light information to obtain a target transmittance, representing the rules for mapping the driving status information and light information to the target transmittance. The initial transmittance of the optical device is adjusted to the target transmittance, ensuring that after the light passes through the adjusted optical device, the glare risk index corresponding to the light is lower than or equal to the risk index threshold. In other words, the embodiments of the present invention introduce a comprehensive evaluation system that combines light information and driving status information, rather than simply adjusting the transmittance based on light intensity. In this way, even under the same light intensity conditions, the transmittance can be adjusted according to the vehicle's driving status information, avoiding excessive adjustment that could affect driving safety. It also avoids the defects of low transmittance adjustment accuracy caused by processing glare phenomena caused by a single light source or a specific angle, thereby solving the technical problem of low light information processing efficiency of vehicles and achieving the technical effect of improving the light information processing efficiency of vehicles. Attached Figure Description

[0021] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0022] Figure 1 This is a flowchart of a vehicle optical information processing method according to an embodiment of this application;

[0023] Figure 2 This is a schematic diagram of the structure of an anti-glare device according to an embodiment of this application;

[0024] Figure 3 This is a flowchart of a control method for an anti-glare device according to an embodiment of this application;

[0025] Figure 4 This is a flowchart of a self-organizing fuzzy control algorithm according to an embodiment of this application;

[0026] Figure 5 This is a schematic diagram of a vehicle optical information processing system according to an embodiment of this application;

[0027] Figure 6 This is a schematic diagram of a vehicle optical information processing device according to an embodiment of this application. Detailed Implementation

[0028] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0029] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0030] According to an embodiment of this application, a method for processing light information of a vehicle is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0031] This embodiment provides a method for processing light information of a vehicle. Figure 1 This is a flowchart of a vehicle optical information processing method according to an embodiment of this application, such as... Figure 1 As shown, the process may include the following steps:

[0032] Step S102: Detect the light in the environment where the vehicle is located to obtain light information.

[0033] In the technical solution provided in step S102 of this application, light is used to be incident on the binoculars of the target object via an optical device. The optical device is a device that allows adjustment of light transmittance, and the target object is located in a vehicle.

[0034] In this embodiment, the light source can be sunlight, headlights from other vehicles, or other strong light sources. The light information can be light intensity (L) and the angle of incidence (θ). Optical devices can be a vehicle's windshield, smart glasses worn by the driver, etc. The target object can be the driver or the front passenger.

[0035] In this embodiment, during vehicle operation, various light sources are encountered in the environment, such as sunlight, headlights from other vehicles, or other strong light sources. Changes in light not only affect the driver's visual comfort, but more importantly, inappropriate lighting conditions can significantly reduce driving safety. Therefore, the light in the vehicle's environment can be detected to obtain light information. Acquiring this light information is fundamental to implementing an in-vehicle adaptive anti-glare system (hereinafter referred to as the anti-glare system), enabling the vehicle to intelligently respond to various light conditions and avoid potential driving risks caused by lighting issues. The anti-glare system can be integrated into the vehicle's electronic architecture, sharing information and resources with other key vehicle systems. For example, the anti-glare system can connect to the vehicle's central control unit, electronic stability program, navigation system, and cameras, exchanging data and transmitting signals through the vehicle's communication bus. This integration allows the anti-glare system to acquire real-time information on the vehicle's speed, direction, position, and changes in ambient light, ensuring it matches the vehicle's current state and external environment.

[0036] Optionally, this embodiment uses a light sensor to detect the light in the vehicle's environment, obtaining light information such as light intensity (lux), direction and angle of light, and trends in light change. Based on this light information, it can determine whether there is a risk of glare and then take corresponding measures, such as adjusting the light transmittance of the windshield or windows, moving the position or angle of the sun visor, and adjusting the light transmittance of the lenses through smart glasses, to reduce glare and ensure that the driver's vision is not interfered with, thereby improving driving safety and driver comfort. Glare risk refers to the possibility and degree to which light interferes with the driver's or passenger's vision during driving, especially when the light intensity exceeds the normal threshold or the light direction directly shines into the eyes, causing a risk of instantaneous decreased vision, blurred vision, or visual discomfort. This risk not only affects the driver's visual comfort but also instantly reduces driving safety and increases the probability of traffic accidents.

[0037] Optionally, the aforementioned light sensor can be installed on the windshield, side windows, roof, rearview mirror, etc., to acquire in real time the ambient light intensity (lux), light incidence angle (°), and light change trend of the vehicle's environment. This is merely an illustrative example, and no specific restrictions are placed on the method of acquiring light information or the deployment method of the light sensor.

[0038] Step S104: Determine glare risk indicators based on light information.

[0039] In the technical solution provided in step S104 of this application, after detecting the light in the environment where the vehicle is located and obtaining light information, a glare risk index can be determined based on the light information. The glare risk index is used to indicate the degree to which the light brings glare risk to the target object.

[0040] In this embodiment, the glare risk index refers to a numerical value assessed based on light information. It quantifies the likelihood of light causing glare interference to the driver or front passenger. The glare risk index comprehensively considers factors such as light intensity, light incidence angle, light source type, and driving environment to determine whether the current light may pose a threat to the driver's visual clarity and driving safety.

[0041] Optionally, accurate determination of glare risk indicators is the basis for the anti-glare system to intelligently adjust the transmittance or position of optical components, enabling the anti-glare system to dynamically adjust anti-glare measures according to the light conditions in different driving environments, providing better visual protection for drivers.

[0042] In this embodiment, by determining the glare risk index, the anti-glare system can accurately identify glare risks, thereby responding more promptly and appropriately to changes in light, reducing driving safety issues caused by changes in light. Because the calculation of the glare risk index considers multiple light information parameters, the anti-glare system can be personalized according to different lighting conditions and user needs, improving the user experience. Furthermore, the quantification of the glare risk index reduces the need for subjective judgment by the driver, making anti-glare adjustment more automated and objective.

[0043] Step S106: In response to the glare risk indicator being higher than the risk indicator threshold, obtain the vehicle's driving status information.

[0044] In the technical solution provided in step S106 of this application, after determining the glare risk index based on light information, the vehicle's driving status information can be obtained when the glare risk index is higher than the risk index threshold. The driving status information is used to characterize the state of the vehicle's driving parameters and can be the vehicle speed (v), which can be real-time vehicle speed, high speed, low speed, etc.

[0045] In this embodiment, since driving status information directly affects the response strategy and control effect of the anti-glare system, and vehicles at different speeds and driving environments have different glare sensitivities and corresponding needs, real-time acquisition of driving status information is a crucial step in ensuring the effectiveness and accuracy of the anti-glare system. When the determined glare risk index exceeds a pre-set risk index threshold, i.e., there is a glare risk, the vehicle's driving status information can be acquired.

[0046] Optionally, driving status information can be obtained through vehicle speed sensors, in-vehicle network systems, Global Positioning System (GPS), and navigation systems. Vehicle speed sensors are used to monitor vehicle speed in real time, providing high-precision speed readings. Driving status information can be transmitted to the anti-glare system's control unit via the vehicle's controller area network, local interconnect network, or other in-vehicle network systems. This communication method ensures the real-time nature and accuracy of the driving status information. GPS and navigation systems can primarily provide location and route information, and can also indirectly reflect the vehicle's driving status.

[0047] It should be noted that the above-mentioned driving status information and the method of obtaining driving status information are only illustrative examples and are not specifically limited here. As long as the information can be used to reflect the status of the vehicle's driving parameters, it is within the protection scope of the embodiments of this application.

[0048] Step S108: Using the target model, the driving state information and light information are mapped to obtain the target transmittance.

[0049] In the technical solution provided in step S108 of this application, after obtaining the vehicle's driving state information, a target model, such as a trigonometric / trapezoidal function, can be used to map the driving state information and light information, such as a fuzzy mapping relationship, to obtain the target transmittance. The target model is used to represent the rules for mapping the driving state information and light information to the target transmittance, such as fuzzy rules or matching rules.

[0050] In this embodiment, the target transmittance refers to the level of light transmission of the windshield or sun visor that the anti-glare system aims to achieve in a specific driving environment, based on an assessment of glare risk and consideration of vehicle driving status information. That is, when a glare risk is detected, the transmittance value can be dynamically adjusted according to preset rules or algorithms, such as fuzzy logic algorithms, to balance visual comfort and driving safety.

[0051] Alternatively, trigonometric functions and trapezoidal functions are often used as the membership function shapes of fuzzy sets, defining the nonlinear relationship between input variables and output target transmittance, enabling the anti-glare system to more accurately adjust the initial transmittance to cope with changes in various lighting and driving conditions.

[0052] Optionally, the target model can handle the uncertainty and continuity of the input parameters by mapping the input parameters to the output target transmittance through mechanisms such as fuzzy sets, fuzzy rules, and fuzzy inference. For example, the fuzzy rule can be: "IF light intensity is strong AND angle is forward AND vehicle speed is high THEN target transmittance is low".

[0053] For example, suppose a vehicle is traveling on an east-west road under direct midday sunlight at a speed of 80 km / h. The light information at the windshield is 1200 lux, the incident angle is close to 0° (direct overhead), and the vehicle is traveling at a stable speed of 80 km / h without acceleration or deceleration. Based on this light and driving status information, a target model can be used for mapping. Assuming the fuzzy rules are: if the light intensity is "strong" (Lux exceeding 1000), the incident angle is "positive" (0°–30°), and the vehicle speed is "medium" (60 km / h–100 km / h), then the target transmittance is "low" (e.g., 20%–40%). After mapping specific values ​​to fuzzy linguistic variables, the following operations can be performed: "Strong" light (Lux = 1200) corresponds to high light intensity. A "positive" incident angle (θ ≈ 0°) indicates that the light is almost perpendicular to the windshield. A "medium" vehicle speed (v = 80 km / h) indicates that the vehicle is in a normal driving state. Through rule matching, it can be determined that the target transmittance should be set to "low" under the current conditions, such as 30%. Then, through deblurring processing, the output of the deblurring process is converted into a specific transmittance instruction and sent to the drive system of the dimmable glass. The glass is then quickly adjusted to 30% transmittance to effectively block direct strong light and avoid glare, while ensuring that the driver has sufficient visibility to observe road conditions.

[0054] In this embodiment of the application, by using the target model to map light information and driving status information, the transmittance can be finely adjusted to ensure that suitable anti-glare protection is provided under different light intensities, incident angles and vehicle speeds.

[0055] Step S110: Adjust the initial transmittance of the optical device to the target transmittance.

[0056] In the technical solution provided in step S110 of this application, after mapping the driving state information and light information using the target model to obtain the target transmittance, the initial transmittance of the optical device can be adjusted to the target transmittance. After the light passes through the adjusted optical device, the glare risk index corresponding to the light is lower than or equal to the risk index threshold.

[0057] In this embodiment, after detecting the glare risk and calculating the target transmittance, the transmittance properties of the optical device can be adjusted to reduce the glare effect. This adjustment process requires the execution component (dimmable glass or sunshade) of the anti-glare system to respond precisely to the control signal to ensure that when light passes through the adjusted optical device, the glare risk index drops below the safety threshold (risk index threshold).

[0058] Optionally, for dimmable glass equipped with electrochromic materials or liquid crystal dimming technology, the control unit can send corresponding adjustment commands, such as pulse width modulation (PWM) signals or serial peripheral interface (SPI) commands, instructing the glass to adjust its initial light transmittance to a target light transmittance. This adjustment can be gradual to avoid discomfort to the driver caused by changes in light. The sun visor can be displaced or angled according to the control unit's adjustment commands to precisely block light from specific directions or intensities while ensuring a clear view for the driver. The adjustment precision of the sun visor needs to reach centimeter-level or higher to effectively manage the risk of glare.

[0059] Optionally, the initial transmittance of the optical device can be adjusted to a target transmittance. This adjustment is not a static process, but a dynamic adjustment based on real-time feedback, i.e., an adaptive adjustment mechanism. If, after adjusting to the target transmittance, a glare risk index higher than the risk index threshold is still detected, the initial transmittance can be reassessed and further adjusted until the glare risk index is lower than or equal to the risk index threshold.

[0060] It should be noted that in the vehicle's optical information processing method of this embodiment, the vehicle can also interact with roadside equipment and terminal equipment. Optionally, the vehicle can send an information subscription request to the roadside equipment. This message subscription request can include specific types of information that the vehicle needs to receive, such as road conditions, traffic signal status, and obstacle warnings ahead. In response to the information subscription request, the roadside equipment can send roadside perception information to the vehicle. For example, the roadside equipment will filter out roadside perception information that meets the vehicle's needs based on its own perception capabilities and stored information, and send it to the vehicle at a certain frequency. In addition to communicating with the roadside equipment, the vehicle can also receive driving scenario switching instructions transmitted by the terminal equipment through the network. For example, the driving scenario switching instructions can be used to switch the vehicle to energy-saving mode, sport mode, autonomous driving mode, etc., so that the vehicle can adapt to new driving scenarios.

[0061] Through steps S102 to S110, the light in the vehicle's environment is detected to obtain light information. The light is incident on the target object's binoculars via an optical device that allows adjustment of transmittance. The target object is located inside the vehicle. Based on the light information, a glare risk index is determined, representing the degree to which the light poses a glare risk to the target object. In response to the glare risk index exceeding a risk index threshold, the vehicle's driving status information is acquired, characterizing the state of the vehicle's driving parameters. Using a target model, the driving status information and light information are mapped to obtain a target transmittance, where the target model represents the rules for mapping driving status information and light information to the target transmittance. The initial transmittance of the optical device is adjusted to the target transmittance, ensuring that after the light passes through the adjusted optical device, the glare risk index corresponding to the light is lower than or equal to the risk index threshold. In other words, the embodiments of the present invention introduce a comprehensive evaluation system that combines light information and driving status information, rather than simply adjusting the transmittance based on light intensity. In this way, even under the same light intensity conditions, the transmittance can be adjusted according to the vehicle's driving status information, avoiding excessive adjustment that could affect driving safety. This also avoids the defects of low transmittance adjustment accuracy caused by processing glare phenomena caused by a single light source or a specific angle, thereby solving the technical problem of low light information processing efficiency of vehicles and achieving the technical effect of improving the light information processing efficiency of vehicles.

[0062] The above-mentioned method of this application will be further described below.

[0063] As an optional implementation, step S108, mapping the driving state information and light information using a target model to obtain the target transmittance, includes: in response to the information value of the light information being within the information value range, mapping the driving state information and light information using the target model to obtain the target transmittance range, wherein the target transmittance range corresponds to the information value range. Within the target transmittance range, the target transmittance is determined.

[0064] In this embodiment, when the information value of the light information is within the information value range, the driving status information and the light information can be mapped using the target model to a range of light transmittance variation (target light transmittance range), rather than a single value. For example, it can be 20% to 100%, thereby providing greater flexibility and accuracy for subsequent precise control.

[0065] Optionally, the correspondence between the range of light information values ​​(such as light intensity, incident angle, etc.) and the range of target transmittance can be predetermined by training a fuzzy logic model. For example, when the light intensity is between 500 lux and 1000 lux, the mapped target transmittance range can be 20% to 50%. In this way, the anti-glare system can flexibly adjust the initial transmittance according to the specific conditions under different light intensities, neither excessively obstructing the field of vision nor failing to effectively reduce glare.

[0066] Optionally, after obtaining the target transmittance range, it is necessary to further determine the specific target transmittance. This can be achieved by using defuzzification techniques in fuzzy logic, such as the center average method and the median method, to transform the fuzzy output into a definite value (target transmittance).

[0067] Optionally, the center-average method involves finding the center point of each fuzzy output set within the target transmittance range and calculating a weighted average of these center points. The weights can be determined based on the degree of matching of the fuzzy rules. Ultimately, the weighted average is used as the specific target transmittance. The median method, on the other hand, selects the median value within the target transmittance range as the specific target transmittance.

[0068] For example, when the light intensity information value (lux) is in the high intensity information value range (e.g., 800 lux to 1000 lux), the target model will map a target transmittance range, such as 30% to 40%. Then, fuzzy inference is performed, assuming the fuzzy set of the fuzzy light intensity information value after fuzzification is "strong," and the matching fuzzy rule is: "IF light intensity is strong THEEN target transmittance is low 30%-40%." Then, using the center-average method, if the center point of the fuzzy set of "strong" is around 35%, and there is no influence from other rules, then the target transmittance is determined to be approximately 35%. Alternatively, the median value method can be used, directly taking the median value of the target transmittance range, i.e., 35%, as the final target transmittance value.

[0069] In this embodiment, by employing a strategy that corresponds information value ranges to target transmittance ranges, and using an effective deblurring method, the anti-glare system's response is more intelligent. This allows the anti-glare system to provide smoother and more natural transmittance adjustment when processing continuously changing light information, avoiding overreaction or underreaction that may be caused by single-point mapping, thus improving the overall anti-glare effect and driving experience. Simultaneously, the selection of the center averaging method and the median method provides different balances between accuracy and simplicity based on specific application scenarios and user needs, ensuring the flexibility and practicality of the anti-glare system design.

[0070] As an optional implementation, the information value of the light information includes the light intensity, the information value range includes the target light intensity range, and the target model includes a first target model. The first target model is used to represent the rule for mapping driving state information and light intensity to a target transmittance range. In response to the information value of the light information being within the information value range, the target model is used to map the driving state information and light information to obtain the target transmittance range, including: in response to the light intensity being within the target light intensity range, the first target model is used to map the driving state information and light intensity to obtain the target transmittance range.

[0071] In this embodiment, in the anti-glare system, illuminance (lux) is a key optical information parameter, with a value range of 0–1000 lux (or other wider ranges, depending on the sensor sensitivity and the design requirements of the anti-glare system). This value range covers various conditions from extremely low light (such as indoor environments at night) to high light intensity (such as outdoor environments during a sunny day). To better adapt to continuous changes in illuminance and the diversity of driving states, and to provide a more flexible and intelligent anti-glare control strategy, a first target model can be used to handle the complex relationship between illuminance and driving state information. Input variables such as vehicle speed and illuminance are mapped to a target transmittance range, rather than a single transmittance value, through preset fuzzy rules and membership functions.

[0072] Optionally, when the illuminance information value (lux value) is within the defined target illuminance range, the vehicle speed and illuminance can be converted into fuzzy linguistic variables using the first target model, such as "vehicle speed: slow / medium / fast" and "illuminance: weak / medium / strong". Then, based on the fuzzy rule base, the current driving state information (vehicle speed) and illuminance information value can be matched to determine a fuzzy output, which can represent a fuzzy set of target transmittance. Defuzzing methods from fuzzy logic, such as the center-average method and the maximum membership method, can be used to convert the fuzzy output into a specific target transmittance range, such as 30% to 50% transmittance.

[0073] For example, suppose the current vehicle speed is 60 km / h, falling within the "medium speed" fuzzy set; and the light intensity is 750 lux, belonging to the "strong light" fuzzy set. The fuzzy rule for the first target model can be defined as: "IF vehicle speed is medium speed AND light intensity is strong light THEN target transmittance is medium to low (30% to 50%)". After detecting that the current driving conditions meet the above rule, the anti-glare system will calculate the target transmittance range to be 30% to 50%.

[0074] In this embodiment, the information values ​​of light information (especially the light intensity) and driving status information are used to intelligently map the target transmittance range through a preset target model, dynamically adjusting the target transmittance range. The target model includes a first target model, which is specifically designed to handle the complex relationship between light intensity and driving status information, mapping the two to a specific target transmittance range. This ensures that when the anti-glare system detects that the information values ​​of light information (such as light intensity) are within a specific target light intensity range, it can make timely and accurate transmittance adjustments based on the vehicle's driving status, such as speed and direction, to achieve a better anti-glare effect.

[0075] As an optional implementation, the method further includes: determining a first initial model, wherein the first initial model is used to represent the mapping relationship between different initial illumination intensity ranges of light samples and different initial transmittance ranges of optical device samples; adjusting the initial illumination intensity range and initial transmittance range using illumination intensity samples and transmittance samples to obtain target illumination intensity range and target transmittance range, wherein, after a light sample with illumination intensity equal to the illumination intensity sample passes through an optical device sample with transmittance equal to the transmittance sample, the glare risk index corresponding to the light sample is lower than or equal to a risk index threshold, the initial illumination intensity range includes the target illumination intensity range, and the initial transmittance range includes the target transmittance range; and training a first target model using the target illumination intensity range and target transmittance range.

[0076] In this embodiment, the first initial model initially establishes a mapping relationship between different initial light intensity ranges of light samples and initial transmittance ranges of optical device samples. This mapping relationship can be a fuzzy mapping relationship. For example, the initial light intensity range can be initially set as "weak" (<500 lux), "medium" (500-700 lux), and "strong" (>700 lux), and the corresponding fuzzy transmittance ranges such as "low transmittance," "medium transmittance," and "high transmittance." Subsequently, the shape of the membership function of the fuzzy set can be adjusted using light intensity samples and transmittance samples (e.g., manually labeled samples). For example, by fine-tuning the boundaries of the triangular or trapezoidal function, the first initial model can more accurately reflect the mapping relationship between light intensity and ideal transmittance in the real world.

[0077] Optionally, this embodiment continuously corrects and improves the fuzzy mapping rules based on sample data feedback from light samples and optical device samples, ensuring that the initial model can make more accurate decisions when dealing with the relationship between light intensity and transmittance, thereby reducing the risk of glare. Through the above adjustments and optimizations, the range of light intensity and transmittance is gradually narrowed to better reflect actual needs, and the boundaries become clearer and more defined, thus obtaining the target light intensity range and target transmittance range.

[0078] In this embodiment, after sufficient sample data verification and parameter optimization of the first initial model, a more mature first target model can be obtained. This first target model not only includes optimized fuzzy mapping relationships, but also dynamically generates a target transmittance range based on real-time light intensity and vehicle driving status information. This ensures that under various lighting conditions, the glare risk index of light passing through optical devices is lower than or equal to a preset risk index threshold, thereby maximizing driving visual comfort and safety.

[0079] As an optional implementation, when the optical device is a windshield deployed on a vehicle, the information value of the light information also includes the incident angle of the light, the information value range includes a target incident angle range, and the target model includes a second target model. The second target model is used to represent the rule for mapping the driving state information and the incident angle to a target position range, and the target position range corresponds to the target incident angle range. The method further includes: in response to the incident angle being within the target incident angle range, using the second target model to map the driving state information and the incident angle to obtain the target position range; within the target position range, determining the target position, wherein the target position is used to represent the position to which the vehicle's sun visor needs to be adjusted; and adjusting the initial position of the sun visor to the target position, wherein the adjusted sun visor is used to block light for the target object.

[0080] In this embodiment, in the anti-glare system, when the optical device refers to the vehicle's windshield, the light information is not limited to light intensity but should also include the incident angle of the light. The range of the incident angle information value can be set from 0° to 180°, covering multiple angles from directly in front, to the side, and to the rear. This is the basis for the anti-glare system to comprehensively assess the risk of glare from light coming from all directions. The second target model focuses on processing the relationship between driving status information and the incident angle of light, mapping it to the position range of the target sun visor through a fuzzy logic algorithm. Unlike the first target model, which focuses on adjusting the light transmittance, the second target model focuses on adjusting the physical position of the sun visor to more directly block glare.

[0081] Optionally, when the detected incident angle is within the target incident angle range, fuzzy input can be used through a second target model to convert vehicle speed and incident angle into fuzzy linguistic variables, such as "vehicle speed: slow / medium / fast" and "incident angle: front / side / rear". Then, rule matching is performed. Based on a preset fuzzy rule library, the current driving state information (vehicle speed) and incident angle information are matched to determine a fuzzy output, which represents a fuzzy set of the target sun visor position. Next, defuzzification processing can be performed to convert the fuzzy output into a specific target position range. For example, if the sun visor needs to be moved to a position within the 0-30cm range, this process can use fuzzy logic defuzzification methods, such as the center-average method, to determine the specific displacement of the sun visor. Finally, the target position can be determined. Within the target position range, a specific target position can be further determined according to actual needs to better block glare without affecting the driver's visibility.

[0082] For example, assuming the current vehicle speed is 60 km / h and the incident angle is 75°, according to the fuzzy rules of the second target model, the following mapping can be obtained: "IF vehicle speed is medium speed AND incident angle is sideways THEN sun visor position is slightly to the left (10cm to 20cm)". Through defuzzification, the anti-glare system determines that the sun visor should be moved to 15cm to minimize the glare effect of strong side light while maintaining a clear view ahead.

[0083] In this embodiment, the design of the second target model takes into account the different requirements for the sun visor position in different driving scenarios. For example, when facing strong oncoming sunlight on a highway, the sun visor may need to be positioned lower to block direct sunlight; while when driving slowly in the city, the adjustment of the sun visor focuses more on avoiding reflected light from the sides. Through the second target model, the anti-glare system can intelligently calculate and precisely adjust the position of the sun visor based on the incident angle and driving status information, effectively avoiding subjective errors during manual operation and achieving a more accurate sunshade effect.

[0084] As an optional implementation, the method further includes: determining a second initial model, wherein the second initial model is used to represent the mapping relationship between different initial incident angle ranges of light samples and different initial position ranges of sunshade samples; adjusting the initial incident angle range and initial position range using incident angle samples and position samples to obtain target incident angle range and target position range, wherein the light sample with incident angle is the incident angle sample is blocked by the sunshade sample with position is the position sample, the initial incident angle range includes the target incident angle range, and the initial position range includes the target position range; and training a second target model using the target incident angle range and target position range.

[0085] In this embodiment, the second initial model in the anti-glare system is based on fuzzy logic and is used to handle the preliminary mapping relationship between the light incident angle and the sun visor position. For example, it initially defines the angle divisions of "directly in front" (<120°), "front side" (120°~150°), and "side" (150°~180°), as well as the fuzzy position ranges of the sun visor such as "stationary," "slightly moved," and "significantly moved." These preliminary mapping relationships provide a starting point for the anti-glare system, but from a practical application perspective, further optimization and calibration are needed. To improve the accuracy and adaptability of the second initial model, dynamic optimization can be performed using a large number of manually labeled incident angle samples and sun visor position samples. By analyzing the sample data of the incident angle samples and sun visor position samples, the membership function shape can be dynamically optimized. Based on the sample data feedback, the membership function shape of the fuzzy set is optimized and adjusted to ensure that the mapping relationship between the incident angle and the sun visor position better conforms to the lighting patterns and shading requirements of the real world. The boundaries and range can be adjusted. Based on sample data, the boundaries of the initial angle range and position range can be dynamically adjusted to gradually narrow the target range, improving the accuracy of the sun visor position adjustment when dealing with different incident angles. Through repeated experiments and data analysis, the fuzzy mapping rules of the second initial model can be continuously corrected and improved to ensure that the sun visor position adjustment strategy can effectively cope with the glare risk caused by various incident angles.

[0086] Optionally, after the optimization process of the membership function shape of the fuzzy set is completed, a second target model can be trained using machine learning algorithms (such as supervised learning) by utilizing the correspondence rules between the target incident angle range and the target position range. This second target model can not only more accurately reflect the complex relationship between the light incident angle and the sun visor position, but also dynamically generate sun visor position adjustment commands based on real-time vehicle driving status and lighting conditions. This ensures that, in various driving scenarios, timely movement of the sun visor can effectively manage and reduce glare, thereby guaranteeing driving safety.

[0087] In this embodiment, a second initial model is determined. This second initial model is based on the mapping relationship between different initial incident angle ranges of light samples and different initial position ranges of sun visor samples. It is learned and adjusted using a large number of incident angle samples and sun visor position samples to gradually optimize a more accurate target incident angle range and target position range. Finally, a second target model is obtained through training with these optimized ranges, achieving intelligent sun visor positioning under specific driving environments.

[0088] As an optional implementation, after adjusting the initial transmittance of the optical device to the target transmittance, the method further includes: using the target transmittance as a transmittance sample and the light information as a light information sample, adjusting the weights of the target model according to a weight adjustment strategy, wherein the weight adjustment strategy is used to represent the rules for adjusting the weights of the target model; and updating the target model before adjustment using the adjusted target model.

[0089] In this embodiment, after adjusting the initial transmittance of the optical device (such as a windshield) to the target transmittance calculated by the anti-glare system, a set of transmittance samples and corresponding light information samples (light intensity, incident angle, etc.) are generated. The sample data of these transmittance samples and corresponding light information samples reflect how the anti-glare system responds and adjusts the transmittance under actual use conditions.

[0090] Optionally, to further improve the accuracy and adaptability of the target model, a self-organizing learning mechanism can be used to dynamically adjust the weights in the target model using collected transmittance and light information samples. The weight adjustment strategy defines a set of rules to guide how to optimize model parameters based on feedback from sample data. For example, an incremental learning approach can be adopted, updating the weights of each rule in the target model based on the effect of each adjustment (such as the degree of reduction in glare risk), enabling the anti-glare system to respond more accurately to future lighting conditions.

[0091] The weight update rule can be determined by the following formula:

[0092] w_i(k+1)=w_i(k)+γ·Δw_i(k)

[0093] Where w_i(k) can be used to represent the weight of the i-th fuzzy rule at time k; γ can be used to represent a learning rate coefficient to determine the speed of the weight update; Δw_i(k) can be used to represent the weight increment calculated based on the transmittance sample and light information sample at time k, reflecting the deviation between the actual effect and the expected effect of the rule; w_i(k+1) can be used to represent the weight of the i-th fuzzy rule at time k+1.

[0094] By following the rules described above, the anti-glare system can continuously learn and optimize the target model parameters, ensuring that it can quickly and accurately adjust the light transmittance in constantly changing lighting environments, thereby reducing the risk of glare.

[0095] The vehicle light information processing method of this invention detects the light in the vehicle's environment to obtain light information. The light is incident on the binoculars of a target object via an optical device that allows adjustment of its transmittance. The target object is located inside the vehicle. Based on the light information, a glare risk index is determined, representing the degree to which the light poses a glare risk to the target object. In response to the glare risk index exceeding a risk index threshold, vehicle driving status information is acquired, characterizing the state of the vehicle's driving parameters. A target model is used to map the driving status information and the light information to obtain a target transmittance, representing the rules for mapping the driving status information and light information to the target transmittance. The initial transmittance of the optical device is adjusted to the target transmittance, wherein after the light passes through the adjusted optical device, the glare risk index corresponding to the light is lower than or equal to the risk index threshold. In other words, the embodiments of the present invention introduce a comprehensive evaluation system that combines light information and driving status information, rather than simply adjusting the transmittance based on light intensity. In this way, even under the same light intensity conditions, the transmittance can be adjusted according to the vehicle's driving status information, avoiding excessive adjustment that could affect driving safety. This also avoids the defects of low transmittance adjustment accuracy caused by processing glare phenomena caused by a single light source or a specific angle, thereby solving the technical problem of low light information processing efficiency of vehicles and achieving the technical effect of improving the light information processing efficiency of vehicles.

[0096] The above technical solutions of the embodiments of this application will be further illustrated below with reference to preferred embodiments of the present invention.

[0097] Currently, while driving, drivers and front passengers may experience glare caused by sunlight, headlights from other vehicles, or other strong light sources. This glare not only affects the driver's vision but may also cause temporary eye discomfort, increasing driving risks.

[0098] Among the relevant technologies, anti-glare technologies mainly include the following: (1) Sun visors: Traditional sun visors can block some light by manual adjustment, but their adjustment range is limited and they cannot cope with complex light changes. (2) Automatic anti-glare rearview mirrors: Some high-end models are equipped with automatic anti-glare rearview mirrors, which can automatically adjust the mirror reflectivity according to the light intensity of vehicles behind, reducing glare. However, this technology is only applicable to rearview mirrors and cannot solve the problem of glare from the front or sides. (3) Polarized glasses: Drivers can wear polarized glasses to reduce light reflection, but this method depends on the driver's subjective operation, and wearing them for a long time may cause eye fatigue.

[0099] In summary, the sun visor's adjustment range is limited and cannot cope with complex changes in light, especially when the angle of sunlight changes rapidly; manual adjustment is not timely enough. Automatic anti-glare rearview mirrors only address the headlights of vehicles behind, failing to solve the glare problem from the front or sides. Polarized glasses require the driver to wear them actively, and prolonged wear may cause eye discomfort, failing to fundamentally solve the glare problem. Therefore, the technical issue of low efficiency in vehicle light information processing remains.

[0100] This application provides a vehicle-mounted adaptive anti-glare method based on fuzzy logic. It introduces a fuzzy control algorithm to realize multi-parameter decision-making from light information (light intensity, angle), driving status information (vehicle speed) to transmittance, and accurately adjusts the transmittance of optical devices (windshield), thereby improving the vehicle's light information processing efficiency and solving the technical problem of low light information processing efficiency in vehicles.

[0101] Figure 2 This is a schematic diagram of the structure of an anti-glare device according to an embodiment of this application, as shown below. Figure 2 The diagram illustrates the layout and connections of a light sensor, a vehicle speed sensor, a control unit, dimmable glass, and a dynamic sun visor, including sensor 1, dimmable glass 2, dynamic sun visor 3, and control unit 4. The sensors include a light sensor and a vehicle speed sensor.

[0102] Sensor 1 includes a light sensor and a vehicle speed sensor. The light sensor can be installed on the windshield, side windows, roof, rearview mirror, etc., to acquire real-time light intensity (lux), light incident angle (°), and light change trend; the vehicle speed sensor can acquire real-time vehicle speed for fuzzy decision input.

[0103] The dimmable glass 2 can adjust the light transmittance range from 20% to 100% based on electrochromic materials or liquid crystal dimming technology.

[0104] The dynamic sunshade 3, as described above, responds to adjustment commands output by the control unit. For example, the glass transmittance adjustment value is directly mapped from the fuzzy control output value (20%). The sunshade control step size achieves a dynamic response with a displacement of 30cm in 1cm increments. It can be electrically extended, retracted, or rotated, with a displacement range of 0–30cm and an angle adjustment accuracy of ±1°.

[0105] Control unit 4 incorporates a self-organizing fuzzy controller to construct a three-dimensional fuzzy input space based on light intensity, incident angle, and vehicle speed. It generates control commands through rule matching and adaptive weight adjustment, driving the transmittance and sun visor mechanism to respond synchronously. Adjustment commands can be calculated based on collected data.

[0106] In this embodiment, a light sensor and a vehicle speed sensor continuously monitor environmental changes, uploading data such as light intensity (lux), incident angle (°), and vehicle speed (km / h) to the control unit. The fuzzy logic algorithm in the control unit performs fuzzification processing on the sensor data based on a preset mapping relationship and rule base. Then, it generates control commands through rule matching and fuzzy inference, including specific target transmittance values ​​and displacement / rotation commands for the sun visor. The control unit transmits the calculated commands to the dimmable glass and the dynamic sun visor. The dimmable glass adjusts its transmittance according to the commands, while the dynamic sun visor adjusts its position or angle to achieve an anti-glare effect.

[0107] Optionally, the structural design of the aforementioned anti-glare device fully embodies the concepts of intelligence and automation, and can automatically adjust under various lighting conditions. Whether it is direct sunlight, side light, or headlights from oncoming vehicles at night, it can respond quickly and is suitable for driving environments that require a high degree of concentration, such as highway driving, driving in adverse weather conditions, and urban night driving, which can significantly improve the driver's sense of security and comfort.

[0108] Figure 3 This is a flowchart of a control method for an anti-glare device according to an embodiment of this application, such as... Figure 3 As shown, the method may include the following steps:

[0109] Step S301: Perform light detection on the environment surrounding the vehicle.

[0110] In this embodiment, high-precision light sensors deployed inside and outside the vehicle are used to detect the light intensity and incident angle in the current environment in real time. These sensors can capture changes in ambient light, whether it is strong sunlight during the day, headlights from oncoming vehicles at night, or changes in light under complex weather conditions, all of which can be perceived immediately.

[0111] Step S302: Analyze the light intensity and incident angle obtained by the light sensor.

[0112] In this embodiment, after the control unit collects data from the light sensor, it performs in-depth data analysis, including but not limited to fuzzifying the light intensity and incident angle, converting them into fuzzy linguistic variables such as "strong light" and "directly in front," for subsequent fuzzy logic processing. Simultaneously, it can also combine this data with vehicle driving status information (such as speed and direction) for comprehensive analysis, providing a complete basis for subsequent decision-making.

[0113] Step S303: Determine whether there is a risk of glare from the light information.

[0114] In this embodiment, based on the above analysis results, an assessment can be performed to determine whether the current lighting conditions will cause glare to the driver or passengers. This assessment process can consider multiple factors, including but not limited to light intensity, incident angle, vehicle speed, and driving environment (such as weather conditions). If a glare risk is determined to exist, step S304 is executed; if no glare risk is determined to exist, execution ends.

[0115] Step S304: Automatically adjust the light transmittance of the windshield and the position of the sun visor.

[0116] In this embodiment, upon detecting a glare risk, an automatic adjustment mechanism is activated. Guided by the second and first target models, the light transmittance of the windshield and the position of the sun visor are adjusted synchronously. This not only ensures that the glare risk is reduced in the shortest possible time but also maintains a clear and safe driving view. This automatic adjustment process requires no driver intervention, improving driving comfort and safety.

[0117] Step S305: Perform continuous monitoring.

[0118] In this embodiment, even after automatic adjustments, the anti-glare system does not immediately cease operation. Instead, it continuously monitors changes in ambient light and updates to driving conditions to ensure the continuity and adaptability of its anti-glare effect. If lighting conditions change, or vehicle driving conditions (such as speed) change significantly, light detection, data analysis, and glare risk assessment can be performed again, and the anti-glare strategy can be adjusted based on the latest information. This continuous monitoring mechanism ensures that the anti-glare system maintains ideal performance in changing environments, providing drivers with continuous safety and a comfortable driving experience.

[0119] In this embodiment of the application, through the above process, the vehicle-mounted adaptive anti-glare system based on fuzzy logic can intelligently cope with various lighting conditions and driving scenarios, effectively prevent glare, improve driving safety, and continuously optimize its control strategy through a self-organizing learning mechanism to ensure high efficiency and adaptability for long-term use.

[0120] Figure 4 This is a flowchart of a self-organizing fuzzy control algorithm according to an embodiment of this application, such as... Figure 4 As shown, the method may include the following steps:

[0121] Step S401: Data acquisition.

[0122] In this embodiment, data acquisition is the starting point of the entire control process in the operation of the vehicle-mounted adaptive anti-glare system. Sensors (such as light sensors and vehicle speed sensors) monitor changes in the surrounding environment in real time, collecting various parameters including but not limited to light intensity, incident angle, and vehicle speed. This data forms the basis for subsequent processing and decision-making, ensuring that the anti-glare system can respond promptly to changes in the external environment.

[0123] Step S402: Perform blurring processing.

[0124] In this embodiment, fuzzification is the process of converting precise numerical values ​​collected by the sensor into fuzzy linguistic variables. For example, light intensity is categorized as weak (<300 lux), medium (200-700 lux), and strong (>500 lux); vehicle speed is categorized as "low," "medium," and "high"; and the incident angle is categorized as directly in front (<30°), front side (30-60°), side (60-120°), and rearward (>120°). Fuzzy output is derived through rule-based reasoning, followed by defuzzification to output specific transmittance values ​​and sun visor movement amounts.

[0125] Step S403: Perform rule matching.

[0126] In this embodiment, fuzzified input variables can be matched with a preset set of fuzzy rules to determine which rules are applicable to the current environmental conditions. For example, "IF light intensity is strong AND incident angle is lateral AND vehicle speed is medium THEN transmittance is low AND sun visor position is lateral" can find matching rules based on the current fuzzy input variables, providing a basis for the next step of decision-making.

[0127] Optionally, the fuzzy mapping relationship can be light intensity (0-1000 lux) → windshield transmittance (20%-100%); incident angle (0°-180°) → sun visor adjustment position (0-30 cm or rotation angle).

[0128] Step S404: Perform fuzzy reasoning.

[0129] In this embodiment, fuzzy inference is the process of generating fuzzy output by applying matching fuzzy rules. Output variables such as fuzzified transmittance and sun visor position can be calculated based on the fuzzy rules. This process simulates the uncertainty of human decision-making, allowing the anti-glare system to make judgments without clear boundaries, thereby improving its flexibility and robustness in handling complex and variable scenarios.

[0130] Optionally, the fuzzy rules can be: IF L is strong AND θ is forward AND v is high speed THEN T is fast dimming of the glass + sun visor slightly lowered; IF L is medium AND θ is lateral AND v is low speed THEN T is glass held and sun visor rotated 15° to the side.

[0131] Step S405: Perform deblurring.

[0132] In this embodiment, deblurring transforms the fuzzy output generated in the previous step into specific, operable action commands. By applying a deblurring algorithm, fuzzy outputs such as "low transmittance" and "sun visor position is side-rotated" derived from fuzzy inference can be converted into precise numbers, such as "transmittance is 30%" and "sun visor rotates 15° to the left." This transformation allows control signals to directly act on actuators, such as dimmable glass and dynamic sun visors, to achieve specific anti-glare measures.

[0133] Step S406: Perform self-organizing learning.

[0134] In this embodiment, self-organizing learning allows the anti-glare system to dynamically adjust the rule weights and fuzzy set boundaries in the model based on actual effects and user feedback. If a driver provides positive feedback after an adjustment (such as a significant reduction in glare), the weight of the rule used for that decision is increased accordingly; conversely, it is decreased. Furthermore, by continuously collecting and analyzing sample data, optimization points at the fuzzy set boundaries can be identified, such as adjusting the fuzzy range of light intensity to better reflect actual driving scenarios, thereby improving control accuracy and responsiveness.

[0135] In this embodiment, the self-organizing fuzzy control algorithm achieves intelligent management of the vehicle-mounted adaptive anti-glare system through the above six steps. Starting with data acquisition, the algorithm undergoes fuzzification processing, rule matching, fuzzy inference, and defuzzification, ultimately implementing specific operations. Through a self-organizing learning mechanism, it continuously optimizes itself to ensure that it can provide appropriate anti-glare measures in the face of complex and ever-changing driving environments, thus protecting the driver's safety and comfort. This control strategy embodies the advanced application of intelligent systems in the vehicle field and is an important technical means to improve driving experience and vehicle safety.

[0136] The following example uses a specific scenario to further illustrate the output and effects obtained by applying the self-organizing fuzzy control algorithm.

[0137] Assuming the scene is a high-speed, strong direct sunlight scene with a light intensity of 850 lux, an incident angle of 12°, and a vehicle speed of 100 km / h, the output can be: 35% light transmittance, sun visor moved down 8cm, achieving a 72% reduction in glare and a visual clarity of >90%.

[0138] Assuming the scenario is a low-speed side glare scenario, the light intensity is 600 lux, the incident angle is 65°, and the vehicle speed is 40 km / h, the output can be: the sun visor rotates 15°, the glass transmittance is maintained, achieving an 83% reduction in glare and an unobstructed rearview mirror.

[0139] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation portals are provided for users to choose to authorize or refuse.

[0140] According to an embodiment of this application, an embodiment of a vehicle optical information processing system is provided. Figure 5 This is a schematic diagram of a vehicle optical information processing system according to an embodiment of this application, such as... Figure 5 As shown, the vehicle's optical information processing system 50 may include: an optical information sensing device 51, a controller 52, and a state sensing device 53.

[0141] The light information sensing device 51 is used to detect the light in the environment where the vehicle is located and obtain light information. The light is used to be incident on the eyes of the target object through an optical device. The optical device is a device that allows adjustment of light transmittance. The target object is located in the vehicle. The optical device is the windshield deployed on the vehicle or the glasses device worn by the target object.

[0142] The controller 52 is used to determine a glare risk index based on light information, wherein the glare risk index is used to indicate the degree to which light poses a glare risk to the target object.

[0143] The state perception device 53 is used to acquire the vehicle's driving state information in response to a glare risk index exceeding a risk index threshold. The driving state information is used to characterize the state of the vehicle's driving parameters. The controller is also used to map the driving state information and light information using a target model to obtain a target transmittance. The target model is used to represent the rules for mapping the driving state information and light information to the target transmittance. The controller adjusts the initial transmittance of the optical device to the target transmittance. After the light passes through the adjusted optical device, the glare risk index corresponding to the light is lower than or equal to the risk index threshold.

[0144] In this embodiment, the light in the vehicle's environment is detected to obtain light information. The light is incident on the target object's binoculars via an optical device that allows adjustment of transmittance. The target object is located inside the vehicle. Based on the light information, a glare risk index is determined, representing the degree to which the light poses a glare risk to the target object. In response to the glare risk index exceeding a risk index threshold, the vehicle's driving status information is acquired, characterizing the state of the vehicle's driving parameters. A target model is used to map the driving status information and the light information to obtain a target transmittance, representing the rules for mapping the driving status information and light information to the target transmittance. The initial transmittance of the optical device is adjusted to the target transmittance, ensuring that after the light passes through the adjusted optical device, the glare risk index corresponding to the light is lower than or equal to the risk index threshold. In other words, the embodiments of the present invention introduce a comprehensive evaluation system that combines light information and driving status information, rather than simply adjusting the transmittance based on light intensity. In this way, even under the same light intensity conditions, the transmittance can be adjusted according to the vehicle's driving status information, avoiding excessive adjustment that could affect driving safety. This also avoids the defects of low transmittance adjustment accuracy caused by processing glare phenomena caused by a single light source or a specific angle, thereby solving the technical problem of low light information processing efficiency of vehicles and achieving the technical effect of improving the light information processing efficiency of vehicles.

[0145] According to an embodiment of this application, a vehicle optical information processing device is provided. It should be noted that the device can be used to execute the above-described vehicle optical information processing method.

[0146] Figure 6 This is a schematic diagram of a vehicle optical information processing device according to an embodiment of this application, such as... Figure 6 As shown, the vehicle's optical information processing device 60 may include: a detection unit 61, a determination unit 62, an acquisition unit 63, a mapping unit 64, and an adjustment unit 65.

[0147] The detection unit 61 is used to detect the light in the environment where the vehicle is located and obtain light information. The light is used to be incident on the eyes of the target object through an optical device. The optical device is a device that allows adjustment of light transmittance. The target object is located in the vehicle.

[0148] The determination unit 62 is used to determine the glare risk index based on light information, wherein the glare risk index is used to represent the degree to which light poses a glare risk to the target object.

[0149] The acquisition unit 63 is used to acquire the vehicle's driving status information in response to the glare risk index being higher than the risk index threshold. The driving status information is used to characterize the state of the vehicle's driving parameters.

[0150] The mapping unit 64 is used to map driving state information and light information using a target model to obtain target transmittance. The target model is used to represent the rules for mapping driving state information and light information to target transmittance.

[0151] The adjustment unit 65 is used to adjust the initial transmittance of the optical device to the target transmittance, wherein after the light passes through the adjusted optical device, the glare risk index corresponding to the light is lower than or equal to the risk index threshold.

[0152] Optionally, the mapping unit 64 includes: a first mapping submodule, used to map the driving state information and the light information using a target model in response to the information value of the light information being within the information value range, to obtain a target transmittance range, wherein the target transmittance range corresponds to the information value range; and a first determining submodule, used to determine the target transmittance within the target transmittance range.

[0153] Optionally, the information value of the light information includes the light intensity, the information value range includes the target light intensity range, the target model includes a first target model, the first target model is used to represent the rule for mapping driving state information and light intensity to a target transmittance range, and the first mapping submodule includes: a second mapping submodule, used to map driving state information and light intensity using the first target model in response to the light intensity being within the target light intensity range, to obtain the target transmittance range.

[0154] Optionally, the vehicle's optical information processing device 60 may further include: a second determining submodule, used to determine a first initial model, wherein the first initial model represents the mapping relationship between different initial light intensity ranges of light samples and different initial transmittance ranges of optical device samples; a first adjusting submodule, used to adjust the initial light intensity range and initial transmittance range using light intensity samples and transmittance samples to obtain target light intensity range and target transmittance range, wherein after a light sample with light intensity equal to the light intensity sample passes through an optical device sample with transmittance equal to the transmittance sample, the glare risk index corresponding to the light sample is lower than or equal to a risk index threshold, the initial light intensity range includes the target light intensity range, and the initial transmittance range includes the target transmittance range; and a first training submodule, used to train a first target model using the target light intensity range and target transmittance range.

[0155] Optionally, when the optical device is a windshield deployed on a vehicle, the information value of the light information also includes the incident angle of the light, the information value range includes a target incident angle range, and the target model includes a second target model. The second target model is used to represent the rule for mapping the driving state information and the incident angle to a target position range, and the target position range corresponds to the target incident angle range. The vehicle's light information processing device 60 may further include: a third mapping submodule, used to map the driving state information and the incident angle using the second target model in response to the incident angle being within the target incident angle range, to obtain the target position range; a third determining submodule, used to determine the target position within the target position range, wherein the target position is used to represent the position to which the vehicle's sun visor needs to be adjusted; and a second adjusting submodule, used to adjust the initial position of the sun visor to the target position, wherein the adjusted sun visor is used to block light for the target object.

[0156] Optionally, the vehicle's optical information processing device 60 may further include: a fourth determining submodule for determining a second initial model, wherein the second initial model represents the mapping relationship between different initial incident angle ranges of light samples and different initial position ranges of sun visor samples; a third adjusting submodule for adjusting the initial incident angle range and initial position range using incident angle samples and position samples to obtain a target incident angle range and a target position range, wherein the light sample with incident angle is the incident angle sample is blocked by the sun visor sample with position is the position sample, the initial incident angle range includes the target incident angle range, and the initial position range includes the target position range; and a second training submodule for training a second target model using the target incident angle range and target position range.

[0157] Optionally, after adjusting the initial transmittance of the optical device to the target transmittance, the vehicle's optical information processing device 60 may further include: a fourth adjustment submodule, used to adjust the weights of the target model according to a weight adjustment strategy, using the target transmittance as a transmittance sample and the optical information as an optical information sample, wherein the weight adjustment strategy is used to represent the rules for adjusting the weights of the target model; and an update submodule, used to update the target model before adjustment using the adjusted target model.

[0158] In the vehicle's optical information processing device of this embodiment, the detection unit 61 detects the light in the vehicle's environment to obtain optical information. The light is incident on the target object's binoculars via an optical device that allows adjustment of transmittance. The target object is located inside the vehicle. The determination unit 62 determines a glare risk index based on the optical information. The glare risk index represents the degree to which the light poses a glare risk to the target object. The acquisition unit 63 acquires the vehicle's driving status information in response to the glare risk index exceeding a risk index threshold. The driving status information characterizes the state of the vehicle's driving parameters. The mapping unit 64 maps the driving status information and the optical information using a target model to obtain a target transmittance. The target model represents the rules for mapping the driving status information and the optical information to the target transmittance. The adjustment unit 65 adjusts the initial transmittance of the optical device to the target transmittance. After the light passes through the adjusted optical device, the glare risk index corresponding to the light is lower than or equal to the risk index threshold. This solves the technical problem of low vehicle optical information processing efficiency and achieves the technical effect of improving vehicle optical information processing efficiency.

[0159] Embodiments of this application also provide a vehicle, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods described in various embodiments of this application when it runs.

[0160] Embodiments of this application also provide a computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0161] Embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the methods of various embodiments of this application.

[0162] Embodiments of this application also provide a computer program product, including a non-volatile computer-readable storage medium for storing a computer program that, when executed by a processor, implements the methods in various embodiments of this application.

[0163] Embodiments of this application also provide a computer program that, when executed by a processor, implements the methods described in the various embodiments of this application.

[0164] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0165] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0166] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0167] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0168] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0169] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for processing optical information of a vehicle, characterized in that, include: The light in the vehicle's environment is detected to obtain light information, wherein the light is used to be incident on the binoculars of the target object via an optical device, the optical device being a device that allows adjustment of light transmittance, and the target object is located inside the vehicle; Based on the light information, a glare risk index is determined, wherein the glare risk index is used to indicate the degree to which the light poses a glare risk to the target object; In response to the dazzling risk indicator being higher than the risk indicator threshold, the driving status information of the vehicle is obtained, wherein the driving status information is used to characterize the state of the vehicle's driving parameters; Using a target model, the driving state information and the light information are mapped to obtain the target transmittance, wherein the target model is used to represent the rules for mapping the driving state information and the light information to the target transmittance; The initial transmittance of the optical device is adjusted to the target transmittance, wherein after the light passes through the adjusted optical device, the glare risk index corresponding to the light is lower than or equal to the risk index threshold.

2. The method according to claim 1, characterized in that, The process of mapping the driving state information and the light information using a target model to obtain the target transmittance includes: In response to the information value of the light information being within the information value range, the target model is used to map the driving state information and the light information to obtain the target transmittance range, wherein the target transmittance range corresponds to the information value range; Within the target transmittance range, the target transmittance is determined.

3. The method according to claim 2, characterized in that, The information value of the light information includes the light intensity of the light, the information value range includes a target light intensity range, and the target model includes a first target model. The first target model is used to represent the rules for mapping the driving state information and the light intensity to the target transmittance range. The process of mapping the driving state information and the light information to obtain the target transmittance range using the target model, in response to the information value of the light information being within the information value range, includes: In response to the light intensity being within the target light intensity range, the driving state information and the light intensity are mapped using the first target model to obtain the target transmittance range.

4. The method according to claim 3, characterized in that, The method further includes: A first initial model is determined, wherein the first initial model is used to represent the mapping relationship between different initial light intensity ranges of the light sample and different initial transmittance ranges of the optical device sample; Using light intensity samples and transmittance samples, the initial light intensity range and the initial transmittance range are adjusted to obtain the target light intensity range and the target transmittance range. Specifically, after a light ray sample with light intensity equal to the light intensity sample passes through an optical device sample with transmittance equal to the transmittance sample, the glare risk index corresponding to the light ray sample is lower than or equal to the risk index threshold. The initial light intensity range includes the target light intensity range, and the initial transmittance range includes the target transmittance range. The first target model is trained using the target illumination intensity range and the target transmittance range.

5. The method according to claim 3, characterized in that, When the optical device is a windshield deployed on the vehicle, the information value of the light information also includes the incident angle of the light, the range of the information value includes a target incident angle range, the target model includes a second target model, the second target model is used to represent the rule for mapping the driving state information and the incident angle to a target position range, the target position range corresponds to the target incident angle range, and the method further includes: In response to the incident angle being within the target incident angle range, the second target model is used to map the driving state information and the incident angle to obtain the target position range; Within the target location range, a target location is determined, wherein the target location represents the position to which the sun visor of the vehicle needs to be adjusted; The initial position of the sunshade is adjusted to the target position, wherein the adjusted sunshade is used to block the light for the target object.

6. The method according to claim 5, characterized in that, The method further includes: A second initial model is determined, wherein the second initial model is used to represent the mapping relationship between different initial incident angle ranges of the light sample and different initial position ranges of the sunshade sample; Using incident angle samples and position samples, the initial incident angle range and the initial position range are adjusted to obtain the target incident angle range and the target position range, wherein the incident angle is the light sample of the incident angle sample, and the position is the sunshade sample of the position sample; the initial incident angle range includes the target incident angle range, and the initial position range includes the target position range. The second target model is trained using the target incident angle range and the target position range.

7. The method according to any one of claims 1 to 6, characterized in that, After adjusting the initial transmittance of the optical device to the target transmittance, the method further includes: Using the target transmittance as a transmittance sample and the light information as a light information sample, the weights of the target model are adjusted according to a weight adjustment strategy, wherein the weight adjustment strategy is used to represent the rules for adjusting the weights of the target model. The original target model is updated using the adjusted target model.

8. A vehicle optical information processing system, characterized in that, include: Optical information sensing devices, state sensing devices, and controllers, among which, The light information sensing device is used to detect the light in the environment where the vehicle is located and obtain light information. The light is used to be incident on the eyes of the target object through an optical device. The optical device is a device that allows adjustment of light transmittance. The target object is located in the vehicle. The optical device is the windshield deployed on the vehicle or the glasses device worn by the target object. The controller is configured to determine a glare risk index based on the light information, wherein the glare risk index is used to indicate the degree to which the light poses a glare risk to the target object; The state perception device is used to obtain the driving state information of the vehicle in response to the glare risk index being higher than the risk index threshold, wherein the driving state information is used to characterize the state of the vehicle's driving parameters. The controller is further configured to use a target model to map the driving state information and the light information to obtain a target transmittance, wherein the target model is used to represent the rules for mapping the driving state information and the light information to the target transmittance; and to adjust the initial transmittance of the optical device to the target transmittance, wherein after the light passes through the adjusted optical device, the glare risk index corresponding to the light is lower than or equal to the risk index threshold.

9. A vehicle, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, performs the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device on which the storage medium is located to perform the method according to any one of claims 1 to 7.

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