Intelligent cabin ambient light visual comfort evaluation method and system

Abstract

The application relates to the technical field of intelligent cockpits, in particular to an intelligent cockpit ambient light visual comfort evaluation method and system. The method comprises the following steps: obtaining structure boundary data, driver reference sitting posture data and light-emitting component arrangement data of a target cockpit, and establishing a cockpit space model, a driver viewpoint reference position and a light-emitting component space distribution model in a simulation environment; obtaining a test scene parameter set corresponding to a preset test scene, and generating an ambient light evaluation scene; extracting light-emitting parameters of each light-emitting component in the vehicle, brightness distribution parameters of a preset observation area and reflection bright spots of a reflection sensitive area; mapping the extracted parameters to the cockpit space model; identifying direct glare risk areas, reflection glare risk areas and visual interference risk areas; and evaluating the ambient light visual comfort according to the extracted parameters and the test scene parameter set. The application solves the problems of lacking scene-based test constraints of intelligent cockpit ambient light.

Description

Technical Field

[0001] This application relates to the field of intelligent cockpit technology, and more specifically, to a method and system for evaluating the visual comfort of ambient light in intelligent cockpits. Background Technology

[0002] With the development of intelligent cockpit technology, the automotive cockpit is gradually evolving from a traditional space dominated by mechanical buttons and instrument displays into a complex human-machine environment integrating information display, interactive control, atmosphere creation, and assisted perception. The application of luminous components such as central control displays, passenger entertainment screens, instrument panels, head-up displays, as well as ambient lighting, door panel decorative lights, and footwell lights within the cockpit is becoming increasingly common. The cabin's internal lighting environment is showing a trend of increasing number of light sources, dispersed installation locations, expanded brightness range, and complex linkage modes. Against this backdrop, cabin ambient light no longer only serves a lighting or decorative function but also directly impacts the driver's visual perception, information recognition, and field of vision.

[0003] Current smart cockpit products generally exhibit a trend towards larger screen sizes, increased display brightness, and more luminous areas. Especially in complex lighting conditions such as nighttime, tunnel entrances / exits, underground parking garages, driving against sunlight, and rain / fog, improper settings for the brightness, color temperature, installation angle, light emission direction, and reflection path of the cockpit's display terminals or ambient lighting can easily create direct glare, reflected glare, or localized high-brightness interference areas within the driver's field of vision. For example, the display screen surface or high-brightness decorative parts may create specular reflections on the windshield, side windows, or rearview mirrors; ambient lighting or localized lighting components may create persistent bright spots within the driver's peripheral vision; and excessive brightness differences between multiple light sources can cause visual adaptation burden. All of these issues can affect the driver's acquisition and recognition of external road condition information.

[0004] Currently, industry attention to in-vehicle lighting environments primarily focuses on lighting design, display optimization, and subjective improvement of the passenger experience. A comprehensive testing and evaluation system for the visual comfort of ambient light in driving scenarios remains incomplete. Existing evaluation methods often rely on subjective questionnaires, expert judgment, or analysis using a single brightness index. These methods suffer from issues such as fragmented evaluation dimensions, insufficient parameter correlation, inconsistent testing conditions, and poor result consistency. In particular, a unified technical solution for quantitative characterization and systematic evaluation of factors such as installation location, luminous area, brightness distribution, reflection path, line-of-sight interaction, and the degree of visual interference in dynamic driving scenarios is still lacking.

[0005] On the other hand, current technologies for analyzing the cabin lighting environment often focus on static illuminance measurements or single-point brightness acquisition, making it difficult to reflect the coupling relationship between changes in the external background and the in-vehicle light-emitting components during actual driving. In other words, relying solely on the brightness value of a single location or a single subjective score is insufficient to accurately characterize the impact of ambient light on the driver's visual comfort. Furthermore, differences in the structural position, material reflectivity, surface curvature, display content brightness, and operating mode of different light-emitting components can lead to varying visual interference characteristics under the same nominal brightness conditions, and existing methods lack a unified modeling and grading evaluation mechanism for this.

[0006] In view of the above, this application is hereby submitted. Summary of the Invention

[0007] The purpose of this application is to provide a method and system for evaluating the visual comfort of ambient light in intelligent cockpits, in order to solve the problems in the prior art regarding the lack of scenario-based testing constraints, the lack of multi-factor correlation analysis mechanisms, and the lack of visual comfort evaluation methods that can output quantitative results for ambient light in intelligent cockpits.

[0008] To achieve the above objectives, this application adopts the following technical solution: Firstly, this application provides a method for evaluating the visual comfort of ambient light in a smart cockpit, including: Acquire structural boundary data of the target cockpit, driver reference sitting posture data, and light-emitting component arrangement data, and establish a cockpit space model, driver viewpoint reference position, and light-emitting component spatial distribution model in the simulation environment; Obtain the test scenario parameter set corresponding to the preset test scenario, and generate the ambient light evaluation scenario under the preset test scenario; wherein, the test scenario parameter set includes: external ambient brightness, driving time, road environment category, weather condition and vehicle operating status; In the real world, extract the luminous parameters of each light-emitting component inside the vehicle, the brightness distribution parameters of the preset observation area, and the reflective bright spots of the reflection-sensitive area; then map the extracted parameters into the cabin space model. In the cockpit space model, the visual field relationship between each light-emitting component and the driver is determined, and based on the visual field relationship and the extracted parameters, the direct glare risk area, the reflected glare risk area, and the visual interference risk area are identified. In the areas of direct glare risk, reflected glare risk, and visual interference risk, the visual comfort of ambient light is evaluated based on the extracted parameters and the parameter set of the test scenario.

[0009] Secondly, this application provides an intelligent cockpit ambient light visual comfort evaluation system, including: The acquisition module is used to acquire structural boundary data of the target cockpit, driver reference sitting posture data, and light-emitting component arrangement data, and to establish a cockpit space model, driver viewpoint reference position, and light-emitting component spatial distribution model in the simulation environment. The simulation module is used to acquire a set of test scenario parameters corresponding to a preset test scenario and generate an ambient light evaluation scenario under the preset test scenario; wherein, the set of test scenario parameters includes: external ambient brightness, driving time, road environment category, weather conditions and vehicle operating status; The data acquisition device is used to extract the luminous parameters of various light-emitting components inside the vehicle, the brightness distribution parameters of the preset observation area, and the reflective bright spots of the reflection-sensitive area in the real world; and to map the extracted parameters into the cockpit space model. The evaluation module is used to determine the visual field relationship between each light-emitting component and the driver in the cockpit space model, and based on the visual field relationship and extracted parameters, identify direct glare risk areas, reflected glare risk areas, and visual interference risk areas; within the direct glare risk areas, reflected glare risk areas, and visual interference risk areas, the ambient light visual comfort is evaluated according to the extracted parameters and the test scene parameter set. Compared with the prior art, this application has the following beneficial effects: This application provides a method and system for evaluating the visual comfort of ambient light in an intelligent cockpit. By performing a unified correlation analysis on the luminous parameters of each luminous component in the cockpit, the driver's visual field relationship, the reflection interference, and the test scene parameters, and outputting a visual comfort score and corresponding level results, it solves the problems in the prior art of lacking scenario-based test constraints, lacking a multi-factor correlation analysis mechanism, and lacking a visual comfort evaluation method that can output quantitative results for ambient light in intelligent cockpits. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0011] Figure 1 This is a flowchart illustrating a method for evaluating the visual comfort of ambient light in an intelligent cockpit, as provided in an embodiment of this application. Figure 2 This is a structural diagram of an intelligent cockpit ambient light visual comfort evaluation system provided in an embodiment of this application. Detailed Implementation

[0012] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of this application, including various details to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0013] Figure 1 This is a flowchart illustrating a method for evaluating the visual comfort of ambient light in a smart cockpit, as provided in this embodiment. This embodiment is applicable to applications that analyze the impact of light-emitting components on driver vision in a smart cockpit. This method can be executed by a smart cockpit ambient light visual comfort evaluation system.

[0014] like Figure 1 As shown in the figure, this embodiment provides a method for evaluating the visual comfort of ambient light in an intelligent cockpit, which specifically includes the following steps: S110. Obtain the structural boundary data of the target cockpit, the driver's reference sitting posture data, and the arrangement data of the light-emitting components, and establish the cockpit space model, the driver's viewpoint reference position, and the spatial distribution model of the light-emitting components in the simulation environment.

[0015] First, the target cabin area of ​​the vehicle to be evaluated is determined, and data related to visual comfort evaluation within the cabin is collected. Structural boundary data may include the spatial relationships of components such as the windshield, side windows, center console, instrument panel, door panels, headliner, and seats; driver baseline seating posture data may include the driver's eye position, head orientation, seat adjustment position, and backrest angle; and data on the arrangement of luminous components may include the installation position, installation angle, and luminous area size of luminous components such as the center console display, instrument display, passenger display, head-up display, ambient lighting, local lighting, and function indicator lights.

[0016] Based on the above data, a cockpit space model of the target cockpit is constructed, and the driver's viewpoint reference position is determined. Simultaneously, the positions of each luminous component are mapped into the cockpit space model. This step provides a unified spatial reference for subsequent scene configuration, viewpoint analysis, and interference identification.

[0017] S120. Obtain the test scenario parameter set corresponding to the preset test scenario, and generate the ambient light evaluation scenario under the preset test scenario; wherein, the test scenario parameter set includes: external ambient brightness, driving time, road environment category, weather status and vehicle operating status.

[0018] Set corresponding test scenarios according to the preset evaluation tasks (such as the evaluation task of ambient light visual comfort when the central control display, instrument display and door panel ambient lights work together in the state of driving on urban roads at night). Optionally, the test scenarios can be set as daytime scenarios, nighttime scenarios, tunnel entrance and exit scenarios, underground garage scenarios, rain and fog weather scenarios or different vehicle speed conditions scenarios according to actual needs.

[0019] The test scenario parameter set is associated with the cockpit space model established in step S110 to form an ambient light evaluation scenario for the corresponding test scenario. In other words, this step not only determines the static positional relationship of the light-emitting components inside the cockpit, but also further determines the external lighting background and vehicle operating conditions of the cockpit, so that the subsequent evaluation results can reflect the visual comfort status under actual use scenarios.

[0020] S130. In the real world, extract the luminous parameters of each luminous component inside the vehicle, the brightness distribution parameters of the preset observation area, and the reflective bright spots of the reflection-sensitive area; map the extracted parameters into the cockpit space model.

[0021] In the real world, the luminous parameters of various light-emitting components (such as displays) in the vehicle are extracted, including: brightness, luminous area, and brightness uniformity. The luminous parameters are used to determine the degree of visual stimulation and interference risk of the display in the driver's field of vision.

[0022] Spatial sampling points are set up in the preset observation area and the reflection-sensitive area. Brightness distribution parameters and reflective bright spots are collected at the spatial sampling points using optical acquisition equipment.

[0023] The preset observation areas include the area directly in front of the driver, the corresponding area of ​​the windshield, the corresponding area of ​​the side windows, the reflective area of ​​the center console, and the area associated with the rearview mirror. Reflection-sensitive areas include reflective surfaces such as glass, used to identify reflection interference caused by the display screen or ambient light sources projecting onto these surfaces. In practice, multiple spatial sampling points are pre-arranged within the driver's head movement range, the area adjacent to the inner side of the windshield, the area above the center console, the area adjacent to the side windows, reflective surfaces, and the area adjacent to the rearview mirror. Miniature optical acquisition units are installed at each spatial sampling point, or movable acquisition probes are used to sequentially reach each sampling point. Each optical acquisition unit collects the incident brightness and reflected bright spots at the corresponding location, and then combines this with the three-dimensional coordinates of the sampling points to form spatial brightness distribution parameters (i.e., brightness carrying location information) and reflected bright spots. The luminous area and brightness uniformity can be obtained mathematically based on the brightness of each point. Thus, the spatial light field distribution of the target cockpit area is constructed based on the spatial brightness dataset.

[0024] S140. In the cockpit space model, determine the visual field relationship between each light-emitting component and the driver, and based on the visual field relationship and the extracted parameters, identify the direct glare risk area, the reflected glare risk area, and the visual interference risk area.

[0025] First, a driver's field of view model is established. The driver's field of view model is used to characterize the main observation range of the driver in normal driving conditions, including the road ahead, the instrument area, the side area, and the rearview mirror area. It can be represented by a three-dimensional coordinate range.

[0026] After establishing the driver's field of view model, the positional relationship of each light-emitting component relative to the driver's field of view is further analyzed to determine the spatial intersection between the light-emitting components and the driver's main observation range.

[0027] The position of the light-emitting component is projected onto the driver's primary field of vision to determine the coverage ratio between the light-emitting component and the driver's field of vision. Based on the coverage ratio, it is determined whether the light-emitting component is located in the driver's core visual field, extended visual field, or peripheral visual field.

[0028] Specifically, the driver's main observation range is divided into the core visual field, the extended visual field, and the peripheral visual field. The core visual field is the key observation area for the driver during normal forward-looking driving; the extended visual field is the area where the driver uses auxiliary observation of instruments, rearview mirrors, and nearby road conditions while completing driving tasks; and the peripheral perception area is the area that is not within the scope of focused attention but can be perceived by the surrounding vision.

[0029] If the coverage of a light-emitting component in any area exceeds 50%, that is, if the driver can see more than 50% of the light-emitting component in a field of view (one of the core field of view, extended field of view, and edge field of view) (for example, 50% of a display screen is in the core field of view), then the light-emitting component is located in that field of view.

[0030] Then, based on the visual field relationship and the extracted parameters, the direct glare risk area, the reflected glare risk area, and the visual interference risk area are identified.

[0031] The extracted parameters include: the luminous parameters of each light-emitting component inside the vehicle, the brightness distribution parameters of the preset observation area, and the reflective bright spots in the reflection-sensitive area.

[0032] Specifically, within the core visual field, areas with brightness exceeding a preset threshold (which can be manually defined) are designated as direct glare risk areas. Direct glare risk areas mainly refer to the risk areas formed when high-brightness light emitted by the light-emitting components directly enters the driver's core visual field.

[0033] Areas that enter the driver's core and extended visual field after being reflected by reflective surfaces are designated as reflective glare risk areas. For example, reflective surfaces include the inner surface of the windshield or the reflective surface of the center console. Reflective glare risk areas refer to the risk zones formed when light emitted from luminous components is reflected by reflective surfaces such as the windshield, side windows, piano black trim, and mirrored decorative elements, entering the driver's core and extended visual field.

[0034] Within the core field of view, extended field of view, or peripheral field of view, areas with brightness exceeding a preset threshold are designated as visual interference risk areas. Visual interference risk areas primarily refer to areas where high-brightness emitting areas are spatially coupled with the driver's primary observation range, thereby interfering with external target identification or cockpit information reading.

[0035] S150. In the areas of direct glare risk, reflected glare risk, and visual interference risk, the visual comfort of ambient light is evaluated based on the extracted parameters and the test scenario parameter set.

[0036] The extracted parameters include the luminous parameters of each light-emitting component inside the vehicle, the brightness distribution parameters of the preset observation area, and the reflective bright spots in the reflection-sensitive area.

[0037] First, within the direct glare risk area, reflected glare risk area, and visual interference risk area, basic light stimulation indicators are calculated based on the (average) brightness, luminous area, and brightness uniformity of each light-emitting component. Since brightness, luminous area, and brightness uniformity are different types of indicators, they need to be dimensionless. Then, the direct glare risk area has the greatest impact on the driver and is therefore given the highest weight; the reflected glare risk area has a moderate impact on the driver and is therefore given a moderate weight; and the visual interference risk area has the least impact on the driver and is therefore given the least weight. The dimensionless (average) brightness (using the aforementioned large, medium, and small weights) of the three risk areas is weighted and summed to obtain a brightness score; the dimensionless luminous area (using the aforementioned large, medium, and small weights) of the three risk areas is weighted and summed to obtain a luminous area score; and the dimensionless brightness uniformity (using the aforementioned large, medium, and small weights) of the three risk areas is weighted and summed to obtain a brightness uniformity score. The brightness score, luminous area score, and brightness uniformity score are then added together to obtain the basic light stimulation indicators.

[0038] Within the risk area of ​​reflected glare, the field-of-view coupling index is calculated based on the reflected bright spots. For example, the brightness and area of ​​the reflected bright spots are dimensionless, and the average value is taken to obtain the field-of-view coupling index.

[0039] Within the visual interference risk area, the interference risk index is calculated based on the degree of obstruction of the external environment by the brightness of each luminous component or the degree of obstruction by the reflected bright spot. Within the visual interference risk area, if the brightness of the luminous component exceeds a certain value, it will obstruct the view of the outside world, making it difficult for the driver to see clearly. This degree of obstruction can be characterized by the ratio of the brightness of the luminous component / reflected bright spot to the brightness of the outside environment. If this ratio is greater than 1.2, it indicates that the brightness of the luminous component / reflected bright spot is significantly higher than the outside environment, causing obstruction, and the interference risk index is 1. If the ratio is between 0.7 and 1.2, it indicates that the brightness of the luminous component / reflected bright spot is similar to the outside environment, and it will also cause some visual interference to the driver; the interference risk index is set to the ratio minus 0. If the ratio is less than 0.8, it is considered not to interfere with the driver, and the interference risk index is set to 0.

[0040] Then, correction factors are determined based on the test scenario parameter set, and the basic light stimulation index, visual coupling index, and interference risk index are corrected according to the correction factors. The test scenario parameter set includes: ambient light outside the vehicle, driving time, road environment type, weather conditions, and vehicle operating status.

[0041] For example, when the ambient light outside the vehicle is less than a set value, the interior brightness will significantly affect the driver's vision, thus increasing the basic light stimulation index, visual coupling index, and interference risk index. Conversely, when the ambient light outside the vehicle is greater than or equal to the set value, these indices should be decreased. The longer the driving time, the more fatigued the driver becomes, and the stronger their sensitivity to light; therefore, the basic light stimulation index, visual coupling index, and interference risk index need to be increased proportionally with driving time. Road environment categories are divided into different levels of driving difficulty, such as easy-to-drive wide asphalt roads, general narrow roads, and difficult-to-drive mountain roads. The more difficult the driving, the greater the increase in the basic light stimulation index, visual coupling index, and interference risk index. Weather conditions are also divided into weather types that affect driving difficulty differently; for example, driving in rain or snow is more difficult than in sunny weather. Similarly, the worse the weather, the greater its impact on driving, and the greater the increase in the basic light stimulation index, visual coupling index, and interference risk index. Vehicle operating status includes both driving and stationary states. The basic light stimulation index, visual field coupling index, and interference risk index should be increased when the vehicle is in motion compared to when it is stationary.

[0042] Optionally, a score can be calculated based on the modified baseline light stimulation index, visual coupling index, and interference risk index; for example, the modified baseline light stimulation index, visual coupling index, and interference risk index can be weighted (the weights can be defined) and summed to obtain the score. A higher score indicates poorer comfort. The comfort evaluation level of the target cabin is determined based on the preset levels of the score (e.g., comfort level, warning level, and restriction level; more levels can also be defined according to actual evaluation needs).

[0043] Optionally, in addition to the overall rating results, further evaluation results at the level of light-emitting components, regional levels, and overall cabin levels can be output. For example, target displays or target ambient light sources that have a significant impact on the evaluation value can be identified, and the corresponding risk area distribution and indicator scores can also be output, thus forming a complete evaluation report. Through this step, the aforementioned modeling, data collection, analysis, and calculation results can be transformed into directly applicable output information.

[0044] In summary, the intelligent cockpit ambient light visual comfort evaluation method and system provided in this application solves the problems of lack of scenario-based testing constraints, lack of multi-factor correlation analysis mechanism, and lack of visual comfort evaluation means that can output quantitative results in the existing technology for intelligent cockpit ambient light by uniformly analyzing the luminous parameters of each luminous component in the cockpit, the relationship between the driver's field of vision, the reflection interference, and the test scene parameters, and outputting visual comfort scores and corresponding level results.

[0045] Optional, see Figure 2 This application also provides an intelligent cockpit ambient light visual comfort evaluation system, including: The acquisition module is used to acquire structural boundary data of the target cockpit, driver reference sitting posture data, and light-emitting component arrangement data, and to establish a cockpit space model, driver viewpoint reference position, and light-emitting component spatial distribution model in the simulation environment. The simulation module is used to acquire a set of test scenario parameters corresponding to a preset test scenario and generate an ambient light evaluation scenario under the preset test scenario; wherein, the set of test scenario parameters includes: external ambient brightness, driving time, road environment category, weather conditions and vehicle operating status; The data acquisition device is used to extract the luminous parameters of various light-emitting components inside the vehicle, the brightness distribution parameters of the preset observation area, and the reflective bright spots of the reflection-sensitive area in the real world; and to map the extracted parameters into the cockpit space model. The evaluation module is used to determine the visual field relationship between each light-emitting component and the driver in the cockpit space model, and to identify direct glare risk areas, reflected glare risk areas, and visual interference risk areas based on the visual field relationship and the extracted parameters; within the direct glare risk areas, reflected glare risk areas, and visual interference risk areas, the ambient light visual comfort is evaluated according to the extracted parameters and the test scene parameter set.

[0046] The intelligent cockpit ambient light visual comfort evaluation system provided in this application can perform any of the aforementioned intelligent cockpit ambient light visual comfort evaluation methods and has the corresponding technical effects, which will not be elaborated here.

[0047] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this application can be achieved, and this is not limited herein.

[0048] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for evaluating the visual comfort of ambient light in an intelligent cockpit, characterized in that, include: Acquire structural boundary data of the target cockpit, driver reference sitting posture data, and light-emitting component arrangement data, and establish a cockpit space model, driver viewpoint reference position, and light-emitting component spatial distribution model in the simulation environment; Obtain the test scenario parameter set corresponding to the preset test scenario, and generate the ambient light evaluation scenario under the preset test scenario; wherein, the test scenario parameter set includes: external ambient brightness, driving time, road environment category, weather condition and vehicle operating status; In the real world, extract the luminous parameters of each light-emitting component inside the vehicle, the brightness distribution parameters of the preset observation area, and the reflective bright spots of the reflection-sensitive area; then map the extracted parameters into the cabin space model. In the cockpit space model, the visual field relationship between each light-emitting component and the driver is determined, and based on the visual field relationship and the extracted parameters, the direct glare risk area, the reflected glare risk area, and the visual interference risk area are identified. Within the direct glare risk area, reflected glare risk area, and visual interference risk area, the ambient light visual comfort is evaluated based on the extracted parameters and the test scene parameter set, including: Within the direct glare risk area, reflected glare risk area, and visual interference risk area, basic light stimulation indices are calculated based on the brightness, luminous area, and brightness uniformity of each light-emitting component. Within the reflected glare risk area, visual coupling indices are calculated based on reflected bright spots. Within the visual interference risk area, interference risk indices are calculated based on the degree of occlusion of the external environment by the brightness of each light-emitting component, or the degree of occlusion of the external environment by reflected bright spots. Correction factors are determined based on the test scene parameter set, and the basic light stimulation indices, visual coupling indices, and interference risk indices are corrected based on these correction factors.

2. The method according to claim 1, characterized in that, In the real world, the luminous parameters of each light-emitting component inside the vehicle, the brightness distribution parameters of the preset observation area, and the reflected bright spots in the reflection-sensitive area are extracted, including: In the real world, extract the brightness, luminous area, and brightness uniformity of each light-emitting component inside the vehicle; Spatial sampling points are set in the preset observation area and the reflection-sensitive area, and brightness distribution parameters and reflective bright spots are collected at the spatial sampling points by optical acquisition equipment.

3. The method according to claim 2, characterized in that, In the cockpit space model, the visual relationship between each luminous component and the driver is determined, including: A driver's field of view model is established, which is used to characterize the driver's observation range of the road ahead, instrument area, side area and rearview mirror area under normal driving conditions; The position of the light-emitting component is projected into the driver's field of vision to determine the coverage ratio between the light-emitting component and the driver's field of vision; Based on the coverage ratio, it is determined whether the light-emitting component is located in the driver's core visual field area, extended visual field area, or edge visual field area.

4. The method according to claim 3, characterized in that, Based on the aforementioned visual field relationships and extracted parameters, direct glare risk areas, reflected glare risk areas, and visual interference risk areas are identified, including: Within the core visual field, areas with brightness exceeding a preset threshold are identified as areas of direct glare risk. The areas that enter the driver's core visual field and extended visual field after being reflected by the reflective surface are identified as areas of risk for reflected glare. Within the core visual field, extended visual field, or edge visual field, areas with brightness exceeding a preset threshold are identified as visual interference risk areas.

5. The method according to claim 1, characterized in that, After correcting the basic optical stimulation index, visual coupling index, and interference risk index according to the correction factor, the following is also included: The score is calculated based on the revised baseline optical stimulation index, visual field coupling index, and interference risk index. The comfort rating level of the target cabin is determined based on the preset rating levels.

6. A smart cockpit ambient light visual comfort evaluation system, characterized in that, include: The acquisition module is used to acquire structural boundary data of the target cockpit, driver reference sitting posture data, and light-emitting component arrangement data, and to establish a cockpit space model, driver viewpoint reference position, and light-emitting component spatial distribution model in the simulation environment. The simulation module is used to acquire a set of test scenario parameters corresponding to a preset test scenario and generate an ambient light evaluation scenario under the preset test scenario; wherein, the set of test scenario parameters includes: external ambient brightness, driving time, road environment category, weather conditions and vehicle operating status; The data acquisition device is used to extract the luminous parameters of various light-emitting components inside the vehicle, the brightness distribution parameters of the preset observation area, and the reflective bright spots of the reflection-sensitive area in the real world; and to map the extracted parameters into the cockpit space model. The evaluation module is used to determine the visual field relationship between each light-emitting component and the driver in the cockpit space model, and based on the visual field relationship and extracted parameters, identify direct glare risk areas, reflected glare risk areas, and visual interference risk areas. Within these areas, the module evaluates the ambient light visual comfort according to the extracted parameters and the test scenario parameter set. This includes: calculating basic light stimulation indices based on the brightness, luminous area, and brightness uniformity of each light-emitting component within these areas; calculating visual field coupling indices based on reflected bright spots within reflected glare risk areas; and calculating interference risk indices based on the degree of occlusion of the external environment by the brightness of each light-emitting component or the degree of occlusion of reflected bright spots within visual interference risk areas. Finally, it determines correction factors based on the test scenario parameter set and corrects the basic light stimulation indices, visual field coupling indices, and interference risk indices based on these correction factors.

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