Urban landscape lighting design optimization method and system based on VR technology

Abstract

The invention provides an urban landscape lighting design optimization method and system based on a VR technology, and relates to the technical field of urban lighting design, and the method comprises the steps: constructing an urban three-dimensional model, and obtaining an urban VR space; fitting a landscape lighting design drawing to the urban three-dimensional model; in the city VR space, lighting simulation rendering is carried out according to design parameters in the landscape lighting design drawing; performing landscape lighting design evaluation through an evaluation module; and obtaining an adjustment optimization parameter according to the optimization target, and modifying and rendering the landscape lighting design drawing. The technical problem that the optimization process is low in efficiency due to the fact that illumination design lacks spatial stereoscopic impression and sense of reality and cannot accurately reflect the actual effect in the prior art can be solved, the urban three-dimensional model is constructed and combined with the landscape illumination design drawing, illumination simulation rendering and optimization are conducted through the VR technology, and the optimization efficiency is improved. Therefore, optimization and accurate control of urban landscape lighting design are realized.

Description

Technical Field

[0001] The present application relates to the field of urban lighting design technology, and in particular to a method and system for optimizing urban landscape lighting design based on VR technology. Background Art

[0002] Urban landscape lighting design refers to improving the visual effects, functionality and safety of urban public spaces at night through reasonable layout and selection of lighting equipment, thereby providing citizens with a more comfortable and safe night environment. The places involved in urban landscape lighting design include public areas such as streets, squares, parks, bridges, and building facades. The main goal of the design is to provide sufficient lighting to ensure the safety of people's activities, while considering energy consumption and environmental impact. The existing urban landscape lighting design optimization method uses an intelligent control system to dynamically adjust the brightness and switch status of the lighting according to actual needs. Although certain results have been achieved in energy saving, light pollution control, and aesthetic effects, the lack of spatial three-dimensionality and realism makes it difficult to accurately present the actual performance of lighting in a complex urban environment, such as the distribution of lighting in different buildings, terrains, streets, etc., light and shadow effects, shadow changes, etc., resulting in an inefficient design optimization process and even failure to achieve the ideal design effect.

[0003] In summary, the prior art has a technical problem that the lighting design lacks spatial stereoscopic sense and sense of reality and cannot accurately reflect the actual effect, resulting in low efficiency of the optimization process. Summary of the invention

[0004] The purpose of this application is to provide a method and system for optimizing urban landscape lighting design based on VR technology, so as to solve the technical problem in the prior art that the lighting design lacks spatial stereoscopic sense and sense of reality, cannot accurately reflect the actual effect, and leads to low efficiency of the optimization process.

[0005] In order to achieve the above objectives, the present application provides a method and system for optimizing urban landscape lighting design based on VR technology.

[0006] In a first aspect, the present application provides an urban landscape lighting design optimization method based on VR technology, which is implemented by an urban landscape lighting design optimization system based on VR technology, wherein the urban landscape lighting design optimization method based on VR technology includes: constructing a three-dimensional urban model, importing the three-dimensional urban model into a VR tool platform, and obtaining an urban VR space; obtaining landscape lighting design drawings, positioning and aligning the landscape lighting design drawings with the three-dimensional urban model, and fitting the landscape lighting design drawings to the three-dimensional urban model based on the positioning alignment relationship; in the urban VR space, performing lighting simulation rendering according to the design parameters in the landscape lighting design drawings; connecting the urban VR space, performing landscape lighting design evaluation through an evaluation module, and locating optimization targets; obtaining adjustment optimization parameters according to the optimization targets, and modifying and re-rendering the landscape lighting design drawings through the adjustment optimization parameters.

[0007] Optionally, image information of the target landscape area is collected; architectural features, terrain features, and ambient light features are identified and extracted from the image information; based on the architectural features, terrain features, and ambient light features, the landscape design scope and targets are analyzed for their geometric shape, color, light, and occlusion influences to obtain key features and invisible features, wherein the key features are features that have an influence on the landscape design, and the invisible features are structural support features that have no influence on the landscape design; global three-dimensional parameters are extracted from the key features, and block border three-dimensional parameters and block parameters are extracted from the invisible features; and the global three-dimensional parameters, block border three-dimensional parameters, and block parameters are spliced ​​according to positional relationships to construct the city three-dimensional model.

[0008] Optionally, a movable structure is identified, wherein the movable structure includes a removable structure and a deformable structure; the demolition difficulty and demolition cost are evaluated according to the removable structure, a demolition cost coefficient is set, and the removable schemes and demolition effects are simulated and fitted to construct demolition timing characteristics of each demolition scheme; deformation timing characteristics are extracted according to the deformable structure to construct deformation timing characteristics; a mobile identification is performed according to the position positioning area of ​​the movable structure, and the demolition timing characteristics and deformation timing characteristics are mapped into a three-dimensional model to construct a timing three-dimensional model; a dynamic window is constructed using the timing three-dimensional model as a dynamic embedded model, and a linkage relationship between the mobile identification and the dynamic window is established, and the dynamic window is used to display the structural state changes of the movable structure.

[0009] Optionally, according to the influence of the geometric shape, color, light, and occlusion, the three-dimensional model is gridded in multiple dimensions according to the influence, and shape grids, color grids, light grids, and occlusion grids are established respectively, and each grid element is the influence and dimensional feature of the corresponding area; the multi-dimensional grid is reduced in dimension based on the influence of the grid elements, and the grids with influence less than a threshold are removed, and the removed grids are subjected to feature aggregation according to the dimensional features to obtain low-dimensional grid parameters; the grid elements whose influence meets the threshold are subjected to full-dimensional feature extraction to obtain high-dimensional parameters; according to the three-dimensional positioning relationship, the high-dimensional parameters are integrated with the low-dimensional grid parameters to obtain the global three-dimensional parameters.

[0010] Optionally, a multidimensional evaluation port is obtained, wherein the multidimensional evaluation port has evaluation attributes, and the evaluation attributes include a lighting effect evaluation dimension and a participating user identity dimension; evaluation weights of each dimension are configured according to the evaluation attributes; the multidimensional evaluation port algorithm is set according to the evaluation attributes, and an evaluation sub-module is constructed; a mapping relationship between the evaluation weights of each dimension and the evaluation sub-module is established, and the evaluation module is constructed.

[0011] Optionally, the evaluation contribution of each dimension is calculated and determined through evaluation weights and evaluation results; the gap between the target evaluation value and the actual evaluation value is compared to determine the optimization range; an evaluation heat map is constructed based on the optimization range and evaluation contribution to identify the optimization target.

[0012] Optionally, based on the evaluation results, current design parameters are traced to obtain the optimization direction and optimization range of the optimization target; the optimization influencing factors are analyzed according to the optimization target; a relationship model between the optimization influencing factors and the optimization target is established, and according to the relationship model, a search is performed with the optimization direction and optimization range as constraints to obtain the adjusted optimization parameters.

[0013] In a second aspect, the present application further provides an urban landscape lighting design optimization system based on VR technology, which is used to execute the urban landscape lighting design optimization method based on VR technology as described in the first aspect, wherein the urban landscape lighting design optimization system based on VR technology includes: a three-dimensional model construction module, the three-dimensional model construction module is used to construct a city three-dimensional model, import the city three-dimensional model into a VR tool platform, and obtain a city VR space; a positioning alignment module, the positioning alignment module is used to obtain landscape lighting design drawings, position and align the landscape lighting design drawings with the city three-dimensional model, and fit the landscape lighting design drawings to the city three-dimensional model based on the positioning alignment relationship; a lighting simulation module, the lighting simulation module is used to perform lighting simulation rendering in the city VR space according to the design parameters in the landscape lighting design drawings; a lighting evaluation module, the lighting evaluation module is used to connect the city VR space, perform landscape lighting design evaluation through the evaluation module, and locate the optimization target; a parameter tuning module, the parameter tuning module is used to obtain adjustment optimization parameters according to the optimization target, and modify and re-render the landscape lighting design drawings through the adjustment optimization parameters.

[0014] One or more technical solutions provided in this application have at least the following technical effects or advantages: By constructing a three-dimensional model of the city, importing the three-dimensional model of the city into the VR tool platform, obtaining a city VR space; obtaining landscape lighting design drawings, positioning and aligning the landscape lighting design drawings with the three-dimensional model of the city, and fitting the landscape lighting design drawings to the three-dimensional model of the city based on the positioning and alignment relationship; in the city VR space, lighting simulation rendering is performed according to the design parameters in the landscape lighting design drawings; connecting the city VR space, evaluating the landscape lighting design through the evaluation module, and locating the optimization target; obtaining adjustment optimization parameters according to the optimization target, and modifying and re-rendering the landscape lighting design drawings through the adjustment optimization parameters. In other words, by constructing a three-dimensional model and importing it into the VR tool platform, forming a city VR space, positioning and aligning the landscape lighting design drawings with the three-dimensional model of the city, performing lighting simulation according to the parameters in the design drawings, evaluating the effect of the lighting design, and adjusting the lighting design parameters accordingly, dynamically adjusting according to actual needs, and improving the overall effect of the lighting design, thereby achieving optimization and precise control of the urban landscape lighting design.

[0015] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented according to the contents of the specification, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are specifically cited below. It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easy to understand through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0017] Figure 1 This is a flow chart of the urban landscape lighting design optimization method based on VR technology in this application; Figure 2 This is a structural schematic diagram of the urban landscape lighting design optimization system based on VR technology in this application.

[0018] Explanation of the reference numerals: three-dimensional model building module 11 , positioning and alignment module 12 , lighting simulation module 13 , lighting evaluation module 14 , parameter tuning module 15 . DETAILED DESCRIPTION

[0019] This application solves the technical problem in the prior art that the lighting design lacks spatial stereoscopic sense and sense of reality, cannot accurately reflect the actual effect, and leads to low efficiency of the optimization process by providing a method and system for optimizing urban landscape lighting design based on VR technology. By constructing a three-dimensional model and importing it into a VR tool platform to form an urban VR space, the landscape lighting design drawings are aligned with the urban three-dimensional model, and lighting simulation is performed according to the parameters in the design drawings to evaluate the effect of the lighting design, and the lighting design parameters are adjusted accordingly. Dynamic adjustments are made according to actual needs to improve the overall effect of the lighting design, thereby achieving optimization and precise control of the urban landscape lighting design.

[0020] Below, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments of the present application. It should be understood that the present application is not limited to the example embodiments described herein. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application. It should also be noted that, for the convenience of description, only the parts related to the present application are shown in the accompanying drawings, rather than all of them.

[0021] For example, please refer to the attached Figure 1 The present application provides a method for optimizing urban landscape lighting design based on VR technology, wherein the method for optimizing urban landscape lighting design based on VR technology is applied to an urban landscape lighting design optimization system based on VR technology, and the method for optimizing urban landscape lighting design based on VR technology specifically includes the following steps: S100: construct a three-dimensional city model, and import the three-dimensional city model into a VR tool platform to obtain a city VR space.

[0022] Specifically, the image information of the target landscape area is collected, processed, and the architectural features, terrain features, and ambient light features are extracted. The architectural features, terrain features, and ambient light features are used to analyze the impact of geometric shapes, colors, light, and occlusion, and identify key features and invisible features. For key features, global three-dimensional parameters are extracted, and invisible features are simplified and block-processed. In the three-dimensional modeling software, the various landscape elements are spliced ​​into a complete three-dimensional model based on the extracted parameters and positional relationships. In this process, each urban element (such as buildings, roads, trees, landscapes, etc.) will be converted into a three-dimensional geometric model and modeled in combination with actual physical properties (such as height, material, color, etc.).

[0023] The 3D model of a city is a 3D digital representation of the physical space of a city, including multiple components such as buildings, roads, bridges, parks, and blocks. It has detailed data such as spatial geometry, size, and material properties, and reflects the real layout and environment of the target landscape area. The VR tool platform is a software platform for building, displaying, and interacting with virtual reality content, and supports interaction with the virtual environment through VR devices (such as head-mounted displays, handles, mobile controllers, etc.).

[0024] Based on the city 3D model, select a VR platform that supports 3D model display and interaction, and import the city 3D model into the VR tool platform. In the VR platform, set the scene's lighting, materials, camera perspective, etc. to ensure the authenticity and visual effects of the virtual city environment. The VR platform will generate an interactive virtual city space, and users can navigate and interact in the virtual city through VR devices. Set user experience elements in the virtual reality environment, such as environmental sound effects (city noise, bird calls, wind sounds, etc.), physical interactions (object collisions, dragging, etc.), and weather changes (such as simulated rain, snow, etc.), which can enhance the immersion of the city VR space. By building and importing the city 3D model into the VR tool platform, the resulting city VR space can provide an immersive urban environment experience. Users can freely explore in the virtual environment, view the buildings, roads and public spaces in the city, and even conduct detailed architectural analysis, urban planning and design optimization.

[0025] S200: Acquire landscape lighting design drawings, perform positioning and alignment between the landscape lighting design drawings and the three-dimensional city model, and fit the landscape lighting design drawings to the three-dimensional city model based on a positioning and alignment relationship.

[0026] Specifically, obtain landscape lighting design drawings, which are drawings that describe the location, type, brightness, color and other design details of lighting equipment in detail, and contain detailed information on lighting equipment, such as the location, power, light source type, lighting effect and layout plan of each lamp. Landscape lighting design drawings are design blueprints for landscape lighting systems, usually including parameters such as the type, quantity, layout location, lighting angle, light intensity, color temperature, etc. of lamps, which are used to plan the nighttime lighting effects of cities or specific areas, and ensure that the design of the lighting system can meet the requirements of functionality, aesthetics and energy saving. Align the coordinate system of the landscape lighting design drawings with the coordinate system in the three-dimensional model of the city, so that each lighting design element on the drawing matches the corresponding part of the actual urban environment, and ensure that the lighting plan can be correctly reflected in the three-dimensional model of the city.

[0027] The 3D model of the city usually has a standard coordinate system (such as geographic coordinate system, world coordinate system), while the landscape lighting design drawings use different coordinate systems (such as local coordinate system). The coordinate systems of the two are connected through a conversion algorithm so that the lighting equipment in the drawing is consistent with the actual position in the 3D model. After the coordinate system is connected, the spatial position must be aligned so that the position of the lamps on the drawing corresponds to the corresponding position in the city model. During the positioning and alignment process, some errors may occur, especially when the resolution or accuracy of the drawing data and the 3D model data is greatly different. Use precision adjustment methods (such as least squares method, interpolation method, etc.) to correct the coordinate error to ensure that the lighting equipment is accurately mapped to the 3D model.

[0028] According to the positioning and alignment relationship, each lighting device (such as lamps, light poles, etc.) in the drawings is mapped to the 3D model according to its position, angle and design parameters. For example, the specific position (such as coordinates), lighting range (such as irradiation radius, beam angle), and light source type (such as LED, sodium lamp, etc.) of each lamp will be mapped to the corresponding position and attributes of the city's 3D model. By positioning, aligning and fitting the landscape lighting design drawings with the city's 3D model, design errors are reduced, construction efficiency is improved, and an accurate basis is provided for subsequent lighting effect simulation and evaluation.

[0029] S300: In the urban VR space, lighting simulation rendering is performed according to the design parameters in the landscape lighting design drawing.

[0030] Specifically, according to the position and type of lamps in the design drawings, light sources are placed at corresponding locations in the 3D model. In addition to the position, other parameters of the lighting design (such as light intensity, color temperature, lighting effect, etc.) also need to be fitted. By connecting the lighting parameters in the design drawings with the lighting system in the 3D model, the effect of each light source is ensured to be accurately presented in the virtual environment. After adding lighting equipment to the 3D model, use the lighting simulation tool to render the lighting effect of the lamps to evaluate whether the light source has achieved the expected design effect.

[0031] The lighting rendering engine is used to calculate the propagation of light, taking into account the effects of light reflection, refraction, shadow, halo, etc., to simulate how the light source illuminates the surrounding environment. After the rendering engine calculates all the details of the lighting, it will generate a rendered image or animation to show the actual effect of the lighting design in the urban space, including brightness distribution, lighting uniformity, shadow effects, etc. The lighting simulation rendering settings include light source settings, environment settings, material and texture settings. The light source settings include adjusting the intensity, color, attenuation and other parameters of the light source to match the characteristics of the actual lighting equipment. The environment settings simulate natural and artificial environmental effects such as atmospheric scattering and glow by setting the ambient light, while adding physical effects such as reflection and refraction to enhance the realism of the rendering. Materials and textures include adjusting the material properties of buildings and landscape elements to ensure that they respond correctly to lighting. By performing lighting simulation rendering according to the design parameters in the landscape lighting design drawings, the actual effect of the lighting design can be accurately presented in the virtual urban space, which can not only provide intuitive visual feedback to designers, but also discover potential problems in the design stage and make optimization adjustments.

[0032] S400: Connecting to the urban VR space, evaluating the landscape lighting design through an evaluation module, and locating optimization targets.

[0033] Specifically, VR devices (such as head-mounted displays, handles, etc.) are used to interact with the virtual city to view the actual effects of landscape lighting. Through the VR space, designers can directly adjust the lighting brightness, color temperature, irradiation angle and other parameters of different areas in the virtual environment. The existing design is analyzed and evaluated through the evaluation module, and the evaluation results of each dimension are calculated based on the multi-dimensional evaluation port to identify the advantages and disadvantages in the lighting design. According to the importance of each evaluation attribute, the corresponding weight is assigned to each dimension. According to the evaluation weight and evaluation results, the evaluation contribution of each dimension is calculated. Based on the preset target evaluation value and the actual evaluation value, the evaluation module outputs the score of each dimension, that is, the gap. Based on the evaluation contribution and the evaluation gap, the dimensions with high evaluation contribution and large gap are identified as the priority optimization targets. Through the multi-dimensional evaluation module, the problem area is accurately located, and the design problems with greater impact are solved first, so that the optimization plan is more targeted and effective.

[0034] S500: obtaining adjustment optimization parameters according to the optimization target, and modifying and re-rendering the landscape lighting design drawing according to the adjustment optimization parameters.

[0035] Specifically, the optimization target is located through the evaluation module and optimization algorithm, and the key factors affecting the optimization target are identified according to the optimization direction and optimization range. A relationship model between the optimization influencing factors and the optimization target is constructed, and the optimization algorithm (such as particle swarm optimization, genetic algorithm, etc.) is used to search for the optimal adjustment optimization parameters. After the optimization target is located, the adjustment optimization parameters are obtained through model search. In the landscape lighting design drawings, the areas related to the optimization target are identified, and the adjustment optimization parameters are applied to the design of the corresponding areas according to the optimization target. The landscape lighting design drawings are modified according to the adjustment optimization parameters, including light source position adjustment, light source height and color temperature adjustment, and lamp type adjustment.

[0036] Re-render the modified landscape lighting design drawings, and simulate and visualize the modified design effects through rendering. Input the modified design parameters (such as lamp position, brightness, etc.) into the 3D modeling and rendering tools to generate new 3D models and renderings. During the rendering process, the lighting simulation engine will perform lighting calculations based on the new design parameters, simulate the propagation, reflection, refraction and other effects of light in the urban space, and generate new lighting renderings. Analyze the rendered renderings to check whether the optimization goals have been achieved, including uniformity, brightness, and light source arrangement.

[0037] If after the first modification and rendering, the designer finds that the lighting effect is still not ideal, or fails to fully achieve the optimization goal, the designer can continue to adjust the optimization parameters, perform the second and third rounds of optimization and re-rendering until a satisfactory effect is achieved. The evaluation module evaluates the results of each rendering, adjusts the optimization direction and amplitude based on the feedback, and continuously optimizes the design. By re-rendering the modified design drawings, the designer can intuitively see the optimized effect, quickly verify the optimization effect, and avoid problems in actual construction.

[0038] Furthermore, the present application S100 includes: Collect image information of the target landscape area; identify and extract architectural features, terrain features, and ambient light features from the image information; analyze the influence of geometry, color, light, and occlusion on the landscape design scope and target based on the architectural features, terrain features, and ambient light features to obtain key features and invisible features, wherein the key features are features that have an impact on the landscape design, and the invisible features are structural support features that have no impact on the landscape design; extract global three-dimensional parameters from the key features, and extract block border three-dimensional parameters and block parameters from the invisible features; splice the global three-dimensional parameters, block border three-dimensional parameters, and block parameters according to positional relationships to construct the city three-dimensional model.

[0039] Specifically, image data of the target landscape area is obtained through photography, satellite images, drone aerial photography or other means, including ground plan, building appearance, roads, green space and other environmental elements. For example, a high-definition camera or drone is used to take all-round photos of the target landscape area, collect enough image data, and obtain image information of the overall layout, architectural style, building facades, streets, trees and other relevant landscape elements.

[0040] The image information is used to identify and extract architectural features, terrain features, and ambient light features, where architectural features include the geometric shape, structural characteristics, and surface material of the building's exterior, such as the building's height, shape, window distribution, and exterior wall material; terrain features refer to the natural or artificial terrain within the landscape area, such as slope, uneven terrain, height difference, roads, and surface material (such as pavement and vegetation); ambient light features refer to the characteristics of the lighting environment within the landscape area, such as sunlight intensity, reflected light, shadow areas, and the distribution of surrounding light sources.

[0041] Based on the architectural features, terrain features, and ambient light features, the scope and objectives of landscape design are analyzed in a variety of ways, including geometry, color, light, and occlusion impact analysis. Geometry analysis refers to the shape, size, and position of elements such as buildings and terrain; color analysis refers to the color of buildings, terrain surfaces, or landscape elements, which may affect the reflection and visual effects of light; light analysis refers to the impact of ambient light, natural light, and artificial light sources on lighting effects; occlusion impact analysis refers to the impact of different buildings or terrain elements on light propagation, such as which areas are blocked and which areas have the most light. Based on a variety of analyses, key features and invisible features are identified.

[0042] Key features refer to features that have a significant impact on landscape lighting design, such as the height, orientation, facade material, terrain undulations, etc. of the building. These features have a direct impact on the distribution of light, lighting effects, and visual perception; invisible features refer to features that have no significant impact on the lighting effects, such as pebbles or decorative vegetation on the ground. These elements will not significantly change the light propagation or lighting effects.

[0043] The global three-dimensional parameter extraction is performed on the key features. The global three-dimensional parameter extraction is mainly aimed at the features that have a significant impact on the landscape design and lighting layout, including the geometric form, reflection characteristics, terrain characteristics, etc. of the building. According to the different characteristics of geometry, color, light and occlusion, the model is divided into multiple independent grid dimensions, and each dimension is stored and processed separately. The three-dimensional model is gridded according to the spatial partition (such as voxels, block areas, etc.), and each grid unit records the impact data of the corresponding area. In the grid of each dimension, unimportant details are removed, and the regional features that have the greatest impact on light and shadow and visual effects are retained. For the removed grids, they are aggregated according to their dimensional features (such as color, shape, etc.) to simplify the model. For the grid elements whose influence meets the threshold, full-dimensional features are extracted, including detailed information such as shape, color, light and occlusion. According to the position of each grid element in three-dimensional space, the high-dimensional parameters are integrated with the low-dimensional grid parameters, and finally a global three-dimensional parameter model that contains important feature details (high-dimensional parameters) and is appropriately simplified is obtained.

[0044] Extract the three-dimensional parameters of the block border and the block parameters of the invisible features, simplify the invisible features into a border model, retain only the volume, position and height information, and use a simplified algorithm to compress unnecessary three-dimensional data. Reduce unnecessary details and improve computing efficiency. Invisible features refer to structural support elements that have little impact on landscape design, lighting and environment, usually including the rear wall of the building, underground structures, some small landscapes or minor roads, etc., which do not require high-precision modeling, but still require a certain simplified model to optimize computing efficiency.

[0045] Block border extraction refers to extracting rough borders of buildings, terrain and other areas through block processing, simplifying areas that do not affect the main landscape effect. For unimportant building parts (such as the back, roof, basement), use simple rectangular or cubic bounding boxes to show their space occupancy. For architectural details that do not affect the distribution of light or landscape effects, use a simplified model with lower precision, such as a low-polygon mesh, to retain spatial relationships and main size information. Block parameter extraction includes the spatial occupancy, geometric proportions, and directionality of the building to simplify modeling. Analyze the scope of influence of the building on the surrounding environment, such as its influence on light, field of view, etc. Simplify the area with little influence into a rectangular or square area; for the building part that is not affected by light, only its outline information is retained, while the complex details and internal distribution are removed; the urban area is modeled according to different functional divisions, such as commercial areas, residential areas, industrial areas, etc., and different areas are modeled with models of different precision.

[0046] According to the global 3D parameters, the 3D parameters of the block border and the block parameters, the various parts of the model are spliced ​​according to the positional relationship, and the connection points between the building and the terrain are corrected to ensure seamless connection and complete the construction of the city 3D model. By classifying and retaining key features and simplifying invisible features, the model processing efficiency is greatly improved. Combined with global parameters and block borders, a 3D model that takes into account both precision and efficiency is constructed.

[0047] Furthermore, the present application also includes the following steps: Identify movable structures, which include removable structures and deformable structures; evaluate the difficulty and cost of demolition according to the removable structures, set a demolition cost coefficient, simulate and fit the removable schemes and demolition effects, and construct demolition timing characteristics of each demolition scheme; extract deformation timing characteristics according to the deformable structure and construct deformation timing characteristics; perform mobile identification according to the position positioning area of ​​the movable structure, and map the demolition timing characteristics and deformation timing characteristics into a three-dimensional model to construct a timing three-dimensional model; construct a dynamic window using the timing three-dimensional model as a dynamic embedded model, establish a linkage relationship between the mobile identification and the dynamic window, and the dynamic window is used to display the structural state changes of the movable structure.

[0048] Specifically, based on urban planning documents, obtain a list of structures that are to be rebuilt or demolished in the target area plan. Classify the structures in the target area and identify movable structures, including removable structures and deformable structures. Removable structures are buildings and facilities with clear demolition plans or that may be demolished, such as temporary buildings, old buildings, etc.; deformable structures are facilities with dynamic adjustment or deformation characteristics, which can be deformed according to external forces or needs, such as movable stages, liftable lamp posts, etc. Calculate the difficulty of demolition based on the characteristics of the removable structure (such as height, volume, material), and evaluate the difficulties that may be encountered during the demolition process, including considering the material, connection method, scale, demolition method, etc. of the structure. Evaluate the economic cost of demolition, which usually includes labor costs, equipment costs, waste disposal costs, etc.

[0049] The demolition cost coefficient is set by comprehensively considering factors such as demolition time, resource requirements, and construction risks. Structural mechanics simulation (such as finite element analysis) is used to simulate the demolition process, fit the cost and effect curves of different demolition schemes, extract the demolition timing characteristics of each scheme, including demolition steps, key nodes, and time consumption, and construct a timing feature that includes multiple demolition schemes. The demolition timing feature refers to the time sequence and dependency of each step in the demolition process, such as which parts to demolish first and the time to restore after demolition.

[0050] For deformable structures, the deformation time series characteristics are extracted according to the actual changes of the structure. The deformation time series characteristics reflect the dynamic characteristics of the structure at different time points, such as shape, displacement, and deformation degree. Use displacement sensors, strain gauges, or laser scanning devices to obtain the deformation data of the structure in real time. The collected data is processed to extract the time series characteristics of the deformation, such as the change in shape, displacement, strain, etc. at each time node. Deformation simulation is performed according to the material of the structure (such as retractable steel) and design parameters (such as deformation amplitude and deformation rate). The dynamic change law of deformation is extracted, including deformation time series characteristics such as deformation start time, key state, and completion time.

[0051] Mark the location of the movable structure in the 3D model according to its geographic coordinate information. Embed dynamic tags in the 3D model to establish a mapping relationship between the movable structure and the corresponding position. Map the demolition timing characteristics and deformation timing characteristics to the 3D model to build a timing 3D model to reflect the dynamic state of the structure over time. Map the demolition timing characteristics (such as demolition order, demolition duration, etc.) to the 3D model to form a dynamically changing demolition process. Map the deformation timing characteristics of the deformable structure (such as the displacement and deformation degree of the structure) to the 3D model to show the morphology of the structure over time. Based on the timing characteristics, create a 3D model that changes over time to show the state of the removable and deformable structures at different time points. Use a hierarchical modeling method to separate static areas from dynamic features for independent updating and optimization.

[0052] A dynamic window is embedded in the time-series 3D model to display the state changes of movable structures (such as demolition progress and deformation process) in real time. A linkage relationship is established between the dynamic window and the mobile identifier in the time-series 3D model, and the window content changes are driven by the time axis. When the user selects a certain area or structure, the dynamic window will display the real-time deformation, demolition and other state changes of the area or structure. The dynamic window and the time-series 3D model interact through a linkage relationship. When a structure in the time-series 3D model changes, the content in the dynamic window will be updated in real time to display the deformation or demolition state of the structure, ensuring that the state changes of the structure are displayed synchronously with the user interface, which is convenient for users to observe, analyze and make decisions. Combined with the user interaction function, it allows real-time adjustment of timing parameters to view dynamic changes under different schemes. By identifying movable structures, extracting demolition and deformation features, time-series 3D modeling and dynamic window display, the visualization and simulation capabilities of the demolition and deformation processes are effectively improved. Designers can view and adjust demolition plans and state changes of deformable structures in real time, optimize the demolition plan and structural deformation design of the building, which not only improves the efficiency of design and construction, but also reduces risks and costs. It can also conduct real-time dynamic monitoring and optimization to ensure the safe and efficient execution of the project.

[0053] Furthermore, the present application also includes the following steps: According to the influence of the geometric shape, color, light, and occlusion, the three-dimensional model is gridded in multiple dimensions according to the influence, and shape grids, color grids, light grids, and occlusion grids are established respectively, and each grid element is the influence and dimensional characteristics of the corresponding area; based on the influence of the grid elements, the multi-dimensional grid is reduced in dimension, and the grids whose influence is less than a threshold are removed, and the removed grids are subjected to feature aggregation according to the dimensional characteristics to obtain low-dimensional grid parameters; the grid elements whose influence meets the threshold are subjected to full-dimensional feature extraction to obtain high-dimensional parameters; according to the three-dimensional positioning relationship, the high-dimensional parameters are integrated with the low-dimensional grid parameters to obtain the global three-dimensional parameters.

[0054] Specifically, according to the influence obtained after the impact analysis of geometric shape, color, light, and occlusion, the three-dimensional model is gridded in multiple dimensions to establish shape grid, color grid, light grid, and occlusion grid respectively. The shape grid records geometric shape features (such as curvature, normal vector, boundary); the color grid records color information (such as RGB value, HSV spatial distribution); the light grid records light characteristics (such as light intensity, direction, reflection path); the occlusion grid records occlusion characteristics (such as occlusion index, occlusion direction). Each grid element contains the influence and dimensional characteristics of the corresponding area. The influence refers to the influence of each grid element on different dimensions, and the dimensional characteristics refer to the parameters related to the dimension.

[0055] According to the geometric shape of the building and the terrain characteristics, each building, plot and other spatial elements are divided into multiple small grids, and each grid unit contains the geometric shape characteristics of the area (such as height, width, depth, etc.). According to the surface color characteristics of each area (such as wall color, ground color, etc.), the model is gridded, and each grid unit represents the hue and reflective properties of the area. According to the illumination of different light sources (such as sunlight, street lights, etc.), the model is divided into multiple light-affecting grids, and each grid unit contains information such as the intensity, direction, and distribution of the light source. According to the blocking of light by buildings or other obstacles, the area is gridded, and each grid unit represents whether the light is blocked by certain buildings or structures, affecting the distribution of light.

[0056] Perform dimensionality reduction on mesh elements to reduce model complexity while retaining key features. Set an influence threshold and remove mesh elements below the threshold. Set a threshold for the different dimensional features (geometry, color, light, and occlusion) of each mesh unit according to their impact on the lighting effect. Remove meshes with an influence less than the threshold, aggregate the dimensional features of the removed meshes to reduce storage and retain statistical information of regional features (such as mean and variance). For mesh elements whose influence meets the threshold, that is, mesh elements greater than or equal to the threshold, retain all their dimensional features and perform full dimensional feature extraction.

[0057] The 3D model is segmented by voxels or evenly meshed. The geometric parameters (such as curvature and normal vector change rate) are calculated in each mesh unit. The curvature features are simplified, and only the local geometric features with significant changes are retained. A shape network is constructed to reflect the local features of the object's geometry, such as surface curvature, sharpness, and complexity. The surface texture of the object is projected into the mesh, and each mesh unit stores the average color value or color distribution characteristics. Clustering algorithms (such as K-means) are used to merge similar colors and reduce the color dimension. Grayscale approximation is used for areas with low visual impact (such as back faces and hidden areas). The global illumination simulation tool is used to generate light propagation paths and intensity distribution in 3D space. The light intensity data is graded and only areas with significant light and shadow changes are stored. The ray casting algorithm is used to calculate the occlusion index (such as the proportion of light directly blocked) of each mesh unit. Occlusion levels (high, medium, and low) are used instead of specific values ​​to simplify storage. For areas far away from the main light source, occlusion information can be ignored.

[0058] Integrate high-dimensional parameters with low-dimensional parameters according to the three-dimensional positioning relationship of each grid unit to form a complete three-dimensional urban model. Based on the spatial coordinates and proximity relationship of the grid, match the low-dimensional grid with the high-dimensional grid according to the position. For the same grid area, high-dimensional parameters are preferentially used to cover low-dimensional parameters to form complete feature data. By configuring the urban landscape area in a multi-dimensional grid and performing dimensionality reduction based on the influence of grid elements, the complexity of the model can be significantly reduced while retaining the key features that have a greater impact on the lighting effect.

[0059] Further, the present application S400 includes: Acquire a multidimensional evaluation port, wherein the multidimensional evaluation port has evaluation attributes, and the evaluation attributes include a lighting effect evaluation dimension and a participating user identity dimension; configure evaluation weights of each dimension according to the evaluation attributes; set the multidimensional evaluation port algorithm according to the evaluation attributes, and construct an evaluation submodule; establish a mapping relationship between the evaluation weights of each dimension and the evaluation submodule, and construct the evaluation module.

[0060] Specifically, obtaining a multi-dimensional evaluation port allows users to evaluate lighting design from multiple perspectives, and comprehensively analyze and give the final evaluation results based on different evaluation attributes. The multi-dimensional evaluation port refers to an interface or module in the evaluation system that comprehensively evaluates landscape lighting through attributes of different dimensions. The multi-dimensional evaluation port not only focuses on the effect of the lighting design itself, but also includes feedback from different user groups or usage scenarios. The evaluation attribute refers to the specific dimension or standard used when evaluating landscape lighting design. The lighting effect evaluation dimension mainly evaluates the effect of lighting design, including illumination uniformity, brightness distribution, color temperature, light pollution, energy efficiency and other aspects. The participating user identity dimension adjusts the evaluation focus according to the identity or needs of different users. For example, designers, ordinary citizens, administrative managers, etc. may have different needs and evaluation criteria for lighting design.

[0061] According to different evaluation dimensions, weights are assigned to each dimension to indicate the importance of the dimension in the overall evaluation. Assume that in a specific project, designers may believe that lighting effects (such as light uniformity and brightness distribution) account for a higher proportion, while energy saving may be relatively low. Based on these judgments, a higher weight is assigned to the light uniformity dimension, while a lower weight is assigned to the energy efficiency dimension. Users of different identities may have different priority requirements for lighting design. For example, citizens may pay more attention to comfort and aesthetics, while designers may pay more attention to the accuracy and functionality of lighting effects. According to these needs, different weights are set for dimensions of different identities.

[0062] According to the evaluation attributes, it refers to the multi-dimensional evaluation port algorithm, which constructs the evaluation sub-module responsible for calculating the evaluation results of specific dimensions. An independent evaluation sub-module is set for each dimension to evaluate the effect of that dimension. The evaluation weights of each dimension are associated with the corresponding evaluation sub-modules through mapping relationships, and the output value of each evaluation sub-module will affect the final result according to its weight. Each sub-module (such as illumination uniformity, brightness distribution) will have a calculation result, which will eventually be weighted and summarized according to the configured weights. The evaluation module will combine the weighted results of each dimension and give the final lighting design evaluation. Through the configuration and implementation of the multi-dimensional evaluation port, designers can comprehensively analyze the advantages and disadvantages of the lighting design according to different evaluation attributes and dimensions, and finally achieve an optimization plan that better meets the needs of multiple parties.

[0063] Furthermore, the present application also includes the following steps: Calculate the evaluation contribution of each dimension and determine it through evaluation weights and evaluation results; compare the gap between the target evaluation value and the actual evaluation value to determine the optimization range; construct an evaluation heat map based on the optimization range and evaluation contribution to identify the optimization target.

[0064] Specifically, the evaluation contribution of each dimension is calculated to measure the degree of influence of each evaluation dimension on the comprehensive evaluation result. The evaluation contribution of each dimension is calculated based on the product of the evaluation weight of each dimension and the evaluation result. The contribution of all dimensions is normalized to the interval [0,1] for intuitive comparison. The gap is calculated based on the target evaluation value and the actual evaluation value of each dimension. After calculating the gap, the gap needs to be normalized to the interval [0,1] to obtain the optimization range. Multiply the normalized evaluation contribution and the optimization range to obtain the thermal value of each dimension. The higher the thermal value, the greater the impact of the dimension on the overall evaluation and the more urgent the optimization need.

[0065] Each cell or area of ​​the evaluation heat map represents an evaluation dimension or optimization target, and its color depth or heat value represents the degree to which the area needs to be optimized. The darker the color, the higher the urgency of optimizing the area. The heat value calculated above is mapped to the color value of the heat map, usually using a gradient from green (low optimization demand) to red (high optimization demand).

[0066] According to the thermal value of each dimension, an evaluation heat map is constructed to intuitively display the distribution of optimization needs through the heat map. Find the largest dimension in the evaluation heat map and prioritize the optimization of targets with high thermal values. Sort by thermal value and prioritize dimensions with high thermal values ​​as optimization targets. By calculating the evaluation contribution and optimization range and constructing an evaluation heat map, you can intuitively see which dimensions have the greatest impact on the overall evaluation results and which dimensions need the most improvement, which helps prioritize the issues that have the greatest impact on the design, thereby improving the efficiency and effectiveness of the design.

[0067] Furthermore, the present application S500 includes: Based on the evaluation results, the current design parameters are traced to obtain the optimization direction and optimization range of the optimization target; the optimization influencing factors are analyzed according to the optimization target; a relationship model between the optimization influencing factors and the optimization target is established, and according to the relationship model, the optimization direction and optimization range are used as constraints to search and obtain the adjusted optimization parameters.

[0068] Specifically, after completing the preliminary lighting design and evaluating it through the evaluation module, based on the evaluation results, trace the impact of the current design parameters on the optimization target, and calculate the optimization direction and optimization range. According to the scores of each dimension provided by the evaluation module (such as lighting uniformity, brightness distribution, energy efficiency, etc.), analyze which design parameters lead to lower scores. By analyzing the parameters in the design one by one, trace back which parameters most directly affect the current evaluation results.

[0069] The optimization goal is to determine the target areas, dimensions or parameters that need to be optimized or adjusted based on the results of the evaluation module during the evaluation and design process. These are usually those design parts with low scores or large gaps, such as lighting uniformity, energy efficiency, visual comfort, etc. The optimization direction refers to determining the adjustment trend of the influencing factors, that is, the improvement direction or adjustment path: if the current optimization target value is lower than the target value, increase the relevant parameters (such as brightness); if the current optimization target value is higher than the target value, reduce the relevant parameters (such as light source spacing). Calculate the adjustment amount based on the gap. The optimization range refers to the degree of gap between the optimization target and the current design result, which usually reflects the scope or degree of change required.

[0070] According to the optimization target, the optimization influencing factor is obtained. The optimization influencing factor is the design parameter or variable directly related to the optimization target. Analyze the dimension to which the optimization target belongs and the optimization influencing factor, and locate the weak link according to the results of the evaluation dimension. Use regression analysis to establish a relationship model to describe the relationship between the optimization influencing factor (such as light source position, light source type, etc.) and the optimization target (such as illumination uniformity, energy efficiency). When the optimization target and the influencing factor are linearly related, for example, assuming that illumination uniformity is used as the optimization target, and the position and beam angle of the lamp are used as influencing factors, use multiple regression analysis to establish a relationship model, illumination uniformity = a + b × light source position + c × irradiation angle + λ. Among them, a is a constant term, b and c are regression coefficients, which represent the influence of each design parameter on illumination uniformity, and λ is an error term.

[0071] Set the parameter range with the optimization direction and amplitude as constraints. Perform parameter search through specific optimization algorithms (such as genetic algorithm, particle swarm optimization, simulated annealing, etc.) to find the optimal adjustment parameters. Find the optimal solution to the optimization target by simulating the movement of particles in the search space. For example, the particle swarm optimization algorithm searches according to the optimization direction and optimization amplitude, adjusts the light source position and illumination angle to minimize the gap between the illumination uniformity score and the target value. Through the search algorithm, a set of optimized design parameters are finally obtained. These parameters meet the requirements of the optimization direction and optimization amplitude and can achieve the optimal effect of the target. When the evaluation results meet the optimization target, the final parameters are output. According to the evaluation results, analyze and trace back the design parameters, accurately identify which design parameters affect the current evaluation results, avoid blind adjustments, determine the most important optimization areas through the analysis of the optimization target, and clarify the direction of adjustment (such as light source position, energy efficiency optimization, etc.).

[0072] In summary, the urban landscape lighting design optimization method based on VR technology provided in this application has the following technical effects: By constructing a three-dimensional model of the city, importing the three-dimensional model of the city into the VR tool platform, obtaining a city VR space; obtaining landscape lighting design drawings, positioning and aligning the landscape lighting design drawings with the three-dimensional model of the city, and fitting the landscape lighting design drawings to the three-dimensional model of the city based on the positioning and alignment relationship; in the city VR space, lighting simulation rendering is performed according to the design parameters in the landscape lighting design drawings; connecting the city VR space, evaluating the landscape lighting design through the evaluation module, and locating the optimization target; obtaining adjustment optimization parameters according to the optimization target, and modifying and re-rendering the landscape lighting design drawings through the adjustment optimization parameters. In other words, by constructing a three-dimensional model and importing it into the VR tool platform, forming a city VR space, positioning and aligning the landscape lighting design drawings with the three-dimensional model of the city, performing lighting simulation according to the parameters in the design drawings, evaluating the effect of the lighting design, and adjusting the lighting design parameters accordingly, dynamically adjusting according to actual needs, and improving the overall effect of the lighting design, thereby achieving optimization and precise control of the urban landscape lighting design.

[0073] Embodiment 2, based on the same inventive concept as the urban landscape lighting design optimization method based on VR technology in the aforementioned embodiment 1, this application also provides an urban landscape lighting design optimization system based on VR technology, please refer to the attached Figure 2 , the urban landscape lighting design optimization system based on VR technology includes: A three-dimensional model construction module 11, the three-dimensional model construction module 11 is used to construct a city three-dimensional model, import the city three-dimensional model into a VR tool platform, and obtain a city VR space; a positioning alignment module 12, the positioning alignment module 12 is used to obtain landscape lighting design drawings, position and align the landscape lighting design drawings with the city three-dimensional model, and fit the landscape lighting design drawings to the city three-dimensional model based on the positioning alignment relationship; a lighting simulation module 13, the lighting simulation module 13 is used to perform lighting simulation rendering in the city VR space according to the design parameters in the landscape lighting design drawings; a lighting evaluation module 14, the lighting evaluation module 14 is used to connect the city VR space, perform landscape lighting design evaluation through an evaluation module, and locate optimization targets; a parameter tuning module 15, the parameter tuning module 15 is used to obtain adjustment optimization parameters according to the optimization targets, and modify and re-render the landscape lighting design drawings through the adjustment optimization parameters.

[0074] Furthermore, the three-dimensional model building module 11 in the urban landscape lighting design optimization system based on VR technology is also used for: Collect image information of the target landscape area; identify and extract architectural features, terrain features, and ambient light features from the image information; analyze the influence of geometry, color, light, and occlusion on the landscape design scope and target based on the architectural features, terrain features, and ambient light features to obtain key features and invisible features, wherein the key features are features that have an impact on the landscape design, and the invisible features are structural support features that have no impact on the landscape design; extract global three-dimensional parameters from the key features, and extract block border three-dimensional parameters and block parameters from the invisible features; splice the global three-dimensional parameters, block border three-dimensional parameters, and block parameters according to positional relationships to construct the city three-dimensional model.

[0075] Furthermore, the three-dimensional model building module 11 in the urban landscape lighting design optimization system based on VR technology is also used for: Identify movable structures, which include removable structures and deformable structures; evaluate the difficulty and cost of demolition according to the removable structures, set a demolition cost coefficient, simulate and fit the removable schemes and demolition effects, and construct demolition timing characteristics of each demolition scheme; extract deformation timing characteristics according to the deformable structure and construct deformation timing characteristics; perform mobile identification according to the position positioning area of ​​the movable structure, and map the demolition timing characteristics and deformation timing characteristics into a three-dimensional model to construct a timing three-dimensional model; construct a dynamic window using the timing three-dimensional model as a dynamic embedded model, establish a linkage relationship between the mobile identification and the dynamic window, and the dynamic window is used to display the structural state changes of the movable structure.

[0076] Furthermore, the three-dimensional model building module 11 in the urban landscape lighting design optimization system based on VR technology is also used for: According to the influence of the geometric shape, color, light, and occlusion, the three-dimensional model is gridded in multiple dimensions according to the influence, and shape grids, color grids, light grids, and occlusion grids are established respectively, and each grid element is the influence and dimensional characteristics of the corresponding area; based on the influence of the grid elements, the multi-dimensional grid is reduced in dimension, and the grids whose influence is less than a threshold are removed, and the removed grids are subjected to feature aggregation according to the dimensional characteristics to obtain low-dimensional grid parameters; the grid elements whose influence meets the threshold are subjected to full-dimensional feature extraction to obtain high-dimensional parameters; according to the three-dimensional positioning relationship, the high-dimensional parameters are integrated with the low-dimensional grid parameters to obtain the global three-dimensional parameters.

[0077] Furthermore, the lighting evaluation module 14 in the urban landscape lighting design optimization system based on VR technology is also used for: Acquire a multidimensional evaluation port, wherein the multidimensional evaluation port has evaluation attributes, and the evaluation attributes include a lighting effect evaluation dimension and a participating user identity dimension; configure evaluation weights of each dimension according to the evaluation attributes; set the multidimensional evaluation port algorithm according to the evaluation attributes, and construct an evaluation submodule; establish a mapping relationship between the evaluation weights of each dimension and the evaluation submodule, and construct the evaluation module.

[0078] Furthermore, the lighting evaluation module 14 in the urban landscape lighting design optimization system based on VR technology is also used for: Calculate the evaluation contribution of each dimension and determine it through evaluation weights and evaluation results; compare the gap between the target evaluation value and the actual evaluation value to determine the optimization range; construct an evaluation heat map based on the optimization range and evaluation contribution to identify the optimization target.

[0079] Furthermore, the parameter tuning module 15 in the urban landscape lighting design optimization system based on VR technology is also used for: Based on the evaluation results, the current design parameters are traced to obtain the optimization direction and optimization range of the optimization target; the optimization influencing factors are analyzed according to the optimization target; a relationship model between the optimization influencing factors and the optimization target is established, and according to the relationship model, the optimization direction and optimization range are used as constraints to search and obtain the adjusted optimization parameters.

[0080] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. Figure 1The urban landscape lighting design optimization method based on VR technology and the specific examples in the first embodiment are also applicable to the urban landscape lighting design optimization system based on VR technology in this embodiment. Through the above detailed description of the urban landscape lighting design optimization method based on VR technology, those skilled in the art can clearly understand the urban landscape lighting design optimization system based on VR technology in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0081] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0082] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalent technology, the present application is also intended to include these modifications and variations.

Claims

1. The urban landscape lighting design optimization method based on VR technology is characterized by: include: Constructing a three-dimensional city model, and importing the three-dimensional city model into a VR tool platform to obtain a city VR space; Acquire landscape lighting design drawings, perform positioning and alignment between the landscape lighting design drawings and the three-dimensional city model, and fit the landscape lighting design drawings to the three-dimensional city model based on the positioning and alignment relationship; In the urban VR space, lighting simulation rendering is performed according to the design parameters in the landscape lighting design drawings; Connecting the urban VR space, evaluating the landscape lighting design through the evaluation module, and locating the optimization target; The optimization parameters are adjusted according to the optimization target, and the landscape lighting design drawings are modified and then rendered according to the optimization parameters.

2. The urban landscape lighting design optimization method based on VR technology according to claim 1 is characterized in that: The construction of the three-dimensional city model comprises: Collect image information of the target landscape area; Recognize and extract architectural features, terrain features, and ambient light features from the image information; According to the architectural features, terrain features, and ambient light features, the geometry, color, light, and occlusion impact analysis is performed on the scope and objectives of the landscape design to obtain key features and invisible features. The key features are features that have an impact on the landscape design, and the invisible features are structural support features that have no impact on the landscape design. Extracting global three-dimensional parameters of the key features, and extracting block border three-dimensional parameters and block parameters of the invisible features; The city three-dimensional model is constructed by splicing the global three-dimensional parameters, the block border three-dimensional parameters and the block parameters according to the position relationship.

3. The urban landscape lighting design optimization method based on VR technology according to claim 2 is characterized in that: Constructing the three-dimensional city model also includes: Identifying a movable structure, wherein the movable structure includes a removable structure and a deformable structure; According to the removable structure, the demolition difficulty and demolition cost are evaluated, a demolition cost coefficient is set, and a simulation fitting is performed on the removable scheme and the demolition effect to construct the demolition time sequence characteristics of each demolition scheme; Extracting deformation time series features according to the deformable structure and constructing deformation time series features; Performing a mobile identification according to the position location area of ​​the movable structure, and mapping the demolition time sequence characteristics and deformation time sequence characteristics to a three-dimensional model to construct a time sequence three-dimensional model; The time-series three-dimensional model is used as a dynamic embedding model to construct a dynamic window, and a linkage relationship between the mobile identifier and the dynamic window is established. The dynamic window is used to display the structural state changes of the movable structure.

4. The urban landscape lighting design optimization method based on VR technology according to claim 2 is characterized in that: Performing global three-dimensional parameter extraction on the key features includes: According to the influence of the geometric shape, color, light, and occlusion, the three-dimensional model is configured in a multi-dimensional grid according to the influence, and a shape grid, a color grid, a light grid, and an occlusion grid are respectively established, and each grid element is the influence and dimensional characteristics of the corresponding area; Based on the influence of grid elements, the multi-dimensional grid is reduced in dimension, the grids whose influence is less than a threshold are removed, and the removed grids are subjected to feature aggregation according to the dimensional features to obtain low-dimensional grid parameters; Extract full-dimensional features of grid elements whose influence meets the threshold to obtain high-dimensional parameters; According to the three-dimensional positioning relationship, the high-dimensional parameters are integrated with the low-dimensional grid parameters to obtain the global three-dimensional parameters.

5. The urban landscape lighting design optimization method based on VR technology according to claim 1 is characterized in that: The landscape lighting design evaluation is performed through the evaluation module, and the evaluation module also includes: Acquire a multi-dimensional evaluation port, wherein the multi-dimensional evaluation port has evaluation attributes, and the evaluation attributes include a lighting effect evaluation dimension and a participating user identity dimension; Configure the evaluation weight of each dimension according to the evaluation attribute; Setting the multi-dimensional evaluation port algorithm according to the evaluation attributes and constructing an evaluation submodule; A mapping relationship between the evaluation weights of each dimension and the evaluation submodule is established to construct the evaluation module.

6. The urban landscape lighting design optimization method based on VR technology according to claim 5 is characterized in that: The positioning optimization objectives include: Calculate the evaluation contribution of each dimension and determine it through evaluation weights and evaluation results; Compare the gap between the target evaluation value and the actual evaluation value to determine the optimization range; An evaluation heat map is constructed based on the optimization range and the evaluation contribution to identify the optimization target.

7. The urban landscape lighting design optimization method based on VR technology according to claim 6 is characterized in that: According to the optimization target, the optimization parameters are adjusted, including: Based on the evaluation results, the current design parameters are traced back to obtain the optimization direction and optimization range of the optimization target; Analyze and optimize the influencing factors according to the optimization goal; A relationship model between the optimization influencing factors and the optimization target is established, and according to the relationship model, a search is performed with the optimization direction and the optimization range as constraints to obtain the adjusted optimization parameters.

8. The urban landscape lighting design optimization system based on VR technology is characterized by: Steps for implementing the method for optimizing urban landscape lighting design based on VR technology as described in any one of claims 1 to 7, wherein the urban landscape lighting design optimization system based on VR technology comprises: A three-dimensional model construction module, wherein the three-dimensional model construction module is used to construct a three-dimensional model of the city, and import the three-dimensional model of the city into a VR tool platform to obtain a city VR space; A positioning and alignment module, the positioning and alignment module is used to obtain a landscape lighting design drawing, perform positioning and alignment on the landscape lighting design drawing and the three-dimensional city model, and fit the landscape lighting design drawing to the three-dimensional city model based on the positioning and alignment relationship; A lighting simulation module, the lighting simulation module is used to perform lighting simulation rendering in the urban VR space according to the design parameters in the landscape lighting design drawings; A lighting evaluation module, which is used to connect to the urban VR space, evaluate the landscape lighting design through the evaluation module, and locate the optimization target; A parameter tuning module is used to obtain adjustment optimization parameters according to the optimization target, and to modify and re-render the landscape lighting design drawings through the adjustment optimization parameters.

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