Urban design auxiliary optimization management system based on multi-modal data

Abstract

The invention discloses a city design auxiliary optimization management system based on multi-modal data, and relates to the field of auxiliary optimization, and the system comprises a data collection module which is used for constructing a three-dimensional city image, obtaining a corresponding three-dimensional city function image layer according to the three-dimensional city image and structure function information, and obtaining function collection data; the data processing module carries out function evaluation on the collected function collection data and obtains function coverage data; the defect analysis module obtains corresponding functional defect data according to the functional coverage data; an optimization analysis module carries out vertical plane superposition and combination on the functional defect data at different positions in each three-dimensional urban functional map layer to obtain functional cooperation data at each position among different structure functional information; the design auxiliary module carries out scheduling matching on function defect data corresponding to different structure function information in sequence according to the obtained function collaboration data, and design auxiliary information is generated; according to the invention, the accuracy of the city design auxiliary optimization management process is improved.

Description

Technical Field

[0001] This invention relates to the field of auxiliary optimization technology, and in particular to an urban design auxiliary optimization management system based on multimodal data. Background Technology

[0002] Urban design is a core element that coordinates urban spatial form, functional layout, ecological environment and people's livelihood needs. The scientific nature of its plan directly determines the efficiency of urban operation and the quality of life of residents. With the acceleration of urbanization, the complexity, dynamism and diversity of urban systems have increased significantly. Traditional urban design and management models are no longer able to meet the development needs of the new era. However, the rapid iteration of multimodal data technology, big data analysis and artificial intelligence algorithms has provided a technical foundation for breaking through the bottlenecks of traditional models.

[0003] A search revealed Chinese invention patent CN120337469A, which discloses a smart city planning method and system based on multi-source remote sensing data fusion. Specifically, it relates to the field of urban planning technology, including: S1, regional division: based on GIS geographic coordinates and urban functional zoning data, the planning area is divided into M dynamic management grids. LiDAR point cloud data assists in identifying terrain undulations and building heights, adjusting grid boundaries, and establishing a bidirectional mapping relationship between the grids and multi-source sensing devices; S2, multi-source data acquisition: through full-domain coverage and multimodal sensing technology, a city holographic dataset is constructed, target city data is acquired in real time, and then multi-level cleaning and spatiotemporal alignment are performed, along with standardization processing, to normalize the data at each layer to obtain city data. This invention overcomes the limitations of traditional single-source data by constructing a space-air-ground-network full-domain sensing network and a multi-level spatiotemporal grid framework, deeply integrating satellite remote sensing, UAV point clouds, ground sensors, and urban operation data.

[0004] Compared with existing technologies, the invention patent with Chinese patent number CN120337469A can overcome the limitations of single-source data in traditional systems, achieve multi-objective nonlinear collaborative optimization, and real-time data-driven dynamic iterative optimization of urban planning processes.

[0005] However, in actual use, the core data relied upon by the above systems are mainly structured static data, which is insufficient for collecting and utilizing dynamic process data of urban operation. Furthermore, different types of data may interact with each other during the dynamic process of urban operation, which to some extent affects the accuracy of urban design-assisted optimization. Summary of the Invention

[0006] The purpose of this invention is to address the shortcomings of insufficient accuracy in existing technologies by proposing a city design auxiliary optimization management system based on multimodal data.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: A city design auxiliary optimization management system based on multimodal data includes a city design auxiliary management platform, which is equipped with a data acquisition module, a data processing module, a defect analysis module, an optimization analysis module, and a design auxiliary module. The data acquisition module is used to acquire basic urban information and structural and functional information, generate a three-dimensional urban image based on the basic urban information, map the structural and functional information into the three-dimensional urban image, obtain a three-dimensional urban functional layer, and set up data acquisition terminals according to the obtained three-dimensional urban functional layers to acquire the corresponding functional acquisition data. The data processing module is used to perform functional evaluation on the functional acquisition data obtained in the 3D city functional layer, obtain the corresponding functional coverage data based on the functional evaluation results, and map the functional acquisition data to the corresponding position in the 3D city functional layer based on the obtained functional coverage data. The defect analysis module is used to perform defect analysis on the mapping results in each 3D city functional layer and obtain the corresponding functional defect data. The optimization analysis module is used to perform vertical overlay and combination processing on the functional defect data obtained in each 3D city functional layer, and to perform functional overlay optimization analysis on the overlay and combination processing results to obtain functional coordination data at the corresponding locations. The design assistance module is used to sequentially perform planar combination processing on the functional coordination data at various locations within the 3D city image, schedule and match the obtained functional coordination data based on the planar combination processing results, and generate design assistance information based on the scheduling and matching results.

[0008] The above technical solution further includes: the data acquisition module includes: The data acquisition module includes a data entry unit, a data visualization unit, and a data acquisition unit. The data entry unit is used to acquire urban basic information and structural function information. The urban basic information includes geospatial basic information, building spatial structure information and planning constraint control information. The structural function information includes environmental structure information, transportation structure information and safety and emergency structure information. The data visualization unit is used to map the obtained basic urban information to a three-dimensional spatial coordinate system for visualization processing, generate a three-dimensional urban image, obtain various types of structural and functional information, map different types of structural and functional information to corresponding positions in the three-dimensional urban image, and obtain the corresponding three-dimensional urban functional layers. The data acquisition unit is used to acquire the corresponding functional data.

[0009] Furthermore, the process by which the data acquisition unit acquires the corresponding functional acquisition data includes: Obtain the three-dimensional urban functional layers corresponding to different types of structural and functional information respectively, and set the data acquisition terminal corresponding to the acquisition of structural and functional information according to the distribution of the corresponding types of structural and functional information in the three-dimensional urban functional layers; The corresponding functional data is acquired through the set data acquisition terminals, and the acquired functional data is marked according to the corresponding location information, time information and type information in the three-dimensional city functional layer.

[0010] Furthermore, the data processing module includes: The data processing module includes a functional evaluation unit and a coverage processing unit. The functional evaluation unit is used to acquire functional data of various types within the three-dimensional city functional layers. It matches the acquisition marker results of the functional data with the corresponding location information within the three-dimensional city functional layers. Based on the location matching results, it sets time alignment sequences and maps the functional data acquired at the corresponding location information to the corresponding time alignment sequences. Functional evaluation indicators are set for the functional data collected in each time-aligned sequence within each 3D city functional layer. The obtained functional data is compared and analyzed with the corresponding functional evaluation indicators. The comparison evaluation results corresponding to each functional evaluation indicator are obtained. The obtained comparison evaluation results are marked according to the corresponding functional evaluation indicators to obtain the functional evaluation results. The coverage processing unit is used to set the corresponding functional coverage data based on the functional evaluation results.

[0011] Furthermore, the process by which the coverage processing unit sets the corresponding functional coverage data based on the functional evaluation results includes: The functional evaluation results at the corresponding locations of each three-dimensional city functional layer are subjected to radiation range quantification and radiation degree quantification respectively. The radiation range quantification and radiation degree quantification process is as follows: according to the functional evaluation results at the corresponding locations within the corresponding three-dimensional city functional layer, range weight data and degree weight data are set respectively, and weighted calculations are performed according to the set range weight data and degree influence data to obtain radiation range quantification data and radiation degree quantification data. The obtained radiation range quantification data and radiation degree quantification data are set as functional coverage data, and the corresponding functional acquisition data are mapped to the corresponding positions of the three-dimensional city functional layer according to the set functional coverage data.

[0012] Furthermore, the process by which the defect analysis module acquires the corresponding functional defect data includes: Color space parameters are set according to the radiation range quantification data and radiation degree quantification data corresponding to the corresponding locations in the 3D city function layers for different functions. The mapping results at each location in each 3D city function layer are obtained. The mapping results at the corresponding locations are visualized according to the color space parameters corresponding to the radiation range quantification data and radiation degree quantification data to obtain the 3D city function visualization layer corresponding to the corresponding function. Set the defect color parameters of the obtained 3D city function visualization layer according to the corresponding function type, compare the difference between the color space parameter of the corresponding position in the 3D city function visualization layer of the corresponding function type and the corresponding defect color parameter, and obtain the corresponding functional defect data based on the difference comparison result.

[0013] Furthermore, the process by which the optimization analysis module obtains functional coordination data at the corresponding location includes: Based on the corresponding function type, the functions of each 3D city function layer are combined. Based on the function combination results, the corresponding positions in the 3D city function layers are vertically superimposed and combined to place the functional defect data of each position in the 3D city function layer on the same vertical plane. The functional defect data at each vertical plane corresponding to the vertical superposition combination processing results of each functional combination result are subjected to functional superposition optimization. The functional superposition optimization includes superposition coupling analysis and spatial conflict identification analysis. The functional defect data at the corresponding position is set with the corresponding functional coordination data according to the corresponding functional superposition optimization results. The functional coordination data is based on the functional coordination relationship between different types of functional defect data at the same vertical plane, which has mutual functional superposition influence.

[0014] Furthermore, the process by which the design assistance module generates design assistance information includes: The functional coordination data corresponding to each function at each location within each 3D city functional layer are mapped according to their respective vertical planes. The functional coordination data of each vertical plane are then combined in a planar manner. Based on the functional coordination data obtained from the planar combination processing results of the corresponding type of function, defect compensation design is performed to obtain design compensation information. The obtained design compensation information is assigned corresponding importance weight values ​​according to the corresponding function type. Based on the importance weight values ​​and the corresponding functions in the optimization analysis module, scheduling and matching analysis are performed sequentially. Based on the scheduling and matching analysis results, the optimal value of the design compensation information corresponding to each function is obtained and marked as design auxiliary information.

[0015] The present invention has the following beneficial effects: 0. In this invention, three-dimensional urban functional layers are set according to different structural functional information types. Defect analysis is performed on the functional data collected in each three-dimensional urban functional layer. The results of the defect analysis are visualized to obtain the corresponding functional defect data. The functional defect data in each three-dimensional urban functional layer are superimposed to obtain the functional coordination data at the corresponding locations. This can improve the coordination between different types of functional data collected in the process of urban design-assisted optimization management to a certain extent, thereby improving the accuracy of the process of urban design-assisted optimization management to a certain extent.

[0016] 1. In this invention, the functional collaborative data corresponding to the functional acquisition information in each three-dimensional city functional layer are used to iteratively analyze the corresponding functional defect data, obtain the influence of the design compensation information at the corresponding location on the functional defect data corresponding to other functional locations, and obtain the minimum value of the functional defect data corresponding to the design auxiliary information in each three-dimensional city functional layer in the three-dimensional city image according to the mutual influence. This is the optimal value of the design compensation information, thereby improving the accuracy and efficiency of the urban design auxiliary optimization management process to a certain extent. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the structure of an urban design auxiliary optimization management system based on multimodal data proposed in this invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1 like Figure 1 As shown, the present invention proposes an urban design auxiliary optimization management system based on multimodal data, including an urban design auxiliary management platform, characterized in that the urban design auxiliary management platform is equipped with a data acquisition module, a data processing module, a defect analysis module, an optimization analysis module, and a design auxiliary module; The data acquisition module is used to acquire basic urban information and structural and functional information, generate a three-dimensional urban image based on the basic urban information, map the structural and functional information into the three-dimensional urban image, obtain a three-dimensional urban functional layer, and set up data acquisition terminals according to the obtained three-dimensional urban functional layers to acquire the corresponding functional acquisition data. The data processing module is used to perform functional evaluation on the functional acquisition data obtained in the 3D city functional layer, obtain the corresponding functional coverage data based on the functional evaluation results, and map the functional acquisition data to the corresponding position in the 3D city functional layer based on the obtained functional coverage data. The defect analysis module is used to perform defect analysis on the mapping results in each 3D city functional layer and obtain the corresponding functional defect data. The optimization analysis module is used to perform vertical overlay and combination processing on the functional defect data obtained in each 3D city functional layer, and to perform functional overlay optimization analysis on the overlay and combination processing results to obtain functional coordination data at the corresponding locations. The design assistance module is used to sequentially perform planar combination processing on the functional coordination data at various locations within the 3D city image, schedule and match the obtained functional coordination data based on the planar combination processing results, and generate design assistance information based on the scheduling and matching results.

[0020] In the specific implementation process, the data acquisition module acquires basic urban information and structural functional information, generates a three-dimensional urban image based on the basic urban information, maps the structural functional information into the three-dimensional urban image to obtain a three-dimensional urban functional layer, and sets up data acquisition terminals according to the obtained three-dimensional urban functional layers to acquire the corresponding functional acquisition data. The process includes: The data acquisition module includes a data entry unit, a data visualization unit, and a data acquisition unit. The data entry unit is used to acquire urban basic information and structural function information. The urban basic information includes geospatial basic information, building spatial structure information and planning constraint control information. The structural function information includes environmental structure information, transportation structure information and safety and emergency structure information, etc. The data visualization unit is used to map the obtained basic urban information to a three-dimensional spatial coordinate system for visualization processing, generate a three-dimensional urban image, obtain various types of structural and functional information, map different types of structural and functional information to corresponding positions in the three-dimensional urban image, and obtain the corresponding three-dimensional urban functional layers. The data acquisition unit is used to acquire corresponding functional data, and the process includes: Obtain the three-dimensional urban functional layers corresponding to different types of structural and functional information respectively, and set the data acquisition terminal corresponding to the acquisition of structural and functional information according to the distribution of the corresponding types of structural and functional information in the three-dimensional urban functional layers; The corresponding functional data is acquired through the set data acquisition terminals, and the acquired functional data is collected and marked according to the corresponding location information, time information and type information in the three-dimensional city functional layer. It should be further explained that the functional data collected in the data acquisition module corresponds to the data information involved in each type of structural functional information. Taking traffic structure information as an example, the functional data involved includes road traffic flow data, public transportation operation data, parking lot utilization information, and intersection traffic flow data. The obtained functional data is used to evaluate whether the corresponding type of structural functional information at the corresponding location meets the standards.

[0021] In the specific implementation process, the data processing module performs functional evaluation on the functional acquisition data obtained within the 3D city functional layer, obtains the corresponding functional coverage data based on the functional evaluation results, and maps the functional acquisition data to the corresponding location in the 3D city functional layer based on the obtained functional coverage data, including: The data processing module includes a functional evaluation unit and a coverage processing unit. The functional evaluation unit is used to acquire functional data of various types within the three-dimensional city functional layers. It matches the acquisition marker results of the functional data with the corresponding location information within the three-dimensional city functional layers. Based on the location matching results, it sets time alignment sequences and maps the functional data acquired at the corresponding location information to the corresponding time alignment sequences. Functional evaluation indicators are set for the functional data collected in each time-aligned sequence within each 3D city functional layer. The obtained functional data is compared and analyzed with the corresponding functional evaluation indicators. The comparison evaluation results corresponding to each functional evaluation indicator are obtained. The obtained comparison evaluation results are marked according to the corresponding functional evaluation indicators to obtain the functional evaluation results. Furthermore, the functional evaluation indicators include residential functional indicators, commercial functional indicators, and public service functional indicators, which are set according to the corresponding planning constraint control information. The set functional evaluation indicators are set with corresponding evaluation periods according to the type of functional data collected in the corresponding type of three-dimensional urban functional layer. Functional data collected within the time alignment sequence is obtained according to the evaluation period. The comparison evaluation results between the obtained functional data collected and the corresponding functional evaluation indicators are set as the functional evaluation results corresponding to the corresponding functional data collection data type. The functional evaluation results are the proportion of the corresponding functional evaluation indicators to which the corresponding functional data belongs. In addition, during this process, the time alignment sequences involved in each evaluation cycle are in the same sequence segment. The functional evaluation results corresponding to each type of functional data collection are set to their respective radar charts for visualization processing to obtain the functional evaluation results corresponding to the structural functional information of the corresponding type. The coverage processing unit is used to set the corresponding functional coverage data based on the functional evaluation results. The process includes: The functional evaluation results at the corresponding locations of each three-dimensional city functional layer are subjected to radiation range quantification and radiation degree quantification respectively. The radiation range quantification and radiation degree quantification process is as follows: according to the functional evaluation results at the corresponding locations within the corresponding three-dimensional city functional layer, range weight data and degree weight data are set respectively, and weighted calculations are performed according to the set range weight data and degree influence data to obtain radiation range quantification data and radiation degree quantification data. Furthermore, in the process of acquiring quantitative data on radiation range and quantitative data on radiation intensity, the functional evaluation results at the location of the functional acquisition data are quantitatively graded according to each connecting axis in the corresponding radar chart, and quantitative grading intervals are set on each connecting axis according to the deviation data between the corresponding functional evaluation index and the functional acquisition data. The basic radiation range and basic radiation level are set according to the quantitative classification interval to which they belong; Additional radiation range and additional radiation level are set according to the corresponding location within the respective quantitative grading interval; The position information of the corresponding connecting axis in the radar chart to which the corresponding function data belongs is weighted according to the corresponding range weight data for the basic radiation range and the additional radiation range, and the corresponding degree weight data for the basic radiation degree and the additional radiation degree, respectively, to obtain the corresponding radiation range quantification data and radiation degree quantification data. The corresponding radiation range quantification data and radiation degree quantification data are then matched one-to-one, and the corresponding function coverage data is obtained based on the one-to-one matching results. The obtained radiation range quantification data and radiation degree quantification data are set as functional coverage data, and the corresponding functional acquisition data are mapped to the corresponding position of the three-dimensional city functional layer according to the set functional coverage data. It should be further explained that the functional coverage data refers to the quantitative data of the coverage range and radiation degree of the corresponding function at the corresponding location when the corresponding structural functional information type is used. The functional coverage data at the corresponding location is mapped to the corresponding location in the three-dimensional city functional layer.

[0022] In the specific implementation process, the defect analysis module performs defect analysis on the mapping results in each three-dimensional city functional layer to obtain the corresponding functional defect data. The process includes: Color space parameters are set according to the radiation range quantification data and radiation degree quantification data corresponding to the corresponding locations in the 3D city function layers for different functions. The mapping results at each location in each 3D city function layer are obtained. The mapping results at the corresponding locations are visualized according to the color space parameters corresponding to the radiation range quantification data and radiation degree quantification data to obtain the 3D city function visualization layer corresponding to the corresponding function. Furthermore, during the process of setting color space parameters: Based on the 3D city function layers corresponding to different structural and functional information, select the corresponding color system. The corresponding color system is then assigned to a higher saturation level from low to high according to the radiation degree quantification data. During this process, set the basic parameters of the color system corresponding to the radiation range quantification data. The set basic parameters of the color system are then incremented by the corresponding saturation level from low to high according to the radiation degree quantification data. The corresponding color space parameters are obtained based on the basic parameters of the color system and the unit increment processing results. The obtained color space parameters are then used to map and visualize the function coverage data corresponding to the function acquisition data, thereby obtaining the corresponding 3D city function visualization layer. Set the defect color parameters of the obtained 3D city function visualization layer according to the corresponding function type, compare the difference between the color space parameters of the corresponding position in the 3D city function visualization layer of the corresponding function type and the corresponding defect color parameters, and obtain the corresponding function defect data based on the difference comparison results. Furthermore, the defect color parameter is set according to the corresponding functional evaluation index. The defect limit value corresponding to each functional evaluation index is obtained. The degree weight data of the corresponding radiation degree quantification data is obtained according to the defect limit value corresponding to each functional evaluation index and then superimposed. The color space parameter corresponding to the defect limit value is obtained. The corresponding color space parameter is marked as the defect color parameter corresponding to the corresponding defect limit value. Then, the difference between the corresponding color space parameter and the corresponding defect color parameter is compared to determine whether the functional acquisition data at the corresponding color space parameter meets the minimum standard. In addition, the difference between the color space parameter and the defect color parameter is marked as functional defect data.

[0023] In the specific implementation process, the optimization analysis module performs vertical overlay and combination processing on the functional defect data obtained in each three-dimensional city functional layer, and performs functional overlay optimization analysis on the overlay and combination processing results to obtain the functional coordination data at the corresponding location. The process includes: Based on the corresponding function type, the functions of each 3D city function layer are combined. Based on the function combination results, the corresponding positions in the 3D city function layers are vertically superimposed and combined to place the functional defect data of each position in the 3D city function layer on the same vertical plane. The functional defect data at the same vertical plane corresponding to the vertical superposition combination processing results of each functional combination result are optimized by functional superposition. The functional superposition optimization includes superposition coupling degree analysis and spatial conflict identification analysis. The functional defect data at the corresponding position is set according to the corresponding functional superposition optimization results. The functional coordination data is based on the functional coordination relationship between different types of functional defect data at the same vertical plane that have mutual functional superposition influence. Furthermore, the superposition coupling degree analysis and spatial conflict identification analysis processes included in the functional superposition optimization process each include the following steps: Overlay coupling analysis process: The types of corresponding functional defect data within different functional combination results are labeled as n, n=1,2, n, functional defect data is marked as Let H be the superposition coupling degree, where: , Furthermore, the closer the value is to 1, the higher the coupling degree. Based on the superposition and coupling degree between different functional defect data, the corresponding functional defect data are subjected to collaborative optimization and superposition processing to determine the collaborative influence relationship between each functional defect data. Spatial conflict identification and analysis process: A functional layout conflict logic comparison table is set up according to the corresponding planning constraint control information. The functional layout conflict logic comparison table marks the conflict and contradiction relationships between functional defect data corresponding to different types of structural function information at the corresponding radiation range and radiation degree. The functional defect data corresponding to different functional combination results at the same vertical plane are matched and analyzed with the marked results in the functional layout conflict logic comparison table in turn to determine whether there is a conflict relationship. If there is a conflict relationship, the conflict relationship is marked. Based on the results of superposition coupling analysis and spatial conflict identification analysis, the functional defect data at various locations within different types of 3D urban functional layers in the same vertical plane are adjusted. The functional defect data of different types of functional data at the same location after mutual influence (i.e., after collaborative optimization) are obtained, and the adjusted functional defect data are obtained.

[0024] In the specific implementation process, the design assistance module sequentially performs planar combination processing based on the functional coordination data at various locations within the 3D city image, schedules and matches the obtained functional coordination data based on the planar combination processing results, and generates design assistance information based on the scheduling and matching results. The functional coordination data corresponding to each function at each location within each 3D city functional layer are mapped according to their respective vertical planes. The functional coordination data of each vertical plane are then combined in a planar manner. Based on the functional coordination data obtained from the planar combination processing results of the corresponding type of function, defect compensation design is performed to obtain design compensation information. Furthermore, the process of obtaining design compensation information includes: In the process of mapping the obtained functional coordination data according to the vertical plane, the functional defect data in each different type of vertical plane is matched one by one with the corresponding functional coordination data. In the process of performing planar combination processing on the functional coordination data of each vertical plane, the vertical planes involved are combined according to the location information of the corresponding functional defect data in different three-dimensional city functional layers to obtain the corresponding planar combination processing results. The planar combination processing results obtained in each 3D city functional layer are sorted by design priority. Based on the design priority sorting results, defect compensation design is carried out on the planar combination processing results obtained in each 3D city functional layer in turn. During the defect design compensation process, the corresponding results of functional coordination data related to other vertical planes in the planar combination processing results are adjusted in real time. Acquire collaborative function defect data, and set corresponding constraint and target conditions based on planning constraint control information; Based on the obtained target condition information, defect compensation design is performed on the corresponding collaborative function defect data, and the defect compensation design results are obtained. The defect compensation design results corresponding to the corresponding collaborative function defect data are verified based on the obtained constraint information. The defect compensation design results that do not meet the constraint information are eliminated, and the remaining defect compensation design results are marked as design compensation information. The obtained design compensation information is assigned corresponding importance weight values ​​according to the corresponding function type. Based on the importance weight values ​​and the corresponding functions in the optimization analysis module, scheduling matching analysis is performed in sequence. Based on the scheduling matching analysis results, the optimal value of the design compensation information corresponding to each function is obtained and marked as design auxiliary information. Furthermore, the process of obtaining design support information includes: The design compensation information with the highest importance weight is obtained. The obtained design compensation information is then used to adjust other types of design compensation information in the same vertical plane according to the corresponding function superposition optimization in the optimization analysis module. The adjusted design auxiliary information at each position in each 3D city functional layer is obtained. The functional defect analysis of the design auxiliary information at each position in each 3D city functional layer is performed. The minimum value of the functional defect data corresponding to the design auxiliary information of each 3D city functional layer in the 3D city image is obtained, which is the optimal value of the design compensation information, and it is marked as the design auxiliary information.

[0025] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A city design auxiliary optimization management system based on multimodal data, comprising a city design auxiliary management platform, characterized in that, The urban design auxiliary management platform is equipped with a data acquisition module, a data processing module, a defect analysis module, an optimization analysis module, and a design assistance module. The data acquisition module is used to acquire basic urban information and structural and functional information, generate a three-dimensional urban image based on the basic urban information, map the structural and functional information into the three-dimensional urban image, obtain a three-dimensional urban functional layer, and set up data acquisition terminals according to the obtained three-dimensional urban functional layers to acquire the corresponding functional acquisition data. The data processing module is used to perform functional evaluation on the functional acquisition data obtained in the 3D city functional layer, obtain the corresponding functional coverage data based on the functional evaluation results, and map the functional acquisition data to the corresponding position in the 3D city functional layer based on the obtained functional coverage data. The defect analysis module is used to perform defect analysis on the mapping results in each 3D city functional layer and obtain the corresponding functional defect data. The optimization analysis module is used to perform vertical overlay and combination processing on the functional defect data obtained in each 3D city functional layer, and to perform functional overlay optimization analysis on the overlay and combination processing results to obtain functional coordination data at the corresponding locations. The design assistance module is used to sequentially perform planar combination processing on the functional coordination data at various locations within the 3D city image, schedule and match the obtained functional coordination data based on the planar combination processing results, and generate design assistance information based on the scheduling and matching results.

2. The urban design auxiliary optimization management system based on multimodal data according to claim 1, characterized in that, The data acquisition module includes: The data acquisition module includes a data entry unit, a data visualization unit, and a data acquisition unit. The data entry unit is used to acquire urban basic information and structural function information. The urban basic information includes geospatial basic information, building spatial structure information and planning constraint control information. The structural function information includes environmental structure information, transportation structure information and safety and emergency structure information. The data visualization unit is used to map the obtained basic urban information to a three-dimensional spatial coordinate system for visualization processing, generate a three-dimensional urban image, obtain various types of structural and functional information, map different types of structural and functional information to corresponding positions in the three-dimensional urban image, and obtain the corresponding three-dimensional urban functional layers. The data acquisition unit is used to acquire the corresponding functional data.

3. The urban design auxiliary optimization management system based on multimodal data according to claim 2, characterized in that, The process by which the data acquisition unit acquires the corresponding functional acquisition data includes: Obtain the three-dimensional urban functional layers corresponding to different types of structural and functional information respectively, and set the data acquisition terminal corresponding to the acquisition of structural and functional information according to the distribution of the corresponding types of structural and functional information in the three-dimensional urban functional layers; The corresponding functional data is acquired through the set data acquisition terminals, and the acquired functional data is marked according to the corresponding location information, time information and type information in the three-dimensional city functional layer.

4. The urban design auxiliary optimization management system based on multimodal data according to claim 3, characterized in that, The data processing module includes: The data processing module includes a functional evaluation unit and a coverage processing unit. The functional evaluation unit is used to acquire functional data of various types within the three-dimensional city functional layers. It matches the acquisition marker results of the functional data with the corresponding location information within the three-dimensional city functional layers. Based on the location matching results, it sets time alignment sequences and maps the functional data acquired at the corresponding location information to the corresponding time alignment sequences. Functional evaluation indicators are set for the functional data collected in each time-aligned sequence within each 3D city functional layer. The obtained functional data is compared and analyzed with the corresponding functional evaluation indicators. The comparison evaluation results corresponding to each functional evaluation indicator are obtained. The obtained comparison evaluation results are marked according to the corresponding functional evaluation indicators to obtain the functional evaluation results. The coverage processing unit is used to set the corresponding functional coverage data based on the functional evaluation results.

5. The urban design auxiliary optimization management system based on multimodal data according to claim 4, characterized in that, The process by which the coverage processing unit sets the corresponding functional coverage data based on the functional evaluation results includes: The functional evaluation results at the corresponding locations of each three-dimensional city functional layer are subjected to radiation range quantification and radiation degree quantification respectively. The radiation range quantification and radiation degree quantification process is as follows: according to the functional evaluation results at the corresponding locations within the corresponding three-dimensional city functional layer, range weight data and degree weight data are set respectively, and weighted calculations are performed according to the set range weight data and degree influence data to obtain radiation range quantification data and radiation degree quantification data. The obtained radiation range quantification data and radiation degree quantification data are set as functional coverage data, and the corresponding functional acquisition data are mapped to the corresponding positions of the three-dimensional city functional layer according to the set functional coverage data.

6. The urban design auxiliary optimization management system based on multimodal data according to claim 5, characterized in that, The process by which the defect analysis module acquires the corresponding functional defect data includes: Color space parameters are set according to the radiation range quantification data and radiation degree quantification data corresponding to the corresponding locations in the 3D city function layers for different functions. The mapping results at each location in each 3D city function layer are obtained. The mapping results at the corresponding locations are visualized according to the color space parameters corresponding to the radiation range quantification data and radiation degree quantification data to obtain the 3D city function visualization layer corresponding to the corresponding function. Set the defect color parameters of the obtained 3D city function visualization layer according to the corresponding function type, compare the difference between the color space parameter of the corresponding position in the 3D city function visualization layer of the corresponding function type and the corresponding defect color parameter, and obtain the corresponding functional defect data based on the difference comparison result.

7. The urban design auxiliary optimization management system based on multimodal data according to claim 6, characterized in that, The process by which the optimization analysis module obtains functional coordination data at the corresponding location includes: Based on the corresponding function type, the functions of each 3D city function layer are combined. Based on the function combination results, the corresponding positions in the 3D city function layers are vertically superimposed and combined to place the functional defect data of each position in the 3D city function layer on the same vertical plane. The functional defect data at each vertical plane corresponding to the vertical superposition combination processing results of each functional combination result are subjected to functional superposition optimization. The functional superposition optimization includes superposition coupling analysis and spatial conflict identification analysis. The functional defect data at the corresponding position is set with the corresponding functional coordination data according to the corresponding functional superposition optimization results. The functional coordination data is based on the functional coordination relationship between different types of functional defect data at the same vertical plane, which has mutual functional superposition influence.

8. The urban design auxiliary optimization management system based on multimodal data according to claim 7, characterized in that, The process by which the design assistance module generates design assistance information includes: The functional coordination data corresponding to each function at each location within each 3D city functional layer are mapped according to their respective vertical planes. The functional coordination data of each vertical plane are then combined in a planar manner. Based on the functional coordination data obtained from the planar combination processing results of the corresponding type of function, defect compensation design is performed to obtain design compensation information. The obtained design compensation information is assigned corresponding importance weight values ​​according to the corresponding function type. Based on the importance weight values ​​and the corresponding functions in the optimization analysis module, scheduling and matching analysis are performed sequentially. Based on the scheduling and matching analysis results, the optimal value of the design compensation information corresponding to each function is obtained and marked as design auxiliary information.

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