49 results about "Urban model" patented technology

The invention relates to a three-dimensional live-action model generation method for city updating. The method comprises the following steps: collecting multi-source city image information, and obtaining semantic data according to the multi-source city image information; performing city modeling visualization according to the multi-source city image information to generate a city model; and matching the semantic data with the city model to obtain a three-dimensional real scene model containing the semantic data. According to the method, city information can be obtained more comprehensively by performing total factor accurate collection through a multi-source three-dimensional monitoring technology, the accuracy of a real scene model is improved, semantic data is matched with a city model, a three-dimensional real scene model containing the semantic data is obtained, multiple materials and textures of the model are combined, and the accuracy of the real scene model is improved. And the model is lightened, so that the purpose of reducing the resource loading time is achieved.

The invention discloses an unmanned aerial vehicle path planning method and device considering urban wind field factors. The method comprises the steps that building and unmanned aerial vehicle airport data are acquired, and a three-dimensional urban model and a rasterized airspace model are constructed; constructing a multi-rotor unmanned aerial vehicle energy consumption model; acquiring dominant wind data and performing CFD urban wind field simulation; dividing a super wind speed area and a turbulent flow area as flight risk areas; constructing an unmanned aerial vehicle path planning model considering the influence of the urban wind field; planning the path of the unmanned aerial vehicle in the wind field. According to the method, risk area division is carried out based on CFD simulation, the wind speed and turbulent kinetic energy spatial distribution can be captured, the method adapts to the wind resistance of the unmanned aerial vehicle and turbulent area flight limitation, the energy consumption can be reduced by utilizing a wind field, the capability of improving the energy efficiency is achieved, and a uniform path planning model with safety and energy efficiency as targets in the wind field is constructed.

The invention provides a low-altitude Internet of Things design simulation system based on an urban CIM model, relates to the field of low-altitude flight, and solves the technical problem that the deviation between path planning and actual operation is large due to the fact that an existing simulation system cannot effectively support dynamic migration of a service function chain. The method comprises the following steps: constructing a city three-dimensional model through a CIM technology, and carrying out grid division on the city three-dimensional model; acquiring environment information; acquiring a grid basic safety risk index of the urban three-dimensional model based on the environment information; the method comprises the following steps: collecting low-altitude internet-of-things sensing data through a plurality of sensors, and preprocessing the low-altitude internet-of-things sensing data; constructing a risk model algorithm based on the grid basic security risk index and the low-altitude internet-of-things perception data; obtaining a comprehensive risk index of each grid through a risk model algorithm; and if the comprehensive risk index is greater than a preset risk threshold, sending a risk airspace early warning signal of the corresponding grid. The method is used in the low-altitude Internet of Things design simulation process.

The invention discloses a construction method and device of a city three-dimensional model and a storage medium, and relates to the technical field of model construction, and the construction method comprises the steps: obtaining building point cloud and preset processing parameters of a city; determining a normal direction of each point cloud data in the building point cloud based on the neighborhood radius; dividing the point cloud data in the building point cloud into vertical point clouds and non-vertical point clouds based on the normal direction, determining a plurality of first plane areas corresponding to the vertical point clouds, and determining building footprint information based on the projection of the non-vertical point clouds in the first plane areas; building contour information is generated based on the height of the non-vertical point cloud projected in the first plane area; and filtering the point cloud data, dividing the filtered point cloud into a wall point cloud and a roof point cloud, and performing space division on the three-dimensional space based on the wall point cloud and the roof point cloud to obtain building surface information. According to the invention, the accuracy of the urban three-dimensional model can be improved.

The invention provides an urban multi-modal large model training method, device and equipment and a medium, and relates to the technical field of artificial intelligence. Constructing an image-text interlaced data set according to the satellite image description text corresponding to each satellite image and the streetscape image description text corresponding to each streetscape image; and training the city multi-modal large model based on the image-text interlaced data set, and adjusting perceptron parameters corresponding to the perceptron in the city multi-modal large model and large language model parameters corresponding to the large language model to obtain a trained target city multi-modal large model. According to the technical scheme, the problems that in the prior art, a training data source is single, and images and texts are independently processed are solved, the trained target city multi-mode large model has good understanding on the city environment, and the space structure and function characteristics of a city can be comprehensively captured.

The invention discloses a three-dimensional city scene construction method, and relates to the technical field of three-dimensional scene generation, and discloses a three-dimensional city scene construction method, which comprises the following steps: in response to a scene assembly instruction, displaying a basic city model resource library on a scene assembly interface, and initializing and loading a scene model according to received model resources; generating a basic scene framework according to a scene theme and an area range parameter contained in the scene assembly instruction; obtaining a semantic tag of the scene model, and determining a spatial layout requirement of the scene model based on the semantic tag; and according to the spatial layout requirement, automatically arranging the scene model into the basic scene framework, and constructing a three-dimensional city scene. According to the method, the spatial layout requirements of the models are determined through the semantic tags, so that the splicing reasonability of the scene models is ensured, and the three-dimensional city scene meeting the planning requirements is accurately constructed.

The invention provides an urban inland inundation simulation method and a risk early-warning risk-avoiding system based on coupling of a one-dimensional model and a two-dimensional model. The method comprises the following steps: performing one-dimensional and two-dimensional hydrodynamic simulation on urban inland inundation rainstorm and flood based on SWMM and OpenFOAM; establishing a water exchange interface between the first model and the second model, dynamically calculating exchange flow according to a water level relationship, and establishing and executing a two-dimensional model coupling mechanism; based on a coupling mechanism, running simulation and outputting data and results; building an urban model based on a Cesium platform, and inputting flood routing data obtained based on model coupling to realize visual simulation of urban inland inundation flood routing; a risk early-warning risk-avoiding system is built on the basis of a visual result and in combination with emergency management theoretical knowledge and comprises a waterlogging simulation module, an early-warning module, a risk zoning module and a risk-avoiding transfer module; risk area division of a target area is realized based on double factors of water depth and flow velocity, and a corresponding optimal risk avoiding route is planned based on a Dijkstra algorithm.

The invention relates to the technical field of city model construction, and discloses a smart city 3D model construction method and system, and the method comprises the steps: S1, enabling an unmanned aerial vehicle to fly over a city according to a preset flight path, dynamically calculating a proper flight height according to the height of a building and the pitch angle of a camera in the flight process, and automatically adjusting the flight height; the flight height is dynamically adjusted according to the building height and the camera pitch angle in the flight process of the unmanned aerial vehicle, and the coverage range and the resolution of image acquisition are ensured; in combination with the real-time analysis capability of the edge calculation module, data defects can be quickly identified and laser radar supplementary acquisition can be triggered, so that the data acquisition efficiency and integrity are remarkably improved; and finally, through multi-source data fusion and automatic modeling of the cloud processing platform, a high-precision and high-reality smart city 3D model is constructed, and a reliable three-dimensional digital basis is provided for city management and planning.

The invention relates to the technical field of three-dimensional rendering, in particular to a digital city design city model visual display system which comprises a purpose calibration module, a component combination module, a path guide module, a view angle scheduling module and a rendering display module. According to the method, more accurate visual representation of urban model space purposes is realized by optimizing purpose calibration in the urban space and careful processing of geographic information, more reasonable space utilization distribution and visual display are realized by dynamically adjusting anchor points of the purpose space, more intelligent decision making in urban planning and building design is supported, and the method has the advantages of being high in practicability and easy to popularize. By extracting and combining building components with different functions, the functional semantic expression of the model is further enhanced, the information value and practicability of the model are enhanced, the interactivity and educational significance of the model are enhanced, and the model is more vivid visually and can reflect the appearance of a real city more accurately due to the improvement of rendering display. And the display quality and attraction of the model are improved.

The invention relates to the technical field of city planning, and provides a dynamic city model system based on scenario planning, a city data acquisition and integration module collects multi-dimensional data and provides a basis for land project evaluation, and a land project evaluation module covers sub-modules of location, matching, cost and financial index measurement and calculation and the like, comprehensively analyzes projects, and improves the evaluation efficiency. The real-time dynamic adjustment module can timely cope with planning change and adjust cost, the scenario planning module considers various scenario simulation project development, and the decision support and strategy making module comprehensively assesses a decision, so that a real estate company can fully consider uncertainty factors, comprehensively assess project investment value and risk, make a scientific decision, and improve the project quality. The method provides a comprehensive, scientific and dynamic tool for real estate companies, and is used for evaluating the investment potential and feasibility of a land project in different scenes, assisting in deciding whether to obtain a land or not and making a subsequent development strategy, ensuring that the project meets the requirements of urban planning and land utilization planning, and maximizing economic benefits.

The invention relates to the technical field of three-dimensional modeling and geographic information processing, and discloses a three-dimensional city model generation optimization method and system, and the method comprises the steps: obtaining a central city area three-dimensional data set of a target city; generating a second fusion data set of unified three-dimensional point cloud representation; based on the key feature point set, a random consistency verification mechanism is adopted to execute preliminary registration operation; and generating a high-precision three-dimensional city model. In the prior art, in a multi-source three-dimensional data fusion process, coordinate system offset and scale difference exist among an oblique photography image, LiDAR point cloud, BIM data and a topographic map, and especially under a large-scale central urban area modeling condition, high-precision and automatic unified alignment is difficult to realize. And dislocation of building boundaries or fracture of terrain curved surfaces are caused. Due to the fact that depth feature extraction and cross-source feature alignment are combined with random consistency verification, the space consistency and modeling reliability of the three-dimensional city model are improved.

The present invention provides a fast ray tracing method and apparatus applicable to urban scene channel modeling. The steps of the method include: dividing regions in the top view plane of a three-dimensional urban model; each time a ray is emitted from an emission position, determining whether it enters a signal receiving point based on the emission position and emission direction of the ray; if the ray does not enter the signal receiving point, determining whether the ray intersects with the obstacle model in the region where the emission position is located after being emitted from the emission position based on the emission position and emission direction of the ray; if there is an intersection, obtaining the obstacle surface where the ray intersects with the obstacle model and emitting again; if there is no intersection, determining the region where the ray intersects based on the emission position and emission direction of the ray, obtaining the obstacle surface where the ray intersects with the obstacle model, and emitting again; if the ray enters the signal receiving point, obtaining the propagation paths of all the rays that enter the signal receiving point from the signal emission point to the signal receiving point.

The invention discloses a city design noise optimization method and system based on artificial intelligence, and the method comprises the steps: carrying out the preprocessing of building form and noise measurement data, and constructing a basic data set after noise simulation verification; a three-dimensional city model and a measuring point network are generated through a layered parameterization framework, the structural noise level is calculated, real-time verification is carried out in combination with planning constraints, and a structural design space, noise basic data and feasibility guarantee are provided; a two-stage multi-layer perceptron network is constructed, local building group acoustic influence and a global city noise mode are processed respectively, and high-precision noise prediction is achieved through training; and deploying a large language model as an optimization agent, and outputting an optimal scheme through multiple rounds of iterative optimization and evaluation. Compared with the prior art, the method has the advantages that the noise prediction precision is effectively improved, a structured design space is provided for parametric modeling, the feasibility is guaranteed through real-time verification, efficient iteration is achieved through large language model optimization, and compared with a traditional method, the efficiency is remarkably improved, and the labor cost is reduced.

The invention discloses a path planning method based on a city engine and an unreal engine. The method comprises the following steps: completing basic data preparation, rule definition, model generation and visual presentation and analysis, and establishing a city model; secondly, constructing a vehicle motion model in an unreal engine, and simulating weather; the three-dimensional static model and a dynamic model in an unreal engine are fused to generate an urban environment; carrying out geographical gridding on the urban area; introducing a trafficability map and physical restrictions of the vehicle, and setting the trafficability map of the vehicle; an improved A * algorithm based on geographic gridding is introduced, path planning is conducted, the improved A * algorithm is used, and path optimization is achieved through a heuristic function and a penalty function; and outputting the generated path plan.

The invention discloses a three-dimensional city generation method and device based on a satellite image, equipment and a medium, and the method comprises the steps: obtaining a satellite image of a city, and extracting an instance segmentation map and a depth map, thereby constructing a three-dimensional volume structure; extracting texture features and geometric features based on the three-dimensional volume structure; according to the texture features and the geometric features, a preset diffusion model is adopted to generate image frames of a plurality of visual angles; wherein the diffusion model carries out inter-frame feature aggregation through inter-frame consistency attention, and different scale features are processed through hierarchical geometric perception attention; performing consistency evaluation based on the image frames of the plurality of visual angles to obtain a consistency score; and based on the three-dimensional volume structure, performing three-dimensional reconstruction according to the consistency score, and generating a three-dimensional city model. According to the method, the generation efficiency and quality of the city-scale 3D scene can be effectively improved, and the problem of multi-view consistency of the city-scale large scene is solved.

The invention discloses a city layout optimization simulation method, system and device for relieving a city heat island effect, and the method comprises the steps: S100: carrying out the grid division of a target city region, adding the city surface temperature data and city data to corresponding grid points, and obtaining a grid city model; s200, extracting average city surface temperature data and influence factor data of each grid point in the grid city model, and respectively constructing a surface temperature prediction model of each grid point by adopting a geographically weighted regression model; and S300, taking the average urban surface temperature data and the influence factor data of each grid point as a state space, taking each influence factor and the action type as an action space, performing reinforcement learning, and simulating an optimization scheme of the urban layout. According to the method, the optimal city layout simulation scheme capable of keeping city functions, controlling optimization cost and relieving a heat island effect can be automatically learned, so that scientific guidance is provided for city layout optimization.

The application relates to the technical field of three-dimensional rendering, in particular to a digital city design city model visual display system, which comprises a use calibration module, a component combination module, a path guiding module, a visual angle scheduling module and a rendering display module. In the application, through optimization of use calibration in city space and detailed processing of geographic information, more accurate visual performance of the use of the city model space is realized, through dynamic adjustment of the anchor point of the use space, more reasonable space utilization distribution and visual display are realized, more intelligent decision making in city planning and building design is supported, through extraction and combination of building components with different functions, the functional semantic expression of the model is further strengthened, the information value and practicability of the model are enhanced, the interactivity and educational significance of the model are strengthened, and the improvement of the rendering display makes the model more realistic in vision and more capable of accurately reflecting the appearance of a real city, thereby improving the display quality and attraction of the model.

The present invention provides a method and system for selecting a connection location of a drainage pipe network, including: constructing a city model; analyzing and confirming location factors; using the confirmed location factors to optimize the city model; obtaining the operation information of the drainage pipe network connection in real time to dynamically adjust the city model; and confirming the connection address information of the drainage pipe network according to the city model. By constructing, optimizing, and dynamically adjusting the city model according to the actual urban construction, the connection address information of the drainage pipe network confirmed by the root city model conforms to the current urban construction, which is systematic. In addition, since the connection address information of the drainage pipe network is automatically generated by the city model according to an algorithm, it does not depend on manual experience and has high scientificity, solving the problem that the existing selection of the connection location of the drainage pipe network lacks scientificity and systematicness.

The invention relates to an unmanned aerial vehicle cluster path planning method, device and equipment for an urban environment, and the method comprises the steps: constructing an unmanned aerial vehicle cluster multi-path planning model and an unmanned aerial vehicle cluster flight path model through an urban three-dimensional model constructed based on the introduction of an AirMatrix concept, and carrying out the multi-path planning of an unmanned aerial vehicle cluster under the models, a reinforcement learning problem is modeled into a Markov decision process model, an unmanned aerial vehicle cluster collaborative exploration game model is constructed, an optimized SAC reinforcement learning method and historical data are adopted to perform iterative training based on the model, and a path planning model for unmanned aerial vehicle cluster path planning in a complex environment is obtained. And planning the flight path of each unmanned aerial vehicle in the unmanned aerial vehicle cluster by using the path planning model according to the cluster task information to obtain a multi-unmanned aerial vehicle cooperative operation path planning result under multiple constraint conditions. By adopting the method, effective path planning can be carried out in a complex and multi-obstacle urban scene.

The invention discloses a flood risk early warning grading standard method based on urban flood simulation forecast. The method is specifically implemented according to the following steps: step 1, constructing a grid city model; step 2, evaluating the disaster-bearing object capability of the grid city model in the step 1; 3, evaluating the waterlogging prevention capability in each grid unit in the grid city model in the step 1; 4, constructing a flood risk assessment model; step 5, constructing a flood risk grading early warning model, quantifying a risk value and a continuous trend of flood, and setting a triggering condition of risk early warning; and step 6, constructing a grading early warning model. According to the method, the problems that the dynamic process of urban flood occurrence cannot be accurately simulated and the matching degree with actual risk early warning is low in an existing grading method are solved, the urban flood risk grade can be accurately predicted and evaluated, and the accuracy and timeliness of early warning are improved.

This invention provides a drainage connection intelligent site selection system based on GIS and the CIM metaverse virtual space. This system aims to achieve intelligent site selection and optimized management of urban drainage network connection points through advanced geographic information system and urban information modeling technologies. The system comprises a model construction module, a drainage network generation module, a model optimization module, a model adjustment module, an address confirmation module, a governance module, and an interaction module. By optimizing and dynamically adjusting city and drainage network models based on actual urban development, drainage network connection address information is aligned with current urban development. This information is automatically generated using an algorithm based on the city and drainage network models, resulting in a highly scientific approach. The system can dynamically adjust the city and drainage network models based on real-time urban development data, addressing the lack of scientific and systematic methods in existing drainage network connection site selection and providing strong technical support for the planning and management of urban drainage systems.

The application relates to the technical field of urban planning and design, in particular to a model generation method suitable for urban planning and design, which comprises the following steps: S1, for a region to be modeled, a plurality of building topographic maps and height data of the region to be modeled are acquired and merged to generate a merged data map; S2, the merged data map is corrected to generate an intermediate design map; and S3, a city model is generated in the region to be modeled by using the intermediate design map and external facade data. The application has the beneficial effect that, in the process of constructing the city model, the building data in the region to be modeled is integrated and processed, and the places where errors exist among the plurality of buildings are excluded to generate the intermediate design map, so that the overall layout effect of the region to be modeled is more coordinated, the problem that design interference among the plurality of buildings is difficult to find and the effect is not unified when only a single building is designed is avoided, and better city model construction effect is achieved.

The embodiment of the invention relates to the technical field of artificial intelligence, and discloses an urban remote sensing image vegetation coverage identification method and system based on deep learning, and the method comprises the steps: firstly obtaining a thermal remote sensing image and a visible light remote sensing image of an urban target region, and carrying out the precise segmentation of the thermal image through the features of the visible light image, high-radiation areas (buildings or roads) and low-radiation areas (potential vegetation areas) are distinguished; and then, through multi-temporal thermal radiation change analysis, a specific thermal area with remarkable thermal radiation dynamic change is further screened out from the low-radiation area. And finally, carrying out area matching verification on the coverage range of the specific thermal area and the building and water area coverage information in the urban model network so as to accurately judge the vegetation coverage area. Therefore, through multi-source data complementation, dynamic feature mining and spatial constraint verification, the problem of low accuracy of judgment and recognition of a single data source in the prior art is effectively solved, and the accuracy of vegetation coverage recognition is improved.

To provide an information processing device that can explore routes suitable for a three-dimensional movement of a user in a cyber urban space.SOLUTION: A head-mounted display (HMD) 100 comprises: 3D urban model information acquisition means 201 of acquiring 3D urban model information on a cyber urban space where a plurality of CG objects exists; user information acquisition means 202 of acquiring user information; route exploration networking means 203 of using the 3D urban model information to network a route exploration network 300, calculating at least a score Sv based on easiness of viewing of the CG object, and a score Su based on preference of a user to the CG object by use of the 3D urban model information, and user information, and thereby setting a link score Score; and route exploration means 206 of, in the route exploration network 300, exploring a route from a departure location to a destination location, using the link score Score.SELECTED DRAWING: Figure 2

This invention discloses a method and system for dynamic monitoring of urban flood disasters based on big data, belonging to the field of disaster management technology. The method includes: constructing a three-dimensional urban model; decoupling and evaluating the structural, functional, and load vulnerability to form a disaster monitoring architecture; supervising and training disaster monitoring components based on this architecture and embedding them into an urban information platform to achieve intelligent learning of disaster probability dependence and vulnerability entropy; combining multi-source sensor data for joint evaluation to determine the disaster monitoring status in real time; and implementing intelligent management and targeted monitoring guidance for urban flood disasters based on the monitoring results. This invention solves the technical problems of existing urban flood monitoring methods lacking comprehensive evaluation and real-time dynamic monitoring of the complex urban environment, leading to delayed disaster identification and insufficient monitoring accuracy. It achieves the technical effect of a big data-driven three-dimensional disaster monitoring architecture, enabling multi-dimensional dynamic evaluation of urban flood disasters and improving disaster identification accuracy and response efficiency.

An artificial intelligence-based urban design noise optimization method and system includes: preprocessing building form and noise measurement data, constructing a basic data set after noise simulation verification; generating a three-dimensional urban model and a network of measurement points through a hierarchical parameterized framework, calculating the structure-borne noise level, and verifying it in real time in conjunction with planning constraints, providing a structured design space, basic noise data, and feasibility assurance; constructing a two-stage multilayer perceptron network to process the acoustic impact of local building clusters and global urban noise patterns, respectively, and achieving high-precision noise prediction through training; deploying a large language model as an optimization agent, and outputting the optimal solution through multiple rounds of iterative optimization and evaluation. Compared with traditional technologies, this invention effectively improves noise prediction accuracy. Parametric modeling provides a structured design space, real-time verification ensures feasibility, and the use of a large language model for optimization enables efficient iteration, significantly improving efficiency and reducing labor costs compared to traditional methods.

The present application discloses a method for matching urban earthquake disaster scenarios, which includes a seismic motion library, an urban earthquake disaster scenario library, and a fast matching algorithm. The fast matching algorithm includes a single wave method, a multi-wave splicing method, and a multi-wave superposition method. The method of the present invention establishes a seismic motion library in advance, uses all seismic motions in the seismic motion library in advance to calculate the seismic response of the urban model, and stores it in the earthquake disaster scenario library. When it is necessary to construct an urban earthquake disaster scenario of a target seismic motion, by comparing the acceleration response spectrum of the target seismic motion with the seismic motion in the seismic motion library, the optimal earthquake disaster scenario is directly matched from the urban earthquake disaster scenario library as the earthquake disaster scenario of the target seismic motion, providing a fast and feasible method for constructing urban earthquake disaster scenarios.

The present invention discloses an intelligent service method for urban management based on the Internet and government affairs big data. The method includes: accessing multi-source heterogeneous data, integrating and aggregating it with basic information resources to obtain multi-source heterogeneous data of events; extracting features of the government affairs scenarios of the events to obtain event feature points; using the event feature points to construct a government affairs association data classification system centered on events to form a multi-layer association network; associating the structured information of the events with the coordinate information of the urban model to form an information coordinate group combining the structured information of the events and the coordinate information; establishing a visualization map combining the event scenarios and the structured information based on the information coordinate group; classifying the visualization map to establish a visualization situation analysis system based on the three-dimensional city; and constructing a theme decision-making model based on the cross-department and multi-field business requirements, business characteristics, and spatio-temporal constraints according to the visualization situation analysis system. By using the present invention, the efficiency of event processing can be improved.

The application discloses a city model generation method and device, electronic equipment and a storage medium, comprising: acquiring city grid model data, and determining the main street corresponding to the city grid model data; acquiring the key view sequence corresponding to the main street, wherein the key view sequence comprises a plurality of virtual camera key views, the plurality of virtual camera key views are obtained by moving and shooting the virtual camera along the main street, and the distance interval of any two virtual camera key views in the plurality of virtual camera key views is the same; based on the key view sequence, a plurality of visual images are generated; for each visual image, each pixel point of the visual image is converted into a particle point in a world coordinate system to obtain a sparse particle field; the sparse particle field is densified to obtain a dense particle field; and based on the dense particle field, a city particle model is obtained. The application can improve the position accuracy of the particle, and accurately determine the geometric information of the building facade in the model.

The invention relates to the technical field of image processing, and provides a low-altitude route planning method and system based on image processing, and the method comprises the steps: obtaining an urban GIS model, point cloud data and a remote sensing image, generating an urban environment high-precision three-dimensional model, and obtaining an urban discrete graph; acquiring a plurality of neighborhood unmanned aerial vehicles of the target unmanned aerial vehicle at the current node; obtaining the dynamic interaction strength and static interaction strength of the target unmanned aerial vehicle and each neighborhood unmanned aerial vehicle in the verification flight stage, and further obtaining the interaction strength of the target unmanned aerial vehicle at the current node; judging whether the target unmanned aerial vehicle needs to adjust a preset node at the current node through the threshold value, and obtaining a plurality of candidate nodes of the target unmanned aerial vehicle at the current node; and acquiring a flight target node of the target unmanned aerial vehicle at the current node to realize low-altitude route real-time planning of the unmanned aerial vehicle. The method aims at solving the problem that unmanned aerial vehicle low-altitude route planning does not consider task scheduling interference of other unmanned aerial vehicles and is difficult to adapt to dynamic environment changes.