Road network model special scene loading management system and method

Abstract

The present application relates to the technical field of road network model loading, in particular to a road network model special scene loading management system and method. The method uses the system, which comprises a model construction module and a model loading module. The model construction module is used to construct a three-dimensional road network model of a target area, adopts a multi-detail level model, divides the target area into several plots, and sets a dynamic scheduling model in each plot to manage and schedule three-dimensional road network models of different detail levels. The model loading module is used to match three-dimensional road network models of corresponding detail levels for surrounding plots according to the distance between a viewpoint and a plot, and load the models in blocks. This technical solution can reduce the loading time of road network models and make the entire loading process more smooth.

Description

Technical Field

[0001] This invention relates to the field of road network model loading technology, specifically to a road network model special scenario loading management system and method. Background Technology

[0002] In recent years, 3D model visualization technology has made significant progress and has been widely applied in many fields. For example, in route navigation and location querying, 3D model visualization technology can be used to construct road network models, presenting abstract geographic information data in a more intuitive way, enabling users to obtain the information they need more conveniently and quickly.

[0003] The road network model focuses on key roads and surrounding buildings, showcasing a complex network structure to provide a more intuitive understanding of a region's traffic conditions and geographical environment. This model not only offers a macroscopic perspective from a viewpoint within the scene but also allows for in-depth exploration at a micro level, such as tracking detailed information about specific road segments or buildings.

[0004] However, despite the many advantages and application scenarios of road network models, some problems still exist in practical applications due to certain objective limitations. For example, in some devices, the wireless network bandwidth may be limited, making it impossible to quickly transmit large amounts of road network model data, which may affect the loading speed and real-time performance of the road network model.

[0005] Furthermore, due to the massive amount of data involved in road network models, the calculation and rendering processes require substantial computing and storage resources. Therefore, insufficient computing and storage capabilities on the device can lead to slow loading speeds, sluggish responses, or even system crashes. These factors limit the application and widespread adoption of road network models in certain scenarios. Summary of the Invention

[0006] The purpose of this invention is to propose a road network model special scenario loading management system and method. This technical solution can reduce the loading time of the road network model and make the entire loading process smoother.

[0007] To achieve the above objectives, in a first aspect, embodiments of this disclosure provide a road network model special scene loading management system, including a model building module and a model loading module; the model building module is used to build a three-dimensional road network model of a target area, adopting a multi-level-of-detail model to divide the target area into several plots, each plot having a dynamic scheduling model for managing and scheduling three-dimensional road network models of different levels of detail; the model loading module is used to match three-dimensional road network models of corresponding levels of detail for surrounding plots according to the distance between the viewpoint and the plot, and load them in blocks.

[0008] Beneficial effects of the basic solution: The model building module can build and manage the 3D road network model of the target area in 3D space. During construction, the target area is divided into several plots, and multiple levels of detail models are set for each plot. When the subsequent model loading module loads, it can load different plots according to different situations, and select different levels of detail 3D road network models for each plot for loading, which improves the loading efficiency of the 3D road network model.

[0009] The segmented land use technology can also improve the accuracy of the 3D road network model. Thanks to the improved loading efficiency, the level of detail of each land parcel model has been improved compared to the previous overall loading technology, which can more accurately capture and express terrain, buildings and other important geographical features.

[0010] The model loading module loads the 3D road network model of the surrounding landmasses in blocks based on the viewpoint's position. Before loading, it matches models with different levels of detail (fineness) based on the distance between the viewpoint and the landmasses, enabling faster model loading and display. This ensures that the scheduling of loading and rendering time can be controlled within a reasonable range for scenes of any size, making the entire loading process smoother and almost imperceptible to the user.

[0011] As a preferred option, the model building module divides land parcels using polygons or by roads.

[0012] Ensure that the model accurately corresponds to the actual road network.

[0013] As a preferred embodiment, the model loading module is also used to collect distance information between each viewpoint and the surrounding plots in the scene in real time, and combine the feature information of the three-dimensional road network model on the plots to predict the optimal distance and viewing angle for the viewpoint to observe the three-dimensional road network model. The feature information of the three-dimensional road network model includes the model type, model volume and model special characteristics, and matches the corresponding level of detail of the three-dimensional road network model according to the optimal distance and viewing angle.

[0014] Model loading is optimized based on the best distance and viewing angle to ensure the display quality of the road network model.

[0015] As a preferred embodiment, the model loading module is also used to predict the loading time of the model based on network bandwidth and model file size. When the prediction result exceeds the set loading threshold, the loading of a three-dimensional road network model with a lower level of detail is adjusted.

[0016] By combining real-time monitoring of network bandwidth and model size to predict loading time, and automatically adjusting the level of detail in loading based on set loading and time thresholds, the system not only reduces user waiting time for loading but also optimizes rendering management efficiency, making the entire system more stable and reliable.

[0017] As a preferred embodiment, the model loading module is also used to determine the user's attention level to the current plot based on the dwell time of the viewpoint at the current position and the total angle of observation rotation. When the user has a high level of attention to the area, the initially matched high-detail model will be loaded.

[0018] This makes the loading and display of the road network model more closely match the user's needs.

[0019] As a preferred embodiment, the model loading module is also used to track the activity status of each viewpoint in the scene and dynamically load or unload the road network model according to the activity status.

[0020] The model loading module can manage the road network model in the scene more flexibly, thereby improving the performance of model loading, reducing memory usage, and reducing loading latency.

[0021] As a preferred embodiment, the model loading module is also used to cache the 3D road network model of each viewpoint in the scene and the surrounding land plots.

[0022] Viewpoint switching is a frequent operation performed by users when using road network models. For example, switching back and forth between several viewpoints or returning to the previous position after moving a certain distance. This technical solution can quickly load when switching viewpoints, reduce loading delays, and improve user experience.

[0023] As a preferred embodiment, the model loading module is used to quickly retrieve nearby road network models based on the current viewpoint position, identify road feature information using road network model feature information, and predict the viewpoint movement direction and speed based on the current viewpoint position, road feature information, and viewpoint movement speed and acceleration.

[0024] The model loading module preloads the 3D road network model of the plots that the viewpoint can observe according to the viewpoint movement direction, and selects 3D road network models with different levels of detail to load according to the viewpoint movement speed.

[0025] The model loading module can effectively improve the loading speed and real-time performance of 3D road network models, providing a smoother virtual environment experience.

[0026] As a preferred embodiment, the model loading module is also used to integrate transition animations into the scene during the loading process, and to preload and cache the transition animations.

[0027] By cleverly integrating loading animations into the scene, the loading process becomes natural and smooth, almost imperceptible to the user. This not only reduces user anxiety during loading but also enhances the scene's appeal. Preloading and caching transition animations allows them to be quickly imported into the scene during loading, avoiding stuttering or delays and minimizing user perception of the loading process. Furthermore, pre-allocating resources to the animation loading submodule allows for greater allocation of system resources to model loading in subsequent processes, thus improving model loading speed.

[0028] Secondly, this disclosure also provides a method for loading and managing special scenarios of a road network model, which utilizes the aforementioned road network model special scenario loading and management system. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of the architecture of the road network model special scenario loading management system;

[0030] Figure 2 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0031] The technical solution of this application will be further described in detail below through specific embodiments:

[0032] Explanation of reference numerals in the attached drawings: Electronic device 500, processor 501, communication interface 502, memory 503, bus 504.

[0033] Example 1

[0034] Reference Figure 1 The road network model special scenario loading management system includes a model building module and a model loading module.

[0035] The model building module is used to construct a 3D road network model of the target area using a multi-level detail (MPM) model, including a land parcel division submodule and a dynamic scheduling submodule.

[0036] The land parcel division submodule is used to divide the target area into several land parcels. In this embodiment, the target land parcel area is preferably 1 square kilometer. The land parcels can be polygons such as rectangles, hexagons, or octagons, or they can be divided according to roads to ensure the accurate correspondence between the model and the actual road network. At the same time, the setting of multiple land parcels also enables the road network model to more accurately capture and express terrain, buildings, and other important geographical features.

[0037] Each plot contains a dynamic scheduling submodule, which includes a dynamic scheduling model for managing and scheduling 3D road network models at different levels of detail, so that the model loading module can selectively load them.

[0038] The model loading module is used to load the road network model in blocks. The model loading module includes a distance prediction submodule and a rendering management submodule.

[0039] The distance prediction submodule is used to collect distance information between each viewpoint and the surrounding plots in the scene in real time. The distance prediction submodule is equipped with a distance prediction model. The distance prediction model combines the distance information and the feature information of the 3D road network model on the plot to predict the optimal distance and viewing angle of the 3D road network model on the plot observed by the viewpoint. The feature information of the 3D road network model includes, but is not limited to, model type, model volume and model special characteristics.

[0040] The distance prediction model combines distance information with the feature information of the 3D road network model on the site to better predict the optimal distance and viewing angle for the 3D road network model observed from a viewpoint. During model training, sample data labeled with known optimal distances and viewing angles are used to adjust model parameters, enabling the model to accurately predict the optimal observation distance and viewing angle. In the prediction process, the model first extracts features from the 3D road network model on the site to obtain information such as the model's type, volume, and other specific characteristics. New viewpoint-distance combinations are then input into the model for prediction. Based on the input feature information and the learned parameters, the model calculates and outputs the optimal observation distance and viewing angle.

[0041] The rendering management submodule is used to match the corresponding level of detail in the 3D road network model based on the optimal distance and viewpoint, and generate model loading instructions. These instructions include information such as the path to the model file to be loaded, the loading priority, and the level of detail required. The model loading operation is then executed on the GPU. After loading, the rendering engine uses the loaded model for rendering, such as vertex shading and texture mapping, to generate the final visualization result. This improves the speed and efficiency of road network model loading.

[0042] The rendering management submodule is also used to predict the loading time of the model based on the real-time monitored network bandwidth and model file size. When the prediction result exceeds the set loading threshold, the loading priority is automatically adjusted, prioritizing the loading of 3D road network models with lower levels of detail, so as to avoid affecting the user experience due to slow loading of road network models.

[0043] The rendering management submodule will also determine the user's attention level to the current plot based on the time the viewpoint stays at the current position and the total angle of observation rotation. When the rendering management submodule determines that the user has a high level of attention to the area, it will load the initially matched high-detail model to improve the visual effects and user experience.

[0044] The rendering management submodule supports various formats of 3D road network model files, such as .obj, .fbx, and .dae, which can meet the needs of 3D road network models from different sources and application scenarios.

[0045] The model loading module also includes a memory management submodule, which automatically tracks the activity status of each viewpoint in the scene and dynamically loads or unloads the road network model based on the activity status. This effectively utilizes memory resources and avoids memory waste and loading latency issues. The memory management submodule caches the 3D road network models of each viewpoint and the surrounding terrain in the scene so that they can be loaded quickly when switching viewpoints, reducing loading latency during viewpoint switching and improving the user experience.

[0046] The model loading module also includes a path prediction submodule, which quickly retrieves nearby road network models based on the current viewpoint's location. Utilizing feature information from these models, it automatically identifies road features, including traffic signs and signals, road intersections, surrounding buildings, and natural landscapes. The prediction submodule uses machine learning algorithms (such as neural networks and decision trees) to train a viewpoint movement prediction model on historical data. This model can predict the next direction and speed of the viewpoint's movement based on the current viewpoint's location, road feature information, and the viewpoint's movement speed and acceleration.

[0047] The rendering management submodule preloads the 3D road network models of the plots that the viewpoint may observe based on the viewpoint's movement direction, and selects 3D road network models with different levels of detail to load based on the predicted speed.

[0048] The model loading module also includes an animation loading submodule. If a loading process still occurs during background data reading, the animation loading submodule will add transition animation effects to the road network model scene, seamlessly integrating the transition animation into the scene. When designing animations, the effects should be simplified as much as possible to avoid overly complex animations that could lead to excessively long loading times. This approach allows for a smooth and natural loading process within 3 seconds.

[0049] The animation loading submodule will preload and cache transition animations so that they can be quickly imported into the scene when loading occurs, avoiding stuttering and delays in the transition animations themselves and minimizing the user's perception of the loading process. At the same time, resources are pre-allocated to the animation loading submodule so that more system resources can be allocated to model loading in subsequent loading processes, thereby improving the speed of model loading.

[0050] Example 2

[0051] The key technical difference between this embodiment and Embodiment 1 lies in the fact that the model loading module further includes a focus prediction submodule. This focus prediction submodule is used to predict the user's focus based on the current viewpoint's scene. A focus refers to the point of interest in a specific detail of the model within the current scene. For example, if the current viewpoint is at an intersection, the predicted focus is on traffic lights and oncoming vehicles; if the current viewpoint is in a global scene, the predicted focus is on the overall model environment; if the current viewpoint is in an accident demonstration scene, the focus is on the accident vehicles and the detailed local model environment of the accident site; if the current viewpoint is in a traffic guidance scene, the predicted focus is on traffic guidance routes and signs.

[0052] The rendering management submodule is also used to preload the 3D road network model detail levels that the viewpoint may need to observe based on the viewpoint's movement direction, and select 3D road network models with different detail levels to load based on the predicted points of interest, while loading 3D road network models of similar scenes in the surrounding plots.

[0053] The memory management submodule is also used to adjust the preloading strategy of the rendering management submodule based on the current device's memory resources and viewpoint state. When the viewpoint arrives at a certain scene, the rendering management submodule loads the overall model's detailed levels based on information such as movement direction, speed, and dwell time. After acquiring the viewpoint's scene location, the memory management submodule adjusts the rendering management submodule's preloading strategy, dynamically switching to the focus-of detail loading strategy described in the current embodiment, and then switching back to the overall loading strategy after the viewpoint moves, in order to optimize memory usage and improve model loading performance.

[0054] This disclosure also provides a method for loading and managing special scenarios of a road network model, which utilizes the aforementioned road network model special scenario loading and management system.

[0055] This disclosure also provides a storage medium storing a computer program. When the computer program is executed by a processor, it can implement all the steps of the above-described method for loading and managing special scenarios of a road network model.

[0056] Those skilled in the art will understand that implementing all or part of the processes in a road network model special scene loading management method can be accomplished by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium. When executed, the program can include the processes of various embodiments of the road network model special scene loading management method. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0057] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps of the aforementioned method for loading and managing special scenarios in a road network model. In this application embodiment, the processor is the control center of the computer system; it can be a physical machine processor or a virtual machine processor.

[0058] Reference Figure 2 The electronic device 500 includes at least one processor 501, at least one communication interface 502, at least one memory 503, and at least one bus 504. The bus 504 is used for communication between these components, the communication interface 502 is used for signaling or data communication with other node devices, and the memory 503 stores machine-readable instructions executable by the processor 501. When the electronic device 500 is running, the processor 501 communicates with the memory 503 via the bus 504. When the machine-readable instructions are invoked by the processor 501, they execute the steps of the aforementioned road network model special scenario loading management method.

[0059] The electronic device 500 in this application embodiment includes, but is not limited to, mobile phones, tablet computers, computers, servers, etc.

[0060] The above content is merely an embodiment of the present invention. Commonly known structures and characteristics of the solutions are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are aware of all existing technologies in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can improve and implement this solution based on the guidance provided in this application and their own capabilities. Some typical known structures or methods should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A road network model special scene loading management system, characterized in that: It includes a model building module and a model loading module; the model building module is used to build a 3D road network model of the target area, adopting a multi-level detail model to divide the target area into several plots, and each plot is equipped with a dynamic scheduling model to manage and schedule 3D road network models of different levels of detail; the model loading module is used to match the corresponding level of detail 3D road network model for the surrounding plots according to the distance between the viewpoint and the plot, and load the model in blocks. The model loading module is also used to collect distance information between each viewpoint and the surrounding plots in the scene in real time, and combine the feature information of the 3D road network model on the plots to predict the best distance and viewing angle for the viewpoint to observe the 3D road network model. The feature information of the 3D road network model includes model type, model volume and model special features, and matches the corresponding level of detail of the 3D road network model according to the best distance and viewing angle. The model loading module is equipped with a distance prediction model. During model training, sample data with known optimal distance and viewpoint labels are used to adjust the model parameters so that the model can accurately predict the optimal observation distance and viewpoint. During the prediction process, the model first extracts features from the 3D road network model on the plot to obtain the model type, volume and other special information. The new viewpoint-distance combination is input into the model for prediction. Based on the input feature information and the learned parameters, the model calculates and outputs the optimal observation distance and viewpoint.

2. The road network model special scene loading management system according to claim 1, characterized in that: The model building module divides land parcels using polygons or based on roads.

3. The road network model special scene loading management system according to claim 1, characterized in that: The model loading module is also used to predict the loading time of the model based on network bandwidth and model file size. When the prediction result exceeds the set loading threshold, it adjusts the loading of a three-dimensional road network model with a lower level of detail.

4. The road network model special scene loading management system according to claim 3, characterized in that: The model loading module is also used to determine the user's attention to the current plot based on the dwell time of the viewpoint at the current position and the total angle of observation rotation. When the user has a high level of attention to the area, the initially matched high-detail model will be loaded.

5. The road network model special scene loading management system according to claim 1, characterized in that: The model loading module is also used to track the activity status of each viewpoint in the scene and dynamically load or unload the road network model according to the activity status.

6. The road network model special scene loading management system according to any one of claims 1 or 5, characterized in that: The model loading module is also used to cache the 3D road network model of each viewpoint in the scene and the surrounding land plots.

7. The road network model special scene loading management system according to claim 1, characterized in that: The model loading module is used to quickly retrieve nearby road network models based on the current viewpoint position, identify road feature information using road network model feature information, and predict the viewpoint movement direction and speed based on the current viewpoint position, road feature information, and viewpoint movement speed and acceleration. The model loading module preloads the 3D road network model of the plots that the viewpoint can observe according to the viewpoint movement direction, and selects 3D road network models with different levels of detail to load according to the viewpoint movement speed.

8. The road network model special scene loading management system according to any one of claims 1, 5 or 7, characterized in that: The model loading module is also used to integrate transition animations into the scene during the loading process, and to preload and cache the transition animations.

9. A method for loading and managing special scenarios in a road network model, characterized in that: The road network model special scenario loading management system as described in any one of claims 1-8 was used.

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