Virtual Aids to Navigation Full-process Automatic Control Method and System

Abstract

The present invention provides a full-process automated control method and system for virtual navigation aids, belonging to the technical field of data processing. Among them, to meet the requirements of the hoisting of the upper structure of bridges and the construction of port terminals, the present invention is based on the independently developed integrated intelligent production software for virtual navigation aids and put into production. The corresponding processing method involved can be presented in the form of software, and is written in the Python language. It is a multi-functional application software with a smooth interactive interface, convenient information editing, and efficient batch production. It mainly includes sub-functions such as virtual navigation aid distribution, automatic generation of navigational warnings and virtual navigation aid confirmation forms, etc. It can automatically associate with external production systems and office software. Through a single software operation interface, users can achieve diversified functions such as quick definition and editing of navigation aid parameters across multiple systems, intelligent compilation and generation of navigational warnings and navigation aid confirmation forms, etc. The virtual navigation aid information involved only needs to be filled in once and does not need to be entered repeatedly.

Description

Technical Field

[0001] The present invention relates to data processing technologies, and in particular, to a method and system for full-process automated control of virtual navigation aids. Background Art

[0002] In the shipping field, virtual navigation aids, as key facilities for ensuring the safety of ship navigation and optimizing waterway utilization, are becoming increasingly important. However, the current planning and management of virtual navigation aids still mainly rely on manual experience and traditional surveying and mapping methods, and there is a significant gap between this mode and the requirements of automated control.

[0003] When manually planning virtual navigation aids, restricted by the cognitive boundaries of humans, it is difficult to comprehensively analyze complex and variable marine environmental elements and inland water environmental factors. For example, the dynamic changes of water flow and the complex conditions of seabed and riverbed topography are difficult to accurately capture and process only by humans. Moreover, the manual planning efficiency is low, and it is difficult to quickly respond when virtual navigation aids need to be set in large sea areas, inland water areas or in emergency situations.

[0004] Traditional surveying and mapping technologies have inherent defects in data collection and processing, and the data accuracy and real-time performance are difficult to meet the requirements of automated control. As a result, the planning and layout of virtual navigation aids lack accuracy and cannot provide reliable data support for intelligent shipping systems.

[0005] With the intelligent upgrade of the transportation industry, the continuous growth of the number of ships and the continuous improvement of intelligent navigation requirements, higher requirements are put forward for the automated control ability of virtual navigation aids. If the full-process automation of virtual navigation aids from planning and design to dynamic adjustment cannot be achieved, it will not only fail to meet the development needs of intelligent shipping, but also restrict the improvement of ship navigation efficiency and safety.

[0006] Therefore, there is an urgent need for a method and system for full-process automated control of virtual navigation aids that can improve the effect of full-process automation. Summary of the Invention

[0007] Based on the above problems, the present invention is proposed to provide a method and system for full-process automated control of virtual navigation aids that can overcome the above problems or at least partially solve the above problems.

[0008] According to one aspect of the present invention, there is provided a method for full-process automated control of virtual navigation aids, including the following steps:

[0009] Establish a route model corresponding to the construction route of a construction project, and determine each different construction node included in the construction project;

[0010] In response to reaching any monitoring period, based on the current construction situation of each construction node, determine a virtual construction area in the route model, and form a virtual construction navigation aid for identifying the virtual construction area;

[0011] When it is determined that any navigation vessel is sailing on the construction route, construction prediction is performed on each construction node based on the time difference segment between the planned sailing time of the corresponding navigation vessel and the adjacent monitoring period, and virtual prediction buoys for identifying the virtual prediction area determined based on the prediction results are formed.

[0012] Optionally, in the method according to the present invention, a virtual construction area is determined in the route model based on the current construction situation of each construction node, and a virtual construction buoy for identifying the virtual construction area is formed, including:

[0013] Obtain the node coordinate points corresponding to each construction node, and control the drone to fly to the node coordinate points for collection to obtain the node images corresponding to each node coordinate point;

[0014] Determine the image construction area indicating the actual construction area in the node image, and generate each image point with the same point spacing based on the image contour of the corresponding image construction area;

[0015] Generate the image connection lines between each image point and the image center point of the corresponding image construction area, and determine the image extension points with a preset buoy spacing from the image points along the image extension direction of the image connection lines;

[0016] Based on the dimension conversion relationship between the node image and the route model, determine the construction extension points in the route model corresponding to each image extension point, and form a virtual construction buoy for identifying the virtual construction area corresponding to the image construction area based on the construction extension points.

[0017] Optionally, in the method according to the present invention, determining the image construction area indicating the actual construction area in the node image includes:

[0018] Perform image recognition on the node image, and determine whether there is an image shore area indicating the actual shore area in the node image based on the recognition result;

[0019] When it is determined that there is none, control the drone to perform successive ascending operations with a corresponding preset ascending height from the initial flight height, and perform collection based on each ascending operation to obtain the updated node image;

[0020] When it is determined that there is one, perform binarization processing on all other areas in the node image except the image shore area to obtain the water flow pixel points corresponding to the first pixel value and the noise pixel points corresponding to the second pixel value;

[0021] Connect the noise pixel points in the adjacent relationship, and determine the image noise area of the image points including the corresponding node coordinate points as the image construction area indicating the actual construction area.

[0022] Optionally, in the method according to the present invention, based on the construction extension points, a virtual construction navigation mark for identifying a virtual construction area corresponding to the image construction area is formed, and then it further includes:

[0023] Connect all the virtual construction navigation marks corresponding to the same virtual construction area adjacent to each other to obtain a navigation mark fence surrounding each virtual construction area;

[0024] In response to the existence of overlapping parts between different navigation mark fences, summarize all the navigation mark fences corresponding to the same overlapping part into the same navigation mark merging group;

[0025] Determine the route extension direction corresponding to the construction route based on the route model, and perform coordinate processing on the route model to obtain a model coordinate system, wherein the Y-axis in the model coordinate system is parallel to the route extension direction;

[0026] Obtain the model coordinate points of each navigation mark fence forming the same navigation mark merging group, and generate a horizontal merging line and a vertical merging line perpendicular to and parallel to the route extension direction based on the model coordinate points corresponding to the horizontal coordinate extreme values and vertical coordinate extreme values;

[0027] Generate a merging fence surrounding each navigation mark fence in the same navigation mark merging group based on the horizontal merging line and the vertical merging line, and form updated virtual construction navigation marks based on each merging point with the same point spacing in the merging fence.

[0028] Optionally, in the method according to the present invention, perform construction prediction on each construction node based on the time difference segment between the planned navigation time of the corresponding navigation vessel and the adjacent monitoring period, and form a virtual prediction navigation mark for identifying a virtual prediction area determined based on the prediction result, including:

[0029] Obtain the construction time period corresponding to each construction node, and summarize each construction node with different overlapping time periods between the construction time period and the time difference segment into a prediction group;

[0030] Determine the monitoring period adjacent to the planned navigation time as the target period, and determine the monitoring period before the target period as the comparison period;

[0031] Based on the route model, determine the regional cycle change between the virtual construction area corresponding to each construction node in the predicted group for the target period and the virtual construction area for the corresponding comparison period, and determine the ratio of the overlapping time period to the construction time period for the same construction node;

[0032] Based on the regional cycle change of each construction node, determine the regional time period change corresponding to the ratio of the time period, and perform construction prediction on the construction node based on the regional time period change, and form a virtual prediction beacon for identifying the virtual prediction area determined based on the prediction result.

[0033] Optionally, in the method according to the present invention, based on the regional cycle change of each construction node, determine the regional time period change corresponding to the ratio of the time period, and perform construction prediction on the construction node based on the regional time period change, and form a virtual prediction beacon for identifying the virtual prediction area determined based on the prediction result, including:

[0034] Based on each regional cycle change, determine the newly added construction area of the corresponding construction node, and generate each newly added point with the same point spacing based on the newly added contour of the corresponding newly added construction area;

[0035] Generate a newly added connection line between each newly added point and the newly added center point of the corresponding newly added construction area, and determine the newly added extension direction of the newly added connection line with the corresponding maximum line segment length as the newly added construction direction;

[0036] Based on the regional comparison between the virtual construction area for the corresponding comparison period and the virtual construction area for the corresponding target period, determine the regional overlapping segment, and determine the newly added construction distance between each newly added point and the regional overlapping segment based on the direction perpendicular to the newly added construction direction;

[0037] Perform a multiplication calculation on each newly added construction distance and the ratio of the time period, and determine each predicted point along the newly added construction direction based on the obtained predicted construction distance;

[0038] Connect the predicted points at adjacent positions, determine the virtual prediction area connected to the newly added construction area, and form a virtual prediction beacon for identifying the virtual prediction area.

[0039] Optionally, in the method according to the present invention, forming a virtual prediction beacon for identifying the virtual prediction area includes:

[0040] Generate a predicted connection line between each predicted point and the predicted center point of the corresponding virtual prediction area, and determine a predicted extension point with a preset beacon spacing from the predicted point along the predicted extension direction of the predicted connection line;

[0041] Based on the construction extension points, a virtual prediction navigation mark for identifying the virtual prediction area is formed, and pixel rendering with a corresponding first pixel value is performed on the virtual construction navigation mark, and pixel rendering with a corresponding second pixel value is performed on the virtual prediction navigation mark.

[0042] Optionally, in the method according to the present invention, the method further includes:

[0043] The navigation coordinate points of the navigation vessel are obtained in real time, a virtual vessel corresponding to the navigation vessel is established in the route model based on the navigation coordinate points, and the route model is sent to the navigation vessel for display.

[0044] The virtual construction navigation mark and the virtual prediction navigation mark corresponding to the same construction node are combined to obtain a virtual combined navigation mark;

[0045] Based on the route model, the route extension direction corresponding to the construction route is determined, and all passing areas for passing each virtual combined navigation mark are determined along the route extension direction;

[0046] The passing width in the corresponding route extension direction of each passing area is determined, and the passing area with a passing width greater than the vessel width of the corresponding navigation vessel is determined to have a passing attribute, otherwise it is determined to have a no-passing attribute;

[0047] In response to determining that the navigation distance between the virtual vessel and any virtual combined navigation mark along the route extension direction is less than a preset distance, all passing areas with passing attributes corresponding to the virtual combined navigation mark are filled with corresponding passing identifiers based on the route model.

[0048] Optionally, in the method according to the present invention, the method further includes:

[0049] The method further includes:

[0050] In response to multiple navigation vessels having the same planned navigation time, based on each virtual combined navigation mark, the passing areas with passing attributes corresponding to all navigation vessels are obtained respectively, and the number of vessels of all navigation vessels corresponding to the same passing area is determined;

[0051] When it is determined that the number of vessels corresponding to any passing area is greater than one, sorting is performed based on the navigation urgency of each navigation vessel to obtain a navigation order,

[0052] Pixel rendering with different identification pixel values is performed on each navigation vessel. In response to determining that any navigation vessel passes through the passing area based on the navigation order, pixel rendering of the corresponding identification pixel value is performed on the passing identifier.

[0053] In response to multiple sailing vessels passing through the same passage area at any moment, the corresponding warning identifiers will be filled in for the corresponding passage area.

[0054] According to another aspect of the present invention, there is provided a virtual navigation mark full-process automated control system, including:

[0055] A model establishment module, configured to establish a navigation route model corresponding to the construction route of a construction project and determine each different construction node included in the construction project;

[0056] A construction navigation mark module, configured to respond to the arrival of any monitoring period, determine a virtual construction area in the navigation route model based on the current construction situation of each construction node, and form a virtual construction navigation mark for identifying the virtual construction area;

[0057] A predicted navigation mark module, configured to when it is determined that any sailing vessel is sailing on the construction route, perform construction prediction on each construction node based on the time difference segment between the planned sailing time of the corresponding sailing vessel and the adjacent monitoring period, and form a virtual predicted navigation mark for identifying the virtual predicted area determined based on the prediction result.

[0058] According to the technical solution of the present application, first of all, by establishing a navigation route model and determining construction nodes, it can lay a foundation for subsequent precise control. On this basis, virtual construction navigation marks are generated according to the construction situation. With the help of drones to collect images and precise image processing technology, the boundary of the construction area can be accurately defined, enabling passing vessels to clearly understand the dangerous range, effectively avoiding accidentally entering the construction area, and ensuring navigation safety; when there is a vessel sailing, the server can perform construction prediction based on the time difference between the planned sailing time and the monitoring period, and generate virtual predicted navigation marks. This measure enables the crew to know in advance the change trend of the construction area and plan a safe route in advance, further reducing potential risks and improving the safety and smoothness of navigation; in addition, the coordinates of the sailing vessel are obtained in real time and a virtual vessel is established, the passage area is determined by combining the virtual construction area and the predicted area, and the passage attribute is judged according to the width of the passage area and the width of the vessel. This not only provides intuitive and clear navigation guidance for the crew, improves navigation efficiency, but also can sort based on the navigation urgency when multiple vessels pass, reasonably arrange the passage order, ensure that vessels on urgent tasks pass first, maintain the overall order of water traffic, comprehensively improve the navigation safety management level during water construction, optimize the utilization efficiency of waterway resources, and achieve the automated control effect of virtual navigation marks. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 The flowchart of the virtual navigation mark full-process automated control method according to an embodiment of the present invention is shown;

[0060] Figure 2Shows a schematic diagram of the node image in this embodiment;

[0061] Figure 3 Shows a structural block diagram of a virtual navigation mark full-process automated control system according to another embodiment of the present invention. Detailed implementation manners

[0062] Hereinafter, exemplary embodiments of the present disclosure will be described in more detail with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be fully conveyed to those skilled in the art.

[0063] To solve the problems existing in the above-mentioned prior art, the inventors propose a solution of the present invention. An embodiment of the present invention provides a virtual navigation mark full-process automated control method, which can be executed in a computing device. Herein, the computing device can be understood as a terminal with data processing functions, such as a mobile phone or a computer.

[0064] It can be stated that to meet the requirements of the hoisting of the upper structure of a bridge and the construction of a port terminal, this embodiment is based on the independently developed virtual navigation mark integrated intelligent production software and put into production. Among them, the corresponding processing methods involved can be presented in the form of software, and are written based on the Python language. It is a multi-functional application software with a smooth interactive interface, convenient information editing, and efficient batch production. It mainly includes sub-functions such as virtual navigation mark distribution, automatic generation of waterway notices and virtual navigation mark confirmation forms, etc. It can automatically associate with external production systems and office software. Through a single software operation interface, users can realize functions such as quick definition and editing of navigation mark parameters across multiple systems, intelligent writing and generation of waterway notices and navigation mark confirmation forms, etc. The virtual navigation mark information involved only needs to be filled in once and does not need to be entered repeatedly; among them, each sub-function can be used jointly according to the requirements of hoisting construction, or can be applied separately according to other actual needs.

[0065] Figure 1 Shows a flowchart of a virtual navigation mark full-process automated control method provided in this embodiment, as Figure 1 shown, the method starts from step S101, and in step S101, it includes the following contents:

[0066] Establish a route model corresponding to the construction route of the construction project, and determine each different construction node included in the construction project.

[0067] For example, in this embodiment, a construction project can be understood as a construction plan pre-planned and generated by engineering personnel for route construction of a construction route. Route construction can include bridge construction, wharf construction, etc. on the construction route. And, to ensure the orderly progress of the construction project, generally, a construction project can have different construction nodes. Each construction node can be understood as corresponding to different construction contents carried out at different route positions. For example, along the route extension direction of the construction route, the construction route can be correspondingly divided into three route parts. By establishing different construction nodes based on the three route parts, different construction contents can be constructed based on different construction nodes during the actual construction process.

[0068] It can be explained that when engineering personnel carry out route construction based on a construction project, as the construction progress of the route construction advances, corresponding construction areas will be formed on the construction route. And according to different construction progress, the area size corresponding to each construction area may also change accordingly. For example, during the construction of a navigation wharf, as the construction progress advances, the construction area corresponding to the navigation wharf will continuously expand its area size until a complete navigation wharf is finally formed. In this case, if any navigation vessel needs to navigate via the construction route, in order to avoid corresponding collision situations between the navigation vessel and the construction area during navigation, therefore, it is necessary to establish corresponding construction navigation aids based on the construction area to identify the construction area. And to improve the warning effect of the corresponding construction navigation aids, in this embodiment, the corresponding construction navigation aids can be displayed in an online form to help the navigation vessel more intuitively obtain the relative position between the navigation vessel and the construction navigation aids.

[0069] Based on the above content, in order to display the corresponding generated construction navigation aids in an online form in this embodiment, the digital twin data of the corresponding construction route can be first obtained, and an airway model corresponding to the construction route can be established based on the digital twin data, so as to complete the online form display of the construction route, and further realize the online form display of the construction navigation aids in the subsequent process.

[0070] In step S102, it includes the following contents:

[0071] In response to the arrival of any monitoring period, based on the current construction situation of each construction node, determine a virtual construction area in the airway model and form a virtual construction navigation aid for identifying the virtual construction area.

[0072] For example, in this embodiment, since the construction navigation mark is used to identify the construction area, and the area size of the construction area corresponding to each construction node may also change as the construction progress advances. Therefore, in order to regularly determine and monitor the construction situation (i.e., the corresponding area size) of each construction area, a corresponding regular monitoring task can be established. Among them, the regular monitoring task can be carried out based on different monitoring cycles. Based on the general construction time and rest time, the monitoring cycle can be set, for example, at 6:00 am every day, that is, the construction situation of each construction area will be monitored at 6:00 am every day. Thus, based on the currently obtained construction situation corresponding to each construction node, a virtual construction area is determined in the route model established in the previous step, and a virtual construction navigation mark for identifying it is formed based on the area location and area size of the virtual construction area.

[0073] Furthermore, in this embodiment, the above-mentioned "determining a virtual construction area in the route model based on the current construction situation of each construction node and forming a virtual construction navigation mark for identifying the virtual construction area" may further include the following steps:

[0074] Obtain the node coordinate points corresponding to each construction node, and control the drone to fly to the node coordinate points for collection to obtain the node images corresponding to each node coordinate point;

[0075] Determine the image construction area indicating the actual construction area in the node image, and generate each image point with the same point spacing based on the image contour of the corresponding image construction area;

[0076] Generate an image connection line between each image point and the image center point of the corresponding image construction area, and determine an image extension point with a preset navigation mark spacing from the image point along the image extension direction of the image connection line;

[0077] Based on the dimension conversion relationship between the node image and the route model, determine the construction extension points corresponding to each image extension point in the route model, and form a virtual construction navigation mark for identifying the virtual construction area corresponding to the image construction area based on the construction extension points.

[0078] For example, in this embodiment, the specific process of monitoring the current construction situation of each construction node for the corresponding regular monitoring task and forming a virtual construction navigation mark based on the determined virtual construction area can be based on the following content:

[0079] First, obtain the node coordinate points corresponding to each construction node. For example, use high-precision positioning technology (GPS) to accurately determine these coordinates. Here, the node coordinate points can be understood as the starting points of construction corresponding to each construction node, that is, the subsequent formed construction areas should all be constructed based on the corresponding construction starting points;

[0080] Then, the server can control the drone to fly to the node coordinate points for collection. Here, it can be stated that the drone can be equipped with high-resolution image acquisition equipment to obtain clear and accurate node images corresponding to each node coordinate point. The beneficial effect of this step is that by collecting images with the drone, real-time image information of the construction area can be obtained efficiently and comprehensively. Compared with on-site manual investigation, it not only improves the efficiency of information collection but also ensures personnel safety and avoids potential dangers caused by the complex environment of the construction area to personnel;

[0081] Next, determine the image construction area in the node image that indicates the actual construction area, and after identifying the image construction area, generate each image point with the same point spacing based on the image contour of the corresponding image construction area. It can be stated that through the evenly distributed image point settings, it provides a basis for more accurately determining the boundary of the virtual construction area in the future, enabling the division of the virtual construction area to be more accurate and reducing errors;

[0082] Subsequently, the server can generate an image connection line between each image point and the image center point of the corresponding image construction area, and determine an image extension point with a preset navigation mark spacing from the image point along the image extension direction of the image connection line. Such an operation can reasonably expand the identification range of the virtual construction area according to the shape and characteristics of the image construction area, enabling the virtual construction navigation mark to cover the actual construction area more comprehensively and effectively reminding passing ships to pay attention to avoidance;

[0083] Finally, based on the dimension conversion relationship between the node image and the route model, determine the construction extension points in the route model corresponding to each image extension point, and further form a virtual construction navigation mark for marking the virtual construction area corresponding to the image construction area based on the construction extension points. That is, in this embodiment, through accurate dimension conversion, the image information and the route model are combined, and the generated virtual construction navigation mark can accurately mark the construction area in the route model, providing an intuitive and accurate navigation warning for sailing ships, greatly improving the navigation safety and management efficiency during the channel construction period.

[0084] Furthermore, in this embodiment, the above "determine the image construction area in the node image that indicates the actual construction area" may further include the following steps:

[0085] Perform image recognition on the node image, and determine whether there is an image shore area indicating the real shore area based on the recognition result;

[0086] When it is determined that there is none, control the drone to perform ascending operations corresponding to the preset ascending height successively from the initial flight height, and perform acquisition based on each ascending operation to obtain an updated node image;

[0087] When it is determined that there is one, perform binarization processing on all other areas of the node image except the image shore area to obtain water flow pixel points corresponding to the first pixel value and noise pixel points corresponding to the second pixel value;

[0088] Connect the positions of adjacent noise pixel points, and determine the image noise area containing the image position points corresponding to the node coordinate points as the image construction area indicating the actual construction area.

[0089] For example, in this embodiment, after obtaining the corresponding node image, determining the image construction area indicating the actual construction area based on the node map image can be specifically implemented based on the following content:

[0090] First, the server can further perform image recognition on the node image. By using an advanced image recognition algorithm, it is determined whether there is an image shore area indicating the real shore area based on the recognition result. That is, through accurate image recognition, the shore area information in the image can be quickly screened out, laying a foundation for accurately judging the construction area subsequently, improving the accuracy and efficiency of the construction area judgment. Here, the recognition of the real shore area can be performed based on an image recognition model obtained through model training methods such as a neural network learning model or a machine learning model;

[0091] Then, when it is determined that there is no image shore area, the drone can be correspondingly controlled to perform ascending operations corresponding to the preset ascending height successively from the initial flight height, and perform acquisition based on each ascending operation to obtain an updated node image. That is, when the image obtained from the initial height cannot recognize the shore area, the drone can be controlled to ascend to collect new images, correspondingly expanding the image acquisition range, obtaining more comprehensive scene information, and avoiding missing all areas of the actual construction area due to shooting angle or range limitations, so as to ensure that the complete construction area can be accurately determined;

[0092] Next, when the server determines that there is an image berthing area, all other areas of the node image except the image berthing area can be binarized to obtain water flow pixel points corresponding to the first pixel value and noise pixel points corresponding to the second pixel value. Binarization can simplify complex image information, highlight water flow pixel points and noise pixel points, facilitate subsequent extraction of the construction area, and improve the efficiency and pertinence of image processing;

[0093] Subsequently, the noise pixel points in the adjacent relationship are connected point by point, and the image noise area containing the image point positions corresponding to the node coordinate points is determined as the image construction area indicating the actual construction area. That is, the construction area can be determined by connecting adjacent noise pixel points. The relevance between noise pixel points and the construction area can be utilized to accurately lock the scope of the construction area under the condition of excluding the interference of the berthing area and water flow pixel points, providing a reliable basis for generating virtual construction navigation marks based on this area later, ensuring the accuracy of the virtual navigation mark indicating the construction area, and then effectively guiding passing ships to avoid the construction area and ensuring navigation safety.

[0094] For example, Figure 2 shows a schematic diagram of the node image in this embodiment. Based on Figure 2 the content, it can be seen that there is an image construction area in the node image, and the image construction area roughly corresponds to the middle of the construction route.

[0095] It can be explained that in the actual application scenario, when any sailing ship sails on the construction route, if there is a corresponding construction area on the construction route, the sailing ship needs to avoid the construction area to sail to ensure that there is no corresponding collision between the sailing ship and the construction area. And if the distance between at least two virtual construction areas is relatively close, there may be an overlap of virtual construction navigation marks corresponding to different virtual construction areas. In this case, in order to further improve the integration of virtual construction navigation marks and the navigation safety of corresponding sailing ships, in this embodiment, after "forming a virtual construction navigation mark for identifying the virtual construction area corresponding to the image construction area based on the construction extension point positions", the following steps can be further included:

[0096] Connect the virtual construction navigation marks adjacent to each other corresponding to the same virtual construction area to obtain a navigation mark fence surrounding each virtual construction area;

[0097] In response to the existence of an overlapping part between different navigation mark fences, summarize all the navigation mark fences corresponding to the same overlapping part into the same navigation mark merging group;

[0098] Determine the route extension direction corresponding to the construction route based on the route model, and perform coordinate transformation on the route model to obtain a model coordinate system, wherein the Y-axis in the model coordinate system is parallel to the route extension direction;

[0099] Obtain the model coordinate points of each beacon fence that makes up the same beacon merging group, and generate a horizontal merging line and a vertical merging line perpendicular to and parallel to the route extension direction based on the model coordinate points corresponding to the extreme horizontal coordinates and extreme vertical coordinates;

[0100] Generate a merged fence that encloses each beacon fence in the same beacon merging group based on the horizontal merging line and the vertical merging line, and form updated virtual construction beacons based on each merged point with the same point spacing in the merged fence.

[0101] For example, in this embodiment, in the case where the corresponding virtual construction beacons overlap due to the small distance between at least two different virtual construction areas, the virtual construction beacons can be updated accordingly based on the following content:

[0102] First, the server connects all the virtual construction beacons corresponding to the same virtual construction area. It should be noted that in a complex water construction environment, the information provided by a single virtual construction beacon is limited. By connecting the beacons in the same virtual construction area, a closed beacon fence can be formed, thus clearly and explicitly outlining the boundary of the virtual construction area, providing a more intuitive and comprehensive warning for passing ships, and effectively reducing the risk of ships straying into the construction area. This step significantly improves the visualization degree and warning effect of the construction area identification, and ensures the navigation safety of passing ships;

[0103] Then, it is possible to determine whether there is an overlapping part between the beacon fences based on the relative positions of each beacon fence, and in response to the existence of an overlapping part between different beacon fences, summarize all the beacon fences corresponding to the same overlapping part into the same beacon merging group; it should be noted that in actual construction, due to the complexity and diversity of the construction area, the virtual construction areas set in different construction stages or different construction tasks may overlap. Therefore, summarizing the beacon fences in the overlapping part can uniformly manage these complex areas, avoid the identification confusion caused by multiple independent fences, and improve the systematicness and orderliness of the virtual construction area management;

[0104] Next, the server can further determine the route extension direction corresponding to the construction route based on the route model, and perform coordinate transformation on the route model to obtain a model coordinate system, where the Y-axis in the model coordinate system is parallel to the route extension direction. Here, by establishing such a model coordinate system, a standardized reference framework can be provided for subsequent coordinate calculations and navigation mark positioning, enabling all position information to be accurately analyzed and calculated in a unified coordinate system when dealing with complex construction areas and navigation routes, greatly improving the accuracy and efficiency of construction area marking and navigation management.

[0105] Subsequently, the server can obtain the model coordinate points of each navigation mark fence that makes up the same navigation mark merging group, and generate a horizontal merging line perpendicular to the route extension direction and a vertical merging line parallel to the route extension direction based on the model coordinate points corresponding to the horizontal coordinate extreme values (including the maximum horizontal coordinate and the minimum horizontal coordinate) and the vertical coordinate extreme values (including the maximum vertical coordinate and the minimum vertical coordinate). That is, generating merging lines using coordinate extreme values can accurately determine the boundary range of the overlapping area, further optimizing the definition of complex construction areas and providing an accurate basis for generating a unified merging fence subsequently.

[0106] Finally, a merging fence surrounding each navigation mark fence in the same navigation mark merging group is generated based on the horizontal merging line and the vertical merging line, and an updated virtual construction navigation mark is formed based on each merging point with the same point spacing within the merging fence. By generating the merging fence and updating the virtual construction navigation mark, the originally complex and overlapping construction area markings can be integrated into a clear and unified marking, avoiding navigation misguidance caused by chaotic navigation mark settings, further enhancing the guiding effect on passing ships, ensuring the safe and orderly passage of the waterway during construction, and also improving the navigation safety of the corresponding navigating ships.

[0107] In step S103, the following content is included:

[0108] When it is determined that any navigating ship is sailing on the construction route, construction prediction is performed on each construction node based on the time difference segment between the planned sailing time of the corresponding navigating ship and the adjacent monitoring period, and a virtual prediction navigation mark for marking the virtual prediction area determined based on the prediction result is formed.

[0109] For example, in this embodiment, based on the above content and the relevant content of step S103, it can be known that there may be corresponding navigation vessels sailing on the corresponding construction route at any time. Among them, the navigation purposes of the navigation vessels may correspondingly include transporting goods or passengers, etc.; and when any navigation vessel is determined to be sailing on the construction route, the server can contact the navigation vessel or pre-contact the management end of the corresponding construction route to obtain the planned navigation time corresponding to the navigation route. The planned navigation time can be understood as the starting time of the navigation of the corresponding navigation vessel; based on the foregoing content, in this embodiment, since the area size of the virtual construction area is determined based on the monitoring of the corresponding monitoring period, that is, the area size of the virtual construction area indicates the construction situation of each monitoring period. Therefore, in order to determine the construction situation at the planned navigation time, it is necessary to use the time difference segment between the planned navigation time and the adjacent monitoring period (for example, the planned navigation time is 10:00 am on April 20, and the adjacent monitoring period is 6:00 am on April 20) to predict the construction of each construction node, so as to determine the virtual prediction area based on the prediction result, and further form a virtual prediction navigation mark for identifying the virtual prediction area, so as to help the navigation vessel understand the real-time construction situation based on the virtual prediction navigation mark and improve the navigation safety of the navigation vessel.

[0110] Further, in this embodiment, the above "predict the construction of each construction node based on the time difference segment between the planned navigation time of the corresponding navigation vessel and the adjacent monitoring period, and form a virtual prediction navigation mark for identifying the virtual prediction area determined based on the prediction result" may further include the following steps:

[0111] Obtain the construction time period corresponding to each construction node, and summarize each construction node with different overlapping time periods between the construction time period and the time difference segment into a prediction group;

[0112] Determine the monitoring period adjacent to the planned navigation time as the target period, and determine the monitoring period before the target period as the comparison period;

[0113] Based on the route model, determine the regional cycle change between the virtual construction area corresponding to the target period and the virtual construction area corresponding to the comparison period for each construction node in the prediction group, and determine the ratio of the overlapping time period to the construction time period for the same construction node;

[0114] Based on the regional cycle change of each construction node, determine the regional time period change of the corresponding ratio of the time period, and predict the construction of the construction node based on the regional time period change, and form a virtual prediction navigation mark for identifying the virtual prediction area determined based on the prediction result.

[0115] For example, in this embodiment, the formation process of the virtual prediction navigation mark can be specifically implemented based on the following content:

[0116] First, the server can obtain the construction time period corresponding to each construction node. Through channels such as the planning documents and progress arrangement records of the construction project, these information can be accurately obtained. Here, the construction time period is also the regular construction time corresponding to the construction node, for example, from 8:00 am to 6:00 pm every day;

[0117] Then, the server aggregates each construction node with different overlapping time periods between the corresponding construction time period and the time difference period into a prediction group. It can be noted that through this step, the construction nodes that may be in a construction state change near the planned navigation time of the sailing vessel can be screened out, focusing on the key nodes for subsequent analysis, avoiding ineffective calculations for irrelevant nodes, improving the pertinence and efficiency of construction prediction, and helping to accurately grasp the dynamics of the construction area that may affect navigation safety;

[0118] Next, the server can determine the monitoring period close to the planned navigation time as the target period, and determine the monitoring period before the target period as the comparison period. By clarifying the target period and the comparison period, a time reference benchmark is provided for subsequent analysis of the changes in the construction area. Further, by comparing the construction area conditions in different periods, the development trend of the construction area can be effectively mined, providing reliable data support for construction prediction, making the prediction result more consistent with the actual construction progress change, and enhancing the warning accuracy for sailing vessels;

[0119] Subsequently, the server determines the regional cycle change between the virtual construction area corresponding to the target period and the virtual construction area corresponding to the comparison period for each construction node in the prediction group based on the route model, and determines the time period ratio between the overlapping time period and the construction time period corresponding to the same construction node; Here, by analyzing the regional cycle change, the expansion, contraction or position change of the construction area in different monitoring periods can be intuitively understood; and calculating the time period ratio can quantify the correlation degree between the planned navigation time of the sailing vessel and the construction time of the construction node. And the acquisition of these two data lays a foundation for more accurately predicting the future state of the construction node, improving the scientificity and reliability of construction prediction, and enabling the sailing vessel to know in advance the possibility and degree of the change in the construction area;

[0120] Finally, after completing the periodic change of the corresponding area and the time period ratio, it is possible to further determine the area time period change of the corresponding time period ratio based on the periodic change of each construction node area, and perform construction prediction on the construction node based on the area time period change, and form a virtual prediction beacon for identifying the virtual prediction area determined based on the prediction result; that is, the server can more accurately predict the construction state of the construction node near the planned navigation time of the navigation vessel by comprehensively considering the area time period change obtained from the area periodic change and the time period ratio, thereby determining the virtual prediction area, and the virtual prediction beacon generated based on the virtual prediction area provides an early warning for the navigation vessel, helps the crew plan the navigation route in advance, and avoid potential construction dangerous areas, greatly ensuring the safety and smoothness of the waterway navigation.

[0121] Furthermore, in this embodiment, the above "determine the area time period change of the corresponding time period ratio based on the periodic change of each construction node area, and perform construction prediction on the construction node based on the area time period change, and form a virtual prediction beacon for identifying the virtual prediction area determined based on the prediction result" may further include the following steps:

[0122] Determine the newly added construction area of the corresponding construction node based on each area periodic change, and generate each newly added point with the same point spacing based on the newly added contour of the corresponding newly added construction area;

[0123] Generate a newly added connection line between each newly added point and the newly added center point of the corresponding newly added construction area, and determine the newly added extension direction of the newly added connection line with the corresponding maximum line segment length as the newly added construction direction;

[0124] Determine the area overlap segment based on the area comparison between the virtual construction area of the corresponding comparison period and the virtual construction area of the corresponding target period, and determine the newly added construction distance between each newly added point and the area overlap segment based on the direction perpendicular to the newly added construction direction;

[0125] Perform a product calculation on each newly added construction distance and the time period ratio, and determine each prediction point along the newly added construction direction based on the obtained predicted construction distance;

[0126] Connect each prediction point at adjacent positions, determine the virtual prediction area connected to the newly added construction area, and form a virtual prediction beacon for identifying the virtual prediction area.

[0127] For example, in this embodiment, after obtaining the periodic change of each construction node area, the construction prediction of the construction node can be performed based on the area periodic change through the following content to further form the corresponding virtual prediction beacon:

[0128] First, through the periodic change of each area, the newly added construction area corresponding to the construction node can be determined. Further, by comparing and analyzing the construction area data of different monitoring periods, the expanded or newly opened parts of the construction area, that is, the newly added construction area, can be accurately identified.

[0129] Then, based on the newly added contour of the corresponding newly added construction area, each newly added point with the same point spacing can be generated. Here, the evenly distributed newly added points can provide key nodes for accurately determining the construction direction and predicting the area in the follow-up, which helps to depict the characteristics of the newly added construction area more meticulously, improve the accuracy and reliability of the prediction, and provide more accurate construction area boundary information for passing ships.

[0130] Next, based on the obtained newly added points, the newly added connection lines between each newly added point and the newly added center point of the corresponding newly added construction area can be further generated, and the newly added extension direction of the newly added connection line with the corresponding maximum line segment length can be determined as the newly added construction direction. Clearly defining the newly added construction direction is crucial for accurately predicting the expansion trend of the construction area. It can help judge the main advancing direction of the construction activities, enable passing ships to know in advance the possible expanding direction of the construction area, so as to plan a safer navigation route in advance and effectively avoid navigation risks caused by changes in the construction area.

[0131] Subsequently, the server can determine the corresponding area overlap segment based on the area comparison between the virtual construction area of the corresponding comparison period and the virtual construction area of the corresponding target period, and determine the newly added construction distance between each newly added point and the area overlap segment based on the direction perpendicular to the newly added construction direction. Here, determining the area overlap segment can understand the relatively stable part of the construction area in different periods, and the determination of the newly added construction distance quantifies the relative position relationship between the newly added points and the existing construction area. These data provide an important basis for further accurately predicting the change range of the construction area, enhance the scientificity and practicality of the prediction results, and ensure the safety of passing ships' navigation.

[0132] After that, each newly added construction distance can be multiplied by the time period ratio, and each predicted point can be determined along the newly added construction direction based on the obtained predicted construction distance. It should be noted that by calculating in combination with the newly added construction distance and the time period ratio, the association between the planned navigation time of the sailing ship and the construction progress is fully considered, making the determination of the predicted points more in line with the actual construction situation, more accurately reflecting the possible position of the construction area when the ship is sailing, and providing a more timely and effective warning for the ship.

[0133] Finally, the server can connect each predicted point in adjacent positions to determine a virtual predicted area connected to the newly added construction area, and further form a virtual predicted navigation mark for identifying the virtual predicted area. Here, connecting the predicted points to form a virtual predicted area and setting a virtual predicted navigation mark can visually show the possible range of the future construction area to passing ships, enabling the crew on the sailing ships to clearly identify and avoid potential dangerous areas during navigation, greatly improving the navigability and orderliness of the waterway during water construction.

[0134] Furthermore, in this embodiment, the above "forming a virtual predicted navigation mark for identifying the virtual predicted area" may further include the following steps:

[0135] Generate a predicted connection line between each predicted point and the predicted center point of the corresponding virtual predicted area, and determine a predicted extension point with a preset navigation mark spacing from the predicted point along the predicted extension direction of the predicted connection line;

[0136] Based on the construction extension points, form a virtual predicted navigation mark for identifying the virtual predicted area, and perform pixel rendering with a corresponding first pixel value on the virtual construction navigation mark and pixel rendering with a corresponding second pixel value on the virtual predicted navigation mark.

[0137] For example, in this embodiment, forming a virtual predicted navigation mark based on the virtual predicted area can be specifically implemented based on the following content:

[0138] First, the server can generate a predicted connection line between each predicted point and the predicted center point of the corresponding virtual predicted area. By determining these predicted connection lines, the relative position relationship between each predicted point and the center of the virtual predicted area can be clearly defined, providing a geometric reference for subsequent determination of the navigation mark position, and this helps to more accurately plan the distribution of the virtual predicted navigation marks, enabling the navigation marks to closely surround the virtual predicted area and improving the warning effect on passing ships;

[0139] Then, further determine a predicted extension point with a preset navigation mark spacing from the predicted point along the predicted extension direction of the predicted connection line. In this embodiment, the preset navigation mark spacing is determined according to the navigation safety requirements of passing ships and the environmental factors of the actual waterway. Determining the predicted extension points in this way can ensure the rationality of the navigation mark distribution while ensuring that passing ships have sufficient time and space to react to the navigation marks during navigation, plan an avoidance route in advance, and effectively prevent ships from straying into the virtual predicted area, ensuring navigation safety;

[0140] Next, the server can form virtual prediction buoys for identifying the virtual prediction area based on the construction extension points. Here, the construction extension points are key positions closely related to the actual construction area. Based on these points, virtual prediction buoys are formed, establishing a direct connection between the virtual prediction buoys and the actual construction area, improving the accuracy and reliability of the virtual prediction buoys in predicting the construction area. Past sailing vessels can intuitively understand the approximate scope of the future construction area through these virtual prediction buoys, thus better planning their sailing routes.

[0141] Finally, in order to distinguish between virtual construction buoys and virtual prediction buoys, pixel rendering corresponding to the first pixel value can be performed on the virtual construction buoys, and pixel rendering corresponding to the second pixel value can be performed on the virtual prediction buoys. That is, different pixel values are used for rendering, which can distinguish virtual construction buoys and virtual prediction buoys by different colors or brightness in the navigation equipment or monitoring system of the sailing vessel. This enables the crew to quickly identify different types of buoys when viewing navigation information, clearly distinguish the current construction area and the possible future construction area, avoid confusion, and further improve the safety and navigation efficiency during the sailing process.

[0142] In addition, in this embodiment, when a sailing vessel sails on a construction route, it needs to avoid each actual construction area on the construction route to ensure its sailing safety. Since the actual construction area has a certain floor area, therefore, along the heading extension direction of the corresponding construction route, the construction route can be divided based on the actual construction area to obtain corresponding passable areas. In order to determine whether each sailing vessel can pass through the corresponding sailing area and further indicate the sailing vessel based on the determination result, in this embodiment, the following steps may further be included:

[0143] Obtain the sailing coordinate points of the sailing vessel in real time, establish a virtual vessel corresponding to the sailing vessel based on the sailing coordinate points in the route model, and send the route model to the sailing vessel for display.

[0144] Combine the virtual construction buoys and virtual prediction buoys corresponding to the same construction node to obtain virtual combined buoys;

[0145] Determine the route extension direction corresponding to the construction route based on the route model, and determine all passable areas for passing each virtual combined buoy along the route extension direction;

[0146] Determine the passing width of each passable area in the corresponding route extension direction, and determine the passable areas with a passing width greater than the vessel width of the corresponding sailing vessel as having a passing attribute, and vice versa as having a non-passing attribute;

[0147] When it is determined that the sailing distance between the virtual vessel and any virtual combined navigation buoy is less than the preset distance along the extending direction of the route, all the passing areas with passing attributes corresponding to the virtual combined navigation buoy are filled with corresponding passing identifiers based on the route model.

[0148] For example, in this embodiment, the acquisition of the passing area and the indication of the sailing vessel based on the passing area can be implemented based on the following specific process:

[0149] First, the server can obtain the sailing coordinate points of the sailing vessel in real time. For example, by means of a high-precision positioning system (Global Navigation Satellite System (GNSS)), continuously and accurately collect the position data of the sailing vessel. Based on these real-time obtained sailing coordinate points, a virtual vessel corresponding to the sailing vessel is established in the pre-constructed route model, which can accurately map the real sailing vessel into the route model, providing an intuitive digital object for subsequent sailing analysis and guidance, and facilitating the monitoring center and the vessel itself to grasp the position status of the vessel near the construction area in real time.

[0150] Subsequently, the server can send the generated route model to the sailing vessel for display, so that the crew can directly view the route model including the position of their own vessel on the ship, clearly understand the surrounding construction area and potential hazards, and thus make reasonable sailing decisions in a timely manner, effectively improving the safety and autonomy of sailing.

[0151] Then, the virtual construction navigation buoy and the virtual prediction navigation buoy corresponding to the same construction node are combined to obtain a virtual combined navigation buoy. Through this combination method, the formed virtual construction navigation buoy and virtual prediction navigation buoy can be integrated based on the current state and the possible future change range of the construction area, forming a more comprehensive and forward-looking regional representation; it helps to uniformly manage and analyze the construction area, and at the same time enables the sailing vessel to understand all the potential impact areas related to the same construction node at one time, avoiding judgment errors caused by scattered information, and improving the accuracy and reliability of sailing planning.

[0152] Next, based on the route model, determine the extending direction of the route corresponding to the construction route, and along this route extending direction, determine all the passing areas for passing each virtual combined navigation buoy. By accurately determining the route extending direction and the passing area, it provides key basic information for evaluating whether the sailing vessel can safely pass through the construction area, which enables considering the actual situation of the construction area when planning the sailing route, reasonably selecting a feasible passing path, and avoiding getting into dangerous areas due to blindly choosing a route, ensuring the smoothness and safety of sailing.

[0153] Subsequently, the passing width corresponding to the extending direction of the route for each passing area is determined. Based on the comparison result between the passing width and the width of the navigating vessel, the passing area where the passing width is greater than the width of the corresponding navigating vessel is determined to have a passing attribute, and vice versa, it is determined to have a no-passing attribute. That is, by accurately quantifying the size of the passing area and judging its passing attribute, a clear quantitative basis is provided for navigation decision-making. The crew can quickly judge which areas can be safely passed and which areas need to be avoided based on this information, greatly improving the efficiency and accuracy of navigation decision-making and effectively reducing navigation risks;

[0154] Finally, when the server responds that the navigation distance between the virtual vessel and any virtual combined navigation mark along the extending direction of the route is less than the preset distance, all passing areas with passing attributes corresponding to the virtual combined navigation mark are filled with corresponding passing identifiers (such as corresponding eye-catching symbols, such as exclamation marks, etc.) based on the route model. That is, when the navigating vessel approaches the construction area, this timely identifier filling operation can highlight the passable areas in the route model, providing clear navigation guidance for the crew, helping them quickly find safe passing areas, and avoiding wasting time in searching for a feasible route in case of an emergency, further ensuring the safety and efficiency of the vessel's navigation near the construction area.

[0155] It can be explained that since there may be multiple different navigating vessels sailing on the construction route during the same time period, resulting in congestion on the construction route. In this case, the following method steps can be used to recommend and indicate the corresponding passing areas for each navigating vessel to alleviate the congestion of the construction route as much as possible and improve the navigation safety of the navigating vessels:

[0156] In response to multiple navigating vessels having the same planned sailing time, based on each virtual combined navigation mark, obtain the passing areas with passing attributes corresponding to each navigating vessel respectively, and determine the number of vessels corresponding to the same passing area;

[0157] When it is determined that the number of vessels corresponding to any passing area is greater than one, sort them based on the navigation urgency of each navigating vessel to obtain the navigation order.

[0158] Perform pixel rendering with different identification pixel values for each navigating vessel. In response to determining that any navigating vessel passes through the passing area based on the navigation order, perform pixel rendering of the passing identifier with the corresponding identification pixel value.

[0159] For example, in this embodiment, in order to enable multiple navigating vessels to pass through the same passing area in an orderly manner, it can be specifically implemented based on the following method:

[0160] First, when the server determines that multiple sailing vessels have the same planned sailing time, it can respond to this situation by obtaining the passing areas with passing attributes corresponding to each sailing vessel based on each virtual combined navigation mark, and determining the number of vessels corresponding to the same passing area; that is, in the actual port operation scenario, the sailing plans of different vessels may overlap, and it is crucial to obtain this information at this time. By accurately counting the number of vessels in the same passing area, the navigation pressure in this area can be intuitively understood, providing data support for reasonably arranging the passing order of vessels subsequently, avoiding congestion and collision risks caused by multiple vessels competing for the lane, and ensuring the orderly passage of the waterway;

[0161] Then, when it is determined that the number of vessels corresponding to any passing area is greater than one, sort them based on the sailing urgency of each corresponding sailing vessel to obtain the sailing order. Here, the sailing urgency can be comprehensively determined according to factors such as the nature of the vessel's task (such as rescue vessels and emergency material transport vessels with higher priorities), the situation of the personnel and goods on board, etc. Since it can be specifically set by the personnel, the specific method for obtaining the sailing urgency is not limited in this embodiment. Through this sorting method, vessels with high urgency can be guaranteed to pass smoothly first, minimizing the delay of vessels on important tasks to the greatest extent, improving the overall shipping efficiency, and maintaining the emergency response ability and normal order of water traffic;

[0162] Next, perform pixel rendering with different identification pixel values for each sailing vessel. It should be noted that on the navigation display system or monitoring platform of the vessel, different identification pixel values mean different display effects, such as different colors or brightness, which enables the crew and monitoring personnel to clearly distinguish different vessels, facilitating the quick identification and tracking of target vessels in a complex sailing environment, and enhancing the visualization and operation convenience of navigation management;

[0163] Finally, in response to determining that any sailing vessel passes through the passing area based on the sailing order, perform pixel rendering of the passing identifier with the corresponding identification pixel value. That is, when a certain sailing vessel is about to enter the passing area according to the sailing order, based on the above content, it can be known that when the sailing distance between the sailing vessel and the virtual combined navigation mark of the corresponding passing area is less than the preset distance, the passing identification symbol for the passing area will be determined. By rendering the passing identifier as the same identification pixel value as the vessel, the association between the currently passing vessel and the corresponding passing area can be intuitively displayed on the navigation display, facilitating other vessels and monitoring personnel to timely know the passing situation, reasonably plan their own sailing routes and operations, avoid misjudgment and conflicts, and further enhance the safety and orderliness of the waterway passage.

[0164] For example, in an actual application scenario, when there are three sailing vessels that need to pass through the same passage area simultaneously, it can be known in advance that vessel A among them has the highest sailing urgency, vessel B has the second highest sailing urgency, and vessel C has the lowest sailing urgency. Also, vessel A corresponds to a red identification pixel value, vessel B corresponds to a yellow identification pixel value, and vessel C corresponds to a green identification pixel value. In this case, based on the sailing order, it can be planned that vessel A passes first, then vessel B passes, and finally vessel C passes. Therefore, when the sailing distance of vessel A is less than the preset distance, in order to inform vessel A that it can pass, the passage identifier can be filled with pixels corresponding to the red identification pixel value. After it is determined based on the sailing coordinate points of vessel A that vessel A has completed passing through the corresponding passage area, it is possible to inform other sailing vessels in sequence again based on the sailing order.

[0165] In summary, based on the technical solution proposed in this embodiment, first, by establishing a navigation route model and determining construction nodes, a foundation can be laid for subsequent precise control. On this basis, virtual construction navigation marks are generated according to the construction situation. With the help of drones to collect images and precise image processing technology, the boundaries of the construction area can be accurately defined, enabling passing vessels to clearly understand the dangerous range, effectively avoiding accidentally entering the construction area, and ensuring navigation safety; when there is a vessel sailing, the server can predict construction based on the time difference between the planned sailing time and the monitoring period, and generate virtual prediction navigation marks. This measure allows the crew to know in advance the change trend of the construction area and plan a safe route in advance, further reducing potential risks and enhancing the safety and smoothness of navigation; in addition, by obtaining the coordinates of sailing vessels in real time and establishing virtual vessels, combining the virtual construction area and the prediction area to determine the passage area, and at the same time judging the passage attribute according to the width of the passage area and the width of the vessel, this not only provides intuitive and clear navigation guidance for the crew, improves navigation efficiency, but also, when multiple vessels are passing, arranges the passage order reasonably based on the sailing urgency, ensures that vessels on urgent tasks pass first, maintains the overall order of water traffic, comprehensively improves the navigation safety management level during water construction, optimizes the utilization efficiency of waterway resources, and realizes the automated control effect of virtual navigation marks.

[0166] Another embodiment of the present invention also provides a virtual navigation mark full-process automated control system, wherein, Figure 3 shows the relevant structural block diagram, as Figure 3 shown, this system includes:

[0167] A model establishment module, configured to establish a navigation route model corresponding to the construction route of a construction project and determine each different construction node included in the construction project;

[0168] A construction navigation mark module is configured to respond to the arrival of any monitoring cycle, determine a virtual construction area in the route model based on the current construction situation of each construction node, and form a virtual construction navigation mark for marking the virtual construction area;

[0169] The prediction navigation mark module is configured to, when it is determined that any sailing vessel is sailing on the construction route, make a construction prediction for each construction node based on the time difference between the planned sailing time of the corresponding sailing vessel and the adjacent monitoring period, and form a virtual prediction navigation mark for marking the virtual prediction area determined based on the prediction result.

[0170] In the description provided herein, algorithms and displays are not inherently related to any particular computer, virtual system or other device. Various general purpose systems can also be used together with the examples of the present invention. According to the above description, it is obvious that the structure required for constructing such systems. In addition, the present invention is not directed to any specific programming language either. It should be understood that various programming languages can be utilized to implement the content of the present invention described herein, and the above description of specific languages is for the purpose of disclosing the preferred embodiment of the present invention.

[0171] In the description provided herein, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0172] Similarly, it should be understood that in order to streamline the present disclosure and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, various features of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof.

[0173] Those skilled in the art will appreciate that the modules or units or components of the devices in the examples disclosed herein may be arranged in the devices described in the embodiment, or alternatively may be located in one or more devices different from the devices in the examples. The modules in the foregoing examples may be combined into one module or may be divided into multiple submodules.

[0174] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and furthermore may be divided into a plurality of submodules or subunits or subcomponents.

[0175] In addition, those skilled in the art will appreciate that although some of the embodiments described herein include certain features included in other embodiments and not others, combinations of features of different embodiments are meant to be within the scope of the present invention and form different embodiments.

[0176] In addition, some of the embodiments are described herein as a method or a combination of method elements that can be implemented by a processor of a computer system or by other devices performing the functions. Thus, a processor having the necessary instructions for implementing the method or method elements forms a means for implementing the method or method elements. In addition, the elements described herein of the apparatus embodiments are examples of the apparatus for performing the functions performed by the elements for the purpose of implementing the invention.

[0177] As used herein, unless otherwise specified, the use of ordinal numbers "first", "second", "third", etc. to describe ordinary objects merely indicates different instances of similar objects and is not intended to imply that the objects so described must have a given order in terms of time, space, ranking, or any other manner.

[0178] Although the present invention has been described in terms of a limited number of embodiments, those skilled in the art within the present technical field will appreciate that other embodiments can be contemplated within the scope of the present invention as thus described. In addition, it should be noted that the language used in this specification has been principally selected for readability and instructional purposes and not for the purpose of explaining or limiting the subject matter of the present invention.

Claims

1. A full-process automated control method for virtual navigation aids, characterized in that, Including the following steps: Establish a route model corresponding to the construction route of the construction project, and determine each different construction node included in the construction project; In response to reaching any monitoring period, determine a virtual construction area in the route model based on the current construction situation of each construction node, and form a virtual construction beacon for identifying the virtual construction area; When it is determined that any navigation vessel is sailing on the construction route, perform construction prediction on each construction node based on the time difference segment between the planned sailing time of the corresponding navigation vessel and the adjacent monitoring period, and form a virtual prediction beacon for identifying the virtual prediction area determined based on the prediction result; Among them, performing construction prediction on each construction node based on the time difference segment between the planned sailing time of the corresponding navigation vessel and the adjacent monitoring period, and forming a virtual prediction beacon for identifying the virtual prediction area determined based on the prediction result, includes: Obtain the construction time period corresponding to each construction node, and summarize each construction node with different overlapping time periods between the corresponding construction time period and the time difference segment into a prediction group; Determine the monitoring period adjacent to the planned sailing time as the target period, and determine the monitoring period before the target period as the comparison period; Based on the route model, determine the regional period change between the virtual construction area corresponding to each construction node in the prediction group for the target period and the virtual construction area corresponding to the comparison period, and determine the period proportion between the overlapping time period and the construction time period corresponding to the same construction node; Determine the regional period change corresponding to the period proportion based on the regional period change of each construction node, perform construction prediction on the construction node based on the regional period change, and form a virtual prediction beacon for identifying the virtual prediction area determined based on the prediction result.

2. The virtual beacon full-process automatic control method according to claim 1, wherein Determining a virtual construction area in the route model based on the current construction situation of each construction node, and forming a virtual construction beacon for identifying the virtual construction area, includes: Obtain the node coordinate points corresponding to each construction node, and control the drone to fly to the node coordinate points for collection to obtain the node images corresponding to each node coordinate point; Determine the image construction area indicating the actual construction area in the node image, and generate each image point with the same point spacing based on the image contour of the corresponding image construction area; Generate an image connection line between each image point and the image center point of the corresponding image construction area, and determine an image extension point with a preset beacon spacing from the image point along the image extension direction of the image connection line; Based on the dimension conversion relationship between the node image and the route model, determine the construction extension points corresponding to each image extension point in the route model, and form a virtual construction beacon for identifying the virtual construction area corresponding to the image construction area based on the construction extension points.

3. The virtual beacon full-process automatic control method according to claim 2, wherein Determine an image construction area indicating the current construction area located in the node image, including: Perform image recognition on the node image, and determine whether there is an image landing area indicating the real landing area in the node image based on the recognition result; When it is determined that there is none, control the drone to perform successive ascending operations corresponding to the preset ascending height from the initial flight height, and perform acquisition based on each ascending operation to obtain an updated node image; When it is determined that there is one, perform binarization processing on all other areas in the node image except the image landing area to obtain water flow pixel points corresponding to the first pixel value and noise pixel points corresponding to the second pixel value; Connect the noise pixel points in the adjacent relationship, and determine the image noise area containing the image point positions of the corresponding node coordinate points as the image construction area indicating the current construction area.

4. The virtual navigation mark full-process automatic control method according to claim 2, wherein Based on the construction extension point positions, form virtual construction navigation marks for marking the virtual construction area corresponding to the image construction area. After that, it further includes: Connect the adjacent virtual construction navigation marks corresponding to the same virtual construction area to obtain a navigation mark fence surrounding each virtual construction area; In response to the existence of overlapping parts between different navigation mark fences, summarize all the navigation mark fences corresponding to the same overlapping part into the same navigation mark merging group; Determine the route extension direction corresponding to the construction route based on the route model, and perform coordinate processing on the route model to obtain a model coordinate system, wherein the Y-axis in the model coordinate system is parallel to the route extension direction; Obtain the model coordinate points of each navigation mark fence forming the same navigation mark merging group, and generate a horizontal merging line and a vertical merging line perpendicular to and parallel to the route extension direction based on the model coordinate points corresponding to the horizontal coordinate extreme values and the vertical coordinate extreme values; Generate a merging fence surrounding each navigation mark fence in the same navigation mark merging group based on the horizontal merging line and the vertical merging line, and form updated virtual construction navigation marks based on each merging point with the same point position spacing in the merging fence.

5. The virtual navigation mark full-process automatic control method according to claim 1, wherein Based on the regional periodic changes of each construction node, determine the regional time period changes of the corresponding time period ratios, and perform construction prediction on the construction nodes based on the regional time period changes to form virtual prediction navigation marks for marking the virtual prediction area determined based on the prediction results, including: Based on each regional periodic change, determine the newly added construction area of the corresponding construction node, and generate each newly added point with the same point position spacing based on the newly added contour of the corresponding newly added construction area; Generate a newly added connection line between each newly added point and the newly added center point of the corresponding newly added construction area, and determine the newly added extension direction of the newly added connection line with the maximum line segment length as the newly added construction direction. Determine the regional overlapping segment based on the comparison between the virtual construction area corresponding to the corresponding comparison period and the virtual construction area corresponding to the corresponding target period, and determine the new construction distance between each new point and the regional overlapping segment based on the direction perpendicular to the new construction direction; Multiply each new construction distance by the time period ratio, and determine each predicted point along the new construction direction based on the obtained predicted construction distance; Connect each predicted point at adjacent positions to determine the virtual predicted area connected to the new construction area, and form a virtual predicted navigation mark for identifying the virtual predicted area.

6. The virtual navigation mark full-process automatic control method according to claim 5, wherein Forming a virtual predicted navigation mark for identifying the virtual predicted area includes: Generate a predicted connection line between each predicted point and the predicted center point of the corresponding virtual predicted area, and determine a predicted extension point with a preset navigation mark spacing from the predicted point along the predicted extension direction of the predicted connection line; Form a virtual predicted navigation mark for identifying the virtual predicted area based on the construction extension point, and perform pixel rendering with a corresponding first pixel value on the virtual construction navigation mark and pixel rendering with a corresponding second pixel value on the virtual predicted navigation mark.

7. The virtual navigation mark full-process automatic control method according to claim 1, wherein The method further includes: Obtain the navigation coordinate points of the sailing vessel in real time, establish a virtual vessel corresponding to the sailing vessel in the route model based on the navigation coordinate points, and send the route model to the sailing vessel for display; Combine the virtual construction navigation mark and the virtual predicted navigation mark corresponding to the same construction node to obtain a virtual combined navigation mark; Determine the route extension direction corresponding to the construction route based on the route model, and determine all passing areas for passing each virtual combined navigation mark along the route extension direction; Determine the passing width of the corresponding route extension direction for each passing area, and determine the passing area with a passing width greater than the vessel width of the corresponding sailing vessel as having a passing attribute, and vice versa as having a no-passing attribute; In response to determining that the sailing distance between the virtual vessel and any virtual combined navigation mark along the route extension direction is less than the preset distance, fill all passing areas with passing attributes corresponding to the virtual combined navigation mark with corresponding passing identifiers based on the route model.

8. The virtual navigation mark full-process automatic control method according to claim 7, wherein The method further includes: In response to multiple sailing vessels having the same planned sailing time, obtain the passing areas with passing attributes corresponding to each sailing vessel based on each virtual combined navigation mark, and determine the number of vessels of all sailing vessels corresponding to the same passing area; When it is determined that the number of vessels corresponding to any passing area is greater than one, sort based on the sailing urgency of each sailing vessel to obtain the sailing order Perform pixel rendering with corresponding different identification pixel values for each sailing vessel, and in response to determining that any sailing vessel passes through the passage area based on the sailing order, perform pixel rendering of the passage identifier with the corresponding identification pixel value.

9. A full-process automated control system for virtual navigation aids, characterized in that, Including: A model establishment module, configured to establish a navigation route model corresponding to the construction route of a construction project and determine each different construction node included in the construction project; A construction navigation mark module, configured to, in response to reaching any monitoring period, determine a virtual construction area in the navigation route model based on the current construction situation of each construction node and form a virtual construction navigation mark for identifying the virtual construction area; A predicted navigation mark module, configured to, when determining that any sailing vessel sails on the construction route, perform construction prediction on each construction node based on the time difference period between the planned sailing time of the corresponding sailing vessel and the adjacent monitoring period, and form a virtual predicted navigation mark for identifying the virtual predicted area determined based on the prediction result; Among them, performing construction prediction on each construction node based on the time difference period between the planned sailing time of the corresponding sailing vessel and the adjacent monitoring period, and forming a virtual predicted navigation mark for identifying the virtual predicted area determined based on the prediction result includes: Obtain the construction time period corresponding to each construction node, and summarize each construction node with different overlapping time periods between the corresponding construction time period and the time difference period into a prediction group; Determine the monitoring period adjacent to the planned sailing time as the target period, and determine the monitoring period before the target period as the comparison period; Based on the route model, determine the area-period change between the virtual construction area corresponding to each construction node in the prediction group for the target period and the virtual construction area corresponding to the comparison period, and determine the period ratio between the overlapping time period and the construction time period corresponding to the same construction node; Based on the area-period change of each construction node, determine the area-time period change corresponding to the period ratio, and perform construction prediction on the construction node based on the area-time period change, and form a virtual predicted navigation mark for identifying the virtual predicted area determined based on the prediction result.

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