Extended reality aided decision-making method and device for highway tunnel construction

Abstract

The invention discloses an expanded reality auxiliary decision-making method and device for highway tunnel construction, and relates to the technical field of highway tunnel intelligent construction. The method comprises the following steps: constructing digital assets of a highway tunnel according to physical information of the highway tunnel, and determining digital space model information and functional feature information of the highway tunnel; based on the digital space model information and the functional feature information, constructing a sensor network for monitoring a construction state, and obtaining various sensor data and sensor coordinate information; generating a fusion feature matrix of the sensor data according to various sensor data; digital space model information and sensor coordinate information are integrated to a game engine platform, and a fusion digital system is obtained; according to real highway tunnel data collected by a camera system in real time, a fusion feature matrix of a fusion digital system and a sensor network is anchored to a physical space of a real highway tunnel, and visualization is achieved. According to the invention, effective space mapping of digital information and physical information can be realized.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent construction of highway tunnels, and particularly to an augmented reality assisted decision-making method and device for highway tunnel construction. Background Art

[0002] During the construction period of highway tunnels, insufficient natural light in concealed spaces is a serious problem, especially during inspection and maintenance. These concealed areas, such as pipelines, machine rooms, and cable troughs, often lack sufficient natural light, resulting in a significant decline in the perception ability of construction and operation and maintenance personnel for the environment and sensor data. Specifically, low light conditions make it difficult for personnel to clearly observe structural details in these areas, and potential safety hazards, such as cracks, corrosion, or equipment failures, are easily missed. These data often need to be monitored and fed back through a sensor network. However, how to effectively visualize the mapping of sensor information to the real concealed space on-site has always been a difficult problem. Summary of the Invention

[0003] To solve the technical problem in the prior art that sensor information cannot be effectively visualized and mapped to the real concealed space on-site, embodiments of the present invention provide an augmented reality assisted decision-making method and device for highway tunnel construction. The technical solutions are as follows:

[0004] On the one hand, an augmented reality assisted decision-making method for highway tunnel construction is provided. This method is implemented by an augmented reality assisted decision-making device for highway tunnel construction, and the method includes:

[0005] S1. Construct a digital asset of the highway tunnel according to the physical information of the highway tunnel;

[0006] S2. Determine the digital space model information and functional characteristic information of the highway tunnel based on the digital asset of the highway tunnel and the game engine platform;

[0007] S3. Based on the digital space model information and functional characteristic information of the highway tunnel, construct a sensor network for monitoring the construction state, and obtain various types of sensor data and sensor coordinate information according to the sensor network;

[0008] S4. Generate a fusion feature matrix of the sensor data according to various types of sensor data, and send the fusion feature matrix of the sensor data to the augmented reality device based on a preset data communication method between the sensor network and the augmented reality device;

[0009] S5. Integrate the digital space model information and sensor coordinate information of the highway tunnel into the game engine platform to obtain a fusion digital system;

[0010] S6. Deploy the fusion feature matrix integrating the digital system and sensor data onto the extended reality device;

[0011] S7. According to the real - world reality highway tunnel data collected in real - time by the camera system, anchor the fusion feature matrix integrating the digital system and the sensor network into the physical space of the real - world reality highway tunnel, and provide real - time visual information for on - site construction workers for their construction behavior decision - making.

[0012] On the other hand, an extended reality - assisted decision - making device for highway tunnel construction is provided. This device is applied to the extended reality - assisted decision - making method for highway tunnel construction. The device includes:

[0013] A first construction unit for constructing the digital assets of the highway tunnel according to the physical information of the highway tunnel;

[0014] A determination unit for determining the digital space model information and functional feature information of the highway tunnel based on the digital assets of the highway tunnel and the game engine platform;

[0015] A second construction unit for constructing a sensor network for monitoring the construction status based on the digital space model information and functional feature information of the highway tunnel, and obtaining various types of sensor data and sensor coordinate information according to the sensor network;

[0016] A sending unit for generating a fusion feature matrix of sensor data according to various types of sensor data, and sending the fusion feature matrix of sensor data to the extended reality device based on a preset data communication method between the sensor network and the extended reality device;

[0017] An integration unit for integrating the digital space model information and sensor coordinate information of the highway tunnel into the game engine platform to obtain a fusion digital system;

[0018] A deployment unit for deploying the fusion feature matrix of the fusion digital system and sensor data onto the extended reality device;

[0019] An anchoring unit for anchoring the fusion feature matrix of the fusion digital system and the sensor network into the physical space of the real - world reality highway tunnel according to the real - world reality highway tunnel data collected in real - time by the camera system, and providing real - time visual information for on - site construction workers for their construction behavior decision - making.

[0020] On the other hand, there is provided an extended reality assisted decision-making device for highway tunnel construction. The extended reality assisted decision-making device for highway tunnel construction includes: a processor; a memory storing computer-readable instructions thereon, and when the computer-readable instructions are executed by the processor, any one of the methods in the above-mentioned extended reality assisted decision-making method for highway tunnel construction is implemented.

[0021] On the other hand, there is provided a computer-readable storage medium storing at least one instruction, and the at least one instruction is loaded and executed by a processor to implement any one of the methods in the above-mentioned extended reality assisted decision-making method for highway tunnel construction.

[0022] The beneficial effects brought by the technical solutions provided in the embodiments of the present invention at least include:

[0023] When the lighting conditions in the concealed space are weak, digital information is used to enhance the personnel's perception of real physical information through extended reality technology. At the same time, the information among people, the environment, and the computer is integrated in the way of spatial anchors to realize the effective spatial mapping of digital information and the corresponding physical information. Based on this mapping and combined with the professional qualities of on-site staff, the perception of the current highway tunnel state is improved, and misjudgments and safety accidents caused by vision problems are reduced. Clear visual information helps personnel detect and handle potential hazards more accurately, improving the safety and reliability of the overall operation. The present invention not only improves the operation safety and efficiency but also enhances the data perception and decision-making capabilities. Such improvements are of profound significance for ensuring the construction quality, improving the maintenance efficiency, and guaranteeing the long-term safe operation of highway tunnels. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0025] Figure 1 is a flowchart of an extended reality assisted decision-making method for highway tunnel construction provided by an embodiment of the present invention;

[0026] Figure 2 is a schematic flowchart of integration into a game engine platform provided by an embodiment of the present invention;

[0027] Figure 3 is a schematic flowchart of coordinate system conversion provided by an embodiment of the present invention;

[0028] Figure 4It is a block diagram of an augmented reality assisted decision-making device for highway tunnel construction provided by an embodiment of the present invention;

[0029] Figure 5 It is a schematic structural diagram of an augmented reality assisted decision-making device for highway tunnel construction provided by an embodiment of the present invention.

[0030] Reference numerals:

[0031] 1. Sensor network for monitoring construction status; 2. Database; 3. Local server; 4. Game engine platform at the local end; 5. Deployed mobile carrying device; 6. Deployed head-mounted mixed reality device; 7. Anchoring the data model to the real space; 8. Three-dimensional coordinates of the digital world; 9. Three-dimensional coordinates of the real world. Detailed implementation manners

[0032] Next, the technical solutions in the present invention will be described with reference to the accompanying drawings.

[0033] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as an "example" in the present invention should not be construed as being more preferred or more advantageous than other embodiments or design solutions. Rather, the use of the word "example" is intended to present concepts in a specific manner. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one of the two can be selected.

[0034] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when their differences are not emphasized, the meanings they express are the same. "(of)", "corresponding", and "corresponding" can sometimes be used interchangeably. It should be noted that when their differences are not emphasized, the meanings they express are the same.

[0035] In the embodiments of the present invention, sometimes subscripts such as W1 may be written in a non-subscript form such as W1. When their differences are not emphasized, the meanings they express are the same.

[0036] To make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments.

[0037] The embodiments of the present invention provide an augmented reality assisted decision-making method for highway tunnel construction. This method can be implemented by an augmented reality assisted decision-making device for highway tunnel construction, and the augmented reality assisted decision-making device for highway tunnel construction can be a terminal or a server. As Figure 1The flowchart of an augmented reality assisted decision-making method for highway tunnel construction provided by the embodiment of the present invention shown in the figure. The processing flow of this method may include the following steps:

[0038] S1. Construct digital assets of the highway tunnel according to the physical information of the highway tunnel.

[0039] Optionally, constructing digital assets of the highway tunnel according to the physical information of the highway tunnel in S1 includes:

[0040] Based on the physical information of the highway tunnel, use a combination of building information model (BIM) and game engine to construct digital assets of the highway tunnel;

[0041] Among them, the digital assets of the highway tunnel include: digital modeling information of the highway tunnel and characteristic information of the construction project of the highway tunnel.

[0042] In a feasible implementation manner, construct digital assets of the highway tunnel system based on a physical engine, and use a combination of "building information model (BIM) + game engine platform" to construct digital assets of the highway tunnel system.

[0043] S2. Based on the digital assets of the highway tunnel and the game engine platform, determine the digital space model information and functional characteristic information of the highway tunnel.

[0044] Optionally, determining the digital space model information and functional characteristic information of the highway tunnel based on the digital assets of the highway tunnel and the game engine platform in S2 may include the following steps S21 - S22:

[0045] S21. Based on the digital modeling information of the highway tunnel in the digital assets of the highway tunnel, construct it in the building information model (BIM) at a digital scale of 1:500, export the construction result as a.fbx file; import the.fbx file into the game engine platform, and based on the matching accuracy of the spatial anchor points, scale the model at a digital scale of 1:100 on the basis of the default model scale of the building information model (BIM) to obtain the digital space model information of the highway tunnel.

[0046] S22. Based on the characteristic information of the construction project of the highway tunnel, store it in the corresponding digital space model information through a dictionary type. The dictionary paradigm is defined as the following formula (1):

[0047] (1)

[0048] Among them, is the name of the construction project described based on the character type; is the number for describing a construction project based on an array type, where l represents the number of sub-projects, s represents the number of sub-items, and k represents the construction sequence number of the project; is the coordinate for describing the geometric spatial center of the project based on an array type; is the functional characteristic information of the highway tunnel construction project in the project described based on a character type.

[0049] S3. Based on the digital space model information and functional characteristic information of the highway tunnel, construct a sensor network for monitoring the construction status, and obtain various sensor data and sensor coordinate information according to the sensor network.

[0050] Among them, the information for deploying the sensor network for monitoring the construction status includes the combination of three types of information: the type of sensor connected by wire, the sensor location matching the spatial location of the functional characteristic information, and the randomly arranged method.

[0051] S4. Generate a fusion feature matrix of the sensor data according to various sensor data, and send the fusion feature matrix of the sensor data to the extended reality device based on the preset data communication method between the sensor network and the extended reality device.

[0052] In a feasible implementation, based on the data processing result, construct a data communication optimization algorithm to ensure that the data can be efficiently transmitted to the head-mounted extended reality device. In the data communication between the extended reality device and the sensor, the key is to reduce the bandwidth consumption and delay, and the goal is to find a data compression and intelligent transmission strategy to maximize the system performance.

[0053] Optionally, generating the fusion feature matrix of the sensor data according to various sensor data in S4 may include the following steps S41 - S44:

[0054] S41. Based on the alignment of the time dimension of various sensors, perform noise reduction on various sensor data based on a low-pass filter.

[0055] In a feasible implementation, a sensor network system is arranged by information matching based on the digital space model information, functional characteristic information, and sensor network information of a highway tunnel. After debugging, information of different data types is subjected to noise reduction, outlier analysis, and missing value processing to ensure that the time-series data is aligned and synchronized in the time dimension, and to standardize and normalize single-category data to construct a sensor data set. Since various sensors are provided by merchants and there are differences in the data accuracy of each type of sensor, data is integrated through data feature extraction and splicing. At the same time, the computational resources and time can be reduced while ensuring data availability. The text, image, and data-type sensors are all matrix-processed. First, based on the alignment of the time dimensions of various sensors, different types of data are denoised based on a low-pass filter, as shown in the following formula (2):

[0056] (2)

[0057] Wherein, is the data after filtering of the j-th sensor in the i-th category of sensors, is the original data of the j-th sensor in the i-th category of sensors, is the filtering coefficient, 。

[0058] S42. Feature extraction and feature fusion are performed on the filtered sensor data, and a feature matrix is constructed. Among them, the time-domain features of the feature matrix are represented by the mean and variance, and the frequency-domain features of the feature matrix are represented based on the fast Fourier transform.

[0059] In a feasible implementation, feature extraction and feature fusion are performed based on the filtered sensor data, and a feature matrix is constructed. The time-domain features are represented by the mean and variance, and the frequency-domain features are represented based on the fast Fourier transform, as shown in the following formula (3):

[0060] (3)

[0061] Wherein, is the frequency-domain information of the j-th sensor in the i-th category of sensors after the fast Fourier transform, is the time-domain information of the j-th sensor in the i-th category of sensors; then, a feature matrix is constructed to represent the feature information of various types of sensors, as shown in the following formula (4):

[0062] (4)。

[0063] S43. Based on the weight information, the data of various sensors and the feature matrix are matrix-fused to obtain a fused feature matrix of the sensor data.

[0064] In a feasible implementation manner, various types of sensor data in the system are matrix-fused based on weight information to prepare for data communication and calculation, as shown in the following formula (5):

[0065] (5)

[0066] Among them, is the data feature splicing matrix of various sensors in the highway tunnel, that is, the cumulative feature fusion value of highway tunnel sensor data. The spatial position clockwise on the left wall is used as the reference starting position according to the traffic flow entrance direction; is the trade-off value of the bias term monitoring error, and its range is specified to be in [0, 1.0];

[0067] Construct an array F of the input data value at time r and the cumulative at time r to represent the real-time sensor data and the cumulative feature fusion value, and provide matching information for on-site personnel, as shown in the following formula (6):

[0068] (6)

[0069] Among them, F represents the fusion feature matrix of sensor data in the highway tunnel, including real-time sensor data and cumulative feature fusion values, represents the real-time data value of the jth sensor in the i category of sensors.

[0070] S44. Use MySQL to construct a structured database for the fusion feature matrix and store it.

[0071] In a feasible implementation manner, storing it in the local server of the highway tunnel project department can ensure the setting of project privacy and access rights.

[0072] Optionally, for the data communication method between the preset sensor network and the extended reality device in S4, sending the fusion feature matrix of sensor data to the extended reality device may include the following steps S45 - S47:

[0073] S45. Compress the fusion feature matrix of sensor data based on entropy coding;

[0074] In a feasible implementation manner, compress the sensor data based on entropy coding to reduce the transmission volume, as shown in the following formulas (7) - (8):

[0075] (7)

[0076] Among them, is the information entropy of the sensor data transmission matrix, is the probability information of data transmission loss;

[0077] (8)

[0078] is the sampling rate of the current duration, is a predefined threshold. To ensure that sensor data captures changes with 1% accuracy, it is defined that , is the amplitude of change of the sensor within a unit of time.

[0079] S46. Use a scheduling algorithm based on the time-sensitive priority of sensor data. Based on the following formula (9), determine the transmission optimization level of the fusion feature matrix of the compressed sensor data:

[0080] (2)

[0081] where, is the transmission priority of the fusion feature matrix of the j-th sensor data in the i-th category of sensors, is the weight of the transmission of the fusion feature matrix of the j-th sensor data in the i-th category of sensors, is the number of weights.

[0082] S47. Based on the TCP / IP protocol, according to the transmission priority of the fusion feature matrix of the compressed sensor data, perform queued transmission on the fusion feature matrix of the compressed sensor data to achieve data communication between the database in the local server and the extended reality device.

[0083] S5. Integrate the digital space model information and sensor coordinate information of the highway tunnel into the game engine platform to obtain a fusion digital system;

[0084] Optionally, as Figure 2 shown, the integration of the digital space model information and sensor coordinate information of the highway tunnel into the game engine platform in S5 to obtain a fusion digital system may include the following steps S51 - S53:

[0085] S51. Save the digital space model information and sensor coordinate information of the highway tunnel in a.txt file, import the saved file into the Paraview data reconstruction platform, reconstruct the visualization information of the data according to the types of point data, surface data, and volume data, and export the visualization information as a.vtk file;

[0086] S52. Write a data reconstruction and rendering script based on Python, convert the.vtk file to an.obj file, and import it into Blender. Build a secondary development program for graphic rendering based on the Python plugin, render the visualization effect in real time, and export the final file in the.fbx file format;

[0087] S53. Import the.fbx file format into the game engine platform to obtain a fused digital system, where the game engine of the game engine platform uses Unity 3D.

[0088] In a feasible implementation, the.fbx file format is imported into the game engine platform. The game engine uses Unity 3D and is deployed as digital resources into the digital scene. According to the visualization effect, the data visualization scene grid and the matching materials are imported. At the same time, the original.txt file is imported. Based on the C# script, the information of the.txt data is read in real time, and the corresponding materials and grids are matched according to the data size to realize the real-time reconstruction and visualization of the highway tunnel sensor data in the game engine.

[0089] S6. Deploy the fused digital system and the fusion feature matrix of the sensor data to the extended reality device.

[0090] In a feasible implementation, the scene where the reconstruction result of the sensor data in the game engine is located is constructed according to the distributed platform, including distributed development of the general Windows platform, IOS platform, and Android platform. Among them, the general Windows platform builds the scene based on the OpenXR platform.

[0091] The development of human-computer interaction is carried out based on the mixed reality toolkit, including hand recognition and eye movement capture recognition, to realize the function of physically operating digital objects with the entity hand in the mixed reality application.

[0092] Based on Visual Studio, the digital assets and sensor reconstruction data of the highway tunnel system are compiled into the head-mounted mixed reality device and the mobile portable device. The mobile portable device includes smartphones, tablets, and other portable devices with a computing operating system and camera equipment.

[0093] S7. According to the camera system, the real-world reality highway tunnel data is collected in real time. The fusion feature matrix of the fused digital system and the sensor network is anchored to the physical space of the real-world reality highway tunnel to provide real-time visualization information for on-site construction workers for construction behavior decision-making by the construction workers.

[0094] Optionally, as Figure 3 shown, the step of collecting the real-world highway tunnel data in real time according to the camera system in S7 and anchoring the fusion feature matrix of the fused digital system and the sensor network to the physical space of the real-world highway tunnel may include the following steps S701 - S710:

[0095] S71. Determine the three-dimensional coordinates of the digital world according to the fusion feature matrix of the fused digital system and the sensor network ;

[0096] S72. Based on the camera system, scan the surface data of the real-world highway tunnel in the real world, convert the surface data into digital information understood by the computer device, and map the digital information to the preset anchor point positions to ensure that the digital information matches the real world; wherein, the camera system includes an extended reality device and a mobile portable device;

[0097] S73. Through the camera system, convert the three-dimensional coordinates in the digital world into the three-dimensional coordinates in the real world according to the following formula (10) :

[0098] (10)

[0099] wherein, is the rotation matrix of the anchor point coordinate system of the camera system, is the translation matrix of the anchor point coordinate system of the camera system, is the built-in initial matrix of the camera system, as shown in the following formula (11):

[0100] (11)

[0101] wherein, and are the focal lengths, and are the principal point coordinates;

[0102] S74. Provide real-time visualization information for on-site construction personnel according to the three-dimensional coordinates in the real world and the surface data of the real-world highway tunnel in the real world for the construction personnel to make construction behavior decisions.

[0103] Optionally, providing real-time visualization information for on-site construction personnel according to the three-dimensional coordinates in the real world and the surface data of the real-world highway tunnel in the real world for the construction personnel to make construction behavior decisions includes:

[0104] S741. Define the image information of the real world recognized by the extended reality device within a unit time as a depth space model with RGB information;

[0105] S742. Regard the brightness of the depth space model as the product of the reflectivity R(x, y, z) of each point and the light intensity L(x, y, z), and reduce the influence of the light L(x, y, z) through appropriate methods to obtain features independent of light, as shown in the following formula (12):

[0106] (12)

[0107] wherein, is the brightness of the depth space model at (x, y, z), is the reflectivity of the spatial point, and L(x, y, z) is the illumination intensity of the spatial point;

[0108] S743. To reduce the influence of illumination, take the logarithm of the brightness of the depth space model to change the multiplication effect into an addition effect, as shown in the following equation (13):

[0109] (13)

[0110] where, is the logarithm of the brightness of the depth space model at (x, y, z), is the logarithm of the reflectivity of the spatial point, is the logarithm of the illumination intensity of the spatial point;

[0111] S744. Extract the local texture features of the depth space model through the local binary pattern in the local area. By comparing the gray value differences between the central pixel and the surrounding pixels, form a binary pattern that is insensitive to illumination, as shown in the following equation (14):

[0112] (14)

[0113] where, is the binary illumination invariance of the depth space model at the point (x, y, z), s(x) is the sign function, which is 1 when x >= 0 and 0 otherwise, is the illumination intensity value adjacent to the depth space model point (x, y, z), taking the lowest illumination value within the hexagonal prism space range centered on the point (x, y, z), and i is the spatial index of the adjacent point of the depth space model point (x, y, z), is the brightness value of the depth space model point (x, y, z); Based on the above calculation process, to reduce the robustness problem of the spatial matching degree of the high-intensity natural light to the extended reality device;

[0114] S745. Visualize the data information based on the real-time communication of the sensor. Based on the entity hand to operate the digital object, provide real-time visual information and a computer operating system convenient for human-computer interaction for on-site construction personnel for the construction behavior decision-making of the construction personnel.

[0115] In the embodiments of the present invention, augmented reality technology is used to make up for the weak lighting conditions in hidden spaces, enhance the perception of real physical information by personnel with digital information, and at the same time, integrate the information between people, the environment, and the computer in the form of spatial anchors to achieve an effective spatial mapping between digital information and the corresponding physical information. Based on this mapping and the professional qualities of on-site workers, the perception of the current state of the highway tunnel is improved, and misjudgments and safety accidents caused by vision problems are reduced. Clear visual information helps personnel detect and handle potential hazards more accurately, improving the safety and reliability of the overall operation. The present invention not only improves the operation safety and efficiency but also enhances the data perception and decision-making capabilities. Such improvements have far-reaching significance for ensuring construction quality, improving maintenance efficiency, and ensuring the long-term safe operation of highway tunnels.

[0116] Figure 4 It is a block diagram of an augmented reality-assisted decision-making device for highway tunnel construction provided by the embodiments of the present invention. This device is used for an augmented reality-assisted decision-making method for highway tunnel construction. Refer to Figure 4 , this device includes:

[0117] A first construction unit 410, configured to construct digital assets of the highway tunnel according to the physical information of the highway tunnel;

[0118] A determination unit 420, configured to determine the digital space model information and functional characteristic information of the highway tunnel based on the digital assets of the highway tunnel and the game engine platform;

[0119] A second construction unit 430, configured to construct a sensor network for monitoring the construction state based on the digital space model information and functional characteristic information of the highway tunnel, and obtain various types of sensor data and sensor coordinate information according to the sensor network;

[0120] A sending unit 440, configured to generate a fusion feature matrix of sensor data according to various types of sensor data, and send the fusion feature matrix of sensor data to the augmented reality device based on a preset data communication method between the sensor network and the augmented reality device;

[0121] An integration unit 450, configured to integrate the digital space model information and sensor coordinate information of the highway tunnel into the game engine platform to obtain a fusion digital system;

[0122] A deployment unit 460, configured to deploy the fusion digital system and the fusion feature matrix of sensor data to the augmented reality device;

[0123] The anchoring unit 470 is used to collect real-world data of a highway tunnel in real time according to a camera system, anchor the fusion feature matrix integrating a digital system and a sensor network into the physical space of the real-world highway tunnel, and provide real-time visualization information for on-site construction personnel for construction behavior decision-making by the construction personnel.

[0124] Optionally, the first construction unit 410 is used for:

[0125] Based on the physical information of the highway tunnel, construct the digital assets of the highway tunnel by using a combination of building information modeling (BIM) and a game engine;

[0126] Wherein, the digital assets of the highway tunnel include: digital modeling information of the highway tunnel and characteristic information of the construction project of the highway tunnel.

[0127] Optionally, the determination unit 420 is used for:

[0128] S21. Based on the digital modeling information of the highway tunnel in the digital assets of the highway tunnel, construct it in the building information model (BIM) at a digital scale of 1:500, export the construction result as a.fbx file; import the.fbx file model into the game engine platform, and based on the matching accuracy of the spatial anchor points, scale the model at a digital scale of 1:100 on the basis of the default model scale of the building information model (BIM) to obtain the digital space model information of the highway tunnel;

[0129] S22. Based on the characteristic information of the construction project of the highway tunnel, store it in the corresponding digital space model information in a dictionary type, and the dictionary paradigm is defined as the following formula (1):

[0130] (1)

[0131] Wherein, is the name of the construction project described based on the character type; is the number of the construction project described based on the array type, where l represents the number of the sub-project, s represents the number of the sub-item project, and k represents the construction sequence number of the project; is the coordinate of the geometric space center of the project described based on the array type; is the functional characteristic information of the highway tunnel construction project in the project described based on the character type.

[0132] Optionally, the sending unit 440 is used for:

[0133] S41. On the basis of aligning the time dimensions of various sensors, perform noise reduction on the data of various sensors based on a low-pass filter;

[0134] S42. Extract and fuse features from the filtered sensor data, and construct a feature matrix. Among them, the time-domain features of the feature matrix are represented by the mean and variance, and the frequency-domain features of the feature matrix are represented based on the fast Fourier transform:

[0135] S43. Based on the weight information, perform matrix fusion on various types of sensor data and the feature matrix to obtain a fused feature matrix of the sensor data;

[0136] S44. Use MySQL to construct a structured database for the fused feature matrix and store it.

[0137] Optionally, the sending unit 440 is used for:

[0138] S45. Compress the fused feature matrix of the sensor data based on entropy coding;

[0139] S46. Use a scheduling algorithm based on the time sensitivity priority of the sensor data. Based on the following formula (2), determine the transmission optimization level of the compressed fused feature matrix of the sensor data:

[0140] (2)

[0141] Where, is the transmission priority of the fused feature matrix of the j-th sensor data in the i-th category of sensors, is the weight of the transmission of the fused feature matrix of the j-th sensor data in the i-th category of sensors, is the number of weights;

[0142] S47. Based on the TCP / IP protocol, according to the transmission priority of the compressed fused feature matrix of the sensor data, perform queued transmission on the compressed fused feature matrix of the sensor data to achieve data communication between the database in the local server and the extended reality device.

[0143] Optionally, the integration unit 450 is used for:

[0144] S51. Save the digital space model information and sensor coordinate information of the highway tunnel in a.txt file, import the saved file into the Paraview data reconstruction platform, reconstruct the visualization information of the data according to the types of point data, surface data, and volume data, and export the visualization information as a.vtk file;

[0145] S52. Write data reconstruction and rendering scripts based on Python, convert the.vtk file to an.obj file, and import it into Blender. Build a secondary development program for graphic rendering based on a Python plugin, render the visualization effect in real time, and export the final file in the.fbx file format;

[0146] S53. Import the.fbx file format into the game engine platform, where the game engine of the game engine platform uses Unity 3D.

[0147] Optionally, the anchoring unit 470 is used for:

[0148] S71. Determine the three-dimensional coordinates of the digital world according to the fusion feature matrix of the fusion digital system and the sensor network ;

[0149] S72. Based on the camera system, scan the surface data of the real-world highway tunnel in the real world, convert the surface data into digital information understood by the computer device, and map the digital information to the preset anchor point positions to ensure that the digital information matches the real world; wherein, the camera system includes an extended reality device and a mobile portable device;

[0150] S73. Through the camera system, convert the three-dimensional coordinates of the digital world to the three-dimensional coordinates of the real world according to the following formula (3) :

[0151] (3)

[0152] Wherein, is the rotation matrix of the anchor point coordinate system of the camera system, is the translation matrix of the anchor point coordinate system of the camera system, is the built-in initial matrix of the camera system, as shown in the following formula (4):

[0153] (4)

[0154] Wherein, and are the focal lengths, and are the principal point coordinates;

[0155] S74. Provide real-time visual information for on-site construction personnel according to the three-dimensional coordinates of the real world and the surface data of the real-world highway tunnel in the real world for the construction behavior decision-making of the construction personnel.

[0156] Optionally, the anchoring unit 470 is used for:

[0157] S741. Define the image information of the real world recognized by the extended reality device within a unit time as a depth space model with RGB information;

[0158] S742. Determine the brightness of the depth space model as the product of the reflectivity R(x, y, z) and the illumination intensity L(x, y, z) of each point according to the following formula (5), and reduce the influence of the illumination L(x, y, z) to obtain features independent of illumination:

[0159] (5)

[0160] where, is the brightness of the depth space model at (x, y, z), is the reflectivity of the spatial point, and L(x, y, z) is the illumination intensity of the spatial point;

[0161] S743. To reduce the influence of illumination, take the logarithm of the brightness of the depth space model according to the following formula (6) to change the multiplication effect to an addition effect:

[0162] (6)

[0163] where, is the logarithm of the brightness of the depth space model at (x, y, z), is the logarithm of the reflectivity of the spatial point, is the logarithm of the illumination intensity of the spatial point;

[0164] S744. According to the following formula (7), extract the local texture features of the depth space model in the local area through local binary pattern, and form a binary pattern insensitive to illumination by comparing the gray value differences between the central pixel and the surrounding pixels:

[0165] (7)

[0166] where, is the binary illumination invariance of the depth space model at the point (x, y, z), s(x) is the sign function, which is 1 when x >= 0 and 0 otherwise, is the illumination intensity value adjacent to the point (x, y, z) of the depth space model, taking the lowest illumination value within the hexagonal prism space range centered on the point (x, y, z), and i is the spatial index of the point adjacent to the point (x, y, z) of the depth space model, is the brightness value of the point (x, y, z) of the depth space model;

[0167] S745. Visualize the data information based on the real-time communication of the sensor, and provide real-time visual information and a computer operating system convenient for human-computer interaction for on-site construction personnel based on the entity hand operating the digital object, for the construction behavior decision-making of the construction personnel.

[0168] In the embodiments of the present invention, augmented reality technology is used to make up for the weak lighting conditions in hidden spaces, and digital information is used to enhance the perception of real physical information by personnel. At the same time, the information between people, the environment, and the computer is integrated through the method of spatial anchors to achieve an effective spatial mapping of digital information and the corresponding physical information. Based on this mapping and the professional qualities of on-site workers, the perception of the current highway tunnel state is enhanced, and misjudgments and safety accidents caused by vision problems are reduced. Clear visual information helps personnel detect and handle potential hazards more accurately, improving the safety and reliability of overall operations. The present invention not only improves the safety and efficiency of operations but also enhances data perception and decision-making capabilities. Such improvements have far-reaching significance for ensuring construction quality, improving maintenance efficiency, and ensuring the long-term safe operation of highway tunnels.

[0169] Figure 5 is a schematic structural diagram of an augmented reality-assisted decision-making device for highway tunnel construction provided by an embodiment of the present invention. As Figure 5 shown, the augmented reality-assisted decision-making device for highway tunnel construction may include the above-mentioned Figure 4 shown augmented reality-assisted decision-making device for highway tunnel construction. Optionally, the augmented reality-assisted decision-making device 510 for highway tunnel construction may include a first processor 2001.

[0170] Optionally, the augmented reality-assisted decision-making device 510 for highway tunnel construction may further include a memory 2002 and a transceiver 2003.

[0171] Among them, the first processor 2001, the memory 2002, and the transceiver 2003 may be connected through a communication bus, for example.

[0172] Next, in combination with Figure 5 each component of the augmented reality-assisted decision-making device 510 for highway tunnel construction will be specifically introduced:

[0173] Among them, the first processor 2001 is the control center of the augmented reality assisted decision-making device 510 for highway tunnel construction, which can be a single processor or a collective term for multiple processing elements. For example, the first processor 2001 is one or more central processing units (CPUs), or can be an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention, such as: one or more digital signal processors (DSPs), or one or more field programmable gate arrays (FPGAs).

[0174] Optionally, the first processor 2001 can execute various functions of the augmented reality assisted decision-making device 510 for highway tunnel construction by running or executing software programs stored in the memory 2002 and calling data stored in the memory 2002.

[0175] In a specific implementation, as an embodiment, the first processor 2001 may include one or more CPUs, such as Figure 5 the CPU0 and CPU1 shown in

[0176] In a specific implementation, as an embodiment, the augmented reality assisted decision-making device 510 for highway tunnel construction may also include multiple processors, such as Figure 5 the first processor 2001 and the second processor 2004 shown in

[0177] Each of these processors can be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). Here, the processor can refer to one or more devices, circuits, and / or processing cores for processing data (such as computer program instructions).

[0178] Optionally, the memory 2002 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 2002 may be integrated with the first processor 2001 or exist independently, and is coupled to the first processor 2001 through an interface circuit ( Figure 5 not shown) of the extended reality assisted decision-making device 510 for highway tunnel construction. The embodiments of the present invention do not make specific limitations on this.

[0179] The transceiver 2003 is used to communicate with network devices or terminal devices.

[0180] Optionally, the transceiver 2003 may include a receiver and a transmitter ( Figure 5 not shown separately). Among them, the receiver is used to implement the receiving function, and the transmitter is used to implement the sending function.

[0181] Optionally, the transceiver 2003 may be integrated with the first processor 2001 or exist independently, and is coupled to the first processor 2001 through an interface circuit ( Figure 5 not shown) of the extended reality assisted decision-making device 510 for highway tunnel construction. The embodiments of the present invention do not make specific limitations on this.

[0182] It should be noted that Figure 5 the structure of the extended reality assisted decision-making device 510 for highway tunnel construction shown in does not constitute a limitation on the router. The actual knowledge structure recognition device may include more or fewer components than shown in the figure, or combine some components, or have different component arrangements.

[0183] In addition, the technical effects of the extended reality assisted decision-making device 510 for highway tunnel construction may refer to the technical effects of the extended reality assisted decision-making method for highway tunnel construction described in the above method embodiments, and will not be elaborated here.

[0184] It should be understood that the first processor 2001 in the embodiments of the present invention may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0185] It should also be understood that the memory in the embodiments of the present invention may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM) or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0186] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (such as infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that contains one or more collections of available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, or magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0187] It should be understood that the term "and / or" in this document is merely a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. Additionally, the character " / " in this document generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship, which can be understood specifically by referring to the context before and after.

[0188] In the present invention, "at least one" means one or more, and "a plurality" means two or more. "At least one of the following" or its similar expressions refer to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or multiple.

[0189] It should be understood that in various embodiments of the present invention, the magnitudes of the sequence numbers of the above processes do not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0190] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0191] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the devices, apparatuses, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0192] In several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be electrical, mechanical, or other forms.

[0193] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0194] In addition, the functional units in each embodiment of the present invention can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0195] When the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0196] As described above, the above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. An augmented reality assisted decision-making method for highway tunnel construction, characterized in that, The method includes: S1. Construct the digital assets of the highway tunnel according to the physical information of the highway tunnel; S2. Based on the digital assets of the highway tunnel and the game engine platform, determine the digital space model information and functional characteristic information of the highway tunnel; S3. Based on the digital space model information and functional characteristic information of the highway tunnel, construct a sensor network for monitoring the construction status, and obtain various sensor data and sensor coordinate information according to the sensor network; S4. Generate a fusion feature matrix of the sensor data according to various sensor data, and send the fusion feature matrix of the sensor data to the extended reality device based on a preset data communication method between the sensor network and the extended reality device; S5. Integrate the digital space model information and sensor coordinate information of the highway tunnel into the game engine platform to obtain a fusion digital system; S6. Deploy the fusion digital system and the fusion feature matrix of the sensor data to the extended reality device; S7. According to the real-world actual highway tunnel data collected by the camera system in real time, anchor the fusion digital system and the fusion feature matrix of the sensor network to the physical space of the real-world actual highway tunnel, and provide real-time visualization information for on-site construction personnel for construction personnel's construction behavior decision-making.

2. The augmented reality assisted decision-making method for highway tunnel construction according to claim 1, wherein, The step of constructing the digital assets of the highway tunnel according to the physical information in S1 includes: Based on the physical information of the highway tunnel, adopt a combination of building information model BIM and game engine to construct the digital assets of the highway tunnel; Among them, the digital assets of the highway tunnel include: the digital modeling information of the highway tunnel and the characteristic information of the construction project of the highway tunnel.

3. The extended reality assisted decision-making method for highway tunnel construction according to claim 2, wherein The step of determining the digital space model information and functional characteristic information of the highway tunnel based on the digital assets of the highway tunnel and the game engine platform in S2 includes: S21. Based on the digital modeling information of the highway tunnel in the digital assets of the highway tunnel, construct it in the building information model BIM at a digital scale of 1:500, and export the construction result as a.fbx file; import the.fbx file into the game engine platform, and based on the matching accuracy of the spatial anchor point, scale the model at a digital scale of 1:100 on the basis of the default model scale of the building information model BIM to obtain the digital space model information of the highway tunnel; S22. Based on the characteristic information of the construction project of the highway tunnel, store it in the matching digital space model information through a dictionary type, and the dictionary paradigm is defined as the following formula (1): （1） Among them, describes the name of the construction project based on the character type; describes the number of the construction project based on the array type, where l represents the number of the sub-project, s represents the number of the sub-item project, and k represents the construction sequence number of the project; describes the coordinates of the geometric space center of the project based on the array type; describes the functional characteristic information of the highway tunnel construction project in the project based on the character type.

4. The augmented reality assisted decision-making method for highway tunnel construction according to claim 3, wherein The step of generating a fusion feature matrix of the sensor data according to various sensor data in S4 includes: S41. On the basis of aligning the time dimensions of various sensors, perform noise reduction on various sensor data based on a low-pass filter; S42. Perform feature extraction and feature fusion on the filtered sensor data, and construct a feature matrix. Among them, the time-domain features of the feature matrix are represented by mean and variance, and the frequency-domain features of the feature matrix are represented based on the fast Fourier transform: S43. Perform matrix fusion on various types of sensor data and the feature matrix based on the weight information to obtain a fused feature matrix of the sensor data; S44. Use MySQL to construct a structured database for the fused feature matrix and store it.

5. The augmented reality assisted decision-making method for highway tunnel construction according to claim 4, wherein The data communication method between the preset sensor network and the extended reality device in S4, which sends the fused feature matrix of the sensor data to the extended reality device, includes: S45. Compress the fused feature matrix of the sensor data based on entropy coding; S46. Use a scheduling algorithm based on the time sensitivity priority of the sensor data. Based on the following formula (2), determine the transmission optimization level of the compressed fused feature matrix of the sensor data: （2） Among them, is the transmission priority of the fusion feature matrix of the j-th sensor data in the i-th category of sensors, is the weight of the transmission of the fusion feature matrix of the j-th sensor data in the i-th category of sensors, is the number of weights; S47. Based on the TCP / IP protocol, perform queued transmission on the compressed fused feature matrix of the sensor data according to the transmission priority of the compressed fused feature matrix of the sensor data, to achieve data communication between the database in the local server and the extended reality device.

6. The augmented reality assisted decision-making method for highway tunnel construction according to claim 4, wherein The S5 of integrating the digital space model information and sensor coordinate information of the highway tunnel into the game engine platform to obtain a fused digital system includes: S51. Save the digital space model information and sensor coordinate information of the highway tunnel in a.txt file, import the saved file into the Paraview data reconstruction platform, reconstruct the visualization information of the data according to the types of point data, surface data, and volume data, and export the visualization information as a.vtk file; S52. Write data reconstruction and rendering scripts based on Python, convert the.vtk file to an.obj file, and import it into Blender. Build a secondary development program for graphic rendering based on a Python plugin to render the visualization effect in real time, and export the final file in the.fbx file format; S53. Import the.fbx file format into the game engine platform to obtain a fused digital system, where the game engine of the game engine platform uses Unity 3D.

7. The augmented reality-assisted decision-making method for highway tunnel construction according to claim 4, wherein The S7 of anchoring the fused feature matrix of the fused digital system and the sensor network to the physical space of the real-world highway tunnel according to the real-world highway tunnel data collected by the camera system in real time, to provide real-time visualization information for on-site construction personnel for construction behavior decision-making by construction personnel, includes: S71. Determine the three-dimensional coordinates of the digital world according to the fusion feature matrix integrating the digital system and the sensor network ; S72. Based on the camera system, scan the surface data of the real-world highway tunnel, convert the surface data into digital information understood by the computer device, and map the digital information to the preset anchor point positions to ensure that the digital information matches the real world; where the camera system includes an extended reality device and a mobile portable device; S73. Through the camera system, convert the three-dimensional coordinates in the digital world into the three-dimensional coordinates in the real world according to the following formula (3) :[[]]END]] （3） Among them, is the rotation matrix of the anchor coordinate system of the camera system, is the translation matrix of the anchor coordinate system of the camera system, is the built-in initial matrix of the camera system, as shown in Equation (4) below: （4） Among them, and are the focal lengths, and are the principal point coordinates; S74. Provide real-time visualization information for on-site construction personnel for construction behavior decision-making by construction personnel according to the three-dimensional coordinates of the real world and the surface data of the real-world highway tunnel.

8. The extended reality assisted decision-making method for highway tunnel construction according to claim 7, wherein The S74 of providing real-time visualization information for on-site construction personnel for construction behavior decision-making by construction personnel according to the three-dimensional coordinates of the real world and the surface data of the real-world highway tunnel includes: S741. Define the image information of the real world recognized by the extended reality device within a unit time as a depth space model with RGB information; S742. According to the following formula (5), determine the brightness of the depth space model as the product of the reflectivity R(x, y, z) of each point and the illumination intensity L(x, y, z), and reduce the influence of the illumination L(x, y, z) to obtain features independent of illumination: （5） Among them, is the brightness of the deep space model at (x, y, z), is the reflectivity of the spatial point, and L(x, y, z) is the illumination intensity of the spatial point; S743. To reduce the influence of illumination, take the logarithm of the brightness of the depth space model according to the following formula (6) to change the multiplication effect to an addition effect: （6） Among them, is the logarithm of the brightness of the deep space model at (x, y, z), is the logarithm of the reflectivity of the spatial point, is the logarithm of the light intensity of the spatial point; S744. According to the following formula (7), extract the local texture features of the depth space model in a local area through local binary pattern, and form a binary pattern insensitive to illumination by comparing the gray value differences between the central pixel and the surrounding pixels: （7） Among them, is the binary illumination invariance of the deep space model at the point (x, y, z), s(x) is the sign function, which is 1 when x >= 0 and 0 otherwise. is the illumination intensity value near the point (x, y, z) of the deep space model, taking the lowest illumination value within the hexagonal prism space range centered on the point (x, y, z), and i is the spatial index of the point near the point (x, y, z) of the deep space model. is the brightness value of the point (x, y, z) of the deep space model; S745. Based on real-time communication of sensors, visualize data information, and operate digital objects based on the physical hands of entities to provide real-time visualization information and a computer operating system convenient for human-computer interaction for on-site construction workers for construction behavior decision-making of the construction workers.

9. An augmented reality assisted decision-making device for highway tunnel construction, the augmented reality assisted decision-making device for highway tunnel construction is used to implement the augmented reality assisted decision-making method for highway tunnel construction according to any one of claims 1-8, characterized in that, The device includes: A first construction unit for constructing the digital assets of the highway tunnel according to the physical information of the highway tunnel; A determination unit for determining the digital space model information and functional feature information of the highway tunnel based on the digital assets of the highway tunnel and the game engine platform; A second construction unit for constructing a sensor network for monitoring the construction state based on the digital space model information and functional feature information of the highway tunnel, and obtaining various types of sensor data and sensor coordinate information according to the sensor network; A sending unit for generating a fusion feature matrix of sensor data according to various types of sensor data, and sending the fusion feature matrix of sensor data to the extended reality device based on a preset data communication method between the sensor network and the extended reality device; An integration unit for integrating the digital space model information and sensor coordinate information of the highway tunnel into the game engine platform to obtain a fusion digital system; A deployment unit for deploying the fusion digital system and the fusion feature matrix of sensor data to the extended reality device; An anchoring unit for anchoring the fusion feature matrix of the fusion digital system and the sensor network to the physical space of the real highway tunnel according to the real-time acquisition of the real highway tunnel data by the camera system, and providing real-time visualization information for on-site construction workers for construction behavior decision-making of the construction workers.

10. An extended reality-assisted decision-making device for highway tunnel construction, characterized in that, The extended reality-assisted decision-making device for highway tunnel construction includes: A processor; A memory, on which computer-readable instructions are stored, and when the computer-readable instructions are executed by the processor, the method described in any one of claims 1 to 8 is implemented.

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