Tunnel information processing method, system and device with information collaborative management and control technology and medium

Abstract

The embodiment of the invention provides a tunnel information processing method, system and device with an information collaborative management and control technology and a medium, and belongs to the field of tunnel information processing. The method comprises the following steps: collecting a tunnel equipment state, traffic flow, environmental parameters and vehicle information through positioning equipment and a sensor arranged in a tunnel; carrying out fusion processing on the collected information, and constructing a tunnel operation state model; and the tunnel operation state is monitored in real time, abnormal events are identified, and an early warning mechanism is triggered. Through the positioning equipment and the sensor which are uniformly deployed in the tunnel, comprehensive and real-time acquisition of tunnel information is realized, and real-time monitoring of the tunnel operation state can be realized based on the constructed tunnel operation state model. And by setting a trigger early warning mechanism, the safety of tunnel management is improved, potential safety hazards and operation risks are reduced, and powerful support is provided for intelligent and refined management of the tunnel.

Description

Technical Field

[0001] The present invention relates to the field of tunnel information processing technology, and in particular to a tunnel information processing method, system, device and medium with information collaborative management and control technology. Background Art

[0002] With the rapid development of economy and the coming of automobile era, the mileage of expressways is increasing. Due to the large number of mountains in some areas, the number of tunnels, which have high transportation efficiency and small land occupation, is also increasing.

[0003] With the rapid development of tunnel construction, problems also exist in tunnel construction. The existing data of tunnels are relatively scattered, lacking effective integration and interconnection and sharing. The collected information resources have not been fully explored, scientifically analyzed and effectively utilized, resulting in obvious problems of multiple collection and duplicate construction by various departments, prominent inconsistency in the same data, relatively few effective resources in the industry system, and poor overall supply efficiency. Summary of the invention

[0004] The purpose of the embodiments of the present invention is to provide a tunnel information processing method, system, device and medium with information collaborative management and control technology, which is used to fully or at least partially solve the technical problems existing in the above-mentioned prior art.

[0005] In order to achieve the above-mentioned object, an embodiment of the present invention provides a tunnel information processing method with information collaborative management and control technology, including:

[0006] Through the positioning equipment and sensors arranged in the tunnel, the tunnel equipment status, traffic flow, environmental parameters and vehicle information are collected;

[0007] The collected tunnel equipment status, traffic flow, environmental parameters and vehicle information are integrated and processed to build a tunnel operation status model;

[0008] Based on the constructed tunnel operation status model, the tunnel operation status is monitored in real time, abnormal events are identified, and an early warning mechanism is triggered.

[0009] Optionally, the collected tunnel equipment status, traffic flow, environmental parameters and vehicle information are integrated and processed to construct a tunnel operation status model, including:

[0010] According to the design drawings of the tunnel, an initial 3D model of the tunnel is created in the BIM software, and the integrated tunnel equipment status, traffic flow, environmental parameters and vehicle information are associated with the initial 3D model through data mapping to ensure that each data point finds the corresponding position and status in the initial 3D model;

[0011] Adding road markings to the initial three-dimensional model, wherein the road markings at least include lane lines, center lines, and stop lines;

[0012] The initial three-dimensional model is corrected using tunnel geometry data measured by a 3D scanner and a laser rangefinder to obtain a tunnel operation status model.

[0013] Based on the constructed tunnel operation status model, the tunnel operation status is monitored in real time, abnormal events are identified, and an early warning mechanism is triggered, including:

[0014] The tunnel operation status model is used to monitor the equipment status, traffic flow, environmental parameters and vehicle information in the tunnel in real time;

[0015] Use threshold detection to monitor whether environmental parameters exceed preset safety ranges, use clustering algorithms to identify abnormal patterns in traffic flow, and use time series analysis to predict and detect equipment failures;

[0016] Classify the identified abnormal events and set corresponding warning levels;

[0017] Warning information is issued to relevant personnel through preset communication channels, where the warning information includes the type, location, time, warning level and recommended measures of the abnormal event.

[0018] Optionally, use threshold detection to monitor whether environmental parameters exceed preset safety ranges, use clustering algorithms to identify abnormal patterns in traffic flow, and use time series analysis to predict and detect equipment failures, including:

[0019] Compare the collected environmental parameters with the preset thresholds. If the data exceeds the threshold range, it is determined to be an abnormal event.

[0020] Extract characteristic data from traffic flow, and use K-means clustering algorithm to perform cluster analysis on the characteristic data to obtain clustering results, and identify normal and abnormal patterns of traffic flow based on the clustering results;

[0021] The LSTM time series analysis method is used to model the historical data of the equipment to obtain a time series model, and the normal mode and change law of the equipment operation are learned through the time series model;

[0022] The time series model is used to predict the future operating status of the equipment, and the abnormal trend of equipment failure is identified by analyzing the prediction results.

[0023] On the other hand, the present invention also provides a tunnel information processing system with information collaboration technology, comprising:

[0024] A collection unit, used to collect tunnel equipment status, traffic flow, environmental parameters and vehicle information through positioning equipment and sensors arranged in the tunnel;

[0025] A fusion unit is used to fuse the collected tunnel equipment status, traffic flow, environmental parameters and vehicle information to build a tunnel operation status model;

[0026] The processing unit is used to monitor the tunnel operation status in real time based on the constructed tunnel operation status model, identify abnormal events, and trigger an early warning mechanism.

[0027] Optionally, the fusion unit is specifically used for:

[0028] According to the design drawings of the tunnel, an initial 3D model of the tunnel is created in the BIM software, and the integrated tunnel equipment status, traffic flow, environmental parameters and vehicle information are associated with the initial 3D model through data mapping to ensure that each data point finds the corresponding position and status in the initial 3D model;

[0029] Adding road markings to the initial three-dimensional model, wherein the road markings at least include lane lines, center lines, and stop lines;

[0030] The initial three-dimensional model is corrected using tunnel geometry data measured by a 3D scanner and a laser rangefinder to obtain a tunnel operation status model.

[0031] Optionally, the processing unit is specifically used for:

[0032] The tunnel operation status model is used to monitor the equipment status, traffic flow, environmental parameters and vehicle information in the tunnel in real time;

[0033] Use threshold detection to monitor whether environmental parameters exceed preset safety ranges, use clustering algorithms to identify abnormal patterns in traffic flow, and use time series analysis to predict and detect equipment failures;

[0034] Classify the identified abnormal events and set corresponding warning levels;

[0035] Warning information is issued to relevant personnel through preset communication channels, where the warning information includes the type, location, time, warning level and recommended measures of the abnormal event.

[0036] Optionally, the processing unit is specifically used for:

[0037] Compare the collected environmental parameters with the preset thresholds. If the data exceeds the threshold range, it is determined to be an abnormal event.

[0038] Extract characteristic data from traffic flow, and use K-means clustering algorithm to perform cluster analysis on the characteristic data to obtain clustering results, and identify normal and abnormal patterns of traffic flow based on the clustering results;

[0039] The LSTM time series analysis method is used to model the historical data of the equipment to obtain a time series model, and the normal mode and change law of the equipment operation are learned through the time series model;

[0040] The time series model is used to predict the future operating status of the equipment, and the abnormal trend of equipment failure is identified by analyzing the prediction results.

[0041] On the other hand, the present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the tunnel information processing method with information collaborative management and control technology described above are implemented.

[0042] On the other hand, the present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the tunnel information processing method with information collaborative management and control technology described above are implemented.

[0043] Through the above technical solutions, through the uniform deployment of positioning equipment and sensors in the tunnel, the comprehensive and real-time collection of tunnel equipment status, traffic flow, environmental parameters and vehicle information is realized, and the massive data collected is integrated and processed. Moreover, based on the constructed tunnel operation status model, the real-time monitoring of the tunnel operation status can be realized. And by setting up a trigger warning mechanism, the security of tunnel management is improved, potential safety hazards and operational risks are reduced, and strong support is provided for the intelligent and refined management of tunnels.

[0044] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following specific implementations, they are used to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the accompanying drawings:

[0046] Figure 1 It is an implementation flow chart of a tunnel information processing method with information collaborative management and control technology provided by an embodiment of the present invention;

[0047] Figure 2 It is a structural diagram of a tunnel information processing system with information collaboration technology provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The specific implementation of the embodiment of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the embodiment of the present invention, and is not used to limit the embodiment of the present invention.

[0049] See also Figure 1 As shown, it is a flowchart of an implementation method of a tunnel information processing method with information collaborative management and control technology provided by an embodiment of the present invention, including the following execution steps:

[0050] Step 100: Collect tunnel equipment status, traffic flow, environmental parameters and vehicle information through positioning equipment and sensors arranged in the tunnel.

[0051] Step 101: The collected tunnel equipment status, traffic flow, environmental parameters and vehicle information are integrated and processed to construct a tunnel operation status model.

[0052] Specifically, when executing step 101, the following steps may be specifically performed:

[0053] S1010: Create an initial three-dimensional model of the tunnel in the BIM software based on the design drawings of the tunnel, and associate the integrated tunnel equipment status, traffic flow, environmental parameters and vehicle information with the initial three-dimensional model through data mapping to ensure that each data point finds the corresponding position and status in the initial three-dimensional model.

[0054] S1011: Add road markings to the initial three-dimensional model, wherein the road markings include at least lane lines, center lines, and stop lines.

[0055] S1012: Correct the initial three-dimensional model using the tunnel geometry data measured by the 3D scanner and the laser rangefinder to obtain a tunnel operation status model.

[0056] Step 102: Based on the constructed tunnel operation status model, the tunnel operation status is monitored in real time, abnormal events are identified, and an early warning mechanism is triggered.

[0057] Specifically, when executing step 102, the following steps may be specifically performed:

[0058] S1020: Real-time monitoring of equipment status, traffic flow, environmental parameters and vehicle information in the tunnel is performed through the tunnel operation status model.

[0059] S1021: Use threshold detection to monitor whether environmental parameters exceed preset safety ranges, use clustering algorithms to identify abnormal patterns in traffic flow, and use time series analysis to predict and detect equipment failures.

[0060] Specifically, when executing step S1021, the following steps may be specifically performed:

[0061] S1: Compare the collected environmental parameters with the preset thresholds. If the data exceeds the threshold range, it is determined to be an abnormal event.

[0062] It should be noted that the preset threshold can be set according to the actual application scenario and is not limited here.

[0063] S2: Extract characteristic data from traffic flow, and use K-means clustering algorithm to perform cluster analysis on the characteristic data to obtain clustering results, and identify normal and abnormal patterns of traffic flow based on the clustering results.

[0064] In traffic flow data, common features include but are not limited to: Time features: such as hour, day of the week, month, etc., which can reflect the periodic changes in traffic flow. Spatial features: such as road section number, intersection location, etc., which can distinguish traffic conditions at different locations. Flow features: such as vehicle volume, average speed, congestion index, etc., which directly reflect the actual situation of traffic flow.

[0065] In some embodiments, the cluster centers are initialized: K sample points are randomly selected as the initial cluster centers, and the allocation step is to calculate the distance from each sample point to each cluster center, and each sample point is allocated to the cluster to which the cluster center closest to it belongs. The updating step is to recalculate the cluster center of each cluster, and usually take the mean of all sample points in the cluster as the new cluster center. Repeat the allocation and updating steps until the cluster center no longer changes significantly or reaches a predetermined number of iterations. K clusters and their corresponding cluster centers are obtained. The traffic flow is further analyzed and interpreted based on the clustering results, such as identifying high-flow periods, congested sections, etc.

[0066] S3: Use the LSTM time series analysis method to model the historical data of the equipment to obtain a time series model, and use the time series model to learn the normal mode and change law of the equipment operation.

[0067] S4: Use the time series model to predict the future operating status of the equipment, and identify abnormal trends of equipment failures by analyzing the prediction results.

[0068] S1022: Classify the identified abnormal events and set corresponding warning levels.

[0069] S1023: Issue warning information to relevant personnel through preset communication channels, where the warning information includes the type, location, time, warning level and recommended measures of the abnormal event.

[0070] Through the above technical solutions, through the uniform deployment of positioning equipment and sensors in the tunnel, the comprehensive and real-time collection of tunnel equipment status, traffic flow, environmental parameters and vehicle information is realized, and the massive data collected is integrated and processed. Moreover, based on the constructed tunnel operation status model, the real-time monitoring of the tunnel operation status can be realized. And by setting up a trigger warning mechanism, the security of tunnel management is improved, potential safety hazards and operational risks are reduced, and strong support is provided for the intelligent and refined management of tunnels.

[0071] See also Figure 2 FIG. 1 is a schematic diagram of a structure of a tunnel information processing system with information collaboration technology provided by an embodiment of the present invention, including:

[0072] The collection unit 20 is used to collect tunnel equipment status, traffic flow, environmental parameters and vehicle information through positioning equipment and sensors arranged in the tunnel;

[0073] A fusion unit 21 is used to fuse the collected tunnel equipment status, traffic flow, environmental parameters and vehicle information to build a tunnel operation status model;

[0074] The processing unit 22 is used to monitor the tunnel operation status in real time based on the constructed tunnel operation status model, identify abnormal events, and trigger an early warning mechanism.

[0075] In some embodiments, the fusion unit is specifically used for:

[0076] According to the design drawings of the tunnel, an initial 3D model of the tunnel is created in the BIM software, and the integrated tunnel equipment status, traffic flow, environmental parameters and vehicle information are associated with the initial 3D model through data mapping to ensure that each data point finds the corresponding position and status in the initial 3D model;

[0077] Adding road markings to the initial three-dimensional model, wherein the road markings at least include lane lines, center lines, and stop lines;

[0078] The initial three-dimensional model is corrected using tunnel geometry data measured by a 3D scanner and a laser rangefinder to obtain a tunnel operation status model.

[0079] In some embodiments, the processing unit is specifically configured to:

[0080] The tunnel operation status model is used to monitor the equipment status, traffic flow, environmental parameters and vehicle information in the tunnel in real time;

[0081] Use threshold detection to monitor whether environmental parameters exceed preset safety ranges, use clustering algorithms to identify abnormal patterns in traffic flow, and use time series analysis to predict and detect equipment failures;

[0082] Classify the identified abnormal events and set corresponding warning levels;

[0083] Warning information is issued to relevant personnel through preset communication channels, where the warning information includes the type, location, time, warning level and recommended measures of the abnormal event.

[0084] In some embodiments, the processing unit is specifically configured to:

[0085] Compare the collected environmental parameters with the preset thresholds. If the data exceeds the threshold range, it is determined to be an abnormal event.

[0086] Extract characteristic data from traffic flow, and use K-means clustering algorithm to perform cluster analysis on the characteristic data to obtain clustering results, and identify normal and abnormal patterns of traffic flow based on the clustering results;

[0087] The LSTM time series analysis method is used to model the historical data of the equipment to obtain a time series model, and the normal mode and change law of the equipment operation are learned through the time series model;

[0088] The time series model is used to predict the future operating status of the equipment, and the abnormal trend of equipment failure is identified by analyzing the prediction results.

[0089] On the other hand, the present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the tunnel information processing method with information collaborative management and control technology described in any one of the above embodiments are implemented.

[0090] On the other hand, the present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the tunnel information processing method with information collaborative management and control technology described in any of the above embodiments are implemented.

[0091] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0092] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0093] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0094] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0095] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0096] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0097] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0098] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0099] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A tunnel information processing method with information collaborative management and control technology, characterized in that: include: Through the positioning equipment and sensors arranged in the tunnel, the tunnel equipment status, traffic flow, environmental parameters and vehicle information are collected; The collected tunnel equipment status, traffic flow, environmental parameters and vehicle information are integrated and processed to build a tunnel operation status model; Based on the constructed tunnel operation status model, the tunnel operation status is monitored in real time, abnormal events are identified, and an early warning mechanism is triggered.

2. The tunnel information processing method with information collaborative management and control technology according to claim 1 is characterized in that: The collected tunnel equipment status, traffic flow, environmental parameters and vehicle information are integrated and processed to build a tunnel operation status model, including: According to the design drawings of the tunnel, an initial 3D model of the tunnel is created in the BIM software, and the integrated tunnel equipment status, traffic flow, environmental parameters and vehicle information are associated with the initial 3D model through data mapping to ensure that each data point finds the corresponding position and status in the initial 3D model; Adding road markings to the initial three-dimensional model, wherein the road markings at least include lane lines, center lines, and stop lines; The initial three-dimensional model is corrected using tunnel geometry data measured by a 3D scanner and a laser rangefinder to obtain a tunnel operation status model.

3. The tunnel information processing method with information collaborative management and control technology according to claim 1 is characterized in that: Based on the constructed tunnel operation status model, the tunnel operation status is monitored in real time, abnormal events are identified, and an early warning mechanism is triggered, including: The tunnel operation status model is used to monitor the equipment status, traffic flow, environmental parameters and vehicle information in the tunnel in real time; Use threshold detection to monitor whether environmental parameters exceed preset safety ranges, use clustering algorithms to identify abnormal patterns in traffic flow, and use time series analysis to predict and detect equipment failures; Classify the identified abnormal events and set corresponding warning levels; Warning information is issued to relevant personnel through preset communication channels, where the warning information includes the type, location, time, warning level and recommended measures of the abnormal event.

4. The tunnel information processing method with information collaborative management and control technology according to claim 3 is characterized in that: Use threshold detection to monitor whether environmental parameters exceed preset safety ranges, use clustering algorithms to identify abnormal patterns in traffic flow, and use time series analysis to predict and detect equipment failures, including: Compare the collected environmental parameters with the preset thresholds. If the data exceeds the threshold range, it is determined to be an abnormal event. Extract characteristic data from traffic flow, and use K-means clustering algorithm to perform cluster analysis on the characteristic data to obtain clustering results, and identify normal and abnormal patterns of traffic flow based on the clustering results; The LSTM time series analysis method is used to model the historical data of the equipment to obtain a time series model, and the normal mode and change law of the equipment operation are learned through the time series model; The time series model is used to predict the future operating status of the equipment, and the abnormal trend of equipment failure is identified by analyzing the prediction results.

5. A tunnel information processing system with information collaboration technology, characterized in that: include: A collection unit, used to collect tunnel equipment status, traffic flow, environmental parameters and vehicle information through positioning equipment and sensors arranged in the tunnel; A fusion unit is used to fuse the collected tunnel equipment status, traffic flow, environmental parameters and vehicle information to build a tunnel operation status model; The processing unit is used to monitor the tunnel operation status in real time based on the constructed tunnel operation status model, identify abnormal events, and trigger an early warning mechanism.

6. The tunnel information processing system with information collaboration technology according to claim 5, characterized in that: The fusion unit is specifically used for: According to the design drawings of the tunnel, an initial 3D model of the tunnel is created in the BIM software, and the integrated tunnel equipment status, traffic flow, environmental parameters and vehicle information are associated with the initial 3D model through data mapping to ensure that each data point finds the corresponding position and status in the initial 3D model; Adding road markings to the initial three-dimensional model, wherein the road markings at least include lane lines, center lines, and stop lines; The initial three-dimensional model is corrected using tunnel geometry data measured by a 3D scanner and a laser rangefinder to obtain a tunnel operation status model.

7. The tunnel information processing system with information collaboration technology according to claim 5, characterized in that: The processing unit is specifically used for: The tunnel operation status model is used to monitor the equipment status, traffic flow, environmental parameters and vehicle information in the tunnel in real time; Use threshold detection to monitor whether environmental parameters exceed preset safety ranges, use clustering algorithms to identify abnormal patterns in traffic flow, and use time series analysis to predict and detect equipment failures; Classify the identified abnormal events and set corresponding warning levels; Warning information is issued to relevant personnel through preset communication channels, where the warning information includes the type, location, time, warning level and recommended measures of the abnormal event.

8. The tunnel information processing system with information collaboration technology according to claim 7, characterized in that: The processing unit is specifically used for: Compare the collected environmental parameters with the preset thresholds. If the data exceeds the threshold range, it is determined to be an abnormal event. Extract characteristic data from traffic flow, and use K-means clustering algorithm to perform cluster analysis on the characteristic data to obtain clustering results, and identify normal and abnormal patterns of traffic flow based on the clustering results; The LSTM time series analysis method is used to model the historical data of the equipment to obtain a time series model, and the normal mode and change law of the equipment operation are learned through the time series model; The time series model is used to predict the future operating status of the equipment, and the abnormal trend of equipment failure is identified by analyzing the prediction results.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the tunnel information processing method with information collaborative management and control technology as described in any one of claims 1-4 are implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, the steps of the tunnel information processing method with information collaborative management and control technology as described in any one of claims 1 to 4 are implemented.

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