Expressway tunnel construction inspection method, device and equipment

Abstract

The invention provides an expressway tunnel construction inspection method, device and equipment, belongs to the technical field of computer information processing, and solves the problems of low inspection efficiency and safety risk of expressway tunnel construction at present. The method comprises the following steps: acquiring environmental data around a driving path of an inspection unmanned vehicle; determining driving route data according to the environmental data; acquiring current coordinate data of the inspection unmanned vehicle; and according to the coordinate data and the driving route data, controlling the inspection unmanned vehicle to drive according to a target path. According to the technical scheme, automatic driving of the inspection unmanned vehicle is achieved, the efficiency of highway tunnel construction inspection is improved, and the safety of tunnel construction is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of computer information processing, and in particular to a method, device and equipment for inspecting highway tunnel construction. Background Art

[0002] In the management and maintenance of highway tunnels, there are many devices with different functions, which together support the normal operation of the tunnel. These devices include lighting systems, ventilation systems, drainage systems, monitoring systems, fire protection systems, and emergency communication systems. Each device has its specific service life and normal working environment conditions, which means that when maintaining and managing these devices, their individual differences and particularities need to be fully considered. For long-distance highway tunnels, the problems caused by equipment failure are more prominent. If an effective inspection path cannot be generated, the time cost and personnel investment of daily inspections will be very high. The inspectors need to cover the entire tunnel within a limited time and check the operating status of each device, which is undoubtedly a difficult task. At the same time, due to the complex internal environment of the tunnel, the inspectors also need to face challenges such as insufficient light and poor air circulation. If the equipment fails and cannot be quickly discovered and repaired, it will bring safety hazards to the operation of the highway tunnel. Summary of the invention

[0003] The present invention provides a highway tunnel construction inspection method, device and equipment, which solve the problems of low efficiency and safety risks in the current highway tunnel construction inspection work.

[0004] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0005] An embodiment of the present invention provides a highway tunnel construction inspection method, comprising:

[0006] Collect environmental data around the route of the patrol unmanned vehicle;

[0007] Determine driving route data according to the environmental data;

[0008] Get the current coordinate data of the inspection unmanned vehicle;

[0009] According to the coordinate data and the driving route data, the inspection unmanned vehicle is controlled to travel along the target path.

[0010] Optionally, the collecting of environmental data around the driving path of the patrol unmanned vehicle includes:

[0011] Environmental data around the driving path of the unmanned inspection vehicle is collected by means of a laser sensor installed on the top and a radar sensor installed on the side of the unmanned inspection vehicle, and a temperature sensor installed on the bottom of the unmanned inspection vehicle. The environmental data includes temperature data in the tunnel, coordinate data of obstacles, and size data of obstacles, wherein the height of the obstacle is greater than a preset value.

[0012] Optionally, determining the driving route data according to the environmental data includes:

[0013] Get map data inside the tunnel;

[0014] The environment data and the map data in the tunnel are combined to obtain tunnel road condition data;

[0015] According to the tunnel road condition data, driving route data including a target path is obtained.

[0016] Optionally, obtaining driving route data including a target path according to the tunnel road condition data includes:

[0017] Performing rasterization processing on the tunnel road condition data to obtain a plurality of raster data, wherein the plurality of raster data includes a start raster and an end raster;

[0018] Starting from the starting grid, the plurality of grid data are processed for path planning according to the constraint conditions to obtain driving route data including the target path.

[0019] Optionally, obtain the current coordinate data of the inspection unmanned vehicle, including:

[0020] The current coordinate data of the inspection unmanned vehicle is obtained by installing a GPS locator on the top of the inspection unmanned vehicle.

[0021] Optionally, controlling the inspection unmanned vehicle to travel along the target path according to the coordinate data and the driving route data includes:

[0022] Performing feature comparison between the coordinate data and the driving route data to obtain a comparison result;

[0023] According to the comparison result, the inspection unmanned vehicle is controlled to travel along the target path.

[0024] Optionally, according to the comparison result, controlling the inspection unmanned vehicle to travel along the target path includes:

[0025] The comparison result indicates that if the coordinate data is in the target path recorded in the driving route data, the inspection unmanned vehicle is controlled to drive along the target path; otherwise, the driving route of the inspection unmanned vehicle is adjusted so that the inspection unmanned vehicle drives along the target path.

[0026] Optionally, adjusting the driving route of the unmanned inspection vehicle so that the unmanned inspection vehicle drives along the target path includes:

[0027] Adjusting the driving route of the inspection unmanned vehicle through remote commands and generating control signals;

[0028] According to the control signal, the inspection unmanned vehicle is controlled to travel along the target path.

[0029] The embodiment of the present invention further provides a highway tunnel construction inspection device, comprising:

[0030] A collection module is used to collect environmental data around the driving path of the inspection unmanned vehicle;

[0031] A processing module is used to determine the driving route data according to the environmental data; and obtain the current coordinate data of the inspection unmanned vehicle;

[0032] The control module is used to control the inspection unmanned vehicle to travel along the target path according to the coordinate data and the driving route data.

[0033] An embodiment of the present invention further provides a computing device, comprising: a processor and a memory storing a computer program, wherein the computer program executes the above method when executed by the processor.

[0034] The above solution of the present invention includes at least the following beneficial effects:

[0035] The above scheme of the present invention collects environmental data around the driving path of the unmanned inspection vehicle; determines the driving route data according to the environmental data; obtains the current coordinate data of the unmanned inspection vehicle; and controls the unmanned inspection vehicle to drive along the target path according to the coordinate data and the driving route data. The technical scheme of the present invention realizes the automatic driving of the unmanned inspection vehicle, improves the efficiency of highway tunnel construction inspection, and improves the safety of tunnel construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a flow chart of a highway tunnel construction inspection method provided by an embodiment of the present invention;

[0037] Figure 2 Schematic diagram of the installation position of the sensor of the inspection unmanned vehicle according to an embodiment of the present invention;

[0038] Figure 3This is a schematic diagram of the path planning of the unmanned inspection vehicle according to an embodiment of the present invention;

[0039] Figure 4 It is a structural diagram of a highway tunnel construction inspection device provided by an embodiment of the present invention;

[0040] Figure 5 is a schematic diagram of the structure of a computing device provided by an embodiment of the present invention;

[0041] Among them, 1. Laser sensor; 2. Radar sensor; 3. Temperature sensor; 4. Charging port; 5. Starting grid; 6. End grid; 7. Planned path. DETAILED DESCRIPTION

[0042] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present invention and to enable the scope of the present invention to be fully communicated to those skilled in the art.

[0043] like Figure 1 and Figure 2 As shown, an embodiment of the present invention provides a highway tunnel construction inspection method, comprising:

[0044] Step 11, collecting environmental data around the driving path of the inspection unmanned vehicle;

[0045] Step 12, determining driving route data according to the environmental data;

[0046] Step 13, obtaining the current coordinate data of the inspection unmanned vehicle;

[0047] Step 14: Control the inspection unmanned vehicle to travel along the target path based on the coordinate data and the driving route data.

[0048] In this embodiment, the inspection unmanned vehicle uses the various sensors it carries to fully perceive its surrounding environment, including collecting environmental data around the driving path of the inspection unmanned vehicle through a laser sensor 1 installed on the top of the inspection unmanned vehicle and a radar sensor 2 installed on the side, as well as a temperature sensor 3 installed on the bottom of the inspection unmanned vehicle, wherein the environmental data includes temperature data in the tunnel, coordinate data of obstacles, and size data of obstacles, wherein the height of the obstacles is greater than a preset value; the current coordinate data of the inspection unmanned vehicle is obtained through a GPS locator installed on the top of the inspection unmanned vehicle; these sensors can capture and generate detailed data about the surrounding environment in real time, including but not limited to the location, shape, and size of obstacles, the condition of the road, such as whether it is flat, whether there are potholes or water stains, and other dynamic factors that may affect driving. The collected environmental data will be further analyzed and processed;

[0049] After obtaining comprehensive environmental data, the data is analyzed to determine the best driving route. In this process, multiple possible driving routes are generated, and the path planning model is used to select the best route; the optimal route will mark the specific path that the inspection unmanned vehicle needs to follow, including turning points, obstacle avoidance strategies, speed control and other information; in order to ensure that the inspection unmanned vehicle can drive according to the planned route, it is necessary to obtain the current location information of the inspection unmanned vehicle in real time, and further improve the positioning accuracy through environmental feature matching; the acquired coordinate data is updated in real time and used for comparison and adjustment with the planned driving route;

[0050] Based on the coordinate data acquired in real time and the pre-planned driving route data, the system generates instructions for specific actions to be taken by the inspection unmanned vehicle; these instructions include adjusting the vehicle speed, steering angle, braking force, etc., to ensure that the unmanned vehicle can accurately and accurately drive along the target path. The control system will also continuously monitor the actual driving status of the unmanned vehicle and compare it with the planned route to promptly detect and correct any deviations. If an emergency occurs, such as an obstacle suddenly appearing or a road closure, the system can quickly adjust the driving strategy to ensure the safety of the unmanned vehicle.

[0051] The technical solution of the present invention realizes the automatic driving of the inspection unmanned vehicle, improves the efficiency of highway tunnel construction inspection, and improves the safety of tunnel construction.

[0052] In an optional embodiment of the present invention, step 12 may include:

[0053] Step 121, obtaining map data in the tunnel;

[0054] Step 122, combining the environment data and the map data in the tunnel to obtain tunnel road condition data;

[0055] Step 123, obtaining driving route data including a target path according to the tunnel road condition data.

[0056] In this embodiment, firstly, map data in the tunnel is collected. Such data generally include information such as the geometric layout of the tunnel (such as length, width, curvature, slope, etc.), entrance and exit locations, emergency exit locations, lane divisions in the tunnel, etc.; the map data in the tunnel can be obtained from the design drawings or design models of the tunnel. After obtaining the map data, the real-time acquired environmental data is integrated with the map data in the tunnel to generate tunnel road condition data containing current road condition information. The merging process includes aligning the environmental data with the map data in time and space to ensure that the two can accurately match so as to accurately superimpose the real-time data on the corresponding position of the map; the merged data will form tunnel road condition data, which not only includes the static layout information of the tunnel, but also includes dynamic information such as current obstacles and environmental conditions; the tunnel road condition data is used to plan an optimal driving route from the starting point to the end point. This route will serve as a guide to guide the inspection unmanned vehicle to pass through the tunnel safely and efficiently.

[0057] like Figure 3 As shown, in an optional embodiment proposed by the present invention, step 123 may include:

[0058] Step 1231, rasterizing the tunnel road condition data to obtain a plurality of raster data, wherein the plurality of raster data includes a start raster 5 and an end raster 6;

[0059] Step 1232, starting from the starting grid 5, according to the constraint conditions, the path planning process is performed on the plurality of grid data to obtain the driving route data including the target path.

[0060] In this embodiment, the tunnel road condition data is rasterized according to a basic grid of 10 cm×10 cm to obtain a plurality of raster data, wherein the plurality of raster data includes a starting grid 5 and an end grid 6; starting from the starting grid 5, the plurality of raster data is subjected to path planning processing according to the constraint conditions to obtain driving route data including the target path, and the specific process includes:

[0061] (1) Taking the minimum total energy consumption of the inspection unmanned vehicle as the objective function, a path planning model for the inspection unmanned vehicle is established, which is expressed as:

[0062]

[0063] Where M is the objective function, E is the total energy consumption of the inspection unmanned vehicle, and E min is the minimum energy consumption of the inspection vehicle, E max is the maximum energy consumption of the inspection unmanned vehicle.

[0064] The total energy consumption of the inspection unmanned vehicle is calculated as follows:

[0065] E=e+ξt wait (2)

[0066] Where, e is the energy consumption of the inspection vehicle, t wai is the downtime of the inspection unmanned vehicle when determining the next movement direction, and ξ is the energy consumed by waiting.

[0067] (2) Establish the constraints of the path planning model, including:

[0068] 1) Motion boundary constraint: It is used to specify that the inspection unmanned vehicle can only move forward, backward, left, right, and pause on the plane. Each movement can only choose one direction. The expression is:

[0069]

[0070] In the formula, is the initial position of the inspection vehicle, x 0 ,y 0 is the initial position coordinate of the inspection unmanned vehicle, is the maximum moving position of the inspection vehicle, x max ,y max is the maximum moving position coordinate of the inspection unmanned vehicle, t max is the maximum running time of the inspection vehicle, S is the grid map, x 0 ,y 0 、x max ,y max Within the range determined by the grid map S.

[0071] 2) Kinematic constraint: This constraint is used to ensure that the speed and acceleration of the inspection vehicle are stable and within the specified range. The expression is:

[0072]

[0073] In the formula, v(t) and a(t) are the speed and acceleration of the inspection vehicle at time t, v max 、a max It is the maximum operating speed and acceleration of the inspection unmanned vehicle.

[0074] (3) The shortest distance for the inspection unmanned vehicle path planning is:

[0075]

[0076] Where L is the shortest distance for the inspection unmanned vehicle path planning, For the inspection of unmanned vehicles in the grid node S The distance between them, when i=0, the inspection unmanned vehicle is at the starting point; when i=n, ​​the inspection unmanned vehicle is at the end point.

[0077] (4) Establish the heuristic function of the ant colony algorithm, expressed as:

[0078]

[0079] Where η ij is the heuristic function of the ant colony algorithm, k is a constant, θ 1 is the angle between the starting point and the end point of the inspection vehicle, θ 2 is the angle between the current grid node and the next grid node of the inspection unmanned vehicle, x j ,y j is the position coordinate of the next grid node of the inspection unmanned vehicle, x end ,y end The location coordinates of the inspection unmanned vehicle’s endpoint.

[0080] θ 1 ,θ 2 The formula is:

[0081]

[0082] In the formula, g is the unit vector of the positive semi-axis in the horizontal axis, x i ,y i It is the position coordinate of the current grid node of the inspection unmanned vehicle.

[0083] (5) According to the constraints and the heuristic function η ij , calculate the transfer probability of the inspection unmanned vehicle, and select the grid to be selected in the next step through the roulette method; calculate the number of grids c that the inspection unmanned vehicle can select in the next step. When c=1, mark the next grid j as an obstacle grid according to the obstacle avoidance rule, return to grid i, and recalculate the transfer probability and select the grid to be selected in the next step.

[0084] (6) Analyze whether the inspection unmanned vehicle has reached the destination in the grid map S. If it has reached the destination, output the shortest path information.

[0085] In an optional embodiment of the present invention, step 14 may include:

[0086] Step 141, performing feature comparison between the coordinate data and the driving route data to obtain a comparison result;

[0087] Step 142, according to the comparison result, controlling the inspection unmanned vehicle to travel along the target path;

[0088] In this embodiment, the current coordinate data of the inspection unmanned vehicle is obtained through GPS and network signals, and the coordinates of the route traveled by the unmanned vehicle are located in the map; the coordinate data and the map data are feature-compared to obtain the comparison result; according to the comparison result, the automobile parts transport vehicle is controlled to travel along the target path; during the early deployment, manual remote control driving can also be adopted in advance to drive the inspection unmanned vehicle along the required route, record information such as roads and obstacles through sensors, and draw the initial driving route data based on this information, which has been used by the unmanned vehicle in the starting section.

[0089] When the inspection unmanned vehicle is in the automatic driving stage, the sensor collects information about the surrounding environment in real time, compares it with the information entered in the system, and analyzes whether it needs to slow down or stop to avoid collision risks. At the same time, the coordinates are collected in real time and compared with the route coordinates in the system to automatically identify whether there are any abnormal objects around the unmanned vehicle. If there are abnormal and moving objects, the system automatically determines whether it will affect the driving of the unmanned vehicle, and promptly issues an alarm and slows down or stops the vehicle. During the driving process, the unmanned vehicle can adjust its driving route through remote commands and generate control signals. According to the control signals, the unmanned vehicle is controlled to drive along the target path.

[0090] like Figure 4 As shown, the embodiment of the present invention further provides a highway tunnel construction inspection device 40, comprising:

[0091] The collection module 41 is used to collect environmental data around the driving path of the inspection unmanned vehicle;

[0092] The processing module 42 is used to determine the driving route data according to the environmental data; and obtain the current coordinate data of the inspection unmanned vehicle;

[0093] The control module 43 is used to control the inspection unmanned vehicle to travel along the target path according to the coordinate data and the driving route data.

[0094] Optionally, the acquisition module 41 is specifically used for:

[0095] Environmental data around the driving path of the unmanned inspection vehicle is collected by means of a laser sensor installed on the top and a radar sensor installed on the side of the unmanned inspection vehicle, and a temperature sensor installed on the bottom of the unmanned inspection vehicle. The environmental data includes temperature data in the tunnel, coordinate data of obstacles, and size data of obstacles, wherein the height of the obstacle is greater than a preset value.

[0096] Optionally, the processing module 42 is specifically used for:

[0097] Get map data inside the tunnel;

[0098] The environment data and the map data in the tunnel are combined to obtain tunnel road condition data;

[0099] According to the tunnel road condition data, driving route data including a target path is obtained.

[0100] Optionally, obtaining driving route data including a target path according to the tunnel road condition data includes:

[0101] Performing rasterization processing on the tunnel road condition data to obtain a plurality of raster data, wherein the plurality of raster data includes a start raster and an end raster;

[0102] Starting from the starting grid, the plurality of grid data are processed for path planning according to the constraint conditions to obtain driving route data including the target path.

[0103] Optionally, the processing module 42 is further specifically configured to:

[0104] The current coordinate data of the inspection unmanned vehicle is obtained by installing a GPS locator on the top of the inspection unmanned vehicle.

[0105] Optionally, the control module 43 is specifically used for:

[0106] Performing feature comparison between the coordinate data and the driving route data to obtain a comparison result;

[0107] According to the comparison result, the inspection unmanned vehicle is controlled to travel along the target path.

[0108] Optionally, according to the comparison result, controlling the inspection unmanned vehicle to travel along the target path includes:

[0109] The comparison result indicates that if the coordinate data is in the target path recorded in the driving route data, the inspection unmanned vehicle is controlled to drive along the target path; otherwise, the driving route of the inspection unmanned vehicle is adjusted so that the inspection unmanned vehicle drives along the target path.

[0110] Optionally, adjusting the driving route of the unmanned inspection vehicle so that the unmanned inspection vehicle drives along the target path includes:

[0111] Adjusting the driving route of the inspection unmanned vehicle through remote commands and generating control signals;

[0112] According to the control signal, the inspection unmanned vehicle is controlled to travel along the target path.

[0113] It should be noted that the device is a device corresponding to the above method, and all implementation methods in the above method embodiment are applicable to this embodiment and can achieve the same technical effect.

[0114] like Figure 5 As shown, the embodiment of the present invention further provides a computing device 50, including a processor 51, a memory 52, and a program or instruction stored in the memory 52 and executable on the processor 51. When the program or instruction is executed by the processor 51, each process of the above-mentioned highway tunnel construction inspection method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it is not repeated here. It should be noted that the computing device in the embodiment of the present invention includes the above-mentioned mobile electronic device and non-mobile electronic device.

[0115] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0116] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0117] In the embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0118] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0119] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0120] If the 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, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical disks.

[0121] In addition, it should be noted that in the apparatus and method of the present invention, it is obvious that each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present invention. Moreover, the steps of performing the above-mentioned series of processing can naturally be performed in chronological order according to the order of description, but it is not necessary to perform them in chronological order, and some steps can be performed in parallel or independently of each other. For those of ordinary skill in the art, it is understood that all or any steps or components of the method and apparatus of the present invention can be implemented in any computing device (including processors, storage media, etc.) or a network of computing devices in hardware, firmware, software or a combination thereof, which can be achieved by those of ordinary skill in the art using their basic programming skills after reading the description of the present invention.

[0122] Therefore, the purpose of the present invention can also be achieved by running a program or a group of programs on any computing device. The computing device can be a well-known general-purpose device. Therefore, the purpose of the present invention can also be achieved by simply providing a program product containing a program code for implementing a method or device. That is to say, such a program product also constitutes the present invention, and a storage medium storing such a program product also constitutes the present invention. Obviously, the storage medium can be any well-known storage medium or any storage medium developed in the future. It should also be pointed out that in the device and method of the present invention, it is obvious that each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present invention. In addition, the steps of performing the above-mentioned series of processing can naturally be performed in chronological order according to the order of description, but it is not necessary to perform them in chronological order. Some steps can be performed in parallel or independently of each other.

[0123] The above are preferred embodiments of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A highway tunnel construction inspection method, characterized in that: include: Collect environmental data around the route of the patrol unmanned vehicle; Determine driving route data according to the environmental data; Get the current coordinate data of the inspection unmanned vehicle; According to the coordinate data and the driving route data, the inspection unmanned vehicle is controlled to travel along the target path.

2. The highway tunnel construction inspection method according to claim 1, characterized in that: The collecting of environmental data around the driving path of the patrol unmanned vehicle includes: Environmental data around the driving path of the unmanned inspection vehicle is collected by means of a laser sensor installed on the top and a radar sensor installed on the side of the unmanned inspection vehicle, and a temperature sensor installed on the bottom of the unmanned inspection vehicle. The environmental data includes temperature data in the tunnel, coordinate data of obstacles, and size data of obstacles, wherein the height of the obstacle is greater than a preset value.

3. The highway tunnel construction inspection method according to claim 1, characterized in that: Determining driving route data according to the environmental data includes: Get map data inside the tunnel; The environment data and the map data in the tunnel are combined to obtain tunnel road condition data; According to the tunnel road condition data, driving route data including a target path is obtained.

4. The highway tunnel construction inspection method according to claim 3, characterized in that: According to the tunnel road condition data, driving route data including a target path is obtained, including: Performing rasterization processing on the tunnel road condition data to obtain a plurality of raster data, wherein the plurality of raster data includes a start raster and an end raster; Starting from the starting grid, the plurality of grid data are processed for path planning according to the constraint conditions to obtain driving route data including the target path.

5. The highway tunnel construction inspection method according to claim 1, characterized in that: Get the current coordinate data of the inspection unmanned vehicle, including: The current coordinate data of the inspection unmanned vehicle is obtained by installing a GPS locator on the top of the inspection unmanned vehicle.

6. The highway tunnel construction inspection method according to claim 1, characterized in that: According to the coordinate data and the driving route data, the inspection unmanned vehicle is controlled to drive along the target path, including: Performing feature comparison between the coordinate data and the driving route data to obtain a comparison result; According to the comparison result, the inspection unmanned vehicle is controlled to travel along the target path.

7. The highway tunnel construction inspection method according to claim 6, characterized in that: According to the comparison result, the inspection unmanned vehicle is controlled to travel along the target path, including: The comparison result indicates that if the coordinate data is in the target path recorded in the driving route data, the inspection unmanned vehicle is controlled to drive along the target path; otherwise, the driving route of the inspection unmanned vehicle is adjusted so that the inspection unmanned vehicle drives along the target path.

8. The highway tunnel construction inspection method according to claim 7, characterized in that: Adjusting the driving route of the unmanned inspection vehicle so that the unmanned inspection vehicle drives according to the target path includes: Adjusting the driving route of the inspection unmanned vehicle through remote commands and generating control signals; According to the control signal, the inspection unmanned vehicle is controlled to travel along the target path.

9. A highway tunnel construction inspection device, characterized in that: include: A collection module is used to collect environmental data around the driving path of the inspection unmanned vehicle; A processing module, used for determining driving route data according to the environmental data; Get the current coordinate data of the inspection unmanned vehicle; The control module is used to control the inspection unmanned vehicle to travel along the target path according to the coordinate data and the driving route data.

10. A computing device, characterized in that: include: A processor and a memory storing a computer program, wherein when the computer program is executed by the processor, the method according to any one of claims 1 to 7 is performed.

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