Automatic road repairing method and system based on robot vehicle and medium

Abstract

The embodiment of the invention provides an automatic road repairing method and system based on a robot vehicle and a medium, and the method comprises the steps: obtaining the abnormal region information of a road, and analyzing the abnormal position information of the road based on the abnormal region information; obtaining position information of the robot vehicle, comparing the position information of the robot vehicle with the abnormal position information of the road to obtain a position difference value, and comparing the position difference value with a set position difference threshold value; if the position difference value is smaller than a set position difference threshold value, it is judged that the robot vehicle arrives at a designated place, and road abnormal state information is obtained in real time; generating a repairing mode based on the road abnormal state information, and repairing the road abnormal area; if the position difference value is larger than or equal to a set position difference threshold value, the position of the robot car is adjusted; the road abnormal position information is obtained by analyzing the road abnormal area information, the robot vehicle is controlled to move, and the corresponding repairing mode is generated according to the road abnormal state information, so that the road is accurately repaired, and the repairing effect is improved.

Description

Technical Field

[0001] The present application relates to the technical field of road repair, and more particularly, to an automatic road repair method, system and medium based on a machine vehicle. Background Art

[0002] In the construction and use of roads, due to the combined action of freeze-thaw cycles, water and salt, and vehicle loads on the road surface, longitudinal and transverse cracks are likely to appear on the road surface layer, which is a phenomenon with great harm. Road cracks are divided into transverse cracks and longitudinal cracks. Transverse cracks are caused by the influence of temperature changes (thermal expansion and contraction) and the action of vehicle rolling, pushing, squeezing and friction. Longitudinal cracks are caused by the decline of the groundwater level, the self-weight of the roadbed and the action of heavy-duty vehicles. Uneven settlement occurs in some roadbeds, and the roadbed slides and cracks the road surface. The common method for repairing road cracks is generally filling and repair. However, due to manual repair in the traditional repair method, the integration level between various devices is relatively low, resulting in low repair efficiency and uneven repair quality, thus causing poor repair quality. Summary of the Invention

[0003] The purpose of the embodiments of the present application is to provide an automatic road repair method, system and medium based on a machine vehicle. By analyzing the information of abnormal road areas, the information of abnormal road positions can be obtained. According to the information of abnormal road positions, the movement of the machine vehicle is controlled, and a corresponding repair method is generated according to the information of abnormal road states, so as to accurately repair the road and improve the repair effect.

[0004] The embodiments of the present application also provide an automatic road repair method based on a machine vehicle, including:

[0005] Obtain the information of abnormal road areas, and analyze the information of abnormal road positions based on the information of abnormal areas;

[0006] Obtain the position information of the machine vehicle, compare the position information of the machine vehicle with the information of abnormal road positions to obtain a position difference, and compare the position difference with a set position difference threshold;

[0007] If the position difference is less than the set position difference threshold, it is determined that the machine vehicle has reached the designated location, and the information of abnormal road states is obtained in real time;

[0008] Generate a repair method based on the information of abnormal road states, and repair the abnormal road areas based on the repair method;

[0009] If the position difference is greater than or equal to the set position difference threshold, adjust the position of the machine vehicle.

[0010] Optionally, in the automatic road repair method based on a machine vehicle described in the embodiments of the present application, obtaining the information of abnormal road areas and analyzing the information of abnormal road positions based on the information of abnormal areas specifically includes:

[0011] Based on on-vehicle sensors, three-dimensional point cloud data of the road surface is obtained in real time. The on-vehicle sensors include lidar, cameras, accelerometers, and gyroscopes;

[0012] The three-dimensional point cloud data of the road surface is compared with standard point cloud data to obtain an analysis result, and road abnormal area information is generated based on the analysis result;

[0013] Based on a geomagnetic sensor, the geomagnetic signal when the detection vehicle passes by is obtained, the fluctuation information of the geomagnetic signal is analyzed, and the geomagnetic abnormal position of the road is analyzed based on the fluctuation information of the geomagnetic signal;

[0014] Based on a piezoelectric sensor, the driving pressure of the detector is analyzed, the driving pressure is converted into an electrical signal, the intensity and frequency change information of the electrical signal is analyzed, and the abnormal position of the road driving pressure is analyzed based on the intensity and frequency change information of the electrical signal;

[0015] Based on the geomagnetic abnormal position of the road and the abnormal position of the road driving pressure, road abnormal position information is generated.

[0016] Optionally, in the road automatic repair method based on a machine vehicle described in the embodiments of the present application, machine vehicle position information is obtained, and the machine vehicle position information is compared with the road abnormal position information to obtain a position difference, which specifically includes:

[0017] Based on a GPS receiver to receive satellite signals, the position information of the machine vehicle is analyzed based on the satellite signals;

[0018] The measurement position and the position of the receiver are obtained, and the distance between the measurement satellite and the receiver is calculated;

[0019] Based on the distance between the measurement satellite and the receiver, the three-dimensional coordinates of the machine vehicle are calculated using the principle of triangulation. The three-dimensional coordinates include longitude, latitude, and altitude;

[0020] The road abnormal position information is obtained, and the distance and azimuth between the road abnormal position and the machine vehicle are analyzed based on the road abnormal position information and the three-dimensional coordinates of the machine vehicle;

[0021] Based on the distance and azimuth between the road abnormal position and the machine vehicle, the position difference is calculated.

[0022] Optionally, in the road automatic repair method based on a machine vehicle described in the embodiments of the present application, if the position difference is less than a set position difference threshold, it is determined that the machine vehicle has reached the designated location, and the road abnormal state information is obtained in real time, which specifically includes:

[0023] Based on high-definition cameras at multiple different angles, the road abnormal area is photographed from multiple angles;

[0024] Obtain the image information of the road surface, and use computer vision technology to analyze the captured images in real time to obtain the appearance characteristics of road anomalies. The appearance characteristics of road anomalies include the shape, orientation, and width change of cracks, and the area and location of pavement spalling;

[0025] Through the comparative analysis of continuously captured images, the dynamic changes of abnormal areas are monitored in real time, and the crack extension state and spalling area are analyzed;

[0026] Based on image recognition technology, analyze the color and texture changes of the road surface, analyze the aging degree of road materials, and obtain road anomaly status information.

[0027] Optionally, in the road automatic repair method based on a machine vehicle described in the embodiments of the present application, a repair method is generated based on the road anomaly status information, and the road abnormal area is repaired based on the repair method. Specifically, it includes:

[0028] Obtain the road anomaly status information, analyze the road anomaly type based on the road anomaly status information. The road anomaly types include cracks, potholes, and asphalt spalling;

[0029] Analyze the crack width, pothole depth, and asphalt spalling area based on the road anomaly status information;

[0030] Compare the crack width, pothole depth, and asphalt spalling area with the set condition information to obtain difference information;

[0031] Generate a repair method based on the difference information, and repair the road abnormal area based on the repair method.

[0032] Optionally, in the road automatic repair method based on a machine vehicle described in the embodiments of the present application, if the position difference is greater than or equal to the set position difference threshold, the position of the machine vehicle is adjusted. Specifically, it includes:

[0033] Establish a machine vehicle movement path based on the road anomaly position information and the three-dimensional coordinates of the machine vehicle;

[0034] Control the movement of the machine vehicle based on the machine vehicle movement path, and obtain the machine vehicle movement parameter information in real time;

[0035] Analyze the machine vehicle movement direction, movement speed, and movement position change information based on the machine vehicle movement parameter information;

[0036] Compare the machine vehicle movement direction, movement speed, and movement position change information with the set machine vehicle movement direction, movement speed, and movement position change information to obtain a movement deviation rate;

[0037] Judge whether the movement deviation rate is greater than or equal to the set movement deviation rate threshold;

[0038] If it is greater than or equal to the set moving deviation rate threshold, correction information is generated, and the moving parameters of the machine vehicle are adjusted in real time based on the correction information;

[0039] If it is less than the set moving deviation rate threshold, the position of the machine vehicle is obtained in real time.

[0040] In a second aspect, an embodiment of the present application provides a road automatic repair system based on a machine vehicle, the system includes: a memory and a processor, the memory includes a program of a road automatic repair method based on a machine vehicle, and when the program of the road automatic repair method based on a machine vehicle is executed by the processor, the following steps are implemented:

[0041] Obtain road abnormal area information, and analyze road abnormal position information based on the abnormal area information;

[0042] Obtain the position information of the machine vehicle, compare the position information of the machine vehicle with the road abnormal position information to obtain a position difference, and compare the position difference with the set position difference threshold;

[0043] If the position difference is less than the set position difference threshold, it is determined that the machine vehicle has reached the specified location, and the road abnormal state information is obtained in real time;

[0044] Generate a repair method based on the road abnormal state information, and repair the road abnormal area based on the repair method;

[0045] If the position difference is greater than or equal to the set position difference threshold, adjust the position of the machine vehicle.

[0046] Optionally, in the road automatic repair system based on a machine vehicle described in the embodiment of the present application, obtaining road abnormal area information and analyzing road abnormal position information based on the abnormal area information specifically includes:

[0047] Obtain the three-dimensional point cloud data of the road surface in real time based on an in-vehicle sensor, and the in-vehicle sensor includes a lidar, a camera, an accelerometer, and a gyroscope;

[0048] Compare the three-dimensional point cloud data of the road surface with the standard point cloud data to obtain an analysis result, and generate road abnormal area information based on the analysis result;

[0049] Obtain the geomagnetic signal when the detection vehicle passes based on a geomagnetic sensor, analyze the fluctuation information of the geomagnetic signal, and analyze the road geomagnetic abnormal position based on the fluctuation information of the geomagnetic signal;

[0050] Analyze the driving pressure of the detector based on a piezoelectric sensor, convert the driving pressure into an electrical signal, analyze the intensity and frequency change information of the electrical signal, and analyze the road driving pressure abnormal position based on the intensity and frequency change information of the electrical signal;

[0051] Generate road anomaly location information based on the positions of road geomagnetic anomalies and road driving pressure anomalies.

[0052] Optionally, in the road automatic repair system based on a machine vehicle described in the embodiments of the present application, obtain the machine vehicle position information, compare the machine vehicle position information with the road anomaly location information to obtain a position difference, specifically including:

[0053] Based on the GPS receiver receiving satellite signals, analyze the position information of the machine vehicle based on the satellite signals;

[0054] Obtain the measurement position and the position of the receiver, and calculate the distance between the measurement satellite and the receiver;

[0055] Based on the distance between the measurement satellite and the receiver, calculate the three-dimensional coordinates of the machine vehicle using the triangulation principle. The three-dimensional coordinates include longitude, latitude, and altitude;

[0056] Obtain the road anomaly location information, and analyze the distance and azimuth between the road anomaly location and the machine vehicle based on the road anomaly location information and the three-dimensional coordinates of the machine vehicle;

[0057] Calculate the position difference based on the distance and azimuth between the road anomaly location and the machine vehicle.

[0058] In a third aspect, the embodiments of the present application further provide a computer-readable storage medium, which includes a program for the road automatic repair method based on a machine vehicle. When the program for the road automatic repair method based on a machine vehicle is executed by a processor, the steps of the road automatic repair method based on a machine vehicle as described in any one of the above are implemented.

[0059] As can be seen from the above, a road automatic repair method, system, and medium based on a machine vehicle provided by the embodiments of the present application obtain road anomaly area information, analyze road anomaly location information based on the anomaly area information; obtain machine vehicle position information, compare the machine vehicle position information with the road anomaly location information to obtain a position difference, and compare the position difference with a set position difference threshold; if the position difference is less than the set position difference threshold, it is determined that the machine vehicle has reached the designated location, and the road anomaly state information is obtained in real time; generate a repair method based on the road anomaly state information, and repair the road anomaly area based on the repair method; if the position difference is greater than or equal to the set position difference threshold, adjust the position of the machine vehicle; obtain the road anomaly location information by analyzing the road anomaly area information, control the movement of the machine vehicle according to the road anomaly location information, and generate a corresponding repair method according to the road anomaly state information, so as to accurately repair the road and improve the repair effect. Description of the Drawings

[0060] To more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required for use in the embodiments of the present application. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other relevant drawings can also be obtained based on these drawings.

[0061] Figure 1 It is a flowchart of the road automatic repair method based on a machine vehicle provided by the embodiments of the present application;

[0062] Figure 2 It is a flowchart of the road abnormal position information analysis method of the road automatic repair method based on a machine vehicle provided by the embodiments of the present application;

[0063] Figure 3 It is a flowchart of the position difference calculation method of the road automatic repair method based on a machine vehicle provided by the embodiments of the present application. Specific embodiments

[0064] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all of them. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the present application to be protected, but only represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present application.

[0065] It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present application, terms such as "first" and "second" are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0066] Please refer to Figure 1 , Figure 1 It is a flowchart of a road automatic repair method based on a machine vehicle in some embodiments of the present application. This road automatic repair method based on a machine vehicle is used in a terminal device. This road automatic repair method based on a machine vehicle includes the following steps:

[0067] S101, obtain road abnormal area information, and analyze road abnormal position information based on the abnormal area information;

[0068] S102. Obtain the position information of the robotic vehicle, compare the position information of the robotic vehicle with the road anomaly position information to obtain a position difference, and compare the position difference with a set position difference threshold.

[0069] S103. If the position difference is less than the set position difference threshold, it is determined that the robotic vehicle has reached the specified location, and the road anomaly status information is obtained in real time.

[0070] S104. Generate a repair method based on the road anomaly status information, and repair the road anomaly area based on the repair method.

[0071] S105. If the position difference is greater than or equal to the set position difference threshold, adjust the position of the robotic vehicle.

[0072] It should be noted that by analyzing the road anomaly area to generate the road anomaly position, controlling the robotic vehicle to move to the road anomaly position according to the road anomaly position, and selecting a suitable repair method to repair the road anomaly position, the repair effect is improved.

[0073] Please refer to Figure 2 , Figure 2 FIG. is a flowchart of a method for analyzing road anomaly position information of an automatic road repair method based on a robotic vehicle in some embodiments of the present application. According to an embodiment of the present invention, road anomaly area information is obtained, and road anomaly position information is analyzed based on the anomaly area information, which specifically includes:

[0074] S201. Based on an in-vehicle sensor, obtain three-dimensional point cloud data of the road surface in real time. The in-vehicle sensor includes a lidar, a camera, an accelerometer, and a gyroscope.

[0075] S202. Compare the three-dimensional point cloud data of the road surface with standard point cloud data to obtain an analysis result, and generate road anomaly area information based on the analysis result.

[0076] S203. Based on a geomagnetic sensor, obtain the geomagnetic signal when the detection vehicle passes by, analyze the fluctuation information of the geomagnetic signal, and analyze the road geomagnetic anomaly position based on the fluctuation information of the geomagnetic signal.

[0077] S204. Based on a piezoelectric sensor, analyze the driving pressure of the detector, convert the driving pressure into an electrical signal, analyze the intensity and frequency change information of the electrical signal, and analyze the road driving pressure anomaly position based on the intensity and frequency change information of the electrical signal.

[0078] S205. Generate road anomaly position information based on the road geomagnetic anomaly position and the road driving pressure anomaly position.

[0079] It should be noted that the geomagnetic sensor can indirectly obtain the condition of the road surface by detecting the geomagnetic changes caused when the vehicle passes by. For example, when the geomagnetic signal shows abnormal fluctuations, it may mean that there are cavities or other structural changes under the road, affecting the interaction between the vehicle and the ground. The piezoelectric sensor can convert the pressure generated by the vehicle driving into an electrical signal, and judge whether there is an abnormality on the road by analyzing the intensity and frequency changes of the electrical signal. If there are sudden spikes or abnormal frequency fluctuations in the electrical signal, it may indicate local damage or unevenness on the road.

[0080] Please refer to Figure 3 , Figure 3 which is a flowchart of the position difference calculation method of a road automatic repair method based on a machine vehicle in some embodiments of the present application. According to the embodiments of the present invention, obtaining the machine vehicle position information, comparing the machine vehicle position information with the road abnormal position information to obtain the position difference, specifically including:

[0081] S301, based on the GPS receiver receiving satellite signals, analyzing the position information of the machine vehicle based on the satellite signals;

[0082] S302, obtaining the positions of the measurement location and the receiver, and calculating the distance between the measurement satellite and the receiver;

[0083] S303, calculating the three-dimensional coordinates of the machine vehicle based on the distance between the measurement satellite and the receiver using the triangulation principle, and the three-dimensional coordinates include longitude, latitude and altitude;

[0084] S304, obtaining the road abnormal position information, and analyzing the distance and azimuth between the road abnormal position and the machine vehicle based on the road abnormal position information and the three-dimensional coordinates of the machine vehicle;

[0085] S305, calculating the position difference based on the distance and azimuth between the road abnormal position and the machine vehicle.

[0086] It should be noted that a GPS or BDS receiver is installed on the machine vehicle, and the position of the machine vehicle is determined by receiving satellite signals. These satellite positioning systems calculate the three-dimensional coordinates (longitude, latitude, altitude) of the machine vehicle by measuring the distance between the satellite and the receiver using the triangulation principle. Generally speaking, the positioning accuracy of civilian GPS can reach several meters, while after adopting differential positioning technology, the positioning accuracy of BDS can be further improved to centimeter level. For example, in an open road environment, the machine vehicle obtains its own longitude and latitude information in real time through the GPS receiver, providing basic data for subsequent comparison with the road abnormal position information.

[0087] According to the embodiments of the present invention, if the position difference is less than the set position difference threshold, it is determined that the machine vehicle reaches the specified location, and the road abnormal state information is obtained in real time, specifically including:

[0088] High-definition cameras from multiple different angles are used to take multi-angle pictures of abnormal areas on the road;

[0089] Image information of the road surface is obtained, and computer vision technology is used to perform real-time analysis on the captured images to obtain the appearance features of road anomalies. The appearance features of road anomalies include the shape, orientation, and width change of cracks, and the area and location of pavement spalling;

[0090] Through comparative analysis of continuously captured images, the dynamic changes of abnormal areas are monitored in real time, and the crack extension state and spalling area are analyzed;

[0091] Based on image recognition technology, the color and texture changes of the road surface are analyzed to analyze the aging degree of road materials and obtain road anomaly state information.

[0092] It should be noted that multiple high-definition cameras with different angles are equipped on the vehicle to take multi-angle pictures of abnormal areas on the road and obtain image information of the road surface. Computer vision technology, such as an image recognition algorithm based on deep learning, is used to perform real-time analysis on the captured images.

[0093] The camera images can clearly show the appearance features of road anomalies, such as the shape, orientation, and width change of cracks, and the area and location of pavement spalling. Through comparative analysis of continuously captured images, the dynamic changes of abnormal areas can be monitored in real time, such as whether the cracks are extending and whether there are new damages in the spalling area. In addition, by combining image recognition technology to analyze the color and texture changes of the road surface, the aging degree of road materials and whether there is damage caused by oil stains or other pollutants to the road can be judged.

[0094] According to the embodiments of the present invention, a repair method is generated based on road anomaly state information, and the abnormal area of the road is repaired based on the repair method, which specifically includes:

[0095] Road anomaly state information is obtained, and the road anomaly type is analyzed based on the road anomaly state information. The road anomaly type includes cracks, potholes, and asphalt spalling;

[0096] The crack width, pothole depth, and asphalt spalling area are analyzed based on the road anomaly state information;

[0097] The crack width, pothole depth, and asphalt spalling area are compared with the set condition information to obtain difference information;

[0098] A repair method is generated based on the difference information, and the abnormal area of the road is repaired based on the repair method.

[0099] It should be noted that for shallow potholes, the direct filling method can be adopted. First, clean the loose materials and sundries in the potholes, and then select repair materials similar to the original road surface materials, such as hot mix asphalt mixture or cold patch asphalt mixture. If hot mix asphalt mixture is used, it needs to be heated to the appropriate construction temperature (generally 150 - 170 °C), poured into the potholes, and compacted with a plate compactor or a small roller to ensure that the repaired road surface is flat and well-connected with the original road surface. Cold patch asphalt mixture can be used at normal temperature, which is convenient and fast, but its durability is slightly worse than that of hot mix asphalt mixture. For crack repair, a sealant with good fluidity can be selected, such as silicone sealant or polyurethane sealant. The sealant can effectively fill the cracks, prevent water from seeping in, and avoid further expansion of the cracks. Before pouring the sealant, it is necessary to use high-pressure air or a wire brush to clean the sundries and dust in the cracks to ensure good bonding between the sealant and the crack walls.

[0100] According to an embodiment of the present invention, if the position difference is greater than or equal to the set position difference threshold, the position of the machine vehicle is adjusted, specifically including:

[0101] Establish a moving path of the machine vehicle based on the abnormal road position information and the three-dimensional coordinates of the machine vehicle;

[0102] Control the movement of the machine vehicle based on the moving path of the machine vehicle, and obtain the moving parameter information of the machine vehicle in real time;

[0103] Analyze the moving direction, moving speed, and moving position change information of the machine vehicle based on the moving parameter information of the machine vehicle;

[0104] Compare the moving direction, moving speed, and moving position change information of the machine vehicle with the set moving direction, moving speed, and moving position change information of the machine vehicle to obtain a moving deviation rate;

[0105] Judge whether the moving deviation rate is greater than or equal to the set moving deviation rate threshold;

[0106] If it is greater than or equal to the set moving deviation rate threshold, generate correction information and adjust the moving parameters of the machine vehicle in real time based on the correction information;

[0107] If it is less than the set moving deviation rate threshold, obtain the position of the machine vehicle in real time.

[0108] It should be noted that the lidar continuously emits laser beams and receives reflected light, calculates the distance to each point on the road surface by measuring the round-trip time of the laser, and thus generates high-precision three-dimensional point cloud data of the road. When the machine vehicle reaches the specified location, the lidar can capture the detailed terrain information of the abnormal road area in real time.

[0109] According to an embodiment of the present invention, it further includes:

[0110] Monitor roads using high - resolution satellite images. Satellite images can cover large areas. Through image analysis techniques, the overall shape and abnormal features of roads can be identified. For example, by comparing satellite images from different periods, changes such as new cracks and road surface collapses can be detected. Using multi - spectral remote sensing technology, information about the road surface material can also be obtained to assist in judging the health status of the road. For example, changes in the road surface material may imply potential damage or aging.

[0111] Use drones or aircraft equipped with high - resolution cameras for aerial photography to obtain detailed images of roads. Compared with satellite remote sensing, aerial photography can obtain higher - resolution images and more clearly identify subtle abnormalities on the road surface, such as small cracks and local spalling. Through stereo matching and 3D reconstruction techniques for aerial images, a 3D model of the road can also be generated to accurately measure information such as the undulation of the road and the depth and height of abnormal areas.

[0112] By establishing a public participation mechanism, encourage road users to feedback road abnormal conditions through channels such as mobile applications and websites. Users can upload photos and videos of road abnormalities and describe information such as the location, type, and severity of the abnormalities. These feedback messages can quickly locate abnormal areas on the road, especially some local subtle abnormalities or emergencies that are difficult to detect by sensors, such as suddenly appearing obstacles on the road.

[0113] Professional road inspection personnel regularly conduct on - site inspections of roads and record road abnormal conditions. Inspection personnel can use portable detection equipment, such as road surface flatness meters and crack width measuring instruments, to quantitatively detect road abnormalities. At the same time, the experience of inspection personnel can also identify some potential road abnormalities, such as signs of potential diseases in the road base. By organizing and analyzing inspection data, detailed information about abnormal areas on the road can be obtained.

[0114] In a second aspect, an embodiment of the present application provides a road automatic repair system based on a machine vehicle. The system includes: a memory and a processor. The memory includes a program for the road automatic repair method based on the machine vehicle. When the program for the road automatic repair method based on the machine vehicle is executed by the processor, the following steps are implemented:

[0115] Obtain information about road abnormal areas and analyze road abnormal position information based on the abnormal area information;

[0116] Obtain machine vehicle position information, compare the machine vehicle position information with the road abnormal position information to obtain a position difference, and compare the position difference with a set position difference threshold;

[0117] If the position difference is less than the set position difference threshold, it is determined that the machine vehicle has reached the designated location, and the road abnormal state information is obtained in real - time;

[0118] Generate a repair method based on the road abnormal state information, and repair the road abnormal area according to the repair method;

[0119] If the position difference is greater than or equal to the set position difference threshold, adjust the position of the machine vehicle.

[0120] It should be noted that by analyzing the road abnormal area to generate the road abnormal position, controlling the machine vehicle to move to the road abnormal position according to the road abnormal position, and selecting a suitable repair method to repair the road abnormal position, the repair effect is improved.

[0121] According to the embodiment of the present invention, obtaining road abnormal area information and analyzing road abnormal position information based on the abnormal area information specifically includes:

[0122] Obtain the three-dimensional point cloud data of the road surface in real time based on the vehicle-mounted sensor, and the vehicle-mounted sensor includes a lidar, a camera, an accelerometer and a gyroscope;

[0123] Compare the three-dimensional point cloud data of the road surface with the standard point cloud data to obtain an analysis result, and generate road abnormal area information based on the analysis result;

[0124] Obtain the geomagnetic signal when the detection vehicle passes based on the geomagnetic sensor, analyze the fluctuation information of the geomagnetic signal, and analyze the road geomagnetic abnormal position based on the fluctuation information of the geomagnetic signal;

[0125] Analyze the driving pressure of the detector based on the piezoelectric sensor, convert the driving pressure into an electrical signal, analyze the intensity and frequency change information of the electrical signal, and analyze the road driving pressure abnormal position based on the intensity and frequency change information of the electrical signal;

[0126] Generate road abnormal position information based on the road geomagnetic abnormal position and the road driving pressure abnormal position.

[0127] It should be noted that the geomagnetic sensor can indirectly obtain the road surface condition by detecting the geomagnetic change caused by the passing of the vehicle. For example, when the geomagnetic signal shows abnormal fluctuations, it may mean that there are cavities or other structural changes under the road, affecting the interaction between the vehicle and the ground. The piezoelectric sensor can convert the pressure generated by the vehicle driving into an electrical signal, and judge whether the road is abnormal by analyzing the intensity and frequency changes of the electrical signal. If the electrical signal shows sudden spikes or abnormal frequency fluctuations, it may indicate local damage or unevenness of the road.

[0128] According to the embodiment of the present invention, obtaining the machine vehicle position information, comparing the machine vehicle position information with the road abnormal position information to obtain a position difference, specifically including:

[0129] Based on the satellite signals received by the GPS receiver, analyze the position information of the machine vehicle based on the health signals;

[0130] Obtain the measured position and the position of the receiver, and calculate the distance between the measured satellite and the receiver;

[0131] Based on the distance between the measured satellite and the receiver, calculate the three-dimensional coordinates of the machine vehicle using the triangulation principle. The three-dimensional coordinates include longitude, latitude, and altitude;

[0132] Obtain the road anomaly position information, and analyze the distance and azimuth between the road anomaly position and the machine vehicle based on the road anomaly position information and the three-dimensional coordinates of the machine vehicle;

[0133] Calculate the position difference based on the distance and azimuth between the road anomaly position and the machine vehicle.

[0134] It should be noted that a GPS or BDS receiver is installed on the machine vehicle, and the position of the machine vehicle is determined by receiving satellite signals. These satellite positioning systems calculate the three-dimensional coordinates (longitude, latitude, altitude) of the machine vehicle by measuring the distance between the satellite and the receiver and using the triangulation principle. Generally speaking, the positioning accuracy of civilian GPS can reach several meters, while after adopting differential positioning technology, the positioning accuracy of BDS can be further improved to the centimeter level. For example, in an open road environment, the machine vehicle obtains its longitude and latitude information in real time through the GPS receiver, providing basic data for subsequent comparison with the road anomaly position information.

[0135] According to the embodiment of the present invention, if the position difference is less than the set position difference threshold, it is determined that the machine vehicle has reached the specified location, and the road anomaly state information is obtained in real time, specifically including:

[0136] Take multi-angle photos of the road anomaly area based on high-definition cameras at multiple different angles;

[0137] Obtain the image information of the road surface, and use computer vision technology to perform real-time analysis on the captured images to obtain the appearance characteristics of the road anomaly. The appearance characteristics of the road anomaly include the shape, trend, and width change of the crack, and the area and position of the pavement spalling;

[0138] Through the comparative analysis of continuously captured images, monitor the dynamic changes of the anomaly area in real time, and analyze the crack extension state and the spalling area;

[0139] Analyze the color and texture changes of the road surface based on image recognition technology, analyze the aging degree of the road material, and obtain the road anomaly state information.

[0140] It should be noted that multiple high-definition cameras with different angles are equipped on the machine vehicle to capture images of the road surface from multiple angles in abnormal areas of the road, and obtain image information of the road surface. Using computer vision technology, such as image recognition algorithms based on deep learning, the captured images are analyzed in real time.

[0141] The camera images can clearly show the appearance characteristics of road anomalies, such as the shape, orientation, and width change of cracks, and the area and location of pavement spalling. By comparing and analyzing consecutive captured images, the dynamic changes in abnormal areas can be monitored in real time. For example, whether the cracks are extending and whether there are new damages in the spalling area. In addition, by analyzing the color and texture changes of the road surface in combination with image recognition technology, the aging degree of road materials and whether there is damage caused by oil stains or other pollutants to the road can be judged.

[0142] According to the embodiments of the present invention, a repair method is generated based on the road anomaly state information, and the abnormal area of the road is repaired based on the repair method, which specifically includes:

[0143] Obtain the road anomaly state information, analyze the road anomaly type based on the road anomaly state information, and the road anomaly types include cracks, potholes, and asphalt spalling;

[0144] Analyze the crack width, pothole depth, and asphalt spalling area based on the road anomaly state information;

[0145] Compare the crack width, pothole depth, and asphalt spalling area with the set condition information to obtain difference information;

[0146] Generate a repair method based on the difference information, and repair the abnormal area of the road based on the repair method.

[0147] It should be noted that for shallow potholes, a direct filling method can be used. First, clean the loose materials and debris in the pothole, and then select a repair material similar to the original road surface material, such as hot mix asphalt mixture or cold patch asphalt mixture. If hot mix asphalt mixture is used, it needs to be heated to an appropriate construction temperature (generally 150 - 170 °C), poured into the pothole, and compacted with a plate compactor or a small roller to ensure that the repaired road surface is flat and well-connected with the original road surface. Cold patch asphalt mixture can be used at normal temperature, which is convenient and fast, but its durability is slightly worse than that of hot mix asphalt mixture. For crack repair, a sealant with good fluidity, such as silicone sealant or polyurethane sealant, can be selected. The sealant can effectively fill the cracks, prevent water from seeping in, and avoid further expansion of the cracks. Before pouring the sealant, it is necessary to use high-pressure air or a wire brush to clean the debris and dust in the cracks to ensure good adhesion of the sealant to the crack walls.

[0148] According to the embodiments of the present invention, if the position difference is greater than or equal to the set position difference threshold, the position of the machine vehicle is adjusted, which specifically includes:

[0149] Establish the moving path of the machine vehicle based on the abnormal position information of the road and the three-dimensional coordinates of the machine vehicle;

[0150] Control the movement of the machine vehicle based on the moving path of the machine vehicle, and obtain the moving parameter information of the machine vehicle in real time;

[0151] Analyze the moving direction, moving speed and moving position change information of the machine vehicle based on the moving parameter information of the machine vehicle;

[0152] Compare the moving direction, moving speed and moving position change information of the machine vehicle with the set moving direction, moving speed and moving position change information of the machine vehicle to obtain the moving deviation rate;

[0153] Judge whether the moving deviation rate is greater than or equal to the set moving deviation rate threshold;

[0154] If it is greater than or equal to the set moving deviation rate threshold, generate correction information and adjust the moving parameters of the machine vehicle in real time based on the correction information;

[0155] If it is less than the set moving deviation rate threshold, obtain the position of the machine vehicle in real time.

[0156] It should be noted that the lidar continuously emits laser beams and receives reflected light, calculates the distance from each point on the road surface by measuring the round-trip time of the laser, and thus generates high-precision three-dimensional point cloud data of the road. When the machine vehicle reaches the designated location, the lidar can capture the detailed terrain information of the abnormal area of the road in real time.

[0157] According to the embodiments of the present invention, it further includes:

[0158] Monitor the road using high-resolution satellite images. Satellite images can cover large areas. Through image analysis technology, the overall shape and abnormal features of the road can be identified. For example, by comparing satellite images of different periods, changes such as new cracks and road surface collapses on the road can be found. Using multi-spectral remote sensing technology, the material information of the road surface can also be obtained to assist in judging the health status of the road. For example, changes in the material of the road surface may imply potential damage or aging.

[0159] Use an unmanned aerial vehicle or an aircraft equipped with a high-resolution camera for aerial photography to obtain detailed images of the road. Compared with satellite remote sensing, aerial photography can obtain higher-resolution images and more clearly identify subtle abnormalities on the road surface, such as small cracks and local spalling. Through stereo matching and three-dimensional reconstruction technology for aerial images, a three-dimensional model of the road can also be generated to accurately measure the undulations of the road and the depth, height, etc. of the abnormal area.

[0160] By establishing a public participation mechanism, road users are encouraged to feedback road anomalies through channels such as mobile applications and websites. Users can upload photos and videos of road anomalies and describe information such as the location, type, and severity of the anomalies. These feedback messages can quickly locate road anomaly areas, especially some local subtle anomalies or emergencies that are difficult to detect by sensors, such as suddenly appearing obstacles on the road.

[0161] Professional road inspection personnel regularly conduct on-site inspections of roads and record road anomalies. Inspection personnel can use portable detection equipment, such as road surface flatness meters and crack width measuring instruments, to quantitatively detect road anomalies. At the same time, the experience of inspection personnel can also identify some potential road anomalies, such as potential disease signs in the road base. By organizing and analyzing inspection data, detailed information on road anomaly areas can be obtained.

[0162] The third aspect of the present invention provides a computer-readable storage medium, which includes a program for the automatic road repair method based on a machine vehicle. When the program for the automatic road repair method based on a machine vehicle is executed by a processor, the steps of the automatic road repair method based on a machine vehicle as described in any one of the above are implemented.

[0163] An automatic road repair method, system, and medium based on a machine vehicle disclosed by the present invention obtain road anomaly area information, analyze road anomaly location information based on the anomaly area information; obtain machine vehicle location information, compare the machine vehicle location information with the road anomaly location information to obtain a location difference, and compare the location difference with a set location difference threshold; if the location difference is less than the set location difference threshold, it is determined that the machine vehicle has reached the designated location, and the road anomaly status information is obtained in real time; generate a repair method based on the road anomaly status information, and repair the road anomaly area based on the repair method; if the location difference is greater than or equal to the set location difference threshold, adjust the machine vehicle location; by analyzing the road anomaly area information to obtain the road anomaly location information, control the movement of the machine vehicle according to the road anomaly location information, and generate a corresponding repair method according to the road anomaly status information, so as to accurately repair the road and improve the repair effect.

[0164] In several embodiments provided by the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of 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 can be integrated into another system, or some features can be ignored, or not executed. In addition, the coupling, direct coupling, or communication connection between the displayed or discussed components can be through some interfaces. The indirect coupling or communication connection of devices or units can be electrical, mechanical, or other forms.

[0165] The units described above as separate components may or may not be physically separated. The components displayed as units may or may not be physical units. 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.

[0166] In addition, each functional unit in the embodiments of the present invention can be fully integrated into a processing unit, or each unit can be separately used as a unit, or two or more units can be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware, or in the form of a combination of hardware and software functional units.

[0167] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a readable storage medium. When the program is executed, it executes the steps including the above method embodiments. The foregoing storage media include various media that can store program codes, such as removable storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0168] Alternatively, if the above-mentioned integrated units of the present invention are implemented in the form of software functional modules and sold or used as independent products, they can also be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiments of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the various embodiments of the present invention. The foregoing storage media include various media that can store program codes, such as removable storage devices, ROM, RAM, magnetic disks, or optical discs.

Claims

1. An automatic road repair method based on a machine vehicle, characterized in that, Including: Obtain information on road abnormal areas, and analyze road abnormal position information based on the abnormal area information; Obtain the position information of the machine vehicle, compare the position information of the machine vehicle with the road abnormal position information to obtain a position difference, and compare the position difference with a set position difference threshold; If the position difference is less than the set position difference threshold, it is determined that the machine vehicle has reached the specified location, and the road abnormal state information is obtained in real time; Generate a repair method based on the road abnormal state information, and repair the road abnormal area based on the repair method; If the position difference is greater than or equal to the set position difference threshold, adjust the position of the machine vehicle.

2. The automatic road repair method based on a machine vehicle according to claim 1, characterized in that, Obtain information on road abnormal areas, and analyze road abnormal position information based on the abnormal area information, specifically including: Obtain the three-dimensional point cloud data of the road surface in real time based on on-vehicle sensors, and the on-vehicle sensors include lidar, cameras, accelerometers, and gyroscopes; Compare the three-dimensional point cloud data of the road surface with the standard point cloud data to obtain an analysis result, and generate road abnormal area information based on the analysis result; Obtain the geomagnetic signal when the detection vehicle passes by based on the geomagnetic sensor, analyze the fluctuation information of the geomagnetic signal, and analyze the road geomagnetic abnormal position based on the fluctuation information of the geomagnetic signal; Analyze the driving pressure of the detector based on the piezoelectric sensor, convert the driving pressure into an electrical signal, analyze the intensity and frequency change information of the electrical signal, and analyze the road driving pressure abnormal position based on the intensity and frequency change information of the electrical signal; Generate road abnormal position information based on the road geomagnetic abnormal position and the road driving pressure abnormal position.

3. The automatic road repair method based on a machine vehicle according to claim 2, wherein Obtain the position information of the machine vehicle, compare the position information of the machine vehicle with the road abnormal position information to obtain a position difference, specifically including: Receive satellite signals based on the GPS receiver, and analyze the position information of the machine vehicle based on the health signals; Obtain the measurement position and the position of the receiver, and calculate the distance between the measurement satellite and the receiver; Calculate the three-dimensional coordinates of the machine vehicle based on the distance between the measurement satellite and the receiver using the triangulation principle, and the three-dimensional coordinates include longitude, latitude, and altitude; Obtain the road abnormal position information, and analyze the distance and azimuth between the road abnormal position and the machine vehicle based on the road abnormal position information and the three-dimensional coordinates of the machine vehicle; Calculate the position difference based on the distance and azimuth between the road abnormal position and the machine vehicle.

4. The automatic road repair method based on a machine vehicle according to claim 3, wherein, If the position difference is less than the set position difference threshold, it is determined that the machine vehicle has reached the specified location, and the road abnormal state information is obtained in real time, specifically including: Take multi-angle photos of the road abnormal area based on high-definition cameras at multiple different angles; Obtain the image information of the road surface, and use computer vision technology to perform real-time analysis on the taken images to obtain the appearance characteristics of the road abnormal, and the appearance characteristics of the road abnormal include the shape, trend, width change of the crack, the area and position of the road surface spalling; Through the comparative analysis of continuously taken images, monitor the dynamic changes of the abnormal area in real time, and analyze the crack extension state and the spalling area; Analyze the color and texture changes of the road surface based on image recognition technology, analyze the aging degree of the road material, and obtain the road abnormal state information.

5. The method for automatically repairing roads based on a machine vehicle according to claim 4, wherein Generate a repair method based on road abnormal state information, and repair the road abnormal area based on the repair method, specifically including: Obtain road abnormal state information, analyze the road abnormal type based on the road abnormal state information, and the road abnormal type includes cracks, potholes, and asphalt spalling; Analyze the crack width, pothole depth, and asphalt spalling area based on the road abnormal state information; Compare the crack width, pothole depth, and asphalt spalling area with the set condition information to obtain difference information; Generate a repair method based on the difference information, and repair the road abnormal area based on the repair method.

6. The road automatic repair method based on a machine vehicle according to claim 5, characterized in that, If the position difference is greater than or equal to the set position difference threshold, adjust the position of the machine vehicle, specifically including: Establish a moving path of the machine vehicle based on the road abnormal position information and the three-dimensional coordinates of the machine vehicle; Control the movement of the machine vehicle based on the moving path of the machine vehicle, and obtain the machine vehicle movement parameter information in real time; Analyze the machine vehicle movement direction, movement speed, and movement position change information based on the machine vehicle movement parameter information; Compare the machine vehicle movement direction, movement speed, and movement position change information with the set machine vehicle movement direction, movement speed, and movement position change information to obtain a movement deviation rate; Judge whether the movement deviation rate is greater than or equal to the set movement deviation rate threshold; If it is greater than or equal to the set movement deviation rate threshold, generate correction information, and adjust the machine vehicle movement parameters in real time based on the correction information; If it is less than the set movement deviation rate threshold, obtain the machine vehicle position in real time.

7. An automatic road repair system based on a machine vehicle, characterized in that, The system includes: a memory and a processor. The memory includes a program of the road automatic repair method based on the machine vehicle. When the program of the road automatic repair method based on the machine vehicle is executed by the processor, the following steps are implemented: Obtain road abnormal area information, and analyze road abnormal position information based on the abnormal area information; Obtain machine vehicle position information, compare the machine vehicle position information with the road abnormal position information to obtain a position difference, and compare the position difference with the set position difference threshold; If the position difference is less than the set position difference threshold, determine that the machine vehicle has reached the specified location, and obtain road abnormal state information in real time; Generate a repair method based on the road abnormal state information, and repair the road abnormal area based on the repair method; If the position difference is greater than or equal to the set position difference threshold, adjust the position of the machine vehicle.

8. The road automatic repair system based on a machine vehicle according to claim 7, characterized in that, Obtain road abnormal area information, and analyze road abnormal position information based on the abnormal area information, specifically including: Obtain the three-dimensional point cloud data of the road surface in real time based on the vehicle-mounted sensor, and the vehicle-mounted sensor includes a lidar, a camera, an accelerometer, and a gyroscope; Compare the three-dimensional point cloud data of the road surface with the standard point cloud data to obtain an analysis result, and generate road abnormal area information based on the analysis result; Obtain the geomagnetic signal when the detection vehicle passes by based on the geomagnetic sensor, analyze the fluctuation information of the geomagnetic signal, and analyze the road geomagnetic abnormal position based on the fluctuation information of the geomagnetic signal; Analyze the driving pressure of the detector based on the piezoelectric sensor, convert the driving pressure into an electric signal, analyze the intensity and frequency change information of the electric signal, and analyze the road driving pressure abnormal position based on the intensity and frequency change information of the electric signal; Generate road anomaly location information based on the road geomagnetic anomaly location and the road driving pressure anomaly location.

9. The road automatic repair system based on a machine vehicle according to claim 8, characterized in that Obtain the location information of the machine vehicle, compare the location information of the machine vehicle with the road anomaly location information, and obtain the location difference, specifically including: Based on the GPS receiver receiving satellite signals, analyze the location information of the machine vehicle based on the health signals; Obtain the measurement location and the location of the receiver, and calculate the distance between the measurement satellite and the receiver; Calculate the three-dimensional coordinates of the machine vehicle based on the distance between the measurement satellite and the receiver using the principle of triangulation. The three-dimensional coordinates include longitude, latitude, and altitude; Obtain the road anomaly location information, and analyze the distance and azimuth between the road anomaly location and the machine vehicle based on the road anomaly location information and the three-dimensional coordinates of the machine vehicle; Calculate the location difference based on the distance and azimuth between the road anomaly location and the machine vehicle.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a program for the automatic road repair method based on the machine vehicle. When the program for the automatic road repair method based on the machine vehicle is executed by a processor, the steps of the automatic road repair method based on the machine vehicle as described in any one of claims 1 to 6 are implemented.

Images