A method and system based on spatiotemporal tracing of pavement disease locations

Abstract

The present invention relates to a method and system based on spatiotemporal tracing of the location of road defects, wherein the spatiotemporal tracing system includes a terminal unit, a cloud unit, and a computing unit that are communicatively connected in sequence; the terminal unit includes an equipment chassis installed on the top of a car, an industrial computer and two on-board cameras are arranged in the equipment chassis, and the shooting ends of the two on-board cameras are respectively facing the front and rear of the car and aimed at the road surface; the industrial computer is provided with a wireless communication module, a positioning module, and a collection program for collecting objects while the car is driving, the positioning module is used to obtain the GPS of the current photo taken by the on-board camera, and at the same time obtain the azimuth and driving speed of the car; the wireless communication module is used to transmit the data and images of the terminal unit to the data collection interface of the cloud unit; the computing unit is connected to the cloud unit to determine whether there is a disease on the road surface. If a disease occurs, the data of each unit is automatically calculated and traced, and displayed through the system platform.

Description

Technical Field

[0001] The present invention relates to the technical field of road engineering, and in particular to a method and system based on spatiotemporal tracing of road surface disease locations. Background Art

[0002] The spatiotemporal tracing of the location of pavement defects is based on the daily changes in the road. It is necessary to track the characteristic development of a certain defect at a certain location and track its changes. The road surface directly bears heavy loads and is exposed to the natural environment for a long time. The environment is relatively harsh. The process of change when a certain defect occurs can be traced back, and targeted observation, maintenance and repair can be carried out to conduct better analysis. Then, better solutions can be issued to maintain and repair the road surface, improve road driving safety, and avoid unnecessary safety accidents.

[0003] Existing technologies often overlook subtle road surface defects during routine inspections. Observation methods rely on manual screening of historical image data or on-site inspections to determine if maintenance is necessary. These approaches are labor-intensive and inefficient, failing to promptly and effectively identify, track, and evaluate road surface issues. These solutions are susceptible to external influences, leading to severe defects that cannot be immediately detected and addressed, potentially compromising road safety.

[0004] On the other hand, manual on-site observations are prone to omissions and are unable to observe whether the condition has deformed. There are many vehicles on the road, which is inefficient and unsafe. The frequency of on-foot observations is low and there is no way to discover problems in time. Large-scale and high-frequency observations cannot meet the requirements, and they are more likely to be ignored in remote areas. Therefore, when deformation occurs, it cannot be handled in time, resulting in the problem of being unable to maintain the road surface in time in serious cases. Summary of the Invention

[0005] In view of the shortcomings of the existing technology, the purpose of the present invention is to provide a method and system based on the spatiotemporal tracing of the location of pavement defects, which solves the problems of manual comparison of images with historical images after manual on-foot and vehicle inspections, which is inefficient, slow, labor-intensive, unable to be rolled out on a large scale, inaccurate visual inspection, and unable to be further analyzed.

[0006] The above-mentioned object of the present invention is achieved through the following technical solutions:

[0007] A spatiotemporal tracing system based on the location of road damage, comprising a terminal unit, a cloud unit, and a computing unit that are sequentially communicatively connected;

[0008] The terminal unit includes an equipment chassis mounted on the top of the car and on-board cameras mounted on the front and rear ends of the car, respectively. An industrial computer is provided in the equipment chassis, and the on-board cameras are data-connected to the industrial computer. The shooting ends of the two on-board cameras are respectively facing the front and rear directions of the car and aimed at the road surface;

[0009] The industrial computer is provided with a wireless communication module, a positioning module and a collection program for collecting objects while the car is driving. The positioning module is used to obtain the GPS of the current photo taken by the on-board camera, and at the same time obtain the azimuth and driving speed of the car;

[0010] The industrial computer is connected to the cloud unit via the wireless communication module, and the wireless communication module is used to transmit the data and images of the terminal unit to the data acquisition interface of the cloud unit;

[0011] The computing unit is connected to the cloud unit to determine whether there is any damage to the road surface. If any damage occurs, the data of each unit is automatically calculated and traced, and displayed through the system platform.

[0012] In a preferred example, the present invention can be further configured as follows: the vehicle-mounted camera is respectively connected to an encoder and a timing module, the encoder is installed on the wheel of the car to calculate the distance to trigger the vehicle-mounted camera to take a photo, and the timing module is used to set the time to trigger the vehicle-mounted camera to take a photo.

[0013] In a preferred example, the present invention can be further configured as follows: when the cloud unit identifies and analyzes the data and images of the terminal unit, it classifies them by time and device identification number and renames the images;

[0014] The GPS data of the image is used to reversely calculate the identifiable road address through Amap inverse encoding;

[0015] If the road is an urban road, it is carried out according to the route drawn in advance by Luge, calculated through spatial data, and then reverse geocoded;

[0016] For high-grade highways and rural roads, the road pile number is used as the standard, and spatial data is used to match the pile number segments within fixed kilometers and hundred meters.

[0017] Road line drawing is done through the cloud management system. The stake numbers and road sections are divided. The data is then linearly interpolated at 10-meter intervals for spatial data range calculation, and road and unit affiliation are done.

[0018] In a preferred example, the present invention can be further configured as follows: the data and image of the terminal unit include the collected original picture, the size of the picture, the time t of the picture, the collected longitude lon and latitude lat.

[0019] In a preferred example, the present invention can be further configured as follows: the cloud unit identifies and analyzes the data and images of the terminal unit to obtain each road defect, and the road defects include potholes, transverse cracks, longitudinal cracks and reticular cracks.

[0020] In a preferred embodiment of the present invention, the method for the calculation unit to calculate and trace each unit data includes the following steps:

[0021] a1. Obtain the disease type, longitude and latitude, and the set tracing range, time, and direction for each location;

[0022] a2. Use the conditions in a1 to find the disease that occurred most recently. If no record is found, create a new disease, find the record of the last inspection, and obtain the code of the current disease label (a code generated when the disease was first added), and store it in the historical record database table;

[0023] a3. Use the platforms of rural roads, urban roads and high-grade highways to trace the location, time and space of individual diseases and track their development process.

[0024] In a preferred example, the present invention can be further configured as follows: the wireless communication module is a 4G module or a 5G module.

[0025] A method for spatiotemporal tracing of pavement damage locations, characterized by comprising the following steps:

[0026] S1. After the system is started, while the vehicle is driving, the acquisition program issues corresponding instructions according to the rules to collect images, and the acquisition program uploads the data and images to the receiving system of the cloud unit through the https protocol and the wireless communication module;

[0027] S2. The cloud unit attributes the data to the road and the unit, and saves the image to the OSS storage object;

[0028] S3, the computing unit accesses the algorithm to identify the image, identifies the presence of a disease, and records relevant information such as the size, type, and severity of the disease, and draws a box to record the pixel location;

[0029] S4. Then, the latitude and longitude are passed to the pre-implemented method. This method searches for the recorded road section information and matches it with the prepared spatial database. If a new record is added, a code is generated and directly stored in the record table. If a record is matched, the latest record code is obtained and labeled and stored in the record table.

[0030] S5. Display through the system platform and users can view it.

[0031] In summary, the present invention includes at least one of the following beneficial technical effects:

[0032] 1. The present invention discloses a method and system for spatiotemporal tracing of pavement defect locations. By using the longitude and latitude of captured images to store them in a spatial database table and establish an index, rapid and precise positioning and real-time viewing can be achieved to trace back to the development process of historical defects, including changes in size and shape. During routine inspections, one only needs to drive a vehicle, install the terminal device, and start the vehicle. Even at high speeds, defects can be identified and spatial tracing can be used to track and evaluate the development process of the defect.

[0033] 2. Compared with existing daily inspections or manual photography methods, the tracing method and system provided by the present invention can more easily, objectively and accurately evaluate the development process of diseases. By promptly discovering the development process of diseases, problems can be discovered in a timely manner, and the disease assessment can be completed quickly, helping maintenance units to automatically analyze road problems that are about to occur or will occur in the future. Relying on high-frequency inspections and high-precision positioning of equipment, including the accuracy of disease identification, long-term tracking can be achieved, and it can be assessed whether the problem will occur again and possible predictions can be made. Compared with manual methods, it is better and has a wider coverage, and it also avoids the safety risks encountered when inspecting the road on site.

[0034] 3. From an economic perspective, the method and system described in this invention primarily rely on intelligent, lightweight terminal equipment (cameras, positioning modules, and data acquisition programs). This significantly increases inspection frequency while also enabling a more granular understanding of the development of diseases. Just like the growth of flowers and plants, minor, moderate, and severe changes are constantly occurring. This reduces the cost of manual screening while reducing the cost of equipment for existing routine inspections, providing wider coverage. By assessing the severity, size, type, and timing of disease damage, maintenance and repairs can be performed before serious, dangerous, and unsafe conditions arise, ensuring traffic and pedestrian safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a block diagram of the overall structure of the display system of the present invention.

[0036] Figure 2 The figure shows the structure of the terminal unit of the present invention.

[0037] Figure 3 The flowchart of the spatiotemporal tracing method of the present invention is shown.

[0038] Figure numerals: 1. terminal unit; 11. equipment chassis; 12. vehicle-mounted camera; 13. industrial computer; 14. wireless communication module; 15. positioning module; 2. cloud unit; 3. computing unit. DETAILED DESCRIPTION

[0039] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application; it is obvious that the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0040] In the description of this application, it should be noted that the terms "upper," "lower," "inner," "outer," "top / bottom," and the like, indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate the description of this application and simplify the description. They do not indicate or imply that the devices or components referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limitations on this application. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0041] In the description of this application, it should be noted that, unless otherwise expressly specified or limited, the terms "installed," "provided with," "mounted / connected," and "connected" should be understood in a broad sense. For example, "connected" can mean a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in this application based on the specific circumstances.

[0042] Example 1:

[0043] Reference Figure 1-2 The present invention discloses a spatiotemporal tracing system for pavement defect locations, comprising a terminal unit 1, a cloud unit 2, and a computing unit 3, which are communicatively connected in sequence. The terminal unit 1 comprises a device chassis 11 mounted on the top of a vehicle and onboard cameras 12 mounted at the front and rear ends of the vehicle, respectively. The device chassis 11 houses an industrial computer 13, which is data-connected to the onboard cameras 12. The imaging ends of the two onboard cameras 12 face the front and rear directions of the vehicle and are aligned with the road surface.

[0044] The industrial computer 13 is equipped with a wireless communication module 14, a positioning module 15, and a collection program for collecting objects while the vehicle is driving. The positioning module 15 is used to obtain the GPS of the current photo taken by the onboard camera 12, and simultaneously obtain the azimuth angle and driving speed of the vehicle. The industrial computer 13 is connected to the cloud unit 2 via the wireless communication module 14. The wireless communication module 14 is used to transmit the data and images of the terminal unit 1 to the data collection interface of the cloud unit 2. The calculation unit 3 is connected to the cloud unit 2 to determine whether there are any road defects. If there are any defects, the calculation and tracing of each unit data are automatically performed and displayed through the system platform. In this embodiment, the wireless communication module 14 is a 4G module or a 5G module.

[0045] Among them, the device chassis 11 is installed on the top of the car, and the on-board camera 12 is installed in the front and rear of the device chassis 11 and aimed at the road surface. It is directly powered by the car's electrical frequency, and the industrial computer 13 can be powered and start working. At this time, a developed acquisition program is installed in the internal system to trigger the photo function. The camera's pixel is >2 million pixels, so the collected image can be used to distinguish road conditions. The image acquisition frequency can be controlled by the software program to trigger the photo.

[0046] The vehicle-mounted camera 12 is connected to an encoder and a timing module respectively. The encoder is installed on the wheel of the car and is used to calculate the distance to trigger the vehicle-mounted camera 12 to take a photo. The timing module is used to set the time to trigger the vehicle-mounted camera 12 to take a photo.

[0047] When the cloud unit 2 identifies and analyzes the data and images of the terminal unit 1, it classifies them by time and device identification number and renames the images; through the GPS data of the image, it reversely calculates the identifiable road address through Gaode inverse coding; if the road is an urban road, it follows the route drawn in advance by the road grid, calculates through spatial data, and then performs reverse geocoding; when it is a high-grade highway or rural road, it takes the road stake number as the standard, and matches it within the fixed kilometer and 100-meter stake number segments through spatial data; the road line drawing is performed through the cloud management system to draw the route, do the stake number and road section splitting, and then perform linear interpolation of the data at a point of 10 meters for spatial data range calculation, and do the road attribution and unit attribution.

[0048] The data and images from terminal unit 1 include the original image, its size, the time t at which the image was captured, and its longitude lon and latitude lat. Cloud unit 2 identifies and analyzes the data and images from terminal unit 1 to identify each road defect, including potholes, transverse cracks, longitudinal cracks, and reticular cracks.

[0049] The method for calculating and tracing each unit data by the calculation unit 3 includes the following steps:

[0050] a1. Obtain the disease type, longitude and latitude, and the set tracing range, time, and direction for each location;

[0051] a2. Use the conditions in a1 to find the most recently occurring disease. If no record is found, create a new disease, find the record of the last inspection, and obtain the code of the current disease label (a code generated when the disease is first added). This code is then stored in the historical record database table.

[0052] a3. Use the platforms of rural roads, urban roads and high-grade highways to trace the location, time and space of individual diseases and track their development process.

[0053] Example 2:

[0054] Reference Figure 3 The present invention also discloses a method for spatiotemporal tracing of pavement disease locations, comprising the following steps:

[0055] S1. After the system is started, while the vehicle is driving, the acquisition program issues corresponding instructions according to the rules to collect images, and the acquisition program uploads the data and images to the receiving system of the cloud unit 2 through the https protocol and the wireless communication module 14;

[0056] S2, cloud unit 2 attributes the data to the road and unit, and saves the image to the OSS storage object;

[0057] S3, the computing unit 3 accesses the algorithm to identify the image, identifies the presence of diseases, and records relevant information such as the size, type, and severity of the diseases, and draws a box to record the pixel location;

[0058] S4. Then, the latitude and longitude are passed to the pre-implemented method. This method searches for the recorded road section information and matches it with the prepared spatial database. If a new record is added, a code is generated and directly stored in the record table. If a record is matched, the latest record code is obtained and labeled and stored in the record table.

[0059] S5. Display through the system platform and users can view it.

[0060] The implementation principle of this embodiment is as follows: The present invention discloses a method and system based on spatiotemporal tracing of pavement disease locations. It uses the latitude and longitude of the collected images to store them in a spatial database table and establish an index. This can achieve fast and accurate positioning and real-time viewing to trace the development process of historical diseases, including changes in size and shape. Therefore, during daily inspections, one only needs to drive a car, install the terminal equipment, start the vehicle, and even at a relatively high speed, identify the disease and then track the development process of the disease through spatial tracing and conduct an evaluation.

[0061] The embodiments of this specific implementation method are all preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Therefore, any equivalent changes made based on the structure, shape, and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A spatiotemporal tracing system based on the location of road defects, characterized by: It includes a terminal unit (1), a cloud unit (2), and a computing unit (3) which are communicatively connected in sequence; The terminal unit (1) includes a device chassis (11) installed on the top of the car and vehicle-mounted cameras (12) installed at the front and rear ends of the car respectively. An industrial computer (13) is provided in the device chassis (11). The vehicle-mounted cameras (12) are data-connected to the industrial computer (13). The shooting ends of the two vehicle-mounted cameras (12) are respectively oriented toward the front and rear directions of the car and are aligned with the road surface. The industrial computer (13) is provided with a wireless communication module (14), a positioning module (15) and a collection program for collecting objects during the driving process of the vehicle. The positioning module (15) is used to obtain the GPS of the current photo taken by the vehicle-mounted camera (12), and simultaneously obtain the azimuth angle and driving speed of the vehicle; The industrial computer (13) is connected to the cloud unit (2) via the wireless communication module (14), and the wireless communication module (14) is used to transmit the data and images of the terminal unit (1) to the data acquisition interface of the cloud unit (2); The computing unit (3) is connected to the cloud unit (2) and is used to determine whether there is any road surface damage. If any damage is found, each unit data is automatically calculated and traced, and displayed through the system platform; When the cloud unit (2) identifies and analyzes the data and images of the terminal unit (1), it classifies them by time and device identification number and renames the images; The GPS data of the image is used to reversely calculate the identifiable road address through Amap inverse encoding; If the road is an urban road, it is carried out according to the route drawn in advance by Luge, calculated through spatial data, and then reverse geocoded; For high-grade highways and rural roads, the road pile number is used as the standard, and spatial data is used to match the pile number segments within fixed kilometers and hundred meters. Road line drawing is done through the cloud management system. The stake numbers and road sections are divided. The data is then linearly interpolated at 10-meter intervals for spatial data range calculation, and road and unit affiliation are done.

2. The spatiotemporal tracing system for pavement damage locations according to claim 1, characterized in that: The vehicle-mounted camera (12) is respectively connected to an encoder and a timing module. The encoder is mounted on the wheel of the vehicle and is used to calculate the distance to trigger the vehicle-mounted camera (12) to take a photo. The timing module is used to set a time to trigger the vehicle-mounted camera (12) to take a photo.

3. The spatiotemporal tracing system for pavement damage locations according to claim 1 is characterized by: The data and images of the terminal unit (1) include the collected original picture, the size of the picture (size), the time t of the picture, the collected longitude lon and latitude lat.

4. The spatiotemporal tracing system for pavement damage locations according to claim 1 is characterized by: The cloud unit (2) identifies and analyzes the data and images of the terminal unit (1) to obtain each road defect, wherein the road defects include potholes, transverse cracks, longitudinal cracks, and reticular cracks.

5. The spatiotemporal tracing system for pavement damage locations according to claim 1 is characterized by: The method for calculating and tracing each unit data by the calculation unit (3) comprises the following steps: a1. Obtain the disease type, longitude and latitude, and the set tracing range, time, and direction for each location; a2. Use the conditions in a1 to find the disease that occurred most recently. If no record is found, create a new disease, find the record of the last inspection, and obtain the code of the current disease label. The code generated when the disease was first added is stored in the historical record database table. a3. Use the platforms of rural roads, urban roads and high-grade highways to trace the location, time and space of individual diseases and track their development process.

6. A spatiotemporal tracing system for pavement damage locations according to any one of claims 1 to 5, characterized in that: The wireless communication module (14) is a 4G module or a 5G module.

7. A method for spatiotemporal tracing of pavement defect locations, applied to a system according to any one of claims 1 to 6, characterized in that: The following steps are involved: S1. After the system is started, while the vehicle is driving, the acquisition program issues corresponding instructions according to the rules to acquire images, and the acquisition program uploads the data and images to the receiving system of the cloud unit (2) through the https protocol and the wireless communication module (14); S2, the cloud unit (2) attributes the data to roads and units, and saves the images to an OSS storage object; S3, the computing unit (3) accesses the algorithm to identify the image, identifies the disease, and records the relevant information of the disease size, type, and severity, and draws a box to record the pixel position; S4. Then, the latitude and longitude are passed to the pre-implemented method. This method searches for the recorded road section information and matches it with the prepared spatial database. If a new record is added, a code is generated and directly stored in the record table. If a record is matched, the latest record code is obtained and labeled and stored in the record table. S5. Display through the system platform and users can view it.

Images