Traffic road surface flatness detection system and detection method

Abstract

The invention discloses a traffic road surface flatness detection system and method, and the system comprises a vehicle which is used for forming on a traffic road surface; the laser 3D camera is used for collecting road end face contour data of a traffic road surface when the vehicle runs; and the processor is used for obtaining the flatness data of the traffic road surface according to the road end face contour data and the driving data and the state data of the vehicle. The traffic road surface flatness detection system and the detection method have the beneficial effects that the traffic road surface flatness detection system and the detection method which can carry out detection quickly and conveniently are provided.

Description

Technical Field

[0001] This application relates to the field of image detection technology, and more specifically, to a traffic road surface smoothness detection system and detection method. Background Technology

[0002] The development of China's expressways has shifted from a phase of large-scale construction to a phase of large-scale maintenance, and efficient and automated pavement measurement and inspection technologies have become an important requirement for the industry.

[0003] Road surface smoothness is one of the key indicators of road surface quality, affecting road safety, comfort, vehicle handling capacity, and the service life of the road surface. Currently, the mainstream methods include: the three-meter straightedge method, the continuous smoothness meter method, the vehicle-mounted bump integrator method, and detection methods based on visual image processing.

[0004] However, existing methods suffer from low detection efficiency or poor adaptability. Summary of the Invention

[0005] The summary section of this application is intended to provide a brief overview of the concepts, which will be described in detail in the detailed description section below. This summary section is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0006] Some embodiments of this application propose a traffic pavement smoothness detection system and method to solve the technical problems mentioned in the background section above.

[0007] As a first aspect of this application, some embodiments of this application provide a traffic pavement smoothness detection system, the traffic pavement smoothness detection system comprising: Vehicles, used for movement on traffic surfaces; A laser 3D camera is used to acquire road end face contour data of the traffic surface while the vehicle is in motion; The processor is used to obtain the smoothness data of the traffic surface based on the road end face contour data and the vehicle's driving data and status data.

[0008] Optionally, in some embodiments of this application, the traffic pavement smoothness detection system includes: Driving sensors are used to detect the driving data of the vehicle.

[0009] Optionally, in some embodiments of this application, the traffic pavement smoothness detection system includes: A status sensor is used to detect the status data of the vehicle.

[0010] Optionally, in some embodiments of this application, the vehicle's driving data includes: vehicle displacement data; The vehicle's status data includes: tire pressure data.

[0011] Optionally, in some embodiments of this application, the processor includes: The correction unit is used to correct the road end face contour data based on the road end face contour data. A fusion unit is used to fuse the corrected road end face contour data from multiple frames to obtain overall road contour data. The calculation unit is used to calculate the smoothness data of the traffic surface based on the overall road contour data.

[0012] As a second aspect of this application, some embodiments of this application provide a method for detecting the smoothness of a traffic surface, characterized in that: The traffic pavement smoothness detection method is implemented by the traffic pavement smoothness detection device; The traffic road surface smoothness detection system includes: Vehicles, used for movement on traffic surfaces; A laser 3D camera is used to acquire road end face contour data of the traffic surface while the vehicle is in motion; The processor is used to obtain the smoothness data of the traffic surface based on the road end face contour data and the vehicle's driving data and status data. The method for detecting the smoothness of traffic surfaces includes: The smoothness data of the traffic surface is obtained based on the road end face contour data, the vehicle's driving data, and the vehicle's status data.

[0013] Optionally, in some embodiments of this application, the traffic pavement smoothness detection system includes: Driving sensors are used to detect the driving data of the vehicle.

[0014] Optionally, in some embodiments of this application, the traffic pavement smoothness detection system includes: A status sensor is used to detect the status data of the vehicle.

[0015] Optionally, in some embodiments of this application, the vehicle's driving data includes: vehicle displacement data; The vehicle's status data includes: tire pressure data.

[0016] Optionally, in some embodiments of this application, the processor includes: The correction unit is used to correct the road end face contour data based on the road end face contour data. A fusion unit is used to fuse the corrected road end face contour data from multiple frames to obtain overall road contour data. A calculation unit is used to calculate the smoothness data of the traffic surface based on the overall road contour data; The method for detecting the smoothness of traffic surfaces includes: Collect the road end face contour data, the driving data, and the status data; The road end face contour data is corrected based on the road end face contour data; The road end face contour data after multi-frame correction is fused to obtain the overall road contour data; The smoothness data of the traffic surface is calculated based on the overall road contour data.

[0017] As a third aspect of this application, some embodiments of this application provide an electronic device, including: one or more processors; and a storage device having one or more programs stored thereon, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation of the first aspect above.

[0018] As a fourth aspect of this application, some embodiments of this application provide a computer-readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method described in any implementation of the first aspect above.

[0019] The beneficial effects of this application are: it provides a traffic road surface smoothness detection system and detection method that can perform detection at high speed and quickly. Attached Figure Description

[0020] The accompanying drawings, which form part of this application, are used to provide a further understanding of the application and to make other features, objects, and advantages of the application more apparent. The illustrative embodiments and descriptions of this application are used to explain the application and do not constitute an undue limitation of the application.

[0021] Furthermore, throughout the accompanying drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the elements are not necessarily drawn to scale.

[0022] In the attached diagram: Figure 1 This is a schematic diagram of the architecture of a traffic pavement smoothness detection system according to an embodiment of this application; Figure 2 This is a schematic diagram of a traffic pavement smoothness detection system according to an embodiment of this application; Figure 3This is a schematic diagram illustrating the detection principle of a laser 3D camera in a traffic pavement smoothness detection system according to an embodiment of this application. Figure 4 This is a schematic diagram illustrating the principle of a traffic pavement smoothness detection method according to an embodiment of this application; Figure 5 This is a schematic diagram of the main steps of a traffic pavement smoothness detection method according to an embodiment of this application; Figure 6 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0023] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0024] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0025] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0026] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0027] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0028] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0029] Reference Figures 1 to 4 As shown, as a first aspect, some embodiments of this application provide a traffic pavement smoothness detection system, the traffic pavement smoothness detection system comprising: a vehicle, a laser 3D camera, and a processor.

[0030] The vehicle is used to move on the traffic surface; the laser 3D camera is used to collect road end face contour data of the traffic surface while the vehicle is moving; the processor is used to obtain the smoothness data of the traffic surface based on the road end face contour data and the vehicle's driving data and status data.

[0031] Reference Figure 3 As shown, as a specific solution, a line laser 3D camera can be selected, whose width along the X-axis should be sufficient to cover the detection area. The curvature of the laser line in the image from the line laser 3D camera can provide feedback on flatness, and therefore can be used to detect flatness.

[0032] Reference Figure 2 As shown, the laser 3D camera can be mounted at the rear of the vehicle, thus avoiding obstruction of the driver's view. Alternatively, laser 3D cameras can be installed at both the front and rear of the vehicle, depending on the needs. The laser 3D camera can be rigidly connected to the vehicle, requiring adjustments based on the vehicle's attitude. As an optional solution, a balancer can be used to maintain the laser 3D camera's height and attitude relative to the road surface as much as possible. The balancer can use gyroscopes or similar devices to dynamically adjust the laser 3D camera's height and attitude relative to the road surface.

[0033] In some embodiments of this application, the traffic surface smoothness detection system includes: a driving sensor and a status sensor. The driving sensor is used to detect the driving data of the vehicle. The status sensor is used to detect the status data of the vehicle.

[0034] In some embodiments of this application, the vehicle's driving data includes: vehicle displacement data; the vehicle's status data includes: vehicle tire pressure data.

[0035] Reference Figure 1 As shown, in some embodiments of this application, the processor includes: a correction unit, a fusion unit, and a computing unit.

[0036] The correction unit is used to correct the road end face contour data based on the road end face contour data; the fusion unit is used to fuse the corrected road end face contour data from multiple frames to obtain the overall road contour data; and the calculation unit is used to calculate the smoothness data of the traffic surface based on the overall road contour data.

[0037] Reference Figure 4 and Figure 5 As shown, as a second aspect, some embodiments of this application provide a method for detecting the smoothness of a traffic road surface. This method for detecting the smoothness of a traffic road surface is implemented by the aforementioned traffic road surface smoothness detection system.

[0038] As a key step, the method for detecting the smoothness of traffic surfaces includes: The smoothness data of the traffic surface is obtained based on the road end face contour data, the vehicle's driving data, and the vehicle's status data.

[0039] As specific steps, the method for detecting the smoothness of traffic surfaces includes: Collect the road end face contour data, the driving data, and the status data; The road end face contour data is corrected based on the road end face contour data; The road end face contour data after multi-frame correction is fused to obtain the overall road contour data; The smoothness data of the traffic surface is calculated based on the overall road contour data.

[0040] As can be seen from the above, this application obtains the flatness of the road surface by fusing road end face contour data.

[0041] As a specific plan, refer to Figure 4 and Figure 5 As shown, the camera's coordinate system changes with the vehicle's position and attitude. Therefore, the data measured by the line laser needs to be unified in the same coordinate system, with the initial coordinate system of the motion as the reference coordinate system.

[0042] When the camera coordinate system changes from O-XYZ to O'-X'Y'Z', it can be decomposed into a translation vector in the XY plane and an attitude change in the XY plane. The calculation process for the displacement and attitude changes is as follows: The tire's rotation angle is calculated using information from the rotary encoder on the tire. The actual radius of the tire axle and the ground is calculated based on the tire pressure information. 1) and 2) can be used to calculate the displacement of each tire. The displacement of the car in the XY plane can be calculated based on the displacement of the four tires. Based on the displacement information of the shock absorbers connecting the tires and the car, the displacement of the compensation camera and the ground in the height direction can be calculated.

[0043] The displacement and attitude changes of the camera as the car moves can be calculated from steps 4) and 5). The road smoothness detection process is as follows: Figure 5 As shown.

[0044] like Figure 6As shown, the electronic device 800 may include a processing unit (e.g., a central processing unit, a graphics processor, etc.) 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage device 808 into a random access memory (RAM) 803. The RAM 803 also stores various programs and data required for the operation of the electronic device 800. The processing unit 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0045] Typically, the following devices can be connected to I / O interface 805: input devices 806 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 807 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 808 including, for example, magnetic tapes, hard disks, etc.; and communication devices 809. Communication device 809 allows electronic device 800 to communicate wirelessly or wiredly with other devices to exchange data. Although... Figure 6 An electronic device 800 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 6 Each box shown can represent a device or multiple devices as needed.

[0046] In particular, according to some embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 809, or installed from a storage device 808, or installed from a ROM 802. When the computer program is executed by the processing device 801, it performs the functions defined in the methods of some embodiments of this disclosure.

[0047] It should be noted that, in some embodiments of this disclosure, the computer-readable medium described above may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0048] In some embodiments of this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In some embodiments of this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0049] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol, such as HTTP (Hypertext Transfer Protocol), and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0050] Computer program code for performing operations of some embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0051] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function.

[0052] It should also be noted that in some alternative implementations, the functions marked in the box may occur in a different order than those marked in the attached figures.

[0053] For example, two consecutively represented blocks can actually be executed in substantially parallel order, and sometimes they can be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, as well as combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified functions or operations, or using a combination of dedicated hardware and computer instructions.

[0054] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0055] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A traffic road surface smoothness detection system, characterized in that: The traffic road surface smoothness detection system includes: Vehicles, used for movement on traffic surfaces; A laser 3D camera is used to acquire road end face contour data of the traffic surface while the vehicle is in motion; The processor is used to obtain the smoothness data of the traffic surface based on the road end face contour data and the vehicle's driving data and status data.

2. The traffic pavement smoothness detection system according to claim 1, characterized in that: The traffic road surface smoothness detection system includes: Driving sensors are used to detect the driving data of the vehicle.

3. The traffic road surface smoothness detection system according to claim 1, characterized in that: The traffic road surface smoothness detection system includes: A status sensor is used to detect the status data of the vehicle.

4. The traffic pavement smoothness detection system according to any one of claims 1 to 3, characterized in that: The vehicle's driving data includes: vehicle displacement data; The vehicle's status data includes: tire pressure data.

5. The traffic pavement smoothness detection system according to claim 4, characterized in that: The processor includes: The correction unit is used to correct the road end face contour data based on the road end face contour data; A fusion unit is used to fuse the corrected road end face contour data from multiple frames to obtain overall road contour data. The calculation unit is used to calculate the smoothness data of the traffic surface based on the overall road contour data.

6. A method for detecting the smoothness of a traffic surface, characterized in that: The traffic pavement smoothness detection method is implemented by the traffic pavement smoothness detection device; The traffic road surface smoothness detection system includes: Vehicles, used for movement on traffic surfaces; A laser 3D camera is used to acquire road end face contour data of the traffic surface while the vehicle is in motion; The processor is used to obtain the smoothness data of the traffic surface based on the road end face contour data and the vehicle's driving data and status data. The method for detecting the smoothness of traffic surfaces includes: The smoothness data of the traffic surface is obtained based on the road end face contour data, the vehicle's driving data, and the vehicle's status data.

7. The method for detecting the smoothness of traffic surfaces according to claim 6, characterized in that: The traffic road surface smoothness detection system includes: Driving sensors are used to detect the driving data of the vehicle.

8. The method for detecting the smoothness of traffic surfaces according to claim 7, characterized in that: The traffic road surface smoothness detection system includes: A status sensor is used to detect the status data of the vehicle.

9. The method for detecting the smoothness of traffic surfaces according to any one of claims 6 to 8, characterized in that: The vehicle's driving data includes: vehicle displacement data; The vehicle's status data includes: tire pressure data.

10. The method for detecting the smoothness of a traffic surface according to claim 9, characterized in that: The processor includes: The correction unit is used to correct the road end face contour data based on the road end face contour data; A fusion unit is used to fuse the corrected road end face contour data from multiple frames to obtain overall road contour data. A calculation unit is used to calculate the smoothness data of the traffic surface based on the overall road contour data; The method for detecting the smoothness of traffic surfaces includes: Collect the road end face contour data, the driving data, and the status data; The road end face contour data is corrected based on the road end face contour data; The road end face contour data after multi-frame correction is fused to obtain the overall road contour data; The smoothness data of the traffic surface is calculated based on the overall road contour data.

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