Wide-area road facility reflectivity calculation method, system, equipment and medium

Abstract

The invention relates to a wide-area road facility reflectivity calculation method, system and device and a medium, and the method comprises the steps: obtaining a function relation between the reflection intensity and reflectivity of a laser radar, and carrying out the parameter correction and parameter calibration of the function relation; collecting and processing laser radar reflection intensity data of a target road section in real time; based on the processed laser radar reflection intensity data, calculating the reflectivity of road facilities in the target road section by using the function relationship after parameter calibration and parameter correction; the system, the equipment and the medium are used for realizing the method. Compared with the prior art, the efficiency and the precision of reflectivity calculation are improved.

Description

Technical Field

[0001] The present invention relates to the field of road engineering, and in particular to a method, system, equipment and medium for calculating the reflectivity of wide-area road facilities. Background Art

[0002] Global climate change is accelerating, the long-term global warming trend is accelerating, and extreme weather events are increasing. Roads are one of the transportation infrastructures with the largest surface area, and have a significant impact on climate change. Roads emit a large amount of greenhouse gases during the stages of raw material acquisition, transportation, construction, and maintenance. How to reduce carbon emissions throughout the life cycle of road construction and maintenance has become an urgent problem to be solved. The reflectivity of road facilities determines the road's ability to reflect solar radiation and directly affects the city's temperature and heat island effect. Road facilities with higher reflectivity can effectively reflect solar radiation, reduce surface temperature, and thus alleviate the heat island effect.

[0003] For the full life cycle management of roads (including construction, use, maintenance and aging stages), it is crucial to study the changes in their reflectivity. As the service life of the road increases, the pavement facilities and materials will age, the deposition of particulate matter will make the pavement darker, and the reflectivity of different materials will also be different, all of which will directly affect the temperature of the road surface. Under high temperature conditions, the increased rolling resistance of the tires leads to a decrease in fuel efficiency, thereby increasing the carbon emissions of the vehicle. High temperature environments will prompt passengers to use the cabin air conditioning system more intensively, thereby increasing fuel consumption and carbon emissions. Therefore, the reflectivity of the road surface will directly affect energy consumption, carbon emissions and the economic cost of road maintenance.

[0004] There are currently a variety of methods for measuring the reflectivity of objects with different accuracies and different usage environments, but most of them are single-point measurements with low efficiency. The workload is too large for reflectivity measurements at the road network level, and single-point measurement equipment is expensive and requires a lot of manpower, especially when applied on a large scale, the cost increases exponentially.

[0005] Therefore, there is an urgent need for a method that can quickly and accurately calculate the reflectivity of urban road networks. Summary of the invention

[0006] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide a method, system, equipment and medium for calculating the reflectivity of wide-area road facilities. A laser radar is used to quickly scan the urban road network to obtain the distribution of the road network reflectivity, and the constructed functional relationship between reflection intensity and distance is parameter corrected and calibrated. The reflectivity of road facilities is calculated using the functional relationship after parameter correction and calibration, thereby improving the efficiency and accuracy of reflectivity calculation.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] According to a first aspect of the present invention, a method for calculating the reflectivity of wide-area road facilities is provided, the method comprising:

[0009] Obtaining a functional relationship between the laser radar reflection intensity and the reflectivity, and performing parameter correction and parameter calibration on the functional relationship;

[0010] Collect and process the laser radar reflection intensity data of the target road section in real time, wherein the laser radar reflection intensity data type is point cloud data;

[0011] Based on the processed lidar reflection intensity data, the reflectivity of the road facilities in the target section is calculated using the functional relationship after parameter calibration and parameter correction.

[0012] As a preferred technical solution, the expression of the functional relationship is:

[0013] R(λ)=k·I0,

[0014] Among them, R(λ) represents reflectivity; k represents the empirical parameter, which is the parameter to be calibrated; I0 represents the standard value of reflection intensity, which is the parameter to be corrected; λ represents the wavelength of the laser radar.

[0015] As a preferred technical solution, the parameter correction method is:

[0016] Collecting and processing first laser radar reflection intensity data of a first sample road section, and calculating the distance from each data point in the processed first laser radar reflection intensity data to the laser radar; the first sample road section includes a plurality of sections with uniform road surfaces;

[0017] Construct the reflection intensity distance attenuation correction function, whose expression is:

[0018] I=a·d+I0,

[0019] Wherein, I represents the measured value of reflection intensity; a represents the attenuation coefficient, which is an unknown quantity; d represents the distance from the data point in the reflection intensity data of the first laser radar to the laser radar; I0 represents the standard value of reflection intensity, which is the value to be corrected;

[0020] Based on the first laser radar reflection intensity data, obtaining a measured reflection intensity value of each first sample road section;

[0021] Based on the measured value of the reflection intensity, calculating the attenuation coefficient of each first sample road section;

[0022] The attenuation coefficients of all sample road sections are averaged to obtain the corrected standard value of reflection intensity: I0=I+a0×d, where a0 represents the average value of the attenuation coefficient.

[0023] As a preferred technical solution, the method for calculating the distance from each data point in the processed first laser radar reflection intensity data to the laser radar is:

[0024] The intersection point of the first sample road segment and the laser radar trajectory is set as the origin;

[0025] The distance between each data point and the origin in the first laser radar reflection intensity data is calculated, and the expression is:

[0026]

[0027] Among them, d i represents the distance from the i-th data point to the origin, (x i ,y i ,z i ) represents the i-th data point in the first lidar reflection intensity data, and (x0, y0, z0) represents the origin.

[0028] As a preferred technical solution, the method for obtaining the attenuation coefficient of each first sample road section is: using the least square method to obtain the reflection intensity distance attenuation correction function of each first sample road section, and extracting the attenuation coefficient.

[0029] As a preferred technical solution, the parameter calibration method is:

[0030] Randomly collect measured reflectivity values ​​of multiple areas in the second sample road, and calculate the average of the measured reflectivity values;

[0031] Empirical parameter fitting is performed based on the mean of the measured reflectivity values ​​and the corrected parameters.

[0032] As a preferred technical solution, the processing includes:

[0033] Eliminate noise points, including abnormal reflection intensity values ​​and air noise points;

[0034] Extract point cloud data of road surface and roadside facilities, and filter non-target point cloud data.

[0035] According to a second aspect of the present invention, a wide-area road facility reflectivity calculation system is provided, and the system is used to implement the above method, comprising: a laser radar: used to emit a laser beam; a data acquisition and processing module: used to collect reflection intensity data and reflected measured values ​​of the laser radar, and process them; a parameter correction module: based on the data output by the data acquisition and processing module, correcting the reflection intensity standard value; a parameter calibration module: calibrating the empirical parameters according to the results of the parameter correction and the reflected measured values; a reflectivity calculation module: calculating the reflectivity of the target road section based on the laser radar reflection intensity data, the results of the parameter correction and the results of the parameter calibration.

[0036] According to a third aspect of the present invention, there is provided a device for calculating reflectivity of wide-area road facilities, comprising a memory and a processor, wherein a computer program is stored in the memory, and the method described is implemented when the processor executes the program.

[0037] According to a fourth aspect of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon, wherein the program implements the method described when executed by a processor.

[0038] Compared with the prior art, the present invention has the following advantages:

[0039] 1) The present invention provides a method for calculating the surface reflectivity of road facilities based on laser radar reflection intensity information. The vehicle-mounted laser radar or airborne laser radar can be used to quickly and batch scan urban roads, thereby obtaining reflection intensity distribution data at the road network level. Compared with the single-point calculation method used in traditional road facility reflectivity calculation, the method provided by the present invention effectively improves the calculation efficiency of the reflectivity; and the present invention performs parameter calibration and parameter correction on the constructed functional relationship between the laser radar reflection intensity and the reflectivity, thereby improving the accuracy of the reflectivity calculation, meeting the needs of large-scale applications, and realizing the calculation of the reflectivity of wide-area road facilities;

[0040] 2) The present invention calculates the reflectivity of road facilities based on laser radar. The laser radar can work stably under different lighting conditions. The collected data can be corrected to reduce the interference of weather and environment on the measurement results. In addition, dynamic detection of the reflectivity of road facilities can be achieved by combining with vehicle-mounted laser radar or airborne laser radar, providing data support for simulation and calculation of thermal effects of roads throughout their life cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 is a flow chart of the method of the present invention;

[0042] Figure 2 A schematic diagram showing the relationship between the laser radar reflection intensity and the distance of the present invention;

[0043] Figure 3 Schematic diagram of point cloud data of the present invention. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0045] Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the" and the like involved in this application do not indicate a quantitative limitation, and may represent the singular or plural. The terms "include", "comprise", "have" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there may be three relationships, for example, "A and / or B" can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects before and after are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0046] Example 1

[0047] This embodiment provides a method for calculating the reflectivity of wide-area road facilities, specifically, calculating the reflectivity of road facilities based on laser radar reflection intensity data. By using vehicle-mounted laser radar or airborne laser radar to quickly scan the urban road network and obtain the distribution of road network reflection intensity, it provides necessary data support for calculating the reflectivity changes, thermal effects and carbon emissions of road facilities at different cycle stages, and also provides necessary theoretical support for understanding the impact of road infrastructure on climate and environment and achieving sustainable development goals.

[0048] Specifically, the process of the method provided in this embodiment is as follows Figure 1 As shown, including:

[0049] S1. Obtain the functional relationship between the laser radar reflection intensity and reflectivity, and perform parameter correction and calibration on the functional relationship.

[0050] The functional relationship between the laser radar reflection intensity and reflectivity is expressed as:

[0051] R(λ)=k·I0,

[0052] R(λ) represents reflectivity; k represents an empirical parameter; I0 represents the standard value of reflection intensity; λ represents the wavelength of the laser radar, where k is the parameter to be calibrated and I0 is the parameter to be corrected.

[0053] S11. Parameter correction:

[0054] S111. Randomly select five newly built road sections with uniform road surface as the first sample sections, collect the first lidar reflection intensity data of the first sample sections and process them. The specific processing process is: eliminate noise points including abnormal reflection intensity values ​​(such as points with zero intensity) and aerial noise points; extract point cloud data of the road surface and roadside facilities, and filter non-target point cloud data such as vehicles, roadside buildings, etc.

[0055] S112, setting the intersection point of the first sample road section and the laser radar track as the origin, and calculating the distance between each data point in the first laser radar reflection intensity data and the origin, and the expression is:

[0056]

[0057] Among them, d i represents the distance from the i-th data point to the origin, (x i ,y i ,z i ) represents the i-th data point in the first lidar reflection intensity data, and (x0, y0, z0) represents the origin.

[0058] S113, constructing a reflection intensity distance attenuation correction function.

[0059] Because the reflection intensity of the laser will attenuate with increasing distance, the relationship between the laser reflection intensity and distance can be defined as: I0=f(I,d,a), where I represents the actual measured value of the reflection intensity; a represents the attenuation coefficient, d represents the distance from the data point in the first laser radar reflection intensity data to the laser radar, and I0 represents the standard value of the reflection intensity.

[0060] By analyzing the measured data, it is found that the reflection intensity decays linearly with increasing distance. Therefore, the reflection intensity and distance can be fitted as follows:

[0061] I=a·d+I0,

[0062] Among them, I represents the measured value of reflection intensity; a represents the attenuation coefficient, which is an unknown quantity; d represents the distance from the data point in the first laser radar reflection intensity data to the laser radar; I0 represents the standard value of reflection intensity, which is the value to be corrected.

[0063] S114. Based on the first laser radar reflection intensity data, obtain the measured value of the reflection intensity of each first sample road section.

[0064] S115, based on the measured value of the reflection intensity, the reflection intensity distance attenuation correction function of each first sample road section is fitted using the least square method, wherein the fitting result of one of the first sample road sections is as follows: Figure 2 As shown, the attenuation coefficient is extracted. Specifically, the fitting results of the five sample sections are:

[0065] Sample 1 fitting result: y = -2006.954x + 33012.368, determination coefficient R 2 =0.823,

[0066] Sample 2 fitting results: y = -2084.696x + 33310.051, determination coefficient R 2 =0.803,

[0067] Sample 3 fitting result: y = -2101.474x + 33110.755, determination coefficient R 2 =0.803,

[0068] Sample 4 fitting result: y = -2230.447x + 33624.779, determination coefficient R 2 =0.819,

[0069] Sample 5 fitting result: y = -2191.562x + 33651.963, determination coefficient R 2 =0.799.

[0070] S116. Taking the average of the attenuation coefficients of the five sample sections, we can get a=-2123.03, the standard value of reflection intensity I0=33341.983, and the corrected standard value of reflection intensity is: I0=I+2123.03×d, which realizes the standard value of reflection intensity obtained by adding distance correction to the measured reflection intensity.

[0071] S12, parameter calibration:

[0072] S121. Select a newly built asphalt road with uniform road surface as the second sample road, use a reflectivity tester to randomly collect reflectivity measured values ​​of multiple areas in the second sample road, and calculate the average of the reflectivity measured values.

[0073] S122. Calculate the mean value R(λ) of the measured reflectivity values * The corresponding reflection intensity standard value I*0, combined with the mean value R(λ) of the measured reflectivity value * Perform empirical parameter fitting, the expression is: We can get k = 6 × 10 -6 , and select different areas in the second sample road for verification. Then we can get, R(λ)=6×10 l6·(I+2123.03·d), parameter calibration is completed.

[0074] S2. Data collection and processing:

[0075] S21. Select a clear and windless day, use a near-infrared band vehicle-mounted single-line laser radar device to scan the target road in real time, and obtain laser radar reflection intensity data in the form of point cloud, such as Figure 3 As shown, the vehicle speed is kept uniform during collection, and repeated scanning is performed to ensure that the point cloud data is dense and uniform.

[0076] S22. Remove noise points including abnormal reflection intensity values ​​(such as points with zero intensity) and aerial noise points, extract point cloud data of the road surface and roadside facilities, and filter non-target point cloud data such as vehicles, roadside buildings, etc.

[0077] S3, based on the processed laser radar reflection intensity data, using R(λ) = 6×10 -6 ·(I+2123.03·d), calculate the reflectivity of road facilities in the target road section and generate a road reflectivity distribution map to provide a basis for road analysis and provide suggestions for road maintenance and material selection.

[0078] Example 2

[0079] The present embodiment provides a wide-area road facility reflectivity calculation system, which is used to implement the method of the above embodiment, including: LiDAR: In the present embodiment, a vehicle-mounted radar or an airborne radar can be selected to emit a laser beam to quickly and batch scan the urban road network. Data acquisition and processing module: used to collect the reflection intensity data and the measured reflection value of the laser radar, and process them. Parameter correction module: based on the data output by the data acquisition and processing module, the reflection intensity standard value is corrected. Parameter calibration module: according to the results of parameter correction and the measured reflection value, the empirical parameters are calibrated. Reflectivity calculation module: the reflectivity of the target road section is calculated based on the laser radar reflection intensity data, the results of parameter correction and the results of parameter calibration.

[0080] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described module can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0081] The present embodiment also provides a wide area road facility reflectivity calculation device, which includes a central processing unit (CPU), which can perform various appropriate actions and processes according to computer program instructions stored in a read-only memory (ROM) or loaded from a storage unit into a random access memory (RAM). In the RAM, various programs and data required for the operation of the device can also be stored. The CPU, ROM and RAM are connected to each other via a bus. An input / output (I / O) interface is also connected to the bus.

[0082] Multiple components in the device are connected to the I / O interface, including: input units, such as keyboards, mice, etc.; output units, such as various types of displays, speakers, etc.; storage units, such as disks, optical disks, etc.; and communication units, such as network cards, modems, wireless communication transceivers, etc. The communication unit allows the device to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunication networks.

[0083] The processing unit performs the various methods and processes described above, such as methods S1 to S3. For example, in some embodiments, methods S1 to S3 may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit. In some embodiments, part or all of the computer program may be loaded and / or installed on the device via a ROM and / or a communication unit. When the computer program is loaded into the RAM and executed by the CPU, one or more steps of methods S1 to S3 described above may be performed. Alternatively, in other embodiments, the CPU may be configured to execute methods S1 to S3 in any other appropriate manner (e.g., by means of firmware).

[0084] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0085] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0086] In the context of the present invention, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0087] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for calculating the reflectivity of wide-area road facilities, characterized in that: The method includes: Obtaining a functional relationship between the laser radar reflection intensity and the reflectivity, and performing parameter correction and parameter calibration on the functional relationship; Collect and process the laser radar reflection intensity data of the target road section in real time, wherein the laser radar reflection intensity data type is point cloud data; Based on the processed lidar reflection intensity data, the reflectivity of the road facilities in the target section is calculated using the functional relationship after parameter calibration and parameter correction.

2. A method for calculating the reflectivity of wide-area road facilities according to claim 1, characterized in that: The expression of the functional relationship is: R(λ)=k·I0, Among them, R(λ) represents reflectivity; k represents the empirical parameter, which is the parameter to be calibrated; I0 represents the standard value of reflection intensity, which is the parameter to be corrected; λ represents the wavelength of the laser radar.

3. A method for calculating the reflectivity of wide-area road facilities according to claim 2, characterized in that: The method for parameter correction is: Collecting and processing first laser radar reflection intensity data of a first sample road section, and calculating the distance from each data point in the processed first laser radar reflection intensity data to the laser radar; the first sample road section includes a plurality of sections with uniform road surfaces; Construct the reflection intensity distance attenuation correction function, whose expression is: I=a·d+I0, Wherein, I represents the measured value of reflection intensity; a represents the attenuation coefficient, which is an unknown quantity; d represents the distance from the data point in the reflection intensity data of the first laser radar to the laser radar; I0 represents the standard value of reflection intensity, which is the value to be corrected; Based on the first laser radar reflection intensity data, obtaining a measured reflection intensity value of each first sample road section; Based on the measured value of the reflection intensity, calculating the attenuation coefficient of each first sample road section; The attenuation coefficients of all sample road sections are averaged to obtain the corrected standard value of reflection intensity: I0=I+a0×d, where a0 represents the average value of the attenuation coefficient.

4. A method for calculating the reflectivity of wide-area road facilities according to claim 3, characterized in that: The method for calculating the distance from each data point in the processed first laser radar reflection intensity data to the laser radar is: The intersection point of the first sample road segment and the laser radar trajectory is set as the origin; The distance between each data point and the origin in the first laser radar reflection intensity data is calculated, and the expression is: Among them, d i represents the distance from the i-th data point to the origin, (x i ,y i ,z i ) represents the i-th data point in the first lidar reflection intensity data, and (x0, y0, z0) represents the origin.

5. A method for calculating the reflectivity of wide-area road facilities according to claim 3, characterized in that: The method for obtaining the attenuation coefficient of each first sample road section is: using the least square method to obtain the reflection intensity distance attenuation correction function of each first sample road section, and extracting the attenuation coefficient.

6. A method for calculating the reflectivity of wide-area road facilities according to claim 2, characterized in that: The method for parameter calibration is: Randomly collect measured reflectivity values ​​of multiple areas in the second sample road, and calculate the average of the measured reflectivity values; Empirical parameter fitting is performed based on the mean of the measured reflectivity values ​​and the corrected parameters.

7. A method for calculating the reflectivity of wide-area road facilities according to claim 1, characterized in that: The processing includes: Eliminate noise points, including abnormal reflection intensity values ​​and air noise points; Extract point cloud data of road surface and roadside facilities, and filter non-target point cloud data.

8. A wide-area road facility reflectivity calculation system, characterized in that: The system is used to implement the method according to any one of claims 1 to 7, comprising: LiDAR: used to emit laser beams to scan urban road networks; Data acquisition and processing module: used to collect and process the reflection intensity data and measured reflection value of the laser mine; Parameter correction module: based on the data output by the data acquisition and processing module, the standard value of reflection intensity is corrected; Parameter calibration module: calibrate the empirical parameters according to the parameter correction results and the reflection measured values; Reflectivity calculation module: Calculates the reflectivity of the target road section based on the lidar reflection intensity data, parameter correction results and parameter calibration results.

9. A device for calculating the reflectivity of wide-area road facilities, comprising a memory and a processor, wherein a computer program is stored in the memory, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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