A three-dimensional road surface modeling method

Abstract

The application provides a three-dimensional pavement modeling method, and relates to the field of three-dimensional pavement modeling, and comprises the following steps: obtaining the difference from the average elevation of the starting cross section to the average elevation of the ending cross section in the original three-dimensional pavement data, determining the cross section with the difference greater than a preset threshold as a jump surface, processing the original three-dimensional pavement data, and obtaining all divided road sections; constructing first time series data according to the average elevation of all cross sections of each divided road section, converting the first time series data into first frequency data, and obtaining the pitch and vibration elevations; constructing second time series data according to the slope of all cross sections of each divided road section, converting the second time series data into second frequency data, and obtaining the roll angle of the corresponding measurement posture of each cross section; and correcting the original three-dimensional pavement data according to the pitch and vibration elevations and the roll angle, so as to complete three-dimensional pavement modeling. The application overcomes the measurement precision defects caused by the measurement posture, improves the measurement precision, and reduces the measurement cost.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of three-dimensional pavement modeling, and in particular to a three-dimensional pavement modeling method. BACKGROUND

[0002] With the rapid development of three-dimensional measurement technology, the pavement three-dimensional measurement technology and equipment have been able to realize the promotion of pavement detection data information from two-dimensional pavement information to three-dimensional pavement information, and how to accurately obtain pavement technical condition information from the original three-dimensional pavement data has become a core technical difficulty.

[0003] The accuracy of pavement technical condition acquisition depends largely on the accuracy of three-dimensional pavement modeling, however, the pavement three-dimensional data is collected in a high dynamic measurement scene, and the measurement data contains obvious measurement attitude information, so that the measurement result is not accurate enough, and the equipment that meets the requirements of the use scene is expensive, and the equipment with a moderate price cannot meet the requirements of the use scene at the same time. SUMMARY

[0004] The present application provides a three-dimensional pavement modeling method to solve the technical defects of low three-dimensional pavement modeling accuracy or high cost, and proposes a technical scheme for determining the pitch and vibration elevation of the cross section corresponding to the measurement attitude, the roll angle of the cross section corresponding to the measurement attitude, and performing measurement attitude compensation after adaptive segmentation of three-dimensional pavement data.

[0005] The present application provides a three-dimensional pavement modeling method, comprising:

[0006] Obtaining the difference between the starting cross section average elevation and the ending cross section average elevation corresponding to any cross section in the original pavement three-dimensional data, determining the cross section with a difference greater than a preset threshold as a jump surface, processing the original pavement three-dimensional data according to all jump surfaces, and obtaining all divided road sections;

[0007] Constructing a first time series data according to the average elevation of all cross sections of each divided road section, converting the first time series data into a first frequency data, and obtaining the pitch and vibration elevation of the measurement attitude corresponding to each cross section according to the first frequency data;

[0008] Constructing a second time series data according to the slope of all cross sections of each divided road section, converting the second time series data into a second frequency data, and obtaining the roll angle of the measurement attitude corresponding to each cross section according to the second frequency data;

[0009] Correcting the original pavement three-dimensional data according to the pitch and vibration elevation of the measurement attitude corresponding to the cross section and the roll angle of the measurement attitude corresponding to the cross section, to complete the three-dimensional pavement modeling;

[0010] The start cross section is a corresponding cross section taken forward by a first preset length along a data collection sequence with the cross section as a center surface, and the end cross section is a corresponding cross section taken backward by the first preset length along the data collection sequence with the cross section as the center surface.

[0011] The three-dimensional pavement modeling method provided by the application processes the original pavement three-dimensional data according to all jump surfaces, and obtains all divided road sections, including:

[0012] After traversing all cross sections, all continuous jump surfaces are obtained, and a section formed by any continuous jump surface and having a section length greater than a second preset length is determined as a jump region;

[0013] After traversing all continuous jump surfaces, all jump regions are obtained, and a section surface is determined according to each jump region;

[0014] The original pavement three-dimensional data is divided according to the section surface, so as to obtain all divided road sections.

[0015] The three-dimensional pavement modeling method provided by the application determines a section surface according to each jump region, including:

[0016] A clustering algorithm is used, and position information of each cross section and an average elevation of each cross section in any jump region are combined to divide the jump region into a first height region and a second height region;

[0017] The section surface corresponding to the jump region is determined according to the first height region and the second height region;

[0018] All jump regions are traversed until the section surface corresponding to each jump region is obtained;

[0019] The first height region is greater than or less than the second height region.

[0020] The three-dimensional pavement modeling method provided by the application constructs first time sequence data according to average elevations of all cross sections of each divided road section, converts the first time sequence data into first frequency data, and obtains a pitch and a vibration elevation of a corresponding measurement posture of each cross section according to the first frequency data, including:

[0021] In each divided road section, average elevations of all cross sections are calculated, a cross section elevation mean set corresponding to each divided road section is obtained, and first time sequence data is constructed according to the cross section elevation mean set;

[0022] After the first time sequence data is processed by a Fourier transform, first frequency data is obtained, and amplitude and phase information of each frequency spectrum component is determined according to the first frequency data;

[0023] After the vibration and pitch frequency range of the measurement posture is obtained according to the amplitude and phase information of each frequency spectrum component, the pitch and vibration periodic signals of the measurement sensor are reconstructed according to the inverse Fourier transform and the vibration and pitch frequency range of the measurement posture, so as to obtain the pitch and vibration elevation of the measurement posture corresponding to each cross section.

[0024] The three-dimensional road surface modeling method provided by the application further comprises the following steps after the first frequency data is obtained:

[0025] The first frequency data is processed by using a simulation analysis method, so as to obtain the vibration and pitch frequency range of the measurement posture.

[0026] Or, the first frequency data is processed by using a historical data statistical analysis method, so as to obtain the vibration and pitch frequency range of the measurement posture.

[0027] Or, the vibration and pitch frequency range is extracted from a preset vibration and pitch frequency range set.

[0028] The three-dimensional road surface modeling method provided by the application further comprises the following steps after the second frequency data is obtained:

[0029] Each cross section is processed by using a linear fitting algorithm, so as to obtain the cross section slope corresponding to each cross section.

[0030] The roll angle of each cross section is determined according to the cross section slope of each cross section, and the second time sequence data is constructed according to the roll angles of all cross sections.

[0031] The second frequency data is obtained by processing the second time sequence data by using a Fourier transform, so as to determine the amplitude and phase information of each frequency spectrum component.

[0032] After the roll frequency range of the measurement posture of the measurement sensor is obtained according to the amplitude and phase information of each frequency spectrum component, the roll periodic signal of the measurement sensor is reconstructed according to the inverse Fourier transform and the roll frequency range of the measurement posture of the measurement sensor, so as to obtain the roll angle of the measurement posture corresponding to each cross section.

[0033] The three-dimensional road surface modeling method provided by the application further comprises the following steps after the second frequency data is obtained:

[0034] The second frequency data is processed by using a simulation analysis method, so as to obtain the roll frequency range of the measurement posture of the measurement sensor.

[0035] Or, the second frequency data is processed according to a historical data statistical analysis method to obtain a roll frequency range of a measurement sensor measuring a posture;

[0036] Or, the roll frequency range is extracted from a preset roll frequency range set.

[0037] According to the three-dimensional pavement modeling method provided by the application, the original pavement three-dimensional data is corrected according to the pitch and vibration elevation of the corresponding measurement posture of the cross section and the roll angle of the corresponding measurement posture of the cross section, so as to complete three-dimensional pavement modeling, comprising:

[0038] For any cross section data, the distance value of all measurement points in the cross section data to the cross section midpoint measurement point in the road width direction is obtained through a calibration file;

[0039] For any cross section data, the roll angle component of all measurement points in the cross section is determined according to the distance value and the roll angle of the corresponding measurement posture of the cross section;

[0040] For any cross section data, the measurement point elevation corresponding to each measurement point in the cross section data, the pitch and vibration elevation of the corresponding measurement posture of the cross section, the working distance obtained in the static calibration state of the sensor head, and the roll angle component of each measurement point in the cross section are determined to determine the corrected measurement point elevation corresponding to each measurement point;

[0041] All cross section data of the original pavement three-dimensional data are traversed until the original pavement three-dimensional data is corrected.

[0042] According to the three-dimensional pavement modeling method provided by the application, before obtaining the difference between the starting cross section average elevation and the ending cross section average elevation corresponding to any cross section in the original pavement three-dimensional data, the method further comprises:

[0043] The original pavement three-dimensional data is obtained by using a line scanning three-dimensional measurement method;

[0044] The average elevation of each cross section is extracted from the original pavement three-dimensional data;

[0045] The average elevation of each cross section is determined according to the measurement point elevation of all measurement points in the road width of each cross section.

[0046] According to the three-dimensional pavement modeling method provided by the application, the original pavement three-dimensional data is obtained by using a line scanning three-dimensional measurement method, comprising:

[0047] The pavement profile data of a plurality of measurement points in the road width direction is obtained under the same measurement posture by using the line scanning three-dimensional measurement method;

[0048] Each cross section data is composed according to the pavement profile data of a plurality of measurement points;

[0049] The original road surface three-dimensional data is determined according to all cross-section data.

[0050] The application provides a three-dimensional road surface modeling method, which utilizes the jumping of original road surface three-dimensional data in the driving direction, takes the jumping point as a segmentation point, and performs adaptive segmentation on the road surface three-dimensional data, extracts the low-frequency signal of the original road surface three-dimensional data in each interval after adaptive segmentation by using a signal separation method, obtains the pitch and vibration elevation of each cross-section corresponding to the measurement posture and the roll angle of each cross-section corresponding to the measurement posture, so as to complete the three-dimensional road surface modeling, and the application can meet the detection demand under large-scale road conditions, solve the core problem of road surface technical condition detection, overcome the measurement precision defect caused by the measurement posture, thereby improving the measurement precision and reducing the measurement cost. BRIEF DESCRIPTION OF DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the application or prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0052] Figure 1 Fig. 1 is a flowchart of the three-dimensional road surface modeling method provided by the application;

[0053] Figure 2 Fig. 2 is a flowchart of obtaining all divided road sections provided by the application;

[0054] Figure 3 Fig. 3 is a flowchart of determining the segmentation surface according to each jumping area provided by the application;

[0055] Figure 4 Fig. 4 is a flowchart of obtaining the pitch and vibration elevation of each cross-section corresponding to the measurement posture provided by the application;

[0056] Figure 5 Fig. 5 is a flowchart of obtaining the roll angle of each cross-section corresponding to the measurement posture provided by the application;

[0057] Figure 6 Fig. 6 is a flowchart of correcting the original road surface three-dimensional data provided by the application;

[0058] Figure 7 Fig. 7 is one of the flowcharts of obtaining the original road surface three-dimensional data provided by the application;

[0059] Figure 8 Fig. 8 is another of the flowcharts of obtaining the original road surface three-dimensional data provided by the application. DETAILED DESCRIPTION

[0060] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely below with reference to the drawings in the present application. Obviously, the described embodiments are only some 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 those of ordinary skill in the art without creative effort belong to the protection scope of the present application.

[0061] Highways are the guarantee of transportation. However, with the increase of service life of transportation facilities and the increase of transportation pressure, various diseases are generated, which greatly reduces the service life and use performance of transportation facilities, and the amount of maintenance engineering to be implemented increases greatly. Scientific maintenance decision and fund allocation depend on timely and accurate acquisition of technical condition data of transportation facilities. With the rapid development of three-dimensional measurement technology, the measurement technology and equipment based on three-dimensional pavement improve the pavement detection data information from two-dimensional pavement information to three-dimensional pavement information. How to accurately obtain the pavement technical condition information from the original three-dimensional pavement data has become a core technical difficulty.

[0062] The accuracy of pavement technical condition acquisition depends largely on the accuracy of three-dimensional pavement modeling. Since the three-dimensional pavement data is collected in a high dynamic measurement scene, the measurement data contains obvious measurement posture information. The existing inertial measurement equipment is relatively complex in acquiring the measurement posture of the measurement sensor, and the acquisition of the measurement frequency and the measurement accuracy cannot meet the requirements of the use scene at the same time. Therefore, the present application aims to design a low-cost and high-precision three-dimensional pavement modeling method to solve the technical problems of high measurement cost and low accuracy of the measurement posture in the prior art.

[0063] Figure 1 It is a flowchart of the three-dimensional pavement modeling method provided by the present application. The present application provides a three-dimensional pavement modeling method, comprising:

[0064] The difference between the starting cross section average elevation and the ending cross section average elevation corresponding to any cross section in the original three-dimensional pavement data is obtained, and the cross section with a difference greater than a preset threshold is determined as a jump surface. The original three-dimensional pavement data is processed according to all jump surfaces, and all divided road sections are obtained.

[0065] The first time series data is constructed according to the average elevation of all cross sections of each divided road section, and the first frequency data is converted from the first time series data. The pitch and vibration elevation of the measurement posture corresponding to each cross section are obtained according to the first frequency data.

[0066] constructing second time-series data according to the slope of each cross section of the divided road section, converting the second time-series data into second frequency data, and obtaining the roll angle of the corresponding measurement attitude of each cross section according to the second frequency data;

[0067] correcting the original road surface three-dimensional data according to the pitch and vibration elevation of the corresponding measurement attitude of the cross section and the roll angle of the corresponding measurement attitude of the cross section, so as to complete three-dimensional road surface modeling;

[0068] The starting cross section is a corresponding cross section obtained by taking the cross section as a center surface and moving forward by a first preset length along the data acquisition sequence, and the ending cross section is a corresponding cross section obtained by taking the cross section as a center surface and moving backward by a first preset length along the data acquisition sequence.

[0069] In step 101, the original road surface three-dimensional data is composed of all cross sections, and for each cross section, the steps of step 101 are performed, that is, the difference between the average elevations of the starting cross section and the ending cross section corresponding to each cross section is determined, the starting cross section is a corresponding cross section obtained by taking the cross section as a center surface and moving forward by a first preset length along the data acquisition sequence, and the ending cross section is a corresponding cross section obtained by taking the cross section as a center surface and moving backward by a first preset length along the data acquisition sequence, the first preset length represents a fixed length, that is, for any cross section, there is a starting cross section and an ending cross section in the driving direction, after determining the starting cross section and the ending cross section corresponding to each cross section, the difference between the average elevations of the starting cross section and the ending cross section is calculated.

[0070] The difference between the average elevations of the starting cross section and the ending cross section can reflect whether there is a larger fluctuation near the current cross section, that is, the cross section with a difference greater than a preset threshold is determined as a cross section with a larger fluctuation, that is, a jump surface, and for all cross sections, the above step 101 is performed, so as to determine all jump surfaces, after determining all jump surfaces, the jump surface is used as a segmentation point to adaptively segment the road surface three-dimensional data according to the jump of the original road surface three-dimensional data in the driving direction, and all divided road sections are obtained.

[0071] In step 102, the first time series data is constructed according to the average elevation of each cross section of the divided road section, the first time series data is converted into first frequency data, and the pitch and vibration elevation of the measurement posture corresponding to each cross section is obtained according to the first frequency data.

[0072] In step 103, the second time series data is constructed according to the slope of each cross section of the divided road section, the second time series data is converted into second frequency data, and the roll angle of the measurement posture corresponding to each cross section is obtained according to the second frequency data.

[0073] In step 104, the original road surface three-dimensional data is corrected according to the pitch and vibration elevation of the measurement posture corresponding to each cross section and the roll angle of the measurement posture corresponding to each cross section, and three-dimensional road surface modeling is completed.

[0074] The present application provides a three-dimensional road surface modeling method, which uses the jump of the original road surface three-dimensional data in the driving direction, uses the jump point as the segmentation point, adaptively segments the road surface three-dimensional data, extracts the low-frequency signal of the original road surface three-dimensional data in each interval after adaptive segmentation by using the signal separation method, obtains the pitch and vibration elevation of the measurement posture corresponding to each cross section and the roll angle of the measurement posture corresponding to each cross section, and completes three-dimensional road surface modeling.

[0075] Figure 2is a flowchart of obtaining all divided road sections provided by the present application, the original road surface three-dimensional data is processed according to all jump surfaces, and all divided road sections are obtained, including:

[0076] After traversing all cross sections, all continuous jump surfaces are obtained, and a section formed by any continuous jump surface and having a section length greater than a second preset length is determined as a jump region;

[0077] After traversing all continuous jump surfaces, all jump regions are obtained, and a section surface is determined according to each jump region;

[0078] The original road surface three-dimensional data is divided according to the section surface, so as to obtain all divided road sections.

[0079] In step 1011, after traversing all cross sections, all continuous jump surfaces are obtained, and a section formed by any continuous jump surface and having a section length greater than a second preset length is determined as a jump region. In the driving direction, each cross section is calculated in sequence, and it is determined whether each cross section is a jump surface. The continuous jump surface is a plurality of jump surfaces having a neighboring relationship, for example, two adjacent jump surfaces, three adjacent jump surfaces, or four adjacent jump surfaces, and so on. Not all cross sections are jump surfaces, but only the surface formed by the plurality of jump surfaces having a continuous jump relationship is a continuous jump surface. Thus, all continuous jump surfaces in the original three-dimensional road surface can be obtained, the section length formed by each continuous jump surface is determined, and it is determined whether the section length formed by each continuous jump surface is greater than the second preset length. The second preset length is a preset fixed length. Only when the section length formed by the continuous jump surface is greater than a certain length, the continuous jump surface can be determined as a jump region.

[0080] Those skilled in the art understand that the jump surface in the present application can be understood as a two-dimensional region represented by the cross section, and the continuous jump surface is a three-dimensional region formed by stretching the two-dimensional region in the driving direction.

[0081] In step 1012, after traversing all continuous jump surfaces, all jump regions are obtained, and a section surface is determined according to each jump region. All continuous jump surfaces having no neighboring relationship in the original three-dimensional road surface are traversed, all jump regions are determined according to whether the second preset length judgment condition is met, and then each jump region is analyzed by using a classification algorithm to divide the road surface into a higher region and a lower region, and the division surface is a section surface.

[0082] In step 1013, for each jump region, a section surface can be determined, all section surfaces are extracted, and the original road surface three-dimensional data is divided according to all section surfaces as a division basis, so as to obtain all divided road sections.

[0083] Figure 3 is a flowchart provided by the present application for determining a segment surface according to each jump region, and the determination of the segment surface according to each jump region comprises:

[0084] The clustering algorithm is adopted, and the position information of each cross section in any jump region and the average elevation of each cross section are combined to divide the jump region into a first height region and a second height region.

[0085] The segment surface corresponding to the jump region is determined according to the first height region and the second height region.

[0086] All jump regions are traversed until the segment surface corresponding to each jump region is obtained.

[0087] The first height region is greater than or less than the second height region.

[0088] In step 10121, in an optional embodiment, the present application adopts a fuzzy clustering algorithm, and the position information of each cross section in any jump region and the average elevation of each cross section are combined. In such an embodiment, the position information of each cross section is used to determine the position coordinates of each cross section, and then the average elevation corresponding to the position coordinates of each cross section is determined, and the average elevation of each cross section is used as a division basis. According to the fuzzy clustering algorithm, the position information of each cross section can be clustered, and then the jump region is divided into a first height region and a second height region.

[0089] In step 10122, the segment surface corresponding to the jump region is determined according to the first height region and the second height region, and the segment surface corresponding to the jump region is the cross section adjacent to the first height region and the second height region. In an optional embodiment, the first height region is greater than the second height region, and in another optional embodiment, the first height region is less than the second height region.

[0090] In step 10123, all jump regions are traversed until the segment surface corresponding to each jump region is obtained. For each jump region, the method in steps 10121 to 10122 is used to determine the segment surface of each jump region.

[0091] Figure 4 is a flowchart provided by the present application for obtaining the pitch and vibration elevation of the measurement attitude corresponding to each cross section, and the first time sequence data is constructed according to the average elevation of all cross sections of each divided section, the first time sequence data is converted into first frequency data, and the pitch and vibration elevation of the measurement attitude corresponding to each cross section is obtained according to the first frequency data, comprising:

[0092] In each divided road section, the average elevation of all cross sections is calculated to obtain a cross section elevation mean set corresponding to each divided road section, so as to construct first time series data according to the cross section elevation mean set;

[0093] After the first time series data is processed by Fourier transform, first frequency data is obtained to determine the amplitude and phase information of each frequency component according to the first frequency data;

[0094] After the vibration and pitch frequency range of the measurement posture is obtained according to the amplitude and phase information of each frequency component, the pitch and vibration periodic signals of the measurement sensor are reconstructed according to the inverse Fourier transform and the vibration and pitch frequency range of the measurement posture, so as to obtain the pitch and vibration elevations of the measurement posture corresponding to each cross section.

[0095] In step 1021, in each divided road section, the average elevation of all cross sections is calculated to obtain a cross section elevation mean set corresponding to each divided road section, so as to construct first time series data, wherein the calculation of the average elevation of all cross sections is to calculate the height mean of all test points on each cross section, and then to construct a set of cross section elevation means in all cross sections in the divided road section, and to construct first time series data according to the cross section elevation mean set.

[0096] In step 1022, after the first time series data is processed by Fourier transform, first frequency data is obtained to determine the amplitude and phase information of each frequency component according to the first frequency data, and the first time series data is converted into first frequency data, and then the amplitude and phase information of each frequency component can be determined according to the first frequency data.

[0097] In step 1023, after the vibration and pitch frequency range of the measurement posture is obtained according to the amplitude and phase information of each frequency component, the pitch and vibration periodic signals of the measurement sensor are reconstructed according to the inverse Fourier transform and the vibration and pitch frequency range of the measurement posture, so as to obtain the pitch and vibration elevations of the measurement posture corresponding to each cross section, and the pitch and vibration periodic signals of the measurement sensor are reconstructed by using the inverse Fourier transform method and combining the frequency range of the pitch and vibration periodic signals of the measurement sensor, so as to obtain the pitch and vibration elevations of the measurement posture at any time.

[0098] Optionally, after the first frequency data is obtained, the method further comprises:

[0099] The first frequency data is processed according to a simulation analysis method to obtain the vibration and pitch frequency range of the measurement posture;

[0100] Or, the first frequency data is processed according to a historical data statistical analysis method to obtain a vibration and pitch frequency range of a measurement posture.

[0101] Or, the vibration and pitch frequency range is extracted from a preset vibration and pitch frequency range set.

[0102] The present application can determine the amplitude and phase information of each frequency spectrum component according to the first frequency data, obtain the vibration and pitch frequency range of the road surface according to the simulation analysis method, and set the pitch and vibration period signal frequency interception range of the measurement sensor, and in other embodiments, the present application can also obtain the vibration and pitch frequency range of the measurement posture through the historical data statistical analysis method, or extract the vibration and pitch frequency range from the preset vibration and pitch frequency range set.

[0103] Figure 5 The present application provides a flowchart for obtaining the roll angle of each cross section corresponding to the measurement posture, the second time sequence data is constructed according to the slope of all cross sections of each divided road section, the second time sequence data is converted into second frequency data, and the roll angle of each cross section corresponding to the measurement posture is obtained according to the second frequency data, comprising:

[0104] Each cross section of each divided road section is processed according to a linear fitting algorithm to obtain the cross section slope corresponding to each cross section;

[0105] The roll angle of each cross section is determined according to the cross section slope of each cross section, and the second time sequence data is constructed according to the roll angle of all cross sections;

[0106] After the second time sequence data is processed by Fourier transform, the second frequency data is obtained, and the amplitude and phase information of each frequency spectrum component is determined according to the second frequency data;

[0107] After the roll frequency range of the measurement posture of the measurement sensor is obtained according to the amplitude and phase information of each frequency spectrum component, the roll period signal of the measurement sensor is reconstructed according to the inverse Fourier transform and the roll frequency range of the measurement posture of the measurement sensor, so as to obtain the roll angle of each cross section corresponding to the measurement posture.

[0108] In step 1031, each cross section of each divided road section is processed according to a linear fitting algorithm to obtain the cross section slope corresponding to each cross section, and the present application linearly fits all measurement points in the cross section cross section by cross section, and then calculates the slope of the cross section.

[0109] In step 1032, the roll angle of each cross section is determined according to the cross section slope of each cross section, so as to construct the second time sequence data according to the roll angles of all cross sections. The present application determines the roll angle of each cross section according to the cross section slope, and constructs the second time sequence data according to the roll angles of each cross section distributed along the driving direction in sequence.

[0110] In step 1033, after the second time sequence data is processed by Fourier transform, the second frequency data is obtained, and the amplitude and phase information of each frequency component are determined according to the second frequency data. The determination of the amplitude and phase information of each frequency component is similar to step 1022. The present application needs to convert the second time sequence data into the second frequency data, so as to obtain the amplitude and phase information of each frequency component.

[0111] In step 1034, after the roll frequency range of the measured posture of the measurement sensor is obtained according to the amplitude and phase information of each frequency component, the roll periodic signal of the measurement sensor is reconstructed according to the inverse Fourier transform and the roll frequency range of the measured posture of the measurement sensor, so as to obtain the roll angle of the measured posture of the measurement sensor corresponding to each cross section. The present application uses the inverse Fourier transform method, and combines the frequency range of the roll periodic signal of the measurement sensor, so as to reconstruct the roll periodic signal of the measurement sensor, and obtain the roll angle of the measured posture of the sensor at any time.

[0112] Optionally, after the second frequency data is obtained, the method further comprises:

[0113] processing the second frequency data according to a simulation analysis method, so as to obtain the roll frequency range of the measured posture of the measurement sensor;

[0114] or, processing the second frequency data according to a historical data statistical analysis method, so as to obtain the roll frequency range of the measured posture of the measurement sensor;

[0115] or, extracting the roll frequency range from a preset roll frequency range set.

[0116] The present application can determine the amplitude and phase information of each frequency component according to the second frequency data, obtain the roll frequency range of the measured posture of the measurement sensor according to the simulation analysis method, and in other embodiments, the present application can also obtain the roll frequency range of the measured posture of the measurement sensor through the historical data statistical analysis method, or extract the roll frequency range from the preset roll frequency range set.

[0117] Figure 6 is a flowchart provided by the present application for correcting the original road surface three-dimensional data. The original road surface three-dimensional data is corrected according to the pitch and vibration elevation of the measured posture of the cross section corresponding to each cross section and the roll angle of the measured posture of the cross section corresponding to each cross section, so as to complete the three-dimensional road surface modeling.

[0118] For any cross-section data, the distance values ​​from all measurement points in the cross-section data to the mid-range measurement point in the cross-section along the road width direction are obtained through the calibration file;

[0119] For any cross-section data, determining the roll angle components of all measurement points in the cross-section according to the distance value and the roll angle of the corresponding measurement posture of the cross-section;

[0120] For any cross-sectional data, the corrected elevation of each measuring point is determined based on the elevation of each measuring point in the cross-sectional data, the pitch and vibration elevation of the corresponding measurement attitude of the cross-sectional data, the working distance obtained by the sensor head in the static calibration state, and the roll angle component of each measuring point in the cross-sectional data.

[0121] All cross-sectional data of the original three-dimensional road surface data are traversed until the original three-dimensional road surface data is corrected.

[0122] In step 1041, the distance value is determined based on the difference between all measurement points in the cross-sectional data and the mid-range measurement point in the cross-sectional data, and the difference between all measurement points in the cross-sectional data is determined in combination with the calibration file information.

[0123] In step 1042 , the roll angle components of all measurement points in the cross section are determined according to the product of the distance value and the roll angle of the measured posture corresponding to the cross section.

[0124] In step 1043, the corrected elevation of each measuring point is determined based on the elevation of each measuring point in the cross-section data, the pitch and vibration elevation of the corresponding measurement posture of the cross-section, the working distance obtained by the sensor head in the static calibration state, and the roll angle component of each measuring point in the cross-section. The elevation can be determined using the following formula:

[0125] z' ti =z ti +d t -D+(x i -x M )*tan(β t )

[0126] In the above formula, i=1,2,…,N,z' ti is the corrected elevation of the i-th test point in the measurement cross section collected at time t; z ti is the elevation of the i-th test point in the measurement cross section collected at time t; N is the number of all test points in the measurement cross section; x i is the position corresponding to the i-th test point along the distribution direction of the cross-section test points; x Mis a position corresponding to the Mth test point in the distribution direction of the cross-section test points; wherein, M=N / 2; D is a working distance of the any sensor head acquired under static calibration conditions; and β t is a roll angle of the any sensor head relative to the horizontal plane at t time; and d t is a pitch and vibration elevation of the any sensor head relative to the horizontal plane at t time.

[0127] Figure 7 is one of flowcharts provided by the present application for acquiring original road surface three-dimensional data, and before the difference between the starting cross-section average elevation and the ending cross-section average elevation corresponding to any cross-section in the original road surface three-dimensional data is acquired, the flowchart further comprises:

[0128] acquiring original road surface three-dimensional data by using a line scanning three-dimensional measurement method;

[0129] extracting an average elevation of each cross-section from the original road surface three-dimensional data;

[0130] the average elevation of each cross-section is determined according to the elevations of all measurement points in the road width of each cross-section.

[0131] In step 201, the present application aims to realize three-dimensional road surface modeling, and original road surface three-dimensional data can be acquired according to the line scanning three-dimensional measurement method, but the influence of measurement posture noise is not considered in the original road surface three-dimensional data, so it is necessary to eliminate the measurement posture noise from the original road surface three-dimensional data based on the present application to correct the original road surface three-dimensional data, and then complete the three-dimensional road surface modeling.

[0132] In step 202, the average elevation of each cross-section is determined according to the elevations of all measurement points in the road width of each cross-section, and according to the original road surface three-dimensional data, all cross-sections are determined, and then the elevation data of all test points in each cross-section is processed by averaging to determine the average elevation of each cross-section.

[0133] Figure 8 is another flowchart provided by the present application for acquiring original road surface three-dimensional data, and the line scanning three-dimensional measurement method for acquiring original road surface three-dimensional data comprises:

[0134] acquiring road surface profile data of multiple measurement points in the road width direction under the same measurement posture by using the line scanning three-dimensional measurement method;

[0135] composing each cross-section data according to the road surface profile data of multiple measurement points;

[0136] determining the original road surface three-dimensional data according to all cross-section data.

[0137] In step 2011, the line scanning three-dimensional measurement method can obtain the road surface profile data, i.e. cross section information, of multiple measurement points in the same measurement posture in a single measurement, and can optionally obtain the road surface profile data of at least 1000 measurement points, wherein the road surface profile data comprises the elevation and grayscale information of the surface of the object to be measured.

[0138] In step 2012, the cross section data of the cross section in the driving direction at the position coordinate is determined according to the road surface profile data of all measurement points in the road width direction in the position coordinate obtained in the same measurement posture by the line scanning three-dimensional measurement method.

[0139] In step 2013, the cross section data at all position coordinates in the driving direction is determined according to step 2012, and the original road surface three-dimensional data is determined according to all cross section data.

[0140] The application also provides a computer program product comprising a computer program, wherein the computer program can be stored on a non-transitory computer readable storage medium, and the computer program can be executed by a processor to enable a computer to perform a three-dimensional road surface modeling method provided by the above method, which comprises: determining the difference between the starting cross section average elevation and the ending cross section average elevation corresponding to any cross section of the original road surface three-dimensional data, determining the cross section with a difference greater than a preset threshold as a jump surface, processing the original road surface three-dimensional data according to all jump surfaces, and obtaining all divided road sections; constructing first time series data according to the average elevation of all cross sections of each divided road section, converting the first time series data into first frequency data, and obtaining the pitch and vibration elevation of the measurement posture corresponding to each cross section according to the first frequency data; constructing second time series data according to the slope of all cross sections of each divided road section, converting the second time series data into second frequency data, and obtaining the roll angle of the measurement posture corresponding to each cross section according to the second frequency data; correcting the original road surface three-dimensional data according to the pitch and vibration elevation of the measurement posture corresponding to each cross section and the roll angle of the measurement posture corresponding to each cross section, and completing three-dimensional road surface modeling; the starting cross section is the corresponding cross section obtained by taking the cross section as the center and moving forward by a first preset length along the data acquisition sequence; and the ending cross section is the corresponding cross section obtained by taking the cross section as the center and moving backward by a first preset length along the data acquisition sequence.

[0141] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented by a processor to execute the three-dimensional road surface modeling method provided by the above-mentioned methods, the method comprising: obtaining the difference between the average elevation of the starting cross section and the average elevation of the ending cross section corresponding to any cross section in the original road surface three-dimensional data, determining the cross section with the difference greater than a preset threshold as a jump surface, processing the original road surface three-dimensional data according to all jump surfaces, and obtaining all divided road sections; constructing a first time series data according to the average elevation of all cross sections of each divided road section, converting the first time series data into a first frequency data, and obtaining the average elevation of each cross section according to the first frequency data. The pitch and vibration elevation of the posture should be measured; a second time series data is constructed according to the slopes of all cross sections of each divided road section, and the second time series data is converted into second frequency data to obtain the roll angle of the corresponding measurement posture of each cross section according to the second frequency data; the original road surface three-dimensional data is corrected according to the pitch and vibration elevation of the corresponding measurement posture of the cross section and the roll angle of the corresponding measurement posture of the cross section to complete the three-dimensional road surface modeling; the starting cross section is the corresponding cross section taken forward with the cross section as the center plane along the data collection sequence and at an interval of the first preset length; the ending cross section is the corresponding cross section taken backward with the cross section as the center plane along the data collection sequence and at an interval of the first preset length.

[0142] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0143] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0144] It should be pointed out finally that the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit the same; and although the present application has been described in detail with reference to the foregoing embodiments, it should be appreciated by those skilled in the art that the technical solutions recorded in the foregoing embodiments can be modified, or some technical features thereof can be replaced equivalently; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A three-dimensional road surface modeling method, characterized in that: include: Obtaining the difference between the average elevation of the starting cross section and the average elevation of the ending cross section corresponding to any cross section in the original road surface three-dimensional data, determining the cross section with the difference greater than a preset threshold as a jump surface, processing the original road surface three-dimensional data based on all jump surfaces, and obtaining all divided road sections, including: After traversing all cross sections, all continuous jump surfaces are obtained, and a section formed by any continuous jump surface whose length is greater than a second preset length is determined as a jump area; After traversing all continuous jump surfaces, all jump areas are obtained to determine a segmented surface according to each jump area; Divide the original road surface three-dimensional data according to the segmented surface to obtain all divided road sections; Constructing first time series data based on the average elevation of all cross sections of each divided road section, converting the first time series data into first frequency data, and obtaining the pitch and vibration elevation of the corresponding measurement posture of each cross section based on the first frequency data; Constructing second time series data based on the slopes of all cross sections of each divided road section, converting the second time series data into second frequency data, and obtaining a roll angle corresponding to a measured posture of each cross section based on the second frequency data; Correcting the original road surface three-dimensional data according to the pitch and vibration elevation of the cross-section corresponding to the measured posture and the roll angle of the cross-section corresponding to the measured posture to complete three-dimensional road surface modeling; The starting cross-section is the corresponding cross-section taken forward with the cross-section as the center plane along the data collection sequence and at intervals of the first preset length; the ending cross-section is the corresponding cross-section taken backward with the cross-section as the center plane along the data collection sequence and at intervals of the first preset length.

2. The three-dimensional road surface modeling method according to claim 1, characterized in that: The step of constructing first time series data based on the average elevation of all cross sections of each divided road section, converting the first time series data into first frequency data, and obtaining the pitch and vibration elevation of the corresponding measurement posture of each cross section based on the first frequency data, includes: In each divided road section, the average elevation of all cross sections is calculated, and a set of mean cross section elevations corresponding to each divided road section is obtained, so as to construct first time series data according to the set of mean cross section elevations; After processing the first time series data using Fourier transform, first frequency data is obtained to determine amplitude and phase information of each spectral component according to the first frequency data; After obtaining the vibration and pitch frequency range of the measurement posture according to the amplitude and phase information of each spectral component, the pitch and vibration periodic signals of the measurement sensor are reconstructed according to the inverse Fourier transform and the vibration and pitch frequency range of the measurement posture to obtain the pitch and vibration elevation of the measurement posture corresponding to each cross section.

3. The three-dimensional road surface modeling method according to claim 1, characterized in that: After obtaining the first frequency data, the method further includes: Processing the first frequency data according to a simulation analysis method to obtain a vibration and pitch frequency range of the measured posture; Alternatively, the first frequency data may be processed according to a historical data statistical analysis method to obtain a vibration and pitch frequency range of the measured posture; Alternatively, the vibration and pitch frequency range is extracted from a preset vibration and pitch frequency range set.

4. The three-dimensional road surface modeling method according to claim 1, characterized in that: The step of constructing second time series data based on the slopes of all cross sections of each divided road section, converting the second time series data into second frequency data, and obtaining the roll angle of the measured posture corresponding to each cross section based on the second frequency data, includes: All cross sections of each divided road section are processed according to the linear fitting algorithm to obtain the cross section slope corresponding to each cross section; determining a roll angle of each cross section according to the cross section slope of each cross section, so as to construct second time series data according to the roll angles of all cross sections; After processing the second time series data using Fourier transform, second frequency data is obtained to determine amplitude and phase information of each spectral component according to the second frequency data; After obtaining the roll frequency range of the measurement sensor's measured attitude based on the amplitude and phase information of each spectral component, the measurement sensor's roll periodic signal is reconstructed based on inverse Fourier transform and the roll frequency range of the measurement sensor's measured attitude to obtain the roll angle of the measurement attitude corresponding to each cross-section.

5. The three-dimensional road surface modeling method according to claim 1, characterized in that: After obtaining the second frequency data, the method further includes: Processing the second frequency data according to a simulation analysis method to obtain a rolling frequency range of the attitude measured by the measurement sensor; Alternatively, the second frequency data is processed according to a historical data statistical analysis method to obtain a rolling frequency range of the attitude measured by the measurement sensor; Alternatively, the roll frequency range is extracted from a preset roll frequency range set.

6. The three-dimensional road surface modeling method according to claim 1, characterized in that: The method of correcting the original road surface three-dimensional data according to the pitch and vibration elevation of the cross-section corresponding to the measured attitude and the roll angle of the cross-section corresponding to the measured attitude to complete the three-dimensional road surface modeling includes: For any cross-section data, the distance values ​​from all measurement points in the cross-section data to the mid-range measurement point in the cross-section along the road width direction are obtained through the calibration file; For any cross-section data, determining the roll angle components of all measurement points in the cross-section according to the distance value and the roll angle of the corresponding measurement posture of the cross-section; For any cross-sectional data, the corrected elevation of each measuring point is determined based on the elevation of each measuring point in the cross-sectional data, the pitch and vibration elevation of the corresponding measurement attitude of the cross-sectional data, the working distance obtained by the sensor head in the static calibration state, and the roll angle component of each measuring point in the cross-sectional data. All cross-sectional data of the original three-dimensional road surface data are traversed until the original three-dimensional road surface data is corrected.

7. The three-dimensional road surface modeling method according to claim 1, characterized in that: Before obtaining the difference between the average elevation of the starting cross section and the average elevation of the ending cross section corresponding to any cross section in the original road surface 3D data, the following steps are also included: Use line scanning 3D measurement method to obtain original road surface 3D data; Extract the average elevation of each cross section from the original road surface 3D data; The average elevation of each cross section is determined based on the elevations of all measuring points in the road width of each cross section.

8. The three-dimensional road surface modeling method according to claim 7, characterized in that: The method of obtaining original road surface three-dimensional data by using a line scanning three-dimensional measurement method includes: Using the line scanning three-dimensional measurement method, the road surface profile data of multiple measurement points along the road width direction are obtained in the same measurement posture; Composing each cross-section data according to the road profile data of multiple measuring points; The original road surface three-dimensional data is determined based on all cross-section data.

Images