A road surface status data acquisition method based on array radar sensor

Abstract

The present invention relates to the field of data processing technology, and in particular to a method for collecting road state data based on an array radar sensor, comprising: obtaining the speed of a collection vehicle, determining the road state matrix to be collected next time according to the flatness of the road state matrix; obtaining the data consistency of the road state matrix in each direction and obtaining the minimum direction of the road state matrix; obtaining a partial matrix of the road state matrix, and a corresponding matrix of the partial matrix, and further obtaining a road state analysis matrix; when the flatness of the road state matrix is ​​less than or equal to a preset road flatness threshold, the corresponding road state analysis matrix is ​​used as an uneven road matrix, and denoised road state data is obtained according to the uneven road matrix and the road state matrix, and the road state data collection based on the array radar sensor is completed. The present invention aims to accurately identify the noise data in the collected data, timely discover abnormal road conditions, and reduce potential risks on the road surface.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a method for collecting road surface status data based on an array radar sensor. Background Art

[0002] An array radar sensor is a radar system that uses multiple receiving and transmitting antennas. It uses the integration of array antennas to form multiple beams, so that the location and other characteristics of the target can be determined more accurately. By using array radar sensors to detect the road surface conditions and denoising and cleaning the collected road surface condition data, the accuracy of the road surface condition data can be guaranteed, which helps to promptly detect defects such as cracks and potholes on the road surface and reduce potential risks on the road surface.

[0003] At present, the method of denoising the collected road condition data usually directly finds the noise data according to the difference between each data and other data, and performs denoising. When the collection vehicle drives to the uphill or downhill turning point, the angle between the collection vehicle and the road surface causes the collected data to be inconsistent with the normal road data, and the noise data may also be within the range of normal road data, resulting in inaccurate recognition of the noise data in the collected data, and the abnormal road condition cannot be discovered in time, increasing the potential risks on the road surface. Summary of the invention

[0004] The present invention provides a road surface status data acquisition method based on an array radar sensor to solve the existing problems.

[0005] A road surface state data collection method based on an array radar sensor of the present invention adopts the following technical solution:

[0006] An embodiment of the present invention provides a method for collecting road surface status data based on an array radar sensor, the method comprising the following steps:

[0007] The speed of the collection vehicle is obtained, and the road surface state matrix for the next collection is obtained according to the flatness of the road surface state matrix collected each time;

[0008] According to the data variation range of the road surface state matrix in different directions, the data consistency of the road surface state matrix collected each time in each direction is obtained; and the direction corresponding to the minimum data consistency is recorded as the minimum direction of the road surface state matrix collected each time;

[0009] According to the speed of the data collection vehicle, a partial matrix of the road surface state matrix collected each time and a corresponding matrix of the partial matrix are obtained; according to the data difference between the partial matrix collected each time and the corresponding matrix of the partial matrix in the minimum direction, an analysis matrix of the road surface state collected each time is obtained;

[0010] When the flatness of the road surface state matrix is ​​less than or equal to the preset road surface flatness threshold, the road surface state analysis matrix corresponding to the number of acquisitions is used as the uneven road surface matrix. Denoising is performed based on the uneven road surface matrix and the road surface state matrix to obtain the denoised road surface state data, thereby completing the road surface state data acquisition based on the array radar sensor.

[0011] Furthermore, the specific method of obtaining the road surface state matrix collected next time is:

[0012] The acquisition interval of the sth collection is obtained as follows:

[0013]

[0014] t s =t×ρ

[0015] Among them, t s represents the collection interval of the sth collection; σ s-1 represents the standard deviation of the road state matrix collected for the s-1th time; t represents the initial collection interval; δ represents the preset hyperparameter; ρ s Indicates the flatness of the road surface collected for the sth time;

[0016] The road surface state matrix of the s-th collection is obtained by using the collection interval of the s-th collection.

[0017] Furthermore, obtaining the data consistency of the road surface state matrix collected each time in each direction includes:

[0018] The cumulative sum of the standard deviations of all data in the u-th direction in the road surface state matrix collected for the s-th time is recorded as the data consistency of the road surface state matrix collected for the s-th time in the u-th direction.

[0019] Furthermore, the specific method of obtaining the direction is:

[0020] The four directions of the road surface state matrix collected each time are the horizontal direction, the vertical direction and two diagonal directions of the road surface state matrix.

[0021] Furthermore, the obtaining of a partial matrix of the road surface state matrix collected each time and a corresponding matrix of the partial matrix include:

[0022] The last row of the road state matrix collected at the sth time is used as the standard row of the road state matrix collected at the sth time. For the vth collection after the sth collection, the standard row of the road state matrix collected at the sth time is the ratio of the change distance in the vth collection to the distance between the road surface positions collected by two adjacent sensors on the array radar sensor. The difference between the total number of rows of the road state matrix and the ratio of the distance is recorded as the number of rows of the standard row of the road state matrix collected at the sth time in the vth collection.

[0023] The number of rows in the road surface state matrix is ​​recorded as L, and the corresponding row in the road surface state matrix collected at the vth time is recorded as the lth row. v,s Row, the Llth row of the road surface state matrix collected for the sth time v,s The row corresponds to the first row in the road surface state matrix collected for the vth time, and the Llth row in the road surface state matrix collected for the sth time. v,s The partial matrix of the sth acquisition is composed of rows from row to standard row, and the pavement state matrix of the vth acquisition is composed of rows from row 1 to row l v,s The rows form the correspondence matrix of the vth acquisition to the sth acquisition.

[0024] Furthermore, the specific method of obtaining the change distance is:

[0025] The product of the speed of the collection vehicle and the collection interval from the sth collection to the vth collection is recorded as the change distance of the standard row of the road state matrix of the sth collection in the vth collection.

[0026] Furthermore, obtaining the road surface condition analysis matrix collected each time includes:

[0027] All the road surface condition data in the minimum direction of the partial matrix collected at the sth time and all the road surface condition data in the same direction of the corresponding matrix collected at the vth time are constructed with the minimum direction as the horizontal axis of the matrix and the vertical axis perpendicular to the minimum direction as the matrix vertical axis, and the obtained matrix is ​​recorded as the co-location matrix of the sth collection and the corresponding co-location matrix of the vth collection for the sth collection;

[0028] The difference between the average value of the co-location matrix corresponding to the s-th acquisition for the v-th acquisition and the average value of the co-location matrix for the s-th acquisition is recorded as the compensation value of the co-location matrix corresponding to the s-th acquisition for the v-th acquisition;

[0029] The difference between the mth road surface state data in the co-location matrix collected at the sth time and the compensation value of the corresponding co-location matrix collected at the vth time is recorded as the mth adjusted road surface state data in the co-location matrix collected at the sth time;

[0030] All adjusted road surface condition data in the co-location matrix collected for the sth time constitute the road surface condition analysis matrix collected for the sth time.

[0031] Furthermore, the denoising is performed according to the uneven road surface matrix and the road surface state matrix to obtain the denoised road surface state data, including:

[0032] When the flatness of the sth acquisition is greater than the road surface flatness threshold When , the road surface state matrix collected for the sth time is recorded as a flat road surface matrix;

[0033] Obtain the abnormality degree of the wth data in the flat road matrix collected for the sth time;

[0034] When the abnormality degree of the wth data in the flat road matrix collected for the sth time is greater than or equal to the preset data abnormality threshold, the wth data in the flat road matrix collected for the sth time is recorded as abnormal data;

[0035] When the number of the wth abnormal data that is continuous with other abnormal data in the minimum direction in the flat road matrix collected for the sth time is greater than or equal to the abnormal data quantity threshold, the wth abnormal data is recorded as noise data;

[0036] When the flatness of the road surface is less than or equal to the preset road surface flatness threshold, the road surface state analysis matrix collected for the sth time is recorded as an uneven road surface matrix;

[0037] Normalize the accumulated sum of the absolute values ​​of the differences between the ath road surface state data in the uneven road surface matrix collected for the sth time and the remaining road surface state data except the ath road surface state data in the uneven road surface matrix collected for the sth time, and record the normalized result as the abnormality degree of the ath road surface state data in the uneven road surface matrix collected for the sth time;

[0038] Normalize the accumulated sum of the absolute values ​​of the difference between the abnormality degree of the ath data in the uneven road matrix collected at the sth time and the abnormality degree of each data in the analysis sequence of the ath data in the uneven road matrix collected at the sth time, and record the normalized result as the possibility that the ath data in the uneven road matrix collected at the sth time is noise data;

[0039] When the possibility that the ath data in the uneven road surface matrix collected for the sth time is noise data is greater than the noise threshold, the ath data in the uneven road surface matrix collected for the sth time is recorded as noise data.

[0040] Furthermore, the abnormality degree of the wth data in the flat road matrix collected for the sth time includes:

[0041] The accumulated absolute value of the difference between the wth data in the flat road matrix collected for the sth time and the remaining data except the wth data in the flat road matrix collected for the sth time is normalized, and the normalized result is recorded as the abnormality degree of the wth data in the flat road matrix collected for the sth time.

[0042] Furthermore, the analysis sequence includes:

[0043] In the corresponding co-location matrix of the s+1th acquisition, data corresponding to the same road surface position of the a-th data is obtained. When the data corresponding to the same road surface position of the a-th data can be obtained in the corresponding co-location matrix of the s+1th acquisition, data corresponding to the same road surface position of the a-th data is obtained in the corresponding co-location matrix of the s+2th acquisition, and so on, until there is a constant c such that when the data corresponding to the same road surface position of the a-th data cannot be obtained in the corresponding co-location matrix of the s+cth acquisition for the s+c-1th acquisition, all the data corresponding to the same road surface position obtained by the a-th data constitute the analysis sequence of the a-th data in the uneven road surface matrix of the s-th acquisition.

[0044] The beneficial effects of the technical solution of the present invention are: obtaining the speed of the collection vehicle, obtaining the road surface state matrix for the next collection according to the flatness of the road surface state matrix collected each time, and shortening the collection interval in order to better judge whether it is noise or interference caused by factors such as road slope at uneven road surface locations, so that multiple collections can be performed on the same road surface location, abnormal conditions are analyzed from the road surface state data collected multiple times, and the road surface state matrix is ​​re-acquired according to the adjusted collection interval; according to the data change amplitude of the road surface state matrix in different directions, the data consistency of the road surface state matrix collected each time in each direction is obtained, and the direction corresponding to the minimum data consistency is recorded as the minimum direction of the road surface state matrix collected each time. When the road surface state matrix changes in a certain direction, the noise data therein may be similar to the normal road surface state data, and thus cannot be directly identified, but in the case of high consistency. In terms of direction, it will not be affected in this way. Therefore, the data consistency of each direction in the collected road state matrix is ​​determined, and the direction corresponding to the minimum data consistency can better reflect the abnormal data in the road state matrix; according to the speed of the collection vehicle, the partial matrix of the road state matrix collected each time and the corresponding matrix of the partial matrix are obtained, and the road state analysis matrix collected each time is obtained according to the data difference between the partial matrix collected each time and the corresponding matrix of the partial matrix in the minimum direction. When the flatness of the road state matrix is ​​less than or equal to the preset road flatness threshold, the road state analysis matrix corresponding to the number of collections is used as an uneven road matrix, and denoising is performed according to the uneven road matrix and the road state matrix to obtain denoised road state data, complete the road state data collection based on the array radar sensor, accurately identify the noise data in the collected data, discover abnormal road state in time, and reduce potential risks on the road surface. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0046] Figure 1 The present invention is a flowchart of the steps of a method for collecting road surface status data based on an array radar sensor. DETAILED DESCRIPTION

[0047] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of a road surface state data collection method based on an array radar sensor proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0048] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0049] The following is a detailed description of a specific solution of a road surface status data collection method based on an array radar sensor provided by the present invention in conjunction with the accompanying drawings.

[0050] See also Figure 1 , which shows a flow chart of a method for collecting road surface status data based on an array radar sensor provided by an embodiment of the present invention, the method comprising the following steps:

[0051] Step S001: Obtain the speed of the data collection vehicle, and obtain the road surface state matrix to be collected next time according to the flatness of the road surface state matrix collected each time.

[0052] The array radar sensor is fixed under the collection vehicle, and the collection vehicle is made to move at a constant speed on the road surface, and the speed of the collection vehicle is recorded; the array radar sensor is used to collect the distance between the road surface and the chassis of the collection vehicle once every initial collection interval of t seconds, and the road surface state matrix collected each time is obtained. Since the sensor distribution of the array radar sensor is similar to a matrix, the road surface state matrix collected at each moment is arranged into a matrix according to the sensor position. The initial collection interval t=10 seconds preset in this embodiment is described as an example, and other values ​​can be set in other implementation modes, which are not limited in this embodiment.

[0053] It should be noted that in locations where the road surface is relatively flat, that is, when the data difference is small, the difference in the road surface state data collected at each moment can be used to analyze whether there is noise. Therefore, in order to improve the collection efficiency, the collection interval can be extended. In locations where the road surface is uneven, in order to better determine whether it is noise or interference caused by factors such as road surface slope, the collection interval needs to be shortened so that multiple collections can be performed on the same road surface location, and abnormal conditions can be analyzed from the road surface state data collected multiple times. Therefore, the initial collection interval should be adjusted according to the flatness of the collected road surface.

[0054] Specifically, for the s-th collection, the method for obtaining the collection interval of the s-th collection is:

[0055]

[0056] t s =t×ρ

[0057] Among them, t s represents the collection interval of the sth collection; σ s-1 represents the standard deviation of the road surface state matrix collected for the s-1th time; t represents the initial collection interval; δ represents a preset hyperparameter, and this embodiment is described by taking δ=0.1 as an example, and other embodiments may set other values; ρ s Indicates the flatness of the road surface collected for the sth time.

[0058] When the standard deviation of the pavement state matrix collected for the s-1th time is zero, it means that the data in the pavement state matrix collected for the s-1th time is consistent, the pavement collected for the sth time is flat, and the collection interval of the sth time is consistent with the initial collection interval.

[0059] Furthermore, the road surface state matrix collected for the sth time is obtained using the collection interval of the sth collection. Similarly, the road surface state matrices collected for all times in one day are obtained according to the collection interval of each collection.

[0060] At this point, the adjusted collection interval is obtained, and the road surface state matrix is ​​recollected according to the adjusted collection interval.

[0061] Step S002: according to the data variation range of the road surface state matrix in different directions, obtain the data consistency of the road surface state matrix collected each time in each direction; record the direction corresponding to the minimum data consistency as the minimum direction of the road surface state matrix collected each time.

[0062] It should be noted that when the road state matrix changes in a certain direction, the noise data may be close to the normal road state data and cannot be directly identified, but in the highly consistent direction, it will not be affected in this way. Therefore, it is necessary to first determine the data consistency in each direction of the collected road state matrix. The direction corresponding to the minimum data consistency can better reflect the abnormal data in the road state matrix.

[0063] Specifically, this embodiment is described by taking the four directions of the pavement state matrix collected each time as an example. Other implementation methods may be set to other directions, which are not limited in this embodiment. The four directions of the pavement state matrix collected each time are the horizontal, vertical and two diagonal directions of the pavement state matrix. The horizontal direction is from the first column to the last column of the pavement state matrix, and the vertical direction is from the first row to the last row of the pavement state matrix. The two diagonal directions refer to from the lower left corner to the upper right corner of the pavement state matrix and from the lower right corner to the upper left corner of the pavement state matrix, respectively.

[0064] The calculation formula for the data consistency of the road surface state matrix collected for the sth time in the uth direction is:

[0065]

[0066] Among them, r s,u Indicates the data consistency of the u-th direction in the road state matrix collected for the s-th time; n s,u Indicates the number of data rows in the u-th direction of the road state matrix collected for the s-th time; σ s,u,k Represents the standard deviation of the kth row of data in the uth direction in the road state matrix collected for the sth time.

[0067] Similarly, the data consistency of each direction in the road surface state matrix collected for the sth time is obtained, and the direction corresponding to the minimum data consistency is recorded as the minimum direction of the road surface state matrix collected each time.

[0068] Step S003: obtaining a partial matrix of the road surface state matrix collected each time and a corresponding matrix of the partial matrix according to the speed of the collection vehicle; obtaining a road surface state analysis matrix collected each time according to the data difference between the partial matrix collected each time and the corresponding matrix of the partial matrix in the minimum direction.

[0069] It should be noted that the minimum direction of the road surface state matrix collected each time can best reflect whether there is noise data in the road surface state matrix. Therefore, to analyze the abnormality of a certain data in the road surface state matrix collected each time, it is necessary to find all the data corresponding to the minimum direction of the data in the road surface state matrix as reference data to determine the abnormality of the data. Since the amount of data used as reference data for a row of data in the minimum direction of the road surface state matrix collected once is too small, it may be affected by accidental factors and is not reliable enough, so it is necessary to further find multiple reference data at the same position. For the road surface position corresponding to any data in the road surface state matrix collected each time, due to the adjustment of the collection interval, the same road surface position will be collected multiple times during multiple collections. Therefore, it is necessary to determine the position of the data corresponding to the same road surface position in the road surface state matrix obtained by different collections.

[0070] Taking the rear of the vehicle as a reference, that is, the last row of data collected in the road state matrix, the position of the same road position in the road state matrix collected at different times will change. For the same road position, according to the position change of the same road position in the road state matrix collected at different times, the data in the road state matrix corresponding to the same road position is obtained, and the corresponding position in the road state data collected at different times is obtained.

[0071] Furthermore, the last row of the pavement state matrix collected for the sth time is used as the standard row of the pavement state matrix collected for the sth time. This embodiment uses the standard row of the pavement state matrix collected for the sth time as a reference for the same pavement position in the pavement state data. Other embodiments use other data marking methods as the same pavement position, which is not specifically limited in this embodiment. Then for the vth acquisition after the sth acquisition, the number of rows of the standard row of the pavement state matrix collected for the sth time in the vth acquisition is:

[0072]

[0073] Among them, l v,s is the number of rows of the standard row of the pavement state matrix collected at the sth time in the vth time; L is the total number of rows of the pavement state matrix; S v,s It represents the change distance of the standard row of the road state matrix collected at the sth time in the vth collection, and the change distance is obtained by multiplying the speed of the collection vehicle by the collection interval from the sth collection to the vth collection, and recording it as the change distance of the standard row of the road state matrix collected at the sth time in the vth collection; x represents the distance between the road surface positions collected by two adjacent sensors on the array radar sensor.

[0074] It should be noted that when the collection vehicle moves forward, the column of the corresponding position of the same road surface position in the road surface state matrix during different collection processes will not change. Therefore, in the road surface state matrix obtained by the sth collection, find the row closest to the last row of data in the road surface state matrix collected for the vth time, where the data in the same column as the road surface position data collected for the sth time is the position of the data corresponding to the same road surface position in the road surface state matrix obtained by different collections.

[0075] It is particularly important to note that the standard row of the road surface state matrix collected for the sth time corresponds to the lth row of the road surface state matrix collected for the vth time. v,s Row, the Llth row of the road surface state matrix collected for the sth time v,s The row corresponds to the first row in the road surface state matrix collected for the vth time, and the Llth row in the road surface state matrix collected for the sth time. v,s The partial matrix of the sth acquisition, which is composed of rows from row to standard row, is the same as the matrix of the road surface state acquired in the vth acquisition, which is composed of rows from row 1 to row l.v,s The sizes of the partial matrices of the vth acquisition formed by the rows are the same, so the partial matrix of the sth acquisition is recorded as the corresponding matrix of the vth acquisition to the sth acquisition.

[0076] At this point, the corresponding matrix of the same data in different acquisition times is obtained.

[0077] It should be noted that, since the angle of the vehicle relative to the ground changes when the collection vehicle goes uphill or downhill, the same road surface position may change in different collection processes. When the vehicle is moving forward, the column of the same collection position will not change, but the number of rows will change as the vehicle moves forward. Therefore, when the collection vehicle is going uphill or downhill, the data difference in the same row of the road state matrix is ​​smaller than the data difference in the same column. When the height of the tire on one side of the collection vehicle is higher than that of the tire on the other side, the data difference in the same column of the road state matrix is ​​smaller than the data difference in the same row. In order to find the noise data, it is necessary to first perform height compensation on the data in different collection processes based on the average value of the data in different collection processes and the minimum direction of the data change difference in the same direction in the road state matrix collected each time, and then adjust all the collected road state data according to the compensation value, and establish a road state analysis matrix based on the adjusted road state data in the road area.

[0078] Specifically, based on the different road conditions encountered by the collection vehicle, all road condition data in the minimum direction of the partial matrix collected for the sth time and all road condition data in the same direction of the corresponding matrix for the sth collection for the vth collection are taken as the horizontal axis of the matrix and the vertical axis perpendicular to the minimum direction. The matrix obtained is recorded as the co-location matrix for the sth collection and the corresponding co-location matrix for the sth collection for the vth collection, and the co-location matrix and the corresponding co-location matrix have the same size.

[0079] Furthermore, the difference between the average value of the corresponding co-location matrix of the v-th acquisition for the s-th acquisition and the average value of the co-location matrix of the s-th acquisition is recorded as the compensation value of the corresponding co-location matrix of the v-th acquisition for the s-th acquisition; the difference between the m-th road surface condition data in the co-location matrix of the s-th acquisition and the compensation value of the corresponding co-location matrix of the v-th acquisition for the s-th acquisition is recorded as the m-th adjusted road surface condition data in the co-location matrix of the s-th acquisition; all adjusted road surface condition data in the co-location matrix of the s-th acquisition constitute the road surface condition analysis matrix of the s-th acquisition.

[0080] Step S004: When the flatness of the road surface state matrix is ​​less than or equal to a preset road surface flatness threshold, the road surface state analysis matrix corresponding to the number of acquisitions is used as an uneven road surface matrix, and denoising is performed based on the uneven road surface matrix and the road surface state matrix to obtain denoised road surface state data, thereby completing the road surface state data acquisition based on the array radar sensor.

[0081] It should be noted that the greater the flatness of each acquisition, the less affected the road surface is by the road surface state. The data corresponding to the road surface position in the road surface state matrix is ​​relatively consistent with the normal road surface state data. When the road surface is flat, the road surface state matrix acquired can directly calculate the abnormality of the road surface state data based on the difference between each data and other data in the road surface state matrix. The smaller the flatness of each acquisition, the more affected the road surface is by the road surface state. For the road surface state analysis matrix acquired when the road surface is uneven, the abnormality of each data is calculated based on the difference between each data and other data in the road surface state analysis matrix obtained above.

[0082] Specifically, the road surface flatness threshold preset in this embodiment is This is used as an example for description. Other values ​​may be set in other implementations and are not limited in this embodiment.

[0083] When the flatness of the sth acquisition is greater than the road surface flatness threshold When , the road surface state matrix collected for the sth time is recorded as the flat road surface matrix. The calculation formula for the abnormality of the wth data in the flat road surface matrix collected for the sth time is:

[0084]

[0085] Among them, f s,w Indicates the abnormality of the wth data in the flat road matrix collected for the sth time; d s,j represents the jth data in the flat road matrix collected for the sth time; d s,w represents the wth data in the flat road matrix collected for the sth time; n represents the number of sensors on the array radar sensor; norm() represents the linear normalization function, which normalizes the data value to the interval [0,1]; || represents the absolute value function.

[0086] The data abnormality threshold b=0.5 preset in this embodiment is described as an example, and other values ​​may be set in other implementations, which are not limited in this embodiment. When the abnormality degree of the wth data in the flat road matrix collected for the sth time is greater than or equal to the preset data abnormality threshold b, the wth data in the flat road matrix collected for the sth time is recorded as abnormal data.

[0087] It should be further explained that abnormal data may be either noise data or road surface defects. Noise data is usually scattered, while road surface defects are continuous. Therefore, noise data can be obtained based on the number of consecutive abnormal data in the flat road surface matrix.

[0088] The preset abnormal data quantity threshold h=3 in this embodiment is described as an example. Other implementations may be set to other values, which are not limited in this embodiment. When the number of the w-th abnormal data that is continuous with other abnormal data in the minimum direction in the flat road matrix collected for the sth time is greater than or equal to the abnormal data quantity threshold h, the w-th abnormal data is recorded as noise data.

[0089] When the flatness of the road surface is less than or equal to the preset road surface flatness threshold When , the road surface condition analysis matrix collected for the sth time is recorded as the uneven road surface matrix. The calculation formula for the abnormality of the ath data in the uneven road surface matrix collected for the sth time is:

[0090]

[0091] Among them, f s,a represents the abnormality of the ath data in the uneven road matrix collected for the sth time; Y represents the number of data in the uneven road matrix; d s,a represents the ath road surface state data in the uneven road surface matrix collected for the sth time; d s,y It represents the yth road surface state data in the uneven road surface matrix collected for the sth time; norm() represents the linear normalization function, which normalizes the data value to the interval [0,1]; || represents the absolute value function.

[0092] It should be further explained that since noise data is random, if the data with a large degree of abnormality is noise data, the multiple data collected at the same road surface location will be inconsistent. Therefore, it is possible to determine whether the collected data is noise data based on the differences between the multiple data collected at the same road surface location.

[0093] Specifically, data corresponding to the same road surface position of the a-th data is obtained in the corresponding co-location matrix for the s-th collection at the s+1-th collection. When data corresponding to the same road surface position of the a-th data can be obtained in the corresponding co-location matrix for the s-th collection at the s+1-th collection, data corresponding to the same road surface position of the a-th data is obtained in the corresponding co-location matrix for the s+1-th collection at the s+2-th collection, and so on, until there is a constant c such that data corresponding to the same road surface position of the a-th data cannot be obtained in the corresponding co-location matrix for the s+c-1-th collection at the s+c-th collection. All data corresponding to the same road surface position obtained by the a-th data constitute an analysis sequence of the a-th data in the uneven road surface matrix collected at the s-th collection.

[0094] The calculation formula for the possibility that the ath data in the uneven road surface matrix collected for the sth time is noise data is:

[0095]

[0096] Among them, p s,a Indicates the possibility that the ath data in the uneven road matrix collected for the sth time is noise data; n s,a represents the sequence length of the analysis sequence of the ath data in the uneven road surface matrix collected for the sth time; f s,a represents the abnormality of the ath data in the uneven road matrix collected for the sth time; f a,s,o It represents the abnormality of the oth data in the analysis sequence of the ath data in the uneven road surface matrix collected for the sth time; norm() represents the linear normalization function, which normalizes the data value to the interval [0,1]; || represents the absolute value function.

[0097] The noise threshold g=0.5 is preset in this embodiment, and is described as an example. Other values ​​may be set in other implementations, and this embodiment does not limit it. When the possibility that the ath data in the uneven road matrix collected for the sth time is noise data is greater than the noise threshold g, the ath data in the uneven road matrix collected for the sth time is recorded as noise data.

[0098] For all noise data, median filtering is performed on the noise data according to the adjacent non-noise data in the road surface state matrix. The result of median filtering is used as the road surface state data after denoising each noise data, and the denoised road surface state data is obtained to complete the collection of road surface state data.

[0099] This is the end of the present invention.

[0100] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for collecting road surface status data based on an array radar sensor, characterized in that: The method comprises the following steps: The speed of the collection vehicle is obtained, and the road surface state matrix for the next collection is obtained according to the flatness of the road surface state matrix collected each time; According to the data variation range of the road surface state matrix in different directions, the data consistency of the road surface state matrix collected each time in each direction is obtained; and the direction corresponding to the minimum data consistency is recorded as the minimum direction of the road surface state matrix collected each time; According to the speed of the data collection vehicle, a partial matrix of the road surface state matrix collected each time and a corresponding matrix of the partial matrix are obtained; according to the data difference between the partial matrix collected each time and the corresponding matrix of the partial matrix in the minimum direction, an analysis matrix of the road surface state collected each time is obtained; When the flatness of the road surface state matrix is ​​less than or equal to the preset road surface flatness threshold, the road surface state analysis matrix corresponding to the number of acquisitions is used as an uneven road surface matrix, and denoising is performed based on the uneven road surface matrix and the road surface state matrix to obtain denoised road surface state data, thereby completing the road surface state data acquisition based on the array radar sensor; The method of obtaining a partial matrix of the road surface state matrix collected each time and a corresponding matrix of the partial matrix includes: The last row of the road state matrix collected at the sth time is used as the standard row of the road state matrix collected at the sth time. For the vth collection after the sth collection, the standard row of the road state matrix collected at the sth time is the ratio of the change distance in the vth collection to the distance between the road surface positions collected by two adjacent sensors on the array radar sensor. The difference between the total number of rows of the road state matrix and the ratio of the distance is recorded as the number of rows of the standard row of the road state matrix collected at the sth time in the vth collection. The number of rows in the road surface state matrix is ​​recorded as L, and the corresponding row in the road surface state matrix collected at the vth time is recorded as the lth row. v,s Row, the Llth row of the road surface state matrix collected for the sth time v,s The row corresponds to the first row in the road surface state matrix collected for the vth time, and the Llth row in the road surface state matrix collected for the sth time. v,s The partial matrix of the sth acquisition is composed of rows from row to standard row, and the pavement state matrix of the vth acquisition is composed of rows from row 1 to row l v,s The rows constitute the corresponding matrix of the vth acquisition to the sth acquisition; The specific method of obtaining the change distance is: The product of the speed of the collection vehicle and the collection interval from the sth collection to the vth collection is recorded as the change distance of the standard row of the road state matrix of the sth collection in the vth collection; The obtaining of the road surface condition analysis matrix collected each time includes: All the road surface condition data in the minimum direction of the partial matrix collected at the sth time and all the road surface condition data in the same direction of the corresponding matrix collected at the vth time are constructed with the minimum direction as the horizontal axis of the matrix and the vertical axis perpendicular to the minimum direction as the matrix vertical axis, and the obtained matrix is ​​recorded as the co-location matrix of the sth collection and the corresponding co-location matrix of the vth collection for the sth collection; The difference between the average value of the co-location matrix corresponding to the s-th acquisition for the v-th acquisition and the average value of the co-location matrix for the s-th acquisition is recorded as the compensation value of the co-location matrix corresponding to the s-th acquisition for the v-th acquisition; The difference between the mth road surface state data in the co-location matrix collected at the sth time and the compensation value of the corresponding co-location matrix collected at the vth time is recorded as the mth adjusted road surface state data in the co-location matrix collected at the sth time; All adjusted road surface condition data in the co-location matrix collected for the sth time constitute the road surface condition analysis matrix collected for the sth time.

2. The method for collecting road surface status data based on an array radar sensor according to claim 1, characterized in that: The specific method of obtaining the road surface state matrix collected next time is: The acquisition interval of the sth collection is obtained as follows: t s =t×p Among them, t s represents the collection interval of the sth collection; σ s-1 represents the standard deviation of the road state matrix collected for the s-1th time; t represents the initial collection interval; δ represents the preset hyperparameter; p s Indicates the flatness of the road surface collected for the sth time; The road surface state matrix of the s-th collection is obtained by using the collection interval of the s-th collection.

3. The method for collecting road surface status data based on an array radar sensor according to claim 1, characterized in that: The obtaining of the data consistency of the road surface state matrix collected each time in each direction includes: The cumulative sum of the standard deviations of all data in the u-th direction in the road surface state matrix collected for the s-th time is recorded as the data consistency of the road surface state matrix collected for the s-th time in the u-th direction.

4. The method for collecting road surface status data based on an array radar sensor according to claim 3, characterized in that: The specific method of obtaining the direction is: The four directions of the road surface state matrix collected each time are the horizontal direction, the vertical direction and two diagonal directions of the road surface state matrix.

5. The method for collecting road surface status data based on array radar sensors according to claim 2, characterized in that: The denoising is performed according to the uneven road surface matrix and the road surface state matrix to obtain the denoised road surface state data, which includes: When the flatness of the sth acquisition is greater than the road surface flatness threshold When , the road surface state matrix collected for the sth time is recorded as a flat road surface matrix; Obtain the abnormality degree of the wth data in the flat road matrix collected for the sth time; When the abnormality degree of the wth data in the flat road matrix collected for the sth time is greater than or equal to the preset data abnormality threshold, the wth data in the flat road matrix collected for the sth time is recorded as abnormal data; When the number of the wth abnormal data that is continuous with other abnormal data in the minimum direction in the flat road matrix collected for the sth time is greater than or equal to the abnormal data quantity threshold, the wth abnormal data is recorded as noise data; When the flatness of the road surface is less than or equal to the preset road surface flatness threshold, the road surface state analysis matrix collected for the sth time is recorded as an uneven road surface matrix; Normalize the accumulated sum of the absolute values ​​of the differences between the ath road surface state data in the uneven road surface matrix collected for the sth time and the remaining road surface state data except the ath road surface state data in the uneven road surface matrix collected for the sth time, and record the normalized result as the abnormality degree of the ath road surface state data in the uneven road surface matrix collected for the sth time; Normalize the accumulated sum of the absolute values ​​of the difference between the abnormality degree of the ath data in the uneven road matrix collected at the sth time and the abnormality degree of each data in the analysis sequence of the ath data in the uneven road matrix collected at the sth time, and record the normalized result as the possibility that the ath data in the uneven road matrix collected at the sth time is noise data; When the possibility that the ath data in the uneven road surface matrix collected for the sth time is noise data is greater than the noise threshold, the ath data in the uneven road surface matrix collected for the sth time is recorded as noise data.

6. The method for collecting road surface status data based on array radar sensors according to claim 5, characterized in that: The abnormality degree of the wth data in the flat road matrix collected for the sth time includes: The accumulated absolute value of the difference between the wth data in the flat road matrix collected for the sth time and the remaining data except the wth data in the flat road matrix collected for the sth time is normalized, and the normalized result is recorded as the abnormality degree of the wth data in the flat road matrix collected for the sth time.

7. The method for collecting road surface status data based on array radar sensors according to claim 5, characterized in that: The analysis sequence includes: In the corresponding co-location matrix of the s+1th acquisition, data corresponding to the same road surface position of the a-th data is obtained. When the data corresponding to the same road surface position of the a-th data can be obtained in the corresponding co-location matrix of the s+1th acquisition, data corresponding to the same road surface position of the a-th data is obtained in the corresponding co-location matrix of the s+2th acquisition, and so on, until there is a constant c such that when the data corresponding to the same road surface position of the a-th data cannot be obtained in the corresponding co-location matrix of the s+cth acquisition for the s+c-1th acquisition, all the data corresponding to the same road surface position obtained by the a-th data constitute the analysis sequence of the a-th data in the uneven road surface matrix of the s-th acquisition.

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