CN116824546A - Method, device, equipment and medium for determining rugged road surface type - Google Patents

Method, device, equipment and medium for determining rugged road surface type Download PDF

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CN116824546A
CN116824546A CN202310804555.0A CN202310804555A CN116824546A CN 116824546 A CN116824546 A CN 116824546A CN 202310804555 A CN202310804555 A CN 202310804555A CN 116824546 A CN116824546 A CN 116824546A
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road surface
point cloud
layer
transverse
rugged
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骆俊凯
李洁辰
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Shanghai Rox Intelligent Technology Co Ltd
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Shanghai Rox Intelligent Technology Co Ltd
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    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
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    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30248—Vehicle exterior or interior
    • G06T2207/30252—Vehicle exterior; Vicinity of vehicle
    • G06T2207/30256—Lane; Road marking
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Abstract

The application provides a method, a device and equipment for determining rugged road surface type and a medium, wherein the method comprises the following steps: collecting point cloud data of a road surface in a preset range in front of a vehicle through a laser radar; aiming at each layer of transverse point cloud, calculating the transverse bumpy of the pavement corresponding to each layer of transverse point cloud based on the height value of each point cloud in the layer of transverse point cloud; calculating the longitudinal roughness of the road surface according to the transverse roughness of the road surface corresponding to each layer of transverse point cloud; and determining the road surface rugged type corresponding to the road surface based on the road surface rugged degree corresponding to each layer of transverse point cloud and the road surface rugged degree in the longitudinal direction. By the aid of the determining method and the determining device, accuracy of determining the rugged road surface type is improved, and driving safety is further improved.

Description

Method, device, equipment and medium for determining rugged road surface type
Technical Field
The application relates to the technical field of data processing, in particular to a method, a device, equipment and a medium for determining a rugged road surface type.
Background
With the rapid development of society and the continuous improvement of the living standard of people, the automobile keeping amount is greatly increased, and more people select self-driving travel during travel and sightseeing travel, so that the travelling comfort level becomes one of the most concerned matters of the automobile driver at present. The level of road roughness is important for the safety and comfort of vehicles traveling on the road. The vehicle-mounted laser radar can acquire three-dimensional point cloud data around a vehicle, and one very important application is to detect road condition information in front of the vehicle so as to judge the rugged degree of a road surface in front.
In the existing method for determining the rugged degree of the road surface according to the point cloud data, a road surface reference straight line is often obtained according to the point cloud data, and the flatness is judged through the road surface reference straight line. However, since the gully regions in the road surface are randomly present and the depth of each gully region is not uniform, the determination of the bumpy degree is not accurate only by the road surface reference straight line.
Disclosure of Invention
In view of the above, the present application is directed to providing a method, a device and a medium for determining a rugged road surface type, which measure the horizontal rugged road surface corresponding to each layer of horizontal point cloud by the point cloud height of each layer of horizontal point cloud, and determine the rugged road surface type corresponding to the road surface by the horizontal rugged road surface corresponding to each layer of horizontal point cloud and the vertical rugged road surface, thereby improving the accuracy of determining the rugged road surface type and further improving the driving safety.
In a first aspect, an embodiment of the present application provides a method for determining a rugged road surface type, the method including:
collecting point cloud data of a road surface in a preset range in front of a vehicle through a laser radar; the point cloud data comprises a plurality of layers of transverse point clouds, and each layer of transverse point clouds comprises a plurality of point clouds;
aiming at each layer of transverse point cloud, calculating the transverse bumpy of the pavement corresponding to each layer of transverse point cloud based on the height value of each point cloud in the layer of transverse point cloud;
calculating the longitudinal roughness of the road surface according to the transverse roughness of the road surface corresponding to each layer of transverse point cloud;
and determining the road surface rugged type corresponding to the road surface based on the road surface rugged degree corresponding to each layer of transverse point cloud and the road surface rugged degree in the longitudinal direction.
Further, the calculating the road surface transverse bumpiness corresponding to the layer of transverse point cloud based on the height value of each point cloud in the layer of transverse point cloud includes:
determining the height value of each point cloud in the horizontal point cloud according to the coordinates of each point cloud in the horizontal point cloud in the layer in the three-dimensional coordinate system;
determining the height average value of the horizontal point clouds of the layer according to the height value of each point cloud in the horizontal point clouds of the layer;
and calculating the height variance value of the horizontal point cloud of the layer according to the height value of each point cloud in the horizontal point cloud of the layer and the height average value of the horizontal point cloud of the layer, and determining the height variance value as the horizontal bumpy degree of the road surface.
Further, calculating the longitudinal road surface roughness according to the transverse road surface roughness corresponding to each layer of transverse point cloud comprises:
calculating a longitudinal height average value by using the height average value of each layer of transverse point cloud;
and calculating a longitudinal height variance value according to the longitudinal height average value and the height average value of each layer of transverse point cloud, and determining the longitudinal height variance value as the longitudinal bumpy of the road surface.
Further, the determining the road surface rugged type corresponding to the road surface based on the road surface rugged corresponding to each layer of the transverse point cloud and the road surface rugged longitudinally comprises:
for each layer of transverse point cloud, multiplying the transverse bumpy of the road surface corresponding to the layer of transverse point cloud by the weight corresponding to the layer of transverse point cloud, and determining the bumpy dimension value corresponding to each layer of transverse point cloud;
summing the rugged dimension values corresponding to each layer of point cloud to obtain a transverse rugged dimension value;
determining the product of the road surface longitudinal bumpy and the longitudinal weight as a longitudinal bumpy dimension value;
adding the transverse bumpy dimension value and the longitudinal bumpy dimension value to obtain the total bumpy dimension of the road surface;
for each preset rugged type, judging whether the total rugged dimension of the road surface is in the rugged dimension range corresponding to the preset rugged type;
if yes, determining the preset rugged type as the rugged type of the road surface corresponding to the road surface.
In a second aspect, an embodiment of the present application further provides a determination device of a road surface roughness type, the determination device including:
the point cloud data acquisition module is used for acquiring point cloud data of a road surface in a preset range in front of the vehicle through a laser radar; the point cloud data comprises a plurality of layers of transverse point clouds, and each layer of transverse point clouds comprises a plurality of point clouds;
the transverse rugged degree determining module is used for calculating the transverse rugged degree of the road surface corresponding to each layer of transverse point cloud based on the height value of each point cloud in the layer of transverse point cloud aiming at each layer of transverse point cloud;
the longitudinal rugged degree determining module is used for calculating the longitudinal rugged degree of the road surface according to the transverse rugged degree of the road surface corresponding to each layer of transverse point cloud;
the road surface rugged type determining module is used for determining the road surface rugged type corresponding to the road surface based on the road surface rugged degree corresponding to each layer of transverse point cloud and the road surface rugged degree corresponding to the road surface.
Further, when the transverse bumpy determination module is used for calculating the transverse bumpy of the road surface corresponding to each point cloud in the layer of transverse point clouds based on the height value of each point cloud in the layer of transverse point clouds, the transverse bumpy determination module is further used for:
determining the height value of each point cloud in the horizontal point cloud according to the coordinates of each point cloud in the horizontal point cloud in the layer in the three-dimensional coordinate system;
determining the height average value of the horizontal point clouds of the layer according to the height value of each point cloud in the horizontal point clouds of the layer;
and calculating the height variance value of the horizontal point cloud of the layer according to the height value of each point cloud in the horizontal point cloud of the layer and the height average value of the horizontal point cloud of the layer, and determining the height variance value as the horizontal bumpy degree of the road surface.
Further, when the longitudinal bumpy determination module is used for calculating the longitudinal bumpy of the road surface according to the transverse bumpy of the road surface corresponding to each layer of transverse point cloud, the longitudinal bumpy determination module is further used for:
calculating a longitudinal height average value by using the height average value of each layer of transverse point cloud;
and calculating a longitudinal height variance value according to the longitudinal height average value and the height average value of each layer of transverse point cloud, and determining the longitudinal height variance value as the longitudinal bumpy of the road surface.
Further, when the road surface rugged type determining module is used for determining the road surface rugged type corresponding to the road surface based on the road surface rugged degree corresponding to each layer of transverse point cloud and the road surface rugged degree, the road surface rugged type determining module is further used for:
for each layer of transverse point cloud, multiplying the transverse bumpy of the road surface corresponding to the layer of transverse point cloud by the weight corresponding to the layer of transverse point cloud, and determining the bumpy dimension value corresponding to each layer of transverse point cloud;
summing the rugged dimension values corresponding to each layer of point cloud to obtain a transverse rugged dimension value;
determining the product of the road surface longitudinal bumpy and the longitudinal weight as a longitudinal bumpy dimension value;
adding the transverse bumpy dimension value and the longitudinal bumpy dimension value to obtain the total bumpy dimension of the road surface;
for each preset rugged type, judging whether the total rugged dimension of the road surface is in the rugged dimension range corresponding to the preset rugged type;
if yes, determining the preset rugged type as the rugged type of the road surface corresponding to the road surface.
In a third aspect, an embodiment of the present application further provides an electronic device, including: the system comprises a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, the processor and the memory communicate through the bus when the electronic device is running, and the machine-readable instructions are executed by the processor to perform the steps of the method for determining the rugged road surface type.
In a fourth aspect, embodiments of the present application also provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method of determining a road surface roughness type as described above.
The embodiment of the application provides a method, a device, equipment and a medium for determining the rugged type of a road surface, wherein the method for determining the rugged type of the road surface comprises the following steps: firstly, acquiring point cloud data of a road surface in a preset range in front of a vehicle through a laser radar; the point cloud data comprises a plurality of layers of transverse point clouds, and each layer of transverse point clouds comprises a plurality of point clouds; then, for each layer of transverse point cloud, calculating the transverse bumpy of the road surface corresponding to each layer of transverse point cloud based on the height value of each point cloud in the layer of transverse point cloud; calculating the longitudinal roughness of the road surface according to the transverse roughness of the road surface corresponding to each layer of transverse point cloud; and finally, determining the road surface rugged type corresponding to the road surface based on the road surface rugged degree corresponding to each layer of transverse point cloud and the road surface rugged degree.
According to the method for determining the rugged road surface type, the horizontal rugged road surface corresponding to each layer of the horizontal point cloud is measured through the point cloud height of each layer of the horizontal point cloud, and the rugged road surface type corresponding to the road surface is determined through the horizontal rugged road surface corresponding to each layer of the horizontal point cloud and the vertical rugged road surface, so that the accuracy of determining the rugged road surface type is improved, and the driving safety is further improved.
In order to make the above objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for determining a type of rough road surface according to an embodiment of the present application;
fig. 2 is a schematic diagram of point cloud data within a preset range according to an embodiment of the present application;
FIG. 3 is a schematic view of a device for determining a rough road surface according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. Based on the embodiments of the present application, every other embodiment obtained by a person skilled in the art without making any inventive effort falls within the scope of protection of the present application.
First, an application scenario to which the present application is applicable will be described. The application can be applied to the technical field of data processing.
With the rapid development of society and the continuous improvement of the living standard of people, the automobile keeping amount is greatly increased, and more people select self-driving travel during travel and sightseeing travel, so that the travelling comfort level becomes one of the most concerned matters of the automobile driver at present. The level of road roughness is important for the safety and comfort of vehicles traveling on the road. The vehicle-mounted laser radar can acquire three-dimensional point cloud data around a vehicle, and one very important application is to detect road condition information in front of the vehicle so as to judge the rugged degree of a road surface in front.
It has been found that in the existing method for determining the road surface roughness according to the point cloud data, a road surface reference straight line is often obtained according to the point cloud data, and the flatness is judged by the road surface reference straight line. However, since the gully regions in the road surface are randomly present and the depth of each gully region is not uniform, the determination of the bumpy degree is not accurate only by the road surface reference straight line.
Based on the above, the embodiment of the application provides a method for determining the rugged road surface type, so that the accuracy of determining the rugged road surface type is improved, and the driving safety is improved.
Referring to fig. 1, fig. 1 is a flowchart of a method for determining a rugged road surface type according to an embodiment of the present application. As shown in fig. 1, the determining method provided by the embodiment of the present application includes:
s101, acquiring point cloud data of a road surface in a preset range in front of a vehicle through a laser radar.
Here, the laser radar may be disposed at a front end of the vehicle, and perform laser scanning on a road surface in a preset range to be passed in front of the vehicle, to obtain laser radar point cloud data of the road surface. The preset range may be a scanning range of the laser radar, or a range set according to actual conditions. For example, the preset range is a range of a longitudinal range from 8 meters to 50 meters in front of the vehicle, and the lateral range is a range of a vehicle width plus 1 meter, and the present application is not particularly limited. The acquired point cloud data comprises a plurality of layers of transverse point clouds, and each layer of transverse point clouds comprises a plurality of point clouds. Here, the point cloud data of the road surface can be obtained through the multi-line laser radar, and each line can obtain a layer of transverse point cloud, wherein each layer of transverse point cloud comprises a plurality of point clouds, and the laser radar is provided with a scanning line.
For the above step S101, in a specific implementation, point cloud data of the road surface within a preset range in front of the vehicle is collected by the laser radar. Each point cloud in the point cloud data contains three-dimensional coordinate information, and may further include a detection distance, a reflection intensity, an azimuth angle, and the like.
Referring to fig. 2, fig. 2 is a schematic diagram of point cloud data within a preset range according to an embodiment of the present application. As shown in fig. 2, the point cloud data includes m+1 layers of transverse point clouds, respectively Layer0 to LayerM, and each Layer of point clouds includes X point clouds. Point cloud data of M layers of transverse point clouds acquired by the laser radar are respectively:
Layer0：P01,P02，…，P0X；
Layer1：P11,P12，…，P1X；
LayerN：PN1,PN2，…，PNX；
…
LayerM：PM1,PM2,…,PMX。
s102, aiming at each layer of transverse point cloud, calculating the transverse bumpy of the road surface corresponding to each layer of transverse point cloud based on the height value of each point cloud in the layer of transverse point cloud.
Note that the height value of the point cloud refers to a coordinate value of the point cloud in the Z-axis direction in the three-dimensional coordinate system. Here, the three-dimensional coordinate system uses the position of the laser radar as the origin of coordinates, the direction perpendicular to the ground as the Z axis, the vehicle advancing direction as the X axis, and the direction perpendicular to the vehicle advancing direction as the Y axis. The road surface transverse bumpiness refers to the bumpiness characterized by the height value of each point cloud in each layer of transverse point clouds.
For the above step S102, in implementation, for each layer of lateral point cloud in the point cloud data, the road surface lateral roughness corresponding to the layer of lateral point cloud is calculated according to the height value of each point cloud in the layer of lateral point cloud.
Specifically, for the step S102, the calculating the lateral roughness of the road surface corresponding to the lateral point cloud based on the height value of each point cloud in the lateral point cloud includes:
and 1021, determining the height value of each point cloud in the horizontal point cloud of the layer according to the coordinates of each point cloud in the horizontal point cloud of the layer in the three-dimensional coordinate system.
For the above step 1021, in implementation, first, the coordinates of each point cloud in the horizontal point cloud of the layer in the three-dimensional coordinate system are obtained, and then, according to the coordinates of each point cloud in the three-dimensional coordinate system, the height value of each point cloud in the horizontal point cloud of the layer is determined. Specifically, the coordinate value of the point cloud in the Z-axis direction in the three-dimensional coordinate system is taken as the height value of the point cloud.
Step 1022, determining a height average value of the horizontal point clouds according to the height value of each point cloud in the horizontal point clouds.
For the above step 1022, in implementation, the average height value of the transverse point cloud of the layer is determined according to the height value of each point cloud in the transverse point cloud of the layer.
Continuing with the embodiment in FIG. 2, the height value z of the point cloud of layer0 through layerM is obtained as follows:
Layer0：Z01,Z02…Z0X
Layer1：Z11,Z12…Z1X
LayerN：ZN1,ZN2…ZNX；
…
LayerM：ZM1,ZM2,…,ZMX。
specifically, for the step 1022, the average value of the height of the transverse point cloud of the layer is determined by the following formula (1):
A N ＝ (ZN1+ZN2+…+ZNX)/X (1)；
wherein A is N The average value of the heights of the N-th layer transverse point clouds is represented, X represents the number of the point clouds in the N-th layer transverse point clouds, ZN1 represents the height value of the 1 st point cloud in the N-th layer transverse point clouds, and ZNX represents the height value of the X-th point cloud in the N-th layer transverse point clouds.
Step 1023, calculating a height variance value of the horizontal point cloud of the layer according to the height value of each point cloud in the horizontal point cloud of the layer and the average value of the heights of the horizontal point clouds of the layer, and determining the height variance value as the horizontal bumpy road surface.
For the step 1023, in the implementation, after determining the height average value of the horizontal point cloud of the layer, according to the height value of each point cloud in the horizontal point cloud of the layer and the height average value of the horizontal point cloud of the layer, calculating the height variance value of the horizontal point cloud of the layer, and determining the obtained height variance value as the horizontal bumpy road surface corresponding to the horizontal point cloud of the layer. Since the variance is a measure of the degree of dispersion when the probability theory and the statistical variance measure the random variable or a set of data, the degree of dispersion of the ground height can be measured by the variance value of the height value of the point cloud in the Z-axis direction in the three-dimensional coordinate system.
Specifically, for the step 1023, the height variance value of the horizontal point cloud of the layer is calculated by the following formula (2):
wherein delta N And representing the height variance value of the N-layer transverse point cloud.
S103, calculating the longitudinal roughness of the road surface according to the transverse roughness of the road surface corresponding to each layer of transverse point cloud.
For the above step S103, in the specific implementation, after the road surface lateral roughness corresponding to each layer of the lateral point cloud is calculated in step S102, the road surface longitudinal roughness is calculated according to the road surface lateral roughness corresponding to each layer of the lateral point cloud.
Specifically, for the step S103, calculating the longitudinal road surface roughness according to the transverse road surface roughness corresponding to each layer of the transverse point cloud includes:
step 1031, calculating a longitudinal height average value by using the height average value of each layer of transverse point cloud.
For the above step 1031, in implementation, since the height average value of each layer of the transverse point cloud has already been calculated in the above step 1022, here, the vertical height average value is calculated using the height average value of each layer of the transverse point cloud.
Specifically, the longitudinal height average value is calculated by the following formula (3).
A＝(A 0 +A 1 +…+A M )/(M+1) (3)；
Wherein A represents a longitudinal height average value, A 0 Representing the height average value of the first layer transverse point cloud, A M Represents the height average of the m+1 layer transverse point cloud.
And 1032, calculating a longitudinal height variance value according to the longitudinal height average value and the height average value of each layer of transverse point cloud, and determining the longitudinal height variance value as the longitudinal bumpy of the pavement.
For the above step 1032, when it is implemented, after the longitudinal height average value is determined, the longitudinal height variance value is calculated according to the longitudinal height average value and the height average value of each layer of transverse point cloud, and the obtained longitudinal height variance value is determined as the longitudinal bumpy road surface.
Specifically, for the step 1023, the height variance value of the horizontal point cloud of the layer is calculated by the following formula (4):
wherein delta Z Representing the longitudinal height variance value.
S104, determining the road surface rugged type corresponding to the road surface based on the road surface rugged degree corresponding to each layer of transverse point cloud and the road surface rugged degree.
For the step S104, in the implementation, after the road surface longitudinal roughness corresponding to each layer of the transverse point cloud is calculated, the road surface longitudinal roughness corresponding to the road surface is determined based on the road surface transverse roughness corresponding to each layer of the transverse point cloud and the road surface longitudinal roughness. Here, according to an embodiment provided by the present application, road surface types are classified according to a variance value result of a point cloud height, and road surface irregularities may be flat road surfaces, low irregularities, medium irregularities, and high irregularities.
Specifically, for the step S104, the determining, based on the lateral roughness of the road surface corresponding to each layer of the lateral point cloud and the longitudinal roughness of the road surface, the type of the road surface corresponding to the road surface includes:
step 1041, for each layer of transverse point cloud, multiplying the transverse bumpy road surface corresponding to the layer of transverse point cloud by the weight corresponding to the layer of transverse point cloud, and determining the bumpy dimension value corresponding to each layer of transverse point cloud.
Here, since the transverse dimension includes m+1 layers of transverse point clouds, each layer of transverse point clouds has a weight of 50%/(m+1), and the longitudinal weight is 50%.
For the step 1041, in the implementation, for each layer of transverse point cloud, the transverse bumpy road surface corresponding to the layer of transverse point cloud is multiplied by the weight corresponding to the layer of transverse point cloud, so as to determine the bumpy dimension value corresponding to each layer of transverse point cloud.
Step 1042, summing the rugged dimension values corresponding to each layer of point cloud to obtain the transverse rugged dimension value.
For the step 1042, in the implementation, after determining the rugged dimension value corresponding to each layer of the transverse point cloud, summing the rugged dimension values corresponding to each layer of the point cloud to obtain the transverse rugged dimension value.
Step 1043, determining a product of the road surface longitudinal roughness and the longitudinal weight as a longitudinal roughness dimension value.
For the above step 1043, in implementation, the product of the road surface longitudinal roughness and the longitudinal weight is determined as the longitudinal roughness dimension value. Here, 50% of the road surface longitudinal roughness is the longitudinal roughness dimension value.
Step 1044, adding the transverse bumpy dimension value and the longitudinal bumpy dimension value to obtain a total bumpy dimension δ of the road surface.
For the above step 1044, in implementation, the obtained lateral bumpy dimension value is added to the obtained longitudinal bumpy dimension value to determine the total bumpy dimension of the road surface.
Step 1045, for each preset bumpy type, determining whether the total bumpy dimension of the road surface is within a range of bumpy dimensions corresponding to the preset bumpy type.
And 1046, if yes, determining the preset rugged type as the rugged type of the pavement corresponding to the pavement.
Here, the preset bumpy type may include a flat road surface, a low-level bumpy, a medium-level bumpy, and a high-level bumpy. The rugged dimension range refers to a typical variance data value range of each different road surface type obtained by carrying out data calibration on a real road surface under each preset rugged type. As an example, the rough dimension range of a flat road surface is 0 < delta less than or equal to T1, the rough dimension range of low rough road surface is T1 < delta less than or equal to T2, the rough dimension range of medium rough road surface is T2 < delta less than or equal to T3, and the rough dimension range of high rough road surface is T3 < delta.
For the steps 1045-1046 described above, in a specific implementation, for each preset bumpy type, it is determined whether the total bumpy dimension of the road surface is within the range of the bumpy dimension corresponding to the preset bumpy type. If not, the road surface rugged type corresponding to the current road surface is not considered to be the preset rugged type. If so, the above step 1046 is performed, and the preset bumpy type is determined as the corresponding bumpy type of the road surface.
The method for determining the rugged road surface comprises the steps of firstly, collecting point cloud data of the road surface in a preset range in front of a vehicle through a laser radar; the point cloud data comprises a plurality of layers of transverse point clouds, and each layer of transverse point clouds comprises a plurality of point clouds; then, for each layer of transverse point cloud, calculating the transverse bumpy of the road surface corresponding to each layer of transverse point cloud based on the height value of each point cloud in the layer of transverse point cloud; calculating the longitudinal roughness of the road surface according to the transverse roughness of the road surface corresponding to each layer of transverse point cloud; and finally, determining the road surface rugged type corresponding to the road surface based on the road surface rugged degree corresponding to each layer of transverse point cloud and the road surface rugged degree.
In a state where the road surface is uneven, the height value of the point cloud data reflected by the ground surface fluctuates relatively greatly. Therefore, the method and the device measure the transverse bumpy of the road surface corresponding to each layer of transverse point cloud through the point cloud height of each layer of transverse point cloud, and then determine the corresponding bumpy type of the road surface through the transverse bumpy of the road surface corresponding to each layer of transverse point cloud and the longitudinal bumpy of the road surface, so that the accuracy of determining the bumpy type of the road surface is improved, and the driving safety is further improved.
Referring to fig. 3, fig. 3 is a schematic structural diagram of a device for determining a rugged road surface type according to an embodiment of the present application. As shown in fig. 3, the determining apparatus 300 includes:
the point cloud data acquisition module 301 is configured to acquire point cloud data of a road surface within a preset range in front of a vehicle through a laser radar; the point cloud data comprises a plurality of layers of transverse point clouds, and each layer of transverse point clouds comprises a plurality of point clouds;
the transverse bumpy determination module 302 is configured to calculate, for each layer of transverse point cloud, a road surface transverse bumpy corresponding to the layer of transverse point cloud based on a height value of each point cloud in the layer of transverse point cloud;
a longitudinal bumpy determination module 303, configured to calculate a longitudinal bumpy of the road surface according to the transverse bumpy of the road surface corresponding to each layer of transverse point cloud;
the road surface rugged type determining module 304 is configured to determine a road surface rugged type corresponding to the road surface based on the road surface rugged degree corresponding to each layer of the transverse point cloud and the road surface longitudinal rugged degree.
Further, when the lateral bumpy determination module 302 is configured to calculate the lateral bumpy of the road surface corresponding to each of the lateral point clouds of the layer based on the height value of each of the point clouds of the lateral point clouds of the layer, the lateral bumpy determination module 302 is further configured to:
determining the height value of each point cloud in the horizontal point cloud according to the coordinates of each point cloud in the horizontal point cloud in the layer in the three-dimensional coordinate system;
determining the height average value of the horizontal point clouds of the layer according to the height value of each point cloud in the horizontal point clouds of the layer;
and calculating the height variance value of the horizontal point cloud of the layer according to the height value of each point cloud in the horizontal point cloud of the layer and the height average value of the horizontal point cloud of the layer, and determining the height variance value as the horizontal bumpy degree of the road surface.
Further, the longitudinal bumpy determination module 303 is further configured to, when configured to calculate the longitudinal bumpy of the road surface according to the lateral bumpy of the road surface corresponding to each layer of the lateral point cloud, further:
calculating a longitudinal height average value by using the height average value of each layer of transverse point cloud;
and calculating a longitudinal height variance value according to the longitudinal height average value and the height average value of each layer of transverse point cloud, and determining the longitudinal height variance value as the longitudinal bumpy of the road surface.
Further, when the road surface rugged type determining module 304 is configured to determine the road surface rugged type corresponding to the road surface based on the road surface rugged degree corresponding to each layer of the transverse point cloud and the road surface rugged degree, the road surface rugged type determining module 304 is further configured to:
for each layer of transverse point cloud, multiplying the transverse bumpy of the road surface corresponding to the layer of transverse point cloud by the weight corresponding to the layer of transverse point cloud, and determining the bumpy dimension value corresponding to each layer of transverse point cloud;
summing the rugged dimension values corresponding to each layer of point cloud to obtain a transverse rugged dimension value;
determining the product of the road surface longitudinal bumpy and the longitudinal weight as a longitudinal bumpy dimension value;
adding the transverse bumpy dimension value and the longitudinal bumpy dimension value to obtain the total bumpy dimension of the road surface;
for each preset rugged type, judging whether the total rugged dimension of the road surface is in the rugged dimension range corresponding to the preset rugged type;
if yes, determining the preset rugged type as the rugged type of the road surface corresponding to the road surface.
Referring to fig. 4, fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the application. As shown in fig. 4, the electronic device 400 includes a processor 410, a memory 420, and a bus 430.
The memory 420 stores machine-readable instructions executable by the processor 410, and when the electronic device 400 is running, the processor 410 communicates with the memory 420 through the bus 430, and when the machine-readable instructions are executed by the processor 410, the steps of the method for determining the type of road surface roughness in the method embodiment shown in fig. 1 can be executed, and the specific implementation is referred to the method embodiment and will not be described herein.
The embodiment of the present application further provides a computer readable storage medium, where a computer program is stored on the computer readable storage medium, where the computer program when executed by a processor may perform the steps of the method for determining a rough road surface type in the method embodiment shown in fig. 1, and a specific implementation manner may refer to the method embodiment and will not be described herein.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer readable storage medium executable by a processor. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
It should be noted that: like reference numerals and letters in the following figures denote like items, and thus once an item is defined in one figure, no further definition or explanation of it is required in the following figures, and furthermore, the terms "first," "second," "third," etc. are used merely to distinguish one description from another and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above examples are only specific embodiments of the present application, and are not intended to limit the scope of the present application, but it should be understood by those skilled in the art that the present application is not limited thereto, and that the present application is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application. Therefore, the protection scope of the application is subject to the protection scope of the claims.

Claims (10)

1. A method of determining a type of road surface roughness, the method comprising:
collecting point cloud data of a road surface in a preset range in front of a vehicle through a laser radar; the point cloud data comprises a plurality of layers of transverse point clouds, and each layer of transverse point clouds comprises a plurality of point clouds;
aiming at each layer of transverse point cloud, calculating the transverse bumpy of the pavement corresponding to each layer of transverse point cloud based on the height value of each point cloud in the layer of transverse point cloud;
calculating the longitudinal roughness of the road surface according to the transverse roughness of the road surface corresponding to each layer of transverse point cloud;
and determining the road surface rugged type corresponding to the road surface based on the road surface rugged degree corresponding to each layer of transverse point cloud and the road surface rugged degree in the longitudinal direction.
2. The method according to claim 1, wherein calculating the road surface lateral roughness corresponding to the layer of lateral point clouds based on the height value of each point cloud in the layer of lateral point clouds includes:
determining the height value of each point cloud in the horizontal point cloud according to the coordinates of each point cloud in the horizontal point cloud in the layer in the three-dimensional coordinate system;
determining the height average value of the horizontal point clouds of the layer according to the height value of each point cloud in the horizontal point clouds of the layer;
and calculating the height variance value of the horizontal point cloud of the layer according to the height value of each point cloud in the horizontal point cloud of the layer and the height average value of the horizontal point cloud of the layer, and determining the height variance value as the horizontal bumpy degree of the road surface.
3. The method according to claim 2, wherein calculating the road surface longitudinal roughness according to the road surface transverse roughness corresponding to each layer of the transverse point cloud comprises:
calculating a longitudinal height average value by using the height average value of each layer of transverse point cloud;
and calculating a longitudinal height variance value according to the longitudinal height average value and the height average value of each layer of transverse point cloud, and determining the longitudinal height variance value as the longitudinal bumpy of the road surface.
4. The method according to claim 1, wherein the determining the road surface roughness type corresponding to the road surface based on the road surface roughness corresponding to each layer of the transverse point cloud and the road surface longitudinal roughness comprises:
for each layer of transverse point cloud, multiplying the transverse bumpy of the road surface corresponding to the layer of transverse point cloud by the weight corresponding to the layer of transverse point cloud, and determining the bumpy dimension value corresponding to each layer of transverse point cloud;
summing the rugged dimension values corresponding to each layer of point cloud to obtain a transverse rugged dimension value;
determining the product of the road surface longitudinal bumpy and the longitudinal weight as a longitudinal bumpy dimension value;
adding the transverse bumpy dimension value and the longitudinal bumpy dimension value to obtain the total bumpy dimension of the road surface;
for each preset rugged type, judging whether the total rugged dimension of the road surface is in the rugged dimension range corresponding to the preset rugged type;
if yes, determining the preset rugged type as the rugged type of the road surface corresponding to the road surface.
5. A determination device of the type of road surface roughness, characterized in that it comprises:
the point cloud data acquisition module is used for acquiring point cloud data of a road surface in a preset range in front of the vehicle through a laser radar; the point cloud data comprises a plurality of layers of transverse point clouds, and each layer of transverse point clouds comprises a plurality of point clouds;
the transverse rugged degree determining module is used for calculating the transverse rugged degree of the road surface corresponding to each layer of transverse point cloud based on the height value of each point cloud in the layer of transverse point cloud aiming at each layer of transverse point cloud;
the longitudinal rugged degree determining module is used for calculating the longitudinal rugged degree of the road surface according to the transverse rugged degree of the road surface corresponding to each layer of transverse point cloud;
the road surface rugged type determining module is used for determining the road surface rugged type corresponding to the road surface based on the road surface rugged degree corresponding to each layer of transverse point cloud and the road surface rugged degree corresponding to the road surface.
6. The determination device of claim 5, wherein the lateral bumpy determination module, when configured to calculate a lateral bumpy of a road surface corresponding to the layer of lateral point clouds based on the height value of each point cloud in the layer of lateral point clouds, is further configured to:
determining the height value of each point cloud in the horizontal point cloud according to the coordinates of each point cloud in the horizontal point cloud in the layer in the three-dimensional coordinate system;
determining the height average value of the horizontal point clouds of the layer according to the height value of each point cloud in the horizontal point clouds of the layer;
and calculating the height variance value of the horizontal point cloud of the layer according to the height value of each point cloud in the horizontal point cloud of the layer and the height average value of the horizontal point cloud of the layer, and determining the height variance value as the horizontal bumpy degree of the road surface.
7. The determination device of claim 6, wherein the longitudinal bumpy determination module, when configured to calculate the longitudinal bumpy of the road surface from the lateral bumpy of the road surface corresponding to each layer of lateral point cloud, is further configured to:
calculating a longitudinal height average value by using the height average value of each layer of transverse point cloud;
and calculating a longitudinal height variance value according to the longitudinal height average value and the height average value of each layer of transverse point cloud, and determining the longitudinal height variance value as the longitudinal bumpy of the road surface.
8. The determination device according to claim 5, wherein the road surface rugged type determination module, when determining the road surface rugged type corresponding to the road surface based on the road surface rugged corresponding to each layer of the transverse point cloud and the road surface longitudinal rugged, is further configured to:
for each layer of transverse point cloud, multiplying the transverse bumpy of the road surface corresponding to the layer of transverse point cloud by the weight corresponding to the layer of transverse point cloud, and determining the bumpy dimension value corresponding to each layer of transverse point cloud;
summing the rugged dimension values corresponding to each layer of point cloud to obtain a transverse rugged dimension value;
determining the product of the road surface longitudinal bumpy and the longitudinal weight as a longitudinal bumpy dimension value;
adding the transverse bumpy dimension value and the longitudinal bumpy dimension value to obtain the total bumpy dimension of the road surface;
for each preset rugged type, judging whether the total rugged dimension of the road surface is in the rugged dimension range corresponding to the preset rugged type;
if yes, determining the preset rugged type as the rugged type of the road surface corresponding to the road surface.
9. An electronic device, comprising: a processor, a memory and a bus, said memory storing machine readable instructions executable by said processor, said processor and said memory communicating via said bus when the electronic device is running, said machine readable instructions being executable by said processor to perform the steps of the method of determining a road surface roughness type as claimed in any of claims 1 to 4.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when executed by a processor, performs the steps of the method of determining a road surface roughness type as claimed in any of claims 1 to 4.
CN202310804555.0A 2023-06-30 2023-06-30 Method, device, equipment and medium for determining rugged road surface type Pending CN116824546A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117670822A (en) * 2023-12-05 2024-03-08 北京路凯智行科技有限公司 Method and system for detecting bumpiness of non-hardened road surface, electronic device and storage medium

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117670822A (en) * 2023-12-05 2024-03-08 北京路凯智行科技有限公司 Method and system for detecting bumpiness of non-hardened road surface, electronic device and storage medium

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