CN113888621B - Loading rate determining method, loading rate determining device, edge computing server and storage medium - Google Patents
Loading rate determining method, loading rate determining device, edge computing server and storage medium Download PDFInfo
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Abstract
The embodiment of the invention provides a method and a device for determining a loading rate, an edge calculation server and a storage medium, wherein the method comprises the following steps: acquiring video stream data acquired by image acquisition equipment, processing the video stream data, and determining whether a detected target vehicle enters a preset cargo area; after determining that the target vehicle enters a preset cargo area, calling electromagnetic wave equipment to detect an area in the field of view of the electromagnetic wave equipment; acquiring full-view point cloud data generated by detecting an area in the view of the electromagnetic wave equipment by the electromagnetic wave equipment, and screening target point cloud data from the full-view point cloud data, wherein the target point cloud data comprises corresponding point cloud data in a compartment of a target vehicle; and determining the vacant volume of the compartment of the target vehicle by using the target point cloud data, and determining the loading rate of the compartment of the target vehicle based on the vacant volume. Through the mutual cooperation of the image acquisition equipment and the electromagnetic wave equipment, the loading rate of a vehicle compartment can be intelligently measured.
Description
Technical Field
The embodiment of the invention relates to the technical field of computers, in particular to a method and a device for determining a loading rate, an edge computing server and a storage medium.
Background
In the field of logistics, loading rate generally refers to the actual cargo volume loaded divided by the maximum loadable volume of the truck. The loading rate can be divided into an instantaneous loading rate and a process loading rate, wherein the instantaneous loading rate refers to a truck loading rate value given when a truck arrives or leaves, and the process loading rate refers to a real-time loading rate of the truck in the process of loading and unloading goods.
The loading rate is a method for evaluating the operation efficiency in the logistics field, and can be used for reflecting the working condition of vehicle transition in logistics. Therefore, in the field of logistics, vehicles can be reasonably dispatched according to the loading rate of the truck, so that vehicle resources are fully utilized, logistics cost is reduced, and operation efficiency is improved to a certain extent.
In the related art, the loading amount of the truck is generally performed by weighing. However, only the weight of the goods loaded on the truck can be obtained by weighing, and the loading rate of the truck cannot be obtained, which means that no solution for intelligently measuring the loading rate of the truck exists in the logistics industry at present.
Disclosure of Invention
In order to solve the technical problem that no solution for intelligently measuring the loading rate of a truck exists in the logistics industry, embodiments of the present invention provide a loading rate determining method, an apparatus, an edge computing server, and a storage medium.
In a first aspect of the embodiments of the present invention, a method for determining a loading rate is first provided, where the method is applied to an edge computing server, and the method includes:
acquiring video stream data acquired by image acquisition equipment, processing the video stream data, and determining whether a detected target vehicle enters a preset cargo area;
after the target vehicle is determined to enter the preset loading area, calling electromagnetic wave equipment to detect an area in the field of view of the electromagnetic wave equipment;
acquiring full-view point cloud data generated by detecting an area in the view of the electromagnetic wave equipment by the electromagnetic wave equipment, and screening target point cloud data from the full-view point cloud data, wherein the target point cloud data comprises point cloud data corresponding to the interior of a compartment of a target vehicle;
determining the free volume of the target vehicle compartment by using the target point cloud data, and determining the loading rate of the target vehicle compartment based on the free volume.
In an optional embodiment, after determining that the target vehicle enters the preset cargo area, invoking an electromagnetic wave device to detect an area within a field of view of the electromagnetic wave device includes:
after the target vehicle is determined to stop moving after entering the preset loading area and the tail door of the target vehicle is in an open state, starting the electromagnetic wave device, and calling the electromagnetic wave device to detect the area in the field of view of the electromagnetic wave device.
In an optional embodiment, the screening target point cloud data from the full-field point cloud data comprises:
filtering the full-view point cloud data based on a preset filtering rule to obtain partial-view point cloud data;
and screening target point cloud data from the partial view point cloud data.
In an optional embodiment, the filtering the full-view point cloud data based on a preset filtering rule to obtain partial-view point cloud data includes:
acquiring a preset angle range for the electromagnetic wave equipment;
and filtering the point cloud data outside the angle range from the full-view point cloud data to obtain partial-view point cloud data.
In an optional embodiment, the screening the target point cloud data from the partial field of view point cloud data comprises:
generating a 3D (three-dimensional) scatter diagram based on the partial field point cloud data, and performing plane projection on the 3D scatter diagram to generate a 2D projection image;
processing the 2D projection image by using a preset Hough line detection algorithm to obtain an initial boundary of the compartment of the target vehicle;
alternatively, the first and second electrodes may be,
carrying out binarization processing on the 2D projection image to obtain a binary image, and processing the binary image by using a preset Hough line detection algorithm to obtain an initial boundary of the compartment of the target vehicle;
processing the initial boundary by using a preset minimum parcel rectangle algorithm to obtain the peripheral boundary of the compartment of the target vehicle;
and screening target point cloud data corresponding to the peripheral boundary from the point cloud number of the partial field of view, wherein XY coordinates of the target point cloud data are located on the peripheral boundary.
In an optional embodiment, the method further comprises:
after the target vehicle is confirmed to enter the preset goods loading area, processing the video stream data by using a license plate recognition algorithm to recognize the license plate number of the target vehicle;
acquiring vehicle information bound with the license plate number, wherein the vehicle information at least comprises the rated volume of the target vehicle;
the determining a loading rate of the target vehicle compartment based on the free volume comprises:
and acquiring the difference between the rated volume and the vacant volume, and determining the quotient of the difference between the rated volume and the vacant volume and the rated volume to obtain the loading rate of the compartment of the target vehicle.
In an alternative embodiment, the determining the free volume of the target vehicle compartment using the target point cloud data includes:
determining the vacant space of the compartment of the target vehicle by using the target point cloud data, and dividing the vacant space into N subspaces according to a preset fixed step length, wherein N is greater than 1;
traversing N subspaces, determining the capacity of each subspace, and obtaining the sum of the capacities of the subspaces to obtain the free volume of the compartment of the target vehicle;
alternatively, the first and second electrodes may be,
the determining the free volume of the target vehicle compartment using the target point cloud data includes:
acquiring a first difference value between X-axis coordinate values of any two point cloud data in the target point cloud data, and judging whether the first difference value is smaller than a preset threshold value or not;
under the condition that the first difference value is smaller than the preset threshold value, selecting L groups of horizontal boundary point cloud data located on the same horizontal line from the target point cloud data, wherein L is larger than or equal to 1;
selecting J groups of vertical boundary point cloud data on the same vertical line from the target point cloud data, wherein J is greater than or equal to 1;
selecting M point cloud data from the target point cloud data according to a preset selection rule, wherein M is greater than or equal to 1;
determining a second difference value between Y-axis coordinate values of each group of the horizontal boundary point cloud data, and determining a first average value of the second difference value;
determining a third difference value between Z-axis coordinate values between each group of the vertical boundary point cloud data, and determining a second average value of the third difference value;
determining a third average value of the X-axis coordinate values of the M point cloud data, and subtracting a preset distance threshold value from the third average value;
and obtaining the product of the first average value, the second average value and the third average value obtained after subtracting the preset distance threshold value to obtain the free volume of the compartment of the target vehicle.
In a second aspect of the embodiments of the present invention, there is provided a load factor determining apparatus, applied to an edge computing server, including:
the data processing module is used for acquiring video stream data acquired by the image acquisition equipment, processing the video stream data and determining whether a detected target vehicle enters a preset goods loading area or not;
the region detection module is used for calling the electromagnetic wave equipment to detect the region in the field of view of the electromagnetic wave equipment after the target vehicle is determined to enter the preset cargo region;
the data screening module is used for acquiring full-view point cloud data generated by the electromagnetic wave equipment detecting the area in the view of the electromagnetic wave equipment and screening target point cloud data from the full-view point cloud data, wherein the target point cloud data comprises point cloud data corresponding to the interior of a compartment of a target vehicle;
and the loading rate determining module is used for determining the vacant volume of the target vehicle compartment by utilizing the target point cloud data and determining the loading rate of the target vehicle compartment based on the vacant volume.
In a third aspect of the embodiments of the present invention, there is further provided an edge computing server, including a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete mutual communication through the communication bus;
a memory for storing a computer program;
a processor, configured to implement the method for determining a loading rate according to the first aspect when executing a program stored in a memory.
In a fourth aspect of the embodiments of the present invention, there is also provided a storage medium, in which instructions are stored, and when the storage medium runs on a computer, the storage medium causes the computer to execute the method for determining a loading rate according to the first aspect.
In a fifth aspect of embodiments of the present invention, there is also provided a computer program product containing instructions which, when run on a computer, cause the computer to perform the method for determining a loading rate as described in the first aspect above.
According to the technical scheme provided by the embodiment of the invention, video stream data acquired by image acquisition equipment is acquired, the video stream data is processed, whether a detected target vehicle enters a preset cargo area is determined, after the target vehicle enters the preset cargo area is determined, an electromagnetic wave device is called to detect an area in a visual field of the electromagnetic wave device, full-visual-field point cloud data generated when the electromagnetic wave device detects the area in the visual field of the electromagnetic wave device is acquired, target point cloud data are screened from the full-visual-field point cloud data, the target point cloud data comprise corresponding point cloud data in a compartment of the target vehicle, the spare volume of the compartment of the target vehicle is determined by using the target point cloud data, and the loading rate of the compartment of the target vehicle is determined based on the spare volume. Therefore, whether the vehicle enters the preset goods area or not is determined through video stream data acquired by the image acquisition equipment, after the vehicle enters the preset goods area, the point cloud data corresponding to the interior of the vehicle compartment are obtained by detecting through the electromagnetic wave equipment, the free volume of the vehicle compartment is determined by utilizing the point cloud data corresponding to the interior of the vehicle compartment, the loading rate of the vehicle compartment is determined based on the free volume, and the loading rate of the vehicle compartment is intelligently determined.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings without inventive labor.
FIG. 1 is a schematic diagram of a loading rate determination system according to an embodiment of the present invention;
fig. 2 is a schematic flow chart illustrating an implementation of a loading rate determining method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a microwave radar with a specified angular range according to an embodiment of the present invention;
fig. 4 is a schematic flow chart illustrating an implementation process of screening target point cloud data from partial field of view point cloud data according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a 3D scattergram shown in an embodiment of the present disclosure;
FIG. 6 is a schematic illustration of a 2D projection image shown in an embodiment of the present invention;
FIG. 7 is a schematic illustration of an initial boundary of a target vehicle compartment as shown in an embodiment of the present invention;
FIG. 8 is a schematic illustration of a peripheral boundary of a target vehicle compartment in accordance with an embodiment of the present invention;
FIG. 9 is a schematic illustration of the free volume of a target vehicle compartment illustrated in an embodiment of the present invention;
FIG. 10 is a schematic flow chart illustrating an embodiment of the present invention for determining the free volume of a target vehicle compartment;
fig. 11 is a schematic structural view of a loading rate determining apparatus according to an embodiment of the present invention;
fig. 12 is a schematic structural diagram of an edge computing server according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
As shown in fig. 1, an architecture schematic diagram of a loading rate determining system provided in an embodiment of the present invention may specifically include an edge computing server, an image capturing device (e.g., a camera), and an electromagnetic wave device (e.g., a radar), where the image capturing device may capture video stream data of a loading area in real time and send the video stream data to the edge computing server, the edge computing server identifies whether a target vehicle enters the loading area for loading, triggers the electromagnetic wave device to start a detection operation after the target vehicle enters the loading area for loading, the electromagnetic wave device may detect an area in a field of view of the electromagnetic wave device, so as to generate point cloud data corresponding to the area in the field of view of the electromagnetic wave device, and the edge computing server may process the video stream data and the point cloud data, so as to determine a loading rate of a compartment of the target vehicle, the intelligent measurement of the loading rate of the compartment of the target vehicle is realized.
Specifically, as shown in fig. 2, an implementation flow diagram of a method for determining a loading rate provided in an embodiment of the present invention is shown, where the method is applied to an edge computing server, and specifically may include the following steps:
s201, acquiring video stream data acquired by image acquisition equipment, processing the video stream data, and determining whether a detected target vehicle enters a preset cargo area.
In the embodiment of the present invention, for an image capturing device, such as a camera, video stream data corresponding to an area in a field of view of the image capturing device (that is, the camera) may be captured in real time, so that the edge computing server may obtain the video stream data captured by the image capturing device (in real time).
For the video stream data acquired by the image acquisition device and acquired by the edge calculation server, the edge calculation server may process the video stream data, so that it may be determined whether the detected target vehicle enters a preset cargo area, for example, whether the detected target vehicle enters a platform cargo area.
It should be noted that, in the embodiment of the present invention, an acquired video stream data collected by an image capturing device may be processed by using a relatively mature target detection algorithm on the market, so as to determine whether a detected target vehicle enters a preset cargo area, which is not limited in the embodiment of the present invention.
For example, as shown in fig. 1, for the edge computing server, video stream data collected by the camera may be acquired in real time and processed by using a target detection algorithm, so as to determine whether the detected target vehicle enters the dock cargo area.
In addition, it should be noted that, the image acquisition device may be, for example, a camera, or may be an image sensor, which is not limited in this embodiment of the present invention.
S202, after the target vehicle is determined to enter the preset cargo area, the electromagnetic wave equipment is called to detect the area in the field of view of the electromagnetic wave equipment.
In the embodiment of the present invention, for the edge calculation server, after it is determined that the target vehicle enters the preset cargo area, the electromagnetic wave device in the preset cargo area may be called to detect the area in the field of view of the electromagnetic wave device.
For example, in the present invention, a radar may be set in the platform cargo area in advance, and the edge calculation server may invoke the radar in the platform cargo area to detect the area in the radar field of view after determining that the target vehicle (e.g., a truck) enters the platform cargo area.
It should be noted that, for the electromagnetic wave device, for example, radar (microwave radar) may be a 3D array sensor, which can detect the target vehicle and the condition inside the compartment of the target vehicle, and the embodiment of the present invention is not limited thereto.
In order to accurately detect the interior of the compartment of the target vehicle, the edge calculation server further determines that the target vehicle is stopped and determines whether the tail door of the target vehicle is opened or not after determining that the target vehicle enters the preset loading area.
For the edge calculation server, after determining that the tail door of the target vehicle is opened, the detection of the interior of the compartment of the target vehicle can be realized, so that the electromagnetic wave device can be started, and the electromagnetic wave device can be called to detect the area in the visual field of the electromagnetic wave device, wherein the interior of the compartment of the target vehicle is positioned in the visual field of the electromagnetic wave device.
It should be noted that, in the embodiment of the present invention, a relatively mature target detection algorithm on the market may be adopted to further process the obtained video stream data collected by the image collecting device, so as to determine whether a tail door of the target vehicle is opened, which is not limited in the embodiment of the present invention.
For example, after determining that the target vehicle (e.g., a truck) enters the dock loading area, the edge calculation server may further process the acquired video stream data collected by the image capture device using a target detection algorithm, so as to determine whether a tail gate (i.e., a truck gate) of the target vehicle is open.
For the edge calculation server, after determining that the tail door (namely the cargo door) of the target vehicle is opened, the indication can detect the internal area of the compartment of the target vehicle, so that the radar can be started, and the radar in the loading area of the platform is called to detect the area in the field of view of the radar.
In addition, for the edge computing server, after the target vehicle is determined to enter the preset goods area, the license plate recognition algorithm can be used for processing the video stream data so as to recognize the license plate number of the target vehicle, so that the vehicle information bound with the license plate number can be obtained, and different vehicle information is bound with different license plate numbers.
For example, for the edge computing server, after it is determined that the target vehicle enters the dock cargo area, the license plate recognition algorithm is used to process the video stream data so as to recognize the license plate number of the target vehicle, so that the vehicle information bound with the license plate number can be obtained, where different vehicle information is bound with different license plate numbers, as shown in table 1 below.
| License plate number | Vehicle information |
| Jing A1 … … | Vehicle information 1 |
| Jing A2 … … | |
| …… | …… |
TABLE 1
It should be noted that, for the vehicle information, in the embodiment of the present invention, at least the rated volume of the target vehicle is included, and the rated volume of the target vehicle may be understood as the maximum volume of the target vehicle.
In addition, it should be noted that, for the acquisition of the vehicle information, in the embodiment of the present invention, the vehicle information may be locally acquired from the edge computing server, and certainly, the vehicle information may also be acquired from a cloud (that is, a cloud server), which is not limited in the embodiment of the present invention.
S203, acquiring full-view point cloud data generated by the electromagnetic wave equipment detecting the area in the view of the electromagnetic wave equipment, and screening target point cloud data from the full-view point cloud data, wherein the target point cloud data comprises point cloud data corresponding to the interior of a compartment of the target vehicle.
For the electromagnetic wave device, the area in the field of view of the electromagnetic wave device is detected, so that the corresponding full-field point cloud data can be generated, wherein the full field refers to the field of view of the electromagnetic wave device. Therefore, for the edge calculation server, full-view point cloud data generated by detecting the area in the field of view of the electromagnetic wave equipment by the electromagnetic wave equipment can be acquired.
For example, for a microwave radar, the area in the field of view of the microwave radar itself is detected, so that corresponding full-field point cloud data can be generated, that is, the point cloud data corresponding to the area in the field of view of the microwave radar itself, and for an edge calculation server, the full-field point cloud data generated by the microwave radar detecting the area in the field of view of the microwave radar itself can be acquired.
In addition, for the edge calculation server, after full-view point cloud data generated by the electromagnetic wave device detecting the area in the field of view of the electromagnetic wave device is acquired, target point cloud data including point cloud data corresponding to the interior of the compartment of the target vehicle may be screened from the full-view point cloud data, which means that point cloud data corresponding to the area in the compartment of the target vehicle is acquired last.
For example, for the edge calculation server, after acquiring full-view point cloud data generated by detecting an area in the field of view of the microwave radar itself by the microwave radar, target point cloud data including point cloud data corresponding to the interior of the compartment of the target vehicle may be screened from the full-view point cloud data, which means that point cloud data corresponding to the area in the interior of the compartment of the target vehicle is acquired last.
In the embodiment of the present invention, the full-view point cloud data may be specifically screened in the following manner, so as to obtain the target point cloud data: and filtering the full-view point cloud data based on a preset filtering rule to obtain partial-view point cloud data, and screening target point cloud data from the partial-view point cloud data.
The preset filtering rule, namely the filtering rule based on the angle, means that an angle range can be appointed to the electromagnetic wave equipment in advance, so that the preset angle range of the electromagnetic wave equipment is obtained in the point cloud data screening stage, point cloud data outside the angle range are filtered out from the full-view point cloud data, and the partial-view point cloud data are obtained.
For example, assuming that the detection angle of the microwave radar is 0-160 degrees, an angle range can be specified for the microwave radar in advance according to the relative position relationship between the cargo area and the detection range of the microwave radar, and assuming that 80-100 degrees are specified, as shown in fig. 3, so that in the point cloud data screening stage, the angle range preset for the microwave radar is obtained, and invalid point cloud data outside the angle range is filtered out from the full-view point cloud data, so that partial point cloud view data is obtained.
It should be noted that, the point cloud data outside the angle range is filtered from the full-view point cloud data, so as to obtain partial-view point cloud data, and the purpose is to retain the point cloud data right in front of the electromagnetic wave equipment, for example, retain the point cloud data right in front of the microwave radar, and remove the influence of the point cloud data in other angle ranges on the determination of the loading rate.
Specifically, as shown in fig. 4, an implementation flow diagram for screening target point cloud data from partial field of view point cloud data provided in the embodiment of the present invention is shown, and the method is applied to an edge computing server, and specifically may include the following steps:
s401, generating a 3D scatter diagram based on the partial field of view point cloud data, and performing plane projection on the 3D scatter diagram to generate a 2D projection image.
In the embodiment of the present invention, for partial field of view point cloud data, that is, point cloud data directly in front of an electromagnetic wave device, an edge calculation server generates a 3D scattergram based on the partial field of view point cloud data, and performs planar projection on the 3D scattergram, which means that the 3D scattergram is projected onto an (x, y) plane, to generate a 2D projection image.
For example, for partial field-of-view point cloud data, that is, point cloud data directly in front of the microwave radar, the edge calculation server generates a 3D scattergram based on the partial field-of-view point cloud data, as shown in fig. 5, and performs planar projection of the 3D scattergram, that is, projection thereof onto an (x, y) plane, to generate a 2D projection image, as shown in fig. 6.
It should be noted that, for partial view point cloud data, that is, point cloud data in front of an electromagnetic wave device, the edge calculation server may draw a 3D scattergram based on the partial view point cloud data with the support of the Axes3D library, so that the 3D scattergram may be generated, which is not limited in the embodiment of the present invention.
S402, processing the 2D projection image by using a preset Hough line detection algorithm to obtain an initial boundary of the compartment of the target vehicle.
In the embodiment of the present invention, for the 2D projection image, a preset hough line detection algorithm may be used to process the 2D projection image, and the hough line detection algorithm may find out lines in the 2D projection image, and form an initial boundary of the compartment of the target vehicle from the lines, so that the initial boundary of the compartment of the target vehicle may be obtained, as shown in fig. 7.
In order to accelerate the finding efficiency of the straight lines, the 2D projection image is subjected to binarization processing, so that a corresponding binary image can be obtained, the binary image is processed by utilizing a preset Hough line detection algorithm, straight lines in the binary image can be found by the Hough line detection algorithm, left and right boundaries of a compartment of the target vehicle are formed by the straight lines, and thus an initial boundary of the compartment of the target vehicle can be obtained.
It should be noted that, in the embodiment of the present invention, a HoughLincesP () function is used, and the HoughLincesP () function adds a P representing Probabilistic (probability) at the end on the basis of the houghlincess () function, and it can use cumulative probability hough transform (PPHT) to find out a straight line in a binary image, so that the execution efficiency is higher.
And S403, processing the initial boundary by using a preset minimum parcel rectangle algorithm to obtain the boundary around the compartment of the target vehicle.
In the embodiment of the present invention, after the initial boundary of the target vehicle compartment is obtained, the initial boundary of the target vehicle compartment may be processed by using a preset minimum parcel rectangle algorithm, and the minimum parcel rectangle algorithm may find out a minimum parcel rectangle in the initial boundary of the target vehicle compartment, so that the peripheral boundaries (i.e., upper, lower, left, and right boundaries) of the target vehicle compartment may be obtained, as shown in fig. 8.
S404, screening target point cloud data corresponding to the peripheral boundary from the partial field of view point cloud data, wherein XY coordinates of the target point cloud data are located on the peripheral boundary.
For the point cloud number of the partial view field, in the embodiment of the present invention, the edge calculation server filters the target point cloud data corresponding to the peripheral boundary of the vehicle compartment of the target vehicle from the point cloud number of the partial view field, which means that the XY coordinates of the target point cloud data are located at the peripheral boundary of the vehicle compartment of the target vehicle.
It should be noted that, for the peripheral boundary of the vehicle compartment of the target vehicle, it is located on the (x, y) plane, so as to regard the point cloud number of the partial field of view, it is only necessary to care whether the XY coordinates thereof are located on the peripheral boundary of the vehicle compartment of the target vehicle, if so, the point cloud data are the target point cloud data, otherwise, the point cloud data are the non-target point cloud data.
And S204, determining the free volume of the target vehicle compartment by using the target point cloud data, and determining the loading rate of the target vehicle compartment based on the free volume.
In the embodiment of the present invention, for the target point cloud data corresponding to the peripheral boundary of the target vehicle compartment, the edge calculation server may determine the free volume of the target vehicle compartment by using the target point cloud data corresponding to the peripheral boundary of the target vehicle compartment, and further may determine the loading rate of the target vehicle compartment based on the free volume.
For the target point cloud data corresponding to the peripheral boundary of the target vehicle compartment, the edge calculation server may integrate the depth of the box body of the target vehicle compartment in the horizontal and vertical directions according to a fixed step length based on the target point cloud data corresponding to the peripheral boundary of the target vehicle compartment, so as to obtain the free volume of the target vehicle compartment.
The volume calculation formula here, considering the surface equation, is as follows:
y＝∫(x，z)。
as known from the scatter selection rule, the integral region is:
D＝{(x，z)∣-1<x<1,0<z<2}。
the volume calculation formula is written as follows:
∫ D f(x,z)dxdz。
in consideration of the problems of computational complexity and continuity, the approximation of the volume is tried to be obtained by approximation of discrete points, and the integral area is divided into the following parts:
D i，j ＝{(x，z)∣X 【i】 <x<X 【i+1】 ，Z 【j】 <z<Z 【j+1】 }。
the volume calculation formula can be approximated as:
(x m ，z n )∈D i，j 。
in the embodiment of the present invention, the loading rate of the target vehicle compartment may be specifically determined by: after the target vehicle enters the preset goods loading area, the edge calculation server processes the video stream data by using a license plate recognition algorithm, recognizes the license plate number of the target vehicle, obtains vehicle information bound with the license plate number, obtains the difference between the rated volume and the vacant volume, determines the quotient of the difference between the rated volume and the vacant volume and the rated volume, and obtains the load factor of the compartment of the target vehicle.
For example, for the edge computing server, after it is determined that the target vehicle enters the platform cargo area, the video stream data is processed by using a license plate recognition algorithm, a license plate number of the target vehicle is recognized, the license plate number of the target vehicle is bound with vehicle information of the target vehicle, so that vehicle information bound with the license plate number can be obtained, wherein the vehicle information at least comprises a rated volume of the target vehicle, for example, 40 cubes, a difference (20 cubes) between the rated volume of the target vehicle and a vacant volume (20 cubes, for example) of the target vehicle is obtained, a difference (0.5) between the rated volume of the target vehicle and the vacant volume of the target vehicle is determined, and a loading rate (50%) of a compartment of the target vehicle is obtained.
In addition, the vehicle information may further include a cargo loading rate, so after the loading rate of the target vehicle compartment is obtained, the edge calculation server subtracts the cargo loading rate from the loading rate of the target vehicle compartment to obtain the loading rate of the current cargo. For example, the original cargo loading rate is 20%, the loading rate of the target vehicle compartment is 50%, and the edge calculation server subtracts the cargo loading rate from the loading rate of the target vehicle compartment to obtain the loading rate of the cargo of this time, i.e. 30%.
For the vehicle information including the rated volume of the target vehicle, after the loading rate of the current cargo is obtained, the edge calculation server may multiply the rated volume of the target vehicle by the loading rate of the current cargo, so as to obtain the volume of the current cargo. For example, the rated volume of the target vehicle, for example, 40 cubes, and the loading rate of the current cargo, that is, 30%, the edge calculation server multiplies the rated volume of the target vehicle by the loading rate of the current cargo, so as to obtain the volume of the current cargo, that is, 12 cubes.
It should be noted that, for information such as the free volume of the compartment of the target vehicle, the loading rate of the cargo of this time, and the volume of the cargo of this time, the information may be stored locally in the edge computing server or uploaded to the cloud, which is not limited in the embodiment of the present invention.
Furthermore, for the free volume of the target vehicle cabin, the embodiment of the present invention may also be determined by: the edge calculation server determines the vacant space of the compartment of the target vehicle by using the target point cloud data, and divides the vacant space into N subspaces according to a preset fixed step length, wherein N is greater than 1; and traversing the N subspaces, determining the capacity of each subspace, and obtaining the sum of the capacities of each subspace to obtain the free volume of the compartment of the target vehicle.
For example, the edge calculation server determines the free space of the target vehicle compartment based on the target point cloud data corresponding to the peripheral boundary of the target vehicle compartment, divides the free space into N subspaces according to a preset fixed step length, traverses the N subspaces, integrates the box depth of the target vehicle compartment in the horizontal and vertical directions, determines the capacity of each subspace, and obtains the sum of the capacities of each subspace to obtain the free volume of the target vehicle compartment, as shown in fig. 9.
For the free volume of the target vehicle cabin, as shown in fig. 10, the embodiment of the present invention may also be determined by:
s1001, acquiring a first difference value between X-axis coordinate values of any two point cloud data in the target point cloud data, and judging whether the first difference value is smaller than a preset threshold value.
In the embodiment of the invention, for the edge calculation server, a first difference value between the coordinate values of the X axis between any two point cloud data in the target point cloud data can be obtained, and the first difference value can represent whether the target point cloud data are approximately located on the same vertical plane, so that whether the first difference value is smaller than a preset threshold value can be judged.
For example, a threshold value of 0.5 is preset, and for the edge calculation server, a first difference (D) between X-axis coordinate values of any two point cloud data in the target point cloud data can be obtained 1 ) The first difference value can represent whether the target point cloud data are approximately positioned on the same vertical plane, so that whether the first difference value is smaller than a preset threshold value can be judged, namely D 1 Whether less than 0.5.
S1002, under the condition that the first difference value is smaller than the preset threshold value, selecting L groups of horizontal boundary point cloud data located on the same horizontal line from the target point cloud data, wherein L is larger than or equal to 1.
S1003, J groups of vertical boundary point cloud data located on the same vertical line are selected from the target point cloud data, wherein J is larger than or equal to 1.
S1004, selecting M point cloud data from the target point cloud data according to a preset selection rule, wherein M is greater than or equal to 1.
In the embodiment of the invention, as for a first difference value between the coordinate values of the X axis between any two point cloud data in the target point cloud data, when the first difference value is smaller than a preset threshold value, it is indicated that the target point cloud data are approximately located on the same vertical plane, the height of the goods carried by the compartment of the target vehicle is substantially consistent with the height of the box body of the compartment of the target vehicle, and the surface of the goods carried by the compartment of the target vehicle detected by the electromagnetic wave device is approximately located on the same vertical plane, at this time, the empty volume of the compartment of the target vehicle can be considered to be approximately a cube, and the length, the width and the height of the compartment of the target vehicle can be obtained, so that the empty volume of the compartment of the target vehicle can be obtained.
Based on the above idea, in the embodiment of the present invention, for the edge calculation server, L groups of horizontal boundary point cloud data located on the same horizontal line may be selected from the target point cloud data, where L is greater than or equal to 1, where each group of horizontal boundary point cloud data includes leftmost point cloud data and rightmost point cloud data, which is not limited in the embodiment of the present invention. For the selection rule of the L groups of horizontal boundary point cloud data, a denser part in the target point cloud data may be determined, and the L groups of horizontal boundary point cloud data are selected from the dense part, which is not limited in the embodiment of the present invention.
Furthermore, in the embodiment of the present invention, for the edge calculation server, J sets of vertical boundary point cloud data located on the same vertical line may be selected from the target point cloud data, where J is greater than or equal to 1, where each set of vertical boundary point cloud data includes the uppermost point cloud data and the lowermost point cloud data, which is not limited in the embodiment of the present invention. For the selection rule of J sets of vertical boundary point cloud data, a denser part in the target point cloud data may be determined, and J sets of vertical boundary point cloud data are selected from the dense part, which is not limited in the embodiment of the present invention.
In addition, in the embodiment of the present invention, for the edge computing server, M point cloud data are selected from the target point cloud data according to a preset selection rule, where M is greater than or equal to 1. For the selection rule of the M point cloud data, a denser part in the target point cloud data may be determined, and the M point cloud data may be selected from the dense part.
S1005, determining a second difference value between Y-axis coordinate values of each group of horizontal boundary point cloud data, and determining a first average value of the second difference value.
For L sets of horizontal boundary point cloud data, in the embodiment of the present invention, the edge calculation server may determine second differences between the Y-axis coordinate values of each set of horizontal boundary point cloud data, and further determine a first average value of the second differences, where the first average value may be considered as the length or width of a cube corresponding to the free volume of the compartment of the target vehicle.
S1006, determining a third difference value between Z-axis coordinate values of each group of vertical boundary point cloud data, and determining a second average value of the third difference value.
For J sets of vertical boundary point cloud data, in the embodiment of the present invention, the edge calculation server may determine third differences between the Y-axis coordinate values of each set of horizontal boundary point cloud data, and may further determine a second average value of the third differences, where the second average value may be considered as a height of a cube corresponding to the free volume of the compartment of the target vehicle.
S1007, determining a third average value of the X-axis coordinate values of the M point cloud data, and subtracting a preset distance threshold value from the third average value.
For the M point cloud data, in the embodiment of the present invention, the edge computing server may determine a third average value of the X-axis coordinate values of the M point cloud data, and subtract the preset distance threshold from the third average value, so that the third average value subtracted by the preset distance threshold may be regarded as the width or length of the cube corresponding to the empty volume of the compartment of the target vehicle.
And S1008, obtaining the product of the first average value, the second average value and the third average value after the preset distance threshold value is subtracted, and obtaining the free volume of the compartment of the target vehicle.
Thus, through the steps, the first average value, the second average value and the third average value after subtracting the preset distance threshold value can be obtained and can be considered to represent the length, the width and the height of the cube corresponding to the free volume of the compartment of the target vehicle respectively, according to the calculation formula of the relevant volume, the product of the first average value, the second average value and the third average value after subtracting the preset distance threshold value can be obtained, and the product of the first average value, the second average value and the third average value can be approximately considered to be the free volume of the compartment of the target vehicle, so that the free volume of the compartment of the target vehicle can be obtained.
According to the technical scheme provided by the embodiment of the invention, video stream data acquired by an image acquisition device is acquired, the video stream data is processed, whether a detected target vehicle enters a preset cargo area or not is determined, after the target vehicle enters the preset cargo area is determined, an electromagnetic wave device is called to detect an area in a visual field of the electromagnetic wave device, full-point cloud visual field data generated when the electromagnetic wave device detects the area in the visual field of the electromagnetic wave device is acquired, the target point cloud data is screened from the full-field point cloud data, the target point cloud data comprises corresponding point cloud data in a compartment of the target vehicle, the spare volume of the compartment of the target vehicle is determined by using the target point cloud data, and the loading rate of the compartment of the target vehicle is determined based on the spare volume.
Therefore, whether the vehicle enters the preset goods area or not is determined through video stream data acquired by the image acquisition equipment, after the vehicle enters the preset goods area, the point cloud data corresponding to the interior of the vehicle compartment are obtained by detecting through the electromagnetic wave equipment, the free volume of the vehicle compartment is determined by utilizing the point cloud data corresponding to the interior of the vehicle compartment, the loading rate of the vehicle compartment is determined based on the free volume, and the loading rate of the vehicle compartment is intelligently determined.
In the above embodiments of the present application, after the information such as the remaining volume, the loading rate, and the loading time of the target vehicle is obtained through the current calculation, the information and the target vehicle information (license plate number, etc.) are stored locally in a correlated manner, or are uploaded to the cloud server and stored in a correlated manner with the target vehicle information (license plate number, etc.).
Corresponding to the foregoing method embodiment, an embodiment of the present invention further provides a device for determining a loading rate, where as shown in fig. 11, the device is applied to an edge computing server, and may include: a data processing module 1110, a region detection module 1120, a data screening module 1130, and a loading rate determination module 1140.
The data processing module 1110 is configured to obtain video stream data acquired by an image acquisition device, process the video stream data, and determine whether a detected target vehicle enters a preset cargo area;
the region detection module 1120 is configured to invoke the electromagnetic wave device to detect a region in a field of view of the electromagnetic wave device after it is determined that the target vehicle enters the preset cargo region;
a data screening module 1130, configured to acquire full-view point cloud data generated by the electromagnetic wave device detecting an area in a view of the electromagnetic wave device, and screen target point cloud data from the full-view point cloud data, where the target point cloud data includes point cloud data corresponding to the interior of a compartment of the target vehicle;
a loading rate determination module 1140 for determining a free volume of the target vehicle car using the target point cloud data, the loading rate of the target vehicle car being determined based on the free volume.
The embodiment of the present invention further provides an edge computing server, as shown in fig. 12, which includes a processor 121, a communication interface 122, a memory 123 and a communication bus 124, where the processor 121, the communication interface 122, and the memory 123 complete mutual communication through the communication bus 124,
a memory 123 for storing a computer program;
the processor 121, when executing the program stored in the memory 123, implements the following steps:
acquiring video stream data acquired by image acquisition equipment, processing the video stream data, and determining whether a detected target vehicle enters a preset cargo area; after the target vehicle is confirmed to enter the preset cargo area, calling electromagnetic wave equipment to detect the area in the field of view of the electromagnetic wave equipment; acquiring full-view point cloud data generated by detecting an area in the view of the electromagnetic wave equipment by the electromagnetic wave equipment, and screening target point cloud data from the full-view point cloud data, wherein the target point cloud data comprises point cloud data corresponding to the interior of a compartment of the target vehicle; and determining the vacant volume of the target vehicle compartment by using the target point cloud data, and determining the loading rate of the target vehicle compartment based on the vacant volume.
The communication bus mentioned in the above edge computing server may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The communication interface is used for communication between the edge computing server and other devices.
The Memory may include a Random Access Memory (RAM), and may also include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the processor.
The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the Integrated Circuit may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, or discrete hardware components.
In yet another embodiment of the present invention, a storage medium is further provided, where instructions are stored, and when the instructions are executed on a computer, the instructions cause the computer to execute the load rate determining method in any one of the above embodiments.
In a further embodiment of the present invention, there is also provided a computer program product comprising instructions which, when run on a computer, cause the computer to perform the method of determining a loading rate as described in any of the above embodiments.
In the above embodiments, all or part of the implementation may be realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a storage medium or transmitted from one storage medium to another, for example, from one website, computer, server, or data center to another website, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The storage medium may be any available medium that can be accessed by a computer or a data storage device including one or more available media integrated servers, data centers, and the like. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on differences from other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.
Claims (9)
1. A method for determining a loading rate, applied to an edge computing server, the method comprising:
acquiring video stream data acquired by image acquisition equipment, processing the video stream data, and determining whether a detected target vehicle enters a preset cargo area;
after the target vehicle is determined to enter the preset loading area, calling electromagnetic wave equipment to detect an area in the field of view of the electromagnetic wave equipment;
acquiring full-view point cloud data generated by the electromagnetic wave equipment detecting the area in the field of view of the electromagnetic wave equipment, and screening target point cloud data from the full-view point cloud data, wherein the full-view point cloud data comprises the following steps: filtering the full-view point cloud data based on a preset filtering rule to obtain partial-view point cloud data, wherein the preset filtering rule comprises an angle-based filtering rule; screening target point cloud data from the partial field of view point cloud data; the target point cloud data comprises point cloud data corresponding to the interior of the compartment of the target vehicle;
screening target point cloud data from the partial field of view point cloud data, comprising: generating a 3D scatter diagram based on the partial field point cloud data, and performing plane projection on the 3D scatter diagram to generate a 2D projection image; carrying out binarization processing on the 2D projection image to obtain a binary image, and processing the binary image by using a preset Hough line detection algorithm to obtain an initial boundary of the compartment of the target vehicle; processing the initial boundary by using a preset minimum parcel rectangle algorithm to obtain the peripheral boundary of the compartment of the target vehicle; screening target point cloud data corresponding to the peripheral boundary from the partial view point cloud number, wherein XY coordinates of the target point cloud data are located on the peripheral boundary;
and determining the vacant volume of the target vehicle compartment by using the target point cloud data, and determining the loading rate of the target vehicle compartment based on the vacant volume.
2. The method of claim 1, wherein the invoking of the electromagnetic wave device to detect the area within the field of view of the electromagnetic wave device after determining that the target vehicle enters the predetermined cargo area comprises:
after the target vehicle is determined to stop moving after entering the preset loading area and the tail door of the target vehicle is in an open state, starting the electromagnetic wave device, and calling the electromagnetic wave device to detect the area in the field of view of the electromagnetic wave device.
3. The method of claim 1, wherein the filtering the full-view point cloud data based on a preset filtering rule to obtain partial-view point cloud data comprises:
acquiring an angle range preset for the electromagnetic wave equipment;
and filtering the point cloud data outside the angle range from the full-view point cloud data to obtain partial-view point cloud data.
4. The method of claim 1, wherein the screening of the partial field of view point cloud data for target point cloud data comprises:
generating a 3D (three-dimensional) scatter diagram based on the partial field point cloud data, and performing plane projection on the 3D scatter diagram to generate a 2D projection image;
processing the 2D projection image by using a preset Hough line detection algorithm to obtain an initial boundary of the compartment of the target vehicle;
processing the initial boundary by using a preset minimum parcel rectangle algorithm to obtain the peripheral boundary of the compartment of the target vehicle;
and screening target point cloud data corresponding to the peripheral boundary from the partial field point cloud number, wherein XY coordinates of the target point cloud data are located on the peripheral boundary.
5. The method of claim 1, further comprising:
after the target vehicle is determined to enter the preset goods loading area, processing the video stream data by using a license plate recognition algorithm to recognize the license plate number of the target vehicle;
acquiring vehicle information bound with the license plate number, wherein the vehicle information at least comprises the rated volume of the target vehicle;
the determining a loading rate of the target vehicle compartment based on the free volume comprises:
and acquiring the difference between the rated volume and the vacant volume, and determining the quotient of the difference between the rated volume and the vacant volume and the rated volume to obtain the loading rate of the compartment of the target vehicle.
6. The method of claim 1, wherein the determining the free volume of the target vehicle cabin using the target point cloud data comprises:
determining the vacant space of the compartment of the target vehicle by using the target point cloud data, and dividing the vacant space into N subspaces according to a preset fixed step length, wherein N is greater than 1;
traversing N subspaces, determining the capacity of each subspace, and obtaining the sum of the capacities of the subspaces to obtain the free volume of the compartment of the target vehicle;
alternatively, the first and second electrodes may be,
the determining the free volume of the target vehicle compartment using the target point cloud data includes:
acquiring a first difference value between X-axis coordinate values of any two point cloud data in the target point cloud data, and judging whether the first difference value is smaller than a preset threshold value or not;
under the condition that the first difference value is smaller than the preset threshold value, selecting L groups of horizontal boundary point cloud data located on the same horizontal line from the target point cloud data, wherein L is larger than or equal to 1;
selecting J groups of vertical boundary point cloud data on the same vertical line from the target point cloud data, wherein J is greater than or equal to 1;
selecting M point cloud data from the target point cloud data according to a preset selection rule, wherein M is greater than or equal to 1;
determining a second difference value between Y-axis coordinate values of each group of the horizontal boundary point cloud data, and determining a first average value of the second difference value;
determining a third difference value between Z-axis coordinate values between each group of the vertical boundary point cloud data, and determining a second average value of the third difference value;
determining a third average value of the X-axis coordinate values of the M point cloud data, and subtracting a preset distance threshold value from the third average value;
and obtaining the product of the first average value, the second average value and the third average value obtained after subtracting the preset distance threshold value to obtain the free volume of the compartment of the target vehicle.
7. A load factor determination apparatus applied to an edge calculation server, the apparatus comprising:
the data processing module is used for acquiring video stream data acquired by the image acquisition equipment, processing the video stream data and determining whether a detected target vehicle enters a preset goods loading area or not;
the region detection module is used for calling the electromagnetic wave equipment to detect the region in the field of view of the electromagnetic wave equipment after the target vehicle is determined to enter the preset cargo region;
the data screening module is used for acquiring full-view point cloud data generated by the electromagnetic wave equipment detecting the area in the field of view of the electromagnetic wave equipment and screening target point cloud data from the full-view point cloud data, and comprises: filtering the full-view point cloud data based on a preset filtering rule to obtain partial-view point cloud data, wherein the preset filtering rule comprises an angle-based filtering rule; screening target point cloud data from the partial view point cloud data; the target point cloud data comprises point cloud data corresponding to the interior of the compartment of the target vehicle;
screening target point cloud data from the partial field of view point cloud data, comprising: generating a 3D scatter diagram based on the partial field point cloud data, and performing plane projection on the 3D scatter diagram to generate a 2D projection image; carrying out binarization processing on the 2D projection image to obtain a binary image, and processing the binary image by using a preset Hough line detection algorithm to obtain an initial boundary of the compartment of the target vehicle; processing the initial boundary by using a preset minimum parcel rectangle algorithm to obtain the peripheral boundary of the compartment of the target vehicle; screening target point cloud data corresponding to the peripheral boundary from the partial field point cloud number, wherein XY coordinates of the target point cloud data are located on the peripheral boundary;
and the loading rate determining module is used for determining the vacant volume of the target vehicle compartment by utilizing the target point cloud data and determining the loading rate of the target vehicle compartment based on the vacant volume.
8. An edge computing server is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor and the communication interface are used for realizing the communication between the processor and the memory through the communication bus;
a memory for storing a computer program;
a processor for implementing the method steps of any one of claims 1 to 6 when executing a program stored on a memory.
9. A storage medium on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 6.
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