CN116266399A - Vehicle protection system and vehicle protection method - Google Patents
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Abstract
The invention provides a vehicle protection system and a vehicle protection method. The vehicle protection system comprises a road side unit and an information processing center, wherein the road side unit utilizes an example segmentation algorithm model to conduct example segmentation on image data in a monitoring area to obtain license plate information of vehicles in the monitoring area, the license plate information is sent to the information processing center, the information processing center judges whether the vehicles are special task vehicles according to the license plate information, the judging result is sent to the road side unit, and the road side unit utilizes pixel coordinate data of the vehicles judged to be the special task vehicles and laser radar point cloud coordinate data to conduct fusion processing and clustering processing according to the judging result to generate special task vehicle protection information, and broadcasts the special task vehicle protection information to the vehicles in the monitoring area.
Description
Technical Field
The invention relates to a vehicle protection system and a vehicle protection method for realizing vehicle protection based on multi-source data fusion.
Background
Various vehicle-road cooperation technologies exist in the field of vehicle-road cooperation, for example, the China telecommunication institute can realize the vehicle-road cooperation of the level L4+I4 at present.
The vehicle-road cooperation is realized by adopting advanced wireless communication, new generation internet technology and the like, vehicle-vehicle and vehicle-road dynamic real-time information interaction is carried out in an omnibearing manner, vehicle active safety control and road cooperation management are carried out on the basis of full-time empty dynamic traffic information acquisition and fusion, the effective cooperation of people and vehicle roads is fully realized, traffic safety is ensured, and traffic efficiency is improved, so that a safe, efficient and environment-friendly road traffic system is formed.
In the vehicle-road cooperative technology, vehicle protection is one of application scenarios, and is mainly used for protecting vehicles with special tasks, such as ambulances, fire engines and the like, which execute special tasks. In the existing vehicle protection, a special task vehicle calculates position and protection area information and the like from itself by, for example, calculating a distance to other vehicles in real time, communicating with other vehicles, or the like. And then, the special task vehicle sends request protection information to the road side unit, and the road side unit broadcasts the special task vehicle protection information such as the position, the type, the protection area and the like of the special task vehicle and the avoidance instruction to the monitoring area according to the request protection information when judging that the special task vehicle is a protected vehicle so as to actively avoid the vehicle in the monitoring area of the current road side unit.
However, in the conventional vehicle protection system, the vehicle itself is required to transmit the request protection information, which makes a high demand for the degree of intellectualization of the vehicle, but many old vehicles with special tasks such as ambulances and fire-fighting vehicles cannot achieve such a degree of intellectualization, and therefore, there is a problem that the vehicles cannot be protected like the vehicles with special tasks having high degree of intellectualization.
Disclosure of Invention
The present invention has been made in view of the above-described problems, and an object of the present invention is to provide a vehicle protection system and a vehicle protection method for realizing vehicle protection based on multi-source data fusion, which can sufficiently protect a vehicle with special tasks such as an old ambulance and a fire truck by improving the intelligence of a roadside unit and reducing the dependency on the intelligence of the vehicle itself.
According to one aspect of the present invention, there is provided a vehicle protection system including a roadside unit that performs an instance division on image data in a monitoring area using an instance division algorithm model, obtains license plate information of a vehicle in the monitoring area, and transmits the license plate information to an information processing center, the information processing center determines whether the vehicle is a special task vehicle based on the license plate information, and transmits a determination result to the roadside unit, and the roadside unit generates special task vehicle protection information by performing a fusion process and a clustering process on pixel coordinate data of the vehicle determined to be the special task vehicle and laser radar point cloud coordinate data based on the determination result, and broadcasts the special task vehicle protection information to the vehicles in the monitoring area.
According to another aspect of the present invention, there is provided a vehicle protection method for a vehicle protection system including a roadside unit and an information processing center, comprising: a transmitting step, wherein the road side unit uses an example segmentation algorithm model to carry out example segmentation on the image data in the monitoring area, obtains license plate information of the vehicle in the monitoring area, and transmits the license plate information to the information processing center; judging step, the information processing center judges whether the vehicle is a special task vehicle according to the license plate information and sends the judging result to the road side unit; and a broadcasting step, wherein the road side unit generates special task vehicle protection information by fusion processing and clustering processing of pixel coordinate data and laser radar point cloud coordinate data of the vehicle which is judged to be the special task vehicle according to the judging result, and broadcasts the special task vehicle protection information to vehicles in a monitoring area.
According to the invention, aiming at special task vehicles such as ambulances and fire trucks for executing special tasks, the information such as category, physical identification, position information, protection area and the like of the protected vehicles is obtained based on multi-source data fusion of camera image acquisition data, radar data and the like of the road side units, and the special task vehicles are enabled to obtain surrounding vehicle avoidance through broadcasting of the special task vehicle protection information by the road side units, so that the requirement on the intelligent degree of the protected vehicles is reduced, and the special task vehicles can be protected.
Other features of the present invention and its advantages will become apparent from the following detailed description of the preferred embodiments of the invention.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a schematic diagram showing the configuration of a vehicle protection system of the present embodiment.
Fig. 2 is a flowchart showing a vehicle protection method of the vehicle protection system of the present embodiment.
Fig. 3 is a diagram illustrating acquired images within a monitored area in accordance with an embodiment of the present invention.
Fig. 4 is a diagram showing an example segmentation result.
Fig. 5 is a diagram showing a result of recognition of license plate information of one of the vehicles in fig. 3.
Fig. 6 is a diagram showing a result of recognition of license plate information of another vehicle in fig. 3.
Detailed Description
Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. In addition, descriptions of well-known structures, functions and configurations may be omitted for clarity and conciseness in the following description.
In the drawings, functionally identical elements are sometimes denoted by the same reference numerals. Furthermore, the drawings illustrate embodiments and structural examples in accordance with the principles of the present invention, but these are only for the understanding of the present invention and are not to be construed in any way as limiting the present invention. The description of the present invention is merely a typical example, and does not limit the claims or application examples of the present invention in any way.
In the present embodiment, the present invention has been described in sufficient detail to enable those skilled in the art to practice the present invention, but it is to be understood that other embodiments may be realized, and that structural and structural changes and substitutions of various elements may be made without departing from the scope and spirit of the technical idea of the present invention. Therefore, the following description should not be construed as limiting the description.
For convenience of explanation and observation, the connection relationships of the respective constituent elements are shown in the drawings, but only those necessary for explanation, and not necessarily all connection relationships of control lines, information lines, and the like are shown in terms of products.
Fig. 1 is a schematic diagram showing the configuration of a vehicle protection system of the present embodiment. The vehicle protection system 1 of the present embodiment includes an information processing center 2 and a roadside unit 3. The information processing center 2 may be, for example, a traffic management center or the like. The roadside unit 3 includes a camera that captures an image of its own management area, a laser radar that acquires laser radar point cloud coordinate data of an object in the management area, and the like, and may include a plurality of roadside units such as the roadside units 3a and 3b … …, for example, and is simply referred to as the roadside unit 3 when it is not necessary to distinguish a specific roadside unit. Here, it is preferable to increase the degree of intelligence of the roadside unit 3, so that the demand for the degree of intelligence of the vehicle can be reduced, and the loss of calculation power to the vehicle-road cooperation server can be reduced.
In the vehicle protection system, a road side unit 3 performs example division on image data in a monitoring area by using an example division algorithm model, obtains license plate information of a vehicle in the monitoring area, and sends the license plate information to an information processing center 2. The information processing center 2 determines whether the vehicle is a special task vehicle based on the license plate information, and transmits the determination result to the roadside unit 3. The road side unit 3 generates special task vehicle protection information by fusion processing and clustering processing of pixel coordinate data and laser radar point cloud coordinate data of the vehicle which is judged to be the special task vehicle according to the judging result, and broadcasts the special task vehicle protection information to the vehicles in the monitoring area, so that the vehicles in the monitoring area actively avoid, a green channel is reserved for the special task vehicle, and the protection of the special task vehicle is realized.
Next, the protection process of the special task vehicle will be described with reference to the flowchart of fig. 2.
Fig. 2 is a flowchart showing a vehicle protection method of the vehicle protection system of the present embodiment. In the following processing, the roadside unit 3a is exemplified.
First, in step S1, the roadside unit 3a performs an example division on the image data in the monitoring area acquired by the camera using an example division algorithm model, recognizes the category of the vehicle, person, bicycle, etc. in the image data, and draws an identification contour line such as a vehicle contour line. Here, as an example of the example segmentation algorithm model, the road side unit 3a may recognize by using a MASK R-CNN algorithm model trained in advance using a COCO data set (a data set provided by microsoft and used for image recognition, which is commonly referred to as Common Objects in COntext), obtain the types of automobiles, people, bicycles, and the like in the image, corresponding pixel coordinate data, confidence (score), and the like, and draw a vehicle contour, for example.
Next, in step S2, the roadside unit 3a recognizes license plate information within the pixel coordinate range of the identification contour line using an OCR (Optical Character Recognition ) algorithm.
Next, in step S3, the roadside unit 3a transmits the identified license plate information to the information processing center 2 to verify whether or not it is a special task vehicle that performs a special task. As an example, the road side unit 3a determines whether the identified license plate information satisfies the license plate information format, converts the license plate information satisfying the license plate information format into an ASCII value, and transmits the ASCII value to the information processing center 2. In the case where the information security requirement is high, for example, the converted ASCII value may be further encrypted to generate a unique physical identifier corresponding to the ASCII value, and the unique physical identifier may be transmitted to the information processing center 2 to verify whether or not the vehicle is a special task vehicle.
Next, in step S4, the information processing center 2 determines whether the vehicle corresponding to the license plate information (or ASCII value or unique physical identifier) is a special task vehicle based on the transmitted license plate information (or ASCII value or unique physical identifier), and transmits the determination result to the roadside unit 3a. The information processing center 2 may transmit the determination result to other roadside units (for example, the roadside unit 3b and the like) around the roadside unit 3a, thereby reducing duplicate verification of the same special task vehicle, and the other roadside units such as the roadside unit 3b may directly confirm the vehicle as the special task vehicle.
Next, in step S5, the roadside unit 3a performs fusion processing using the pixel coordinate data of the vehicle determined to be the special task vehicle and the laser radar point cloud coordinate data, and performs clustering processing on the point cloud coordinate data within the pixel coordinate range, and calculates special task vehicle protection information such as world position coordinate information and protection area information of the vehicle with reference to the radar. For example, the image data in the identification contour line and the corresponding radar point cloud coordinate data are fused by utilizing the conversion relation between the pixel coordinate system and the laser radar coordinate system, the identification range of the radar point cloud coordinate data corresponding to the vehicle to be protected is reduced, the radar point cloud coordinate data corresponding to the protected vehicle is further screened out, the centroid position coordinate of the radar point cloud coordinate data is calculated, the position information of the protected vehicle can be obtained, and the special task vehicle protection information is generated.
Next, in step S6, the road side unit 3a broadcasts special task vehicle protection information such as physical identification, location information, protection area information, emergency avoidance information, and the like of the special task vehicle to the vehicles and the like in the monitoring area, so that the vehicles in the monitoring area give up a green channel for the special task vehicle, and the purpose of protecting the special task vehicle is achieved. The roadside unit 3a may transmit the special-task vehicle protection information to other nearby roadside units (for example, the roadside unit 3b and the like), so that the other roadside units broadcast the special-task vehicle protection information to vehicles and the like in the respective monitoring areas, thereby fully playing the area linkage function and reducing the calculation load of the other roadside units.
One embodiment of the vehicle protection system is described below using fig. 3 to 6.
Fig. 3 shows an image acquired by a camera of a roadside unit.
In this embodiment, the road side unit 3 reads the image data in fig. 3 by using the trained MASK R-CNN algorithm model, generates a contour frame, an identification box, an identified object category, a pixel coordinate range and a score of the identification box, and generates the result as shown in fig. 4 and [ table 1]. In [ table 1], person in the identification category, "car" indicates a car, "bus" indicates a bus, "traffic light" indicates a traffic light, "truck" indicates a truck, but each field and its meaning are not limited thereto, and each field and its meaning may be set as necessary.
TABLE 1 MASK R-CNN model calculation results
In the present embodiment, the categories of the first left ambulance and the second left ambulance in fig. 3 are "car" and "truck", respectively, the pixel coordinates of the upper left corner of the mark box are the first left (676,1484), the second left (2004,1332), and the pixel coordinates of the lower right corner are the first left (2162,3038), the second left (3295,2689), and the OCR recognition algorithm is used to recognize the car license plate information in the two pixel coordinate ranges. Fig. 5 and 6 show recognition results of license plate information, respectively, wherein fig. 5 shows OCR recognition results of a left first ambulance license plate number, and fig. 6 shows OCR recognition results of a left second ambulance license plate number. As a result of recognition of license plate information, the result shown in [ table 2] can be obtained. The road side unit 3 converts license plate information into ASCII code, encrypts it to generate a unique physical identifier corresponding to the ASCII value, and transmits it to the information processing center 2 to verify whether the two vehicles are vehicles performing a special task.
TABLE 2 information on identifiable vehicles obtained after instance segmentation
Then, the information processing center 2 transmits the verification result to the roadside unit 3. The road side unit 3 calculates special task vehicle protection information such as world position coordinate information and protection area information by fusion processing and clustering processing according to the verification result aiming at the ambulance needing protection.
As an example of the fusion process, the following fusion process may be performed on the pixel coordinate data and the laser radar point cloud coordinate data.
The image data captured by the camera is represented by (U, V), the 3-dimensional lattice cloud captured by the lidar is represented by (X, Y, Z), and in order to build a transformation matrix M, the 3-dimensional points (X, Y, Z) are mapped to the 2-dimensional points (U, V) as in equation (1).
Wherein A is a scale factor matrix, R is a rotation matrix, and t is a translation vector.
The compound is subjected to finishing to obtain the formula (2).
The above 2 equations are developed, and a matrix form written with ax=0 is extracted by linear abstraction as in the following equation (3).
According to the calibration plate plane under different postures, 12 linear equations can be obtained, 12 unknown data 12 equations are combined to solve the element values of the M matrix, and then calibration parameters can be solved, so that the mapping relation between pixel coordinate data and laser radar point cloud coordinate data is obtained.
Taking the left ambulance as an example, taking the centroid pixel coordinate in the identification box in the image as a starting point step length which is 2 pixels, taking pixel coordinate values to the periphery according to the aspect ratio of the identification box, dispersing the ambulance in the box into more than 50 points, converting the points into 3D coordinates by utilizing the mapping relation of the pixel coordinates and the laser radar coordinates, obtaining the coordinates actually collected by the laser radar according to the principle of nearby, clustering the data to obtain all point cloud coordinate data corresponding to the ambulance, calculating the radar coordinates of the centroid by utilizing the point cloud coordinate data, converting the radar coordinates into world coordinates (X, Y and Z) by utilizing a conversion formula, and converting the world coordinates into a formula (4) as follows.
As described above, the roadside unit 3 calculates special-task vehicle protection information such as world position coordinate information and protection area information by fusion processing and clustering processing, and broadcasts the special-task vehicle protection information to surrounding vehicles. Furthermore, the protection area information (the protection area range is 8 meters x3 meters, and the area centroid coordinates are the longitude and latitude corresponding to the current laser radar world position coordinate information) can be calculated according to the radar-based world position coordinate information of the vehicle, and then the road side unit 3 sends special task vehicle protection information such as the physical identification, the position information, the protection area information and the emergency avoidance information of the vehicle to other road side units within 1000 meters, so that the other road side units broadcast the special task vehicle protection information to give up a green channel for the vehicle, and the purpose of protecting the vehicle is achieved.
The vehicle protection system has low requirement on the intelligent degree of the vehicle to be protected, and can automatically implement protection measures even in the existing common ambulance or fire truck.
In addition, the license plate number of the vehicle is obtained through image recognition, and the contour range of the vehicle is obtained through instance segmentation, so that the clustering range of the 3D point cloud coordinate data can be reduced, the characteristics of the vehicle are efficiently extracted and protected, and the calculation power consumption of the vehicle-road cooperative server is reduced.
It will be appreciated by those skilled in the art that the structures described in this disclosure may be implemented as a system, apparatus, method, or computer readable medium as a computer program product. Accordingly, the present invention may be embodied in various forms, such as entirely hardware embodiments, entirely software embodiments (including firmware, resident software, micro-program code, etc.), or software and hardware embodiments such as circuits, modules or systems. Furthermore, the invention may also be embodied in any tangible media as a computer program product having computer-executable program code stored thereon.
With respect to the description of the present invention, it will be understood that each block of the flowchart illustrations and/or block diagrams, and any combination of blocks in the flowchart illustrations and/or block diagrams, can also be implemented using computer program instructions, as desired. These computer program instructions may be executed by a machine, such as a processor of a general purpose computer or special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the computer or other programmable data processing apparatus, create means for implementing the functions or acts specified in the flowchart and/or block diagram block or blocks.
Each block in the flowchart and block diagrams of the various functions and operations of embodiments of the invention shown in the figures may represent a module, segment, or portion of program code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some other embodiments, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order of the figures, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The embodiments of the present invention have been described above, and the above description is illustrative and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the various embodiments described. The terminology used herein was chosen in order to best explain the principles of the embodiments, the practical application, or the technical improvement of market technology, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (10)
1. A vehicle protection system, characterized in that,
the vehicle protection system is provided with a roadside unit and an information processing center,
the road side unit performs instance segmentation on the image data in the monitoring area by utilizing an instance segmentation algorithm model to obtain license plate information of the vehicle in the monitoring area, and sends the license plate information to the information processing center,
the information processing center judges whether the vehicle is a special task vehicle according to the license plate information and sends the judging result to the road side unit,
and the road side unit performs fusion processing and clustering processing on the pixel coordinate data of the vehicle determined to be the special task vehicle and the laser radar point cloud coordinate data according to the determination result to generate special task vehicle protection information, and broadcasts the special task vehicle protection information to vehicles in a monitoring area.
2. The vehicle protection system of claim 1, wherein,
the example segmentation algorithm model is a MASK R-CNN algorithm model,
and the road side unit draws an identification contour line of the vehicle in the monitoring area and utilizes an OCR algorithm to identify license plate information in a pixel coordinate range of the identification contour line.
3. The vehicle protection system according to claim 1 or 2, characterized in that,
the road side unit judges whether the license plate information meets the license plate information format, converts the license plate information meeting the license plate information format into an ASCII value, encrypts the ASCII value to generate a unique physical identifier corresponding to the ASCII value, and sends the unique physical identifier to the information processing center.
4. The vehicle protection system of claim 1, wherein,
the information processing center transmits the determination result to other roadside units around the roadside unit,
and the road side unit sends the special task vehicle protection information to the other road side units.
5. The vehicle protection system of claim 2, wherein,
and the road side unit performs fusion processing on the image data in the identification contour line and the corresponding radar point cloud coordinate data by utilizing the conversion relation between the pixel coordinate system and the laser radar coordinate system, reduces the identification range of the radar point cloud coordinate data corresponding to the special task vehicle, screens out the radar point cloud coordinate data corresponding to the special task vehicle, calculates the centroid position coordinates of the radar point cloud coordinate data to obtain the position information of the protection vehicle, and generates the special task vehicle protection information.
6. A vehicle protection method for a vehicle protection system provided with a roadside unit and an information processing center, comprising:
a transmitting step, wherein the road side unit uses an example segmentation algorithm model to carry out example segmentation on the image data in the monitoring area, obtains license plate information of the vehicle in the monitoring area, and transmits the license plate information to the information processing center;
judging step, the information processing center judges whether the vehicle is a special task vehicle according to the license plate information and sends the judging result to the road side unit; and
and a broadcasting step, wherein the road side unit generates special task vehicle protection information by fusion processing and clustering processing of pixel coordinate data of the vehicle determined to be the special task vehicle and laser radar point cloud coordinate data according to the determination result, and broadcasts the special task vehicle protection information to vehicles in a monitoring area.
7. The method for protecting a vehicle according to claim 6, wherein,
the example segmentation algorithm model is a MASK R-CNN algorithm model,
in the transmitting step, the road side unit draws an identification contour line of the vehicle in the monitoring area, and recognizes license plate information in a pixel coordinate range of the identification contour line by utilizing an OCR algorithm.
8. The method for protecting a vehicle according to claim 6 or 7, wherein,
in the transmitting step, the road side unit judges whether the license plate information meets a license plate information format, converts the license plate information meeting the license plate information format into an ASCII value, encrypts the ASCII value to generate a unique physical identifier corresponding to the ASCII value, and transmits the unique physical identifier to the information processing center.
9. The method for protecting a vehicle according to claim 6, wherein,
in the judging step, the information processing center transmits the judging result to other roadside units in the periphery of the roadside unit,
in the broadcasting step, the roadside unit transmits the special-task vehicle protection information to the other roadside units.
10. The method for protecting a vehicle according to claim 7, wherein,
in the broadcasting step, the road side unit performs fusion processing on the image data in the identification contour line and the corresponding radar point cloud coordinate data by utilizing the conversion relation between the pixel coordinate system and the laser radar coordinate system, reduces the identification range of the radar point cloud coordinate data corresponding to the special task vehicle, screens out the radar point cloud coordinate data corresponding to the special task vehicle, calculates the centroid position coordinate of the radar point cloud coordinate data to obtain the position information of the protection vehicle, and generates the special task vehicle protection information.
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