CN115271751A - Vehicle-mounted charging abnormity identification method and device, electronic equipment and storage medium - Google Patents
Vehicle-mounted charging abnormity identification method and device, electronic equipment and storage medium Download PDFInfo
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- CN115271751A CN115271751A CN202210720691.7A CN202210720691A CN115271751A CN 115271751 A CN115271751 A CN 115271751A CN 202210720691 A CN202210720691 A CN 202210720691A CN 115271751 A CN115271751 A CN 115271751A
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- 238000004590 computer program Methods 0.000 claims description 15
- 230000003287 optical effect Effects 0.000 description 4
- 238000012986 modification Methods 0.000 description 2
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
- G06V20/54—Surveillance or monitoring of activities, e.g. for recognising suspicious objects of traffic, e.g. cars on the road, trains or boats
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/60—Type of objects
- G06V20/62—Text, e.g. of license plates, overlay texts or captions on TV images
Abstract
The invention relates to a vehicle-mounted charging abnormity identification method, a device, electronic equipment and a storage medium, comprising the following steps of: s1, acquiring road traffic big data through a road traffic management system to acquire all first vehicle driving data according to the road traffic big data; s2, acquiring the charge big data through a vehicle charge system to acquire all second vehicle running data according to the charge big data; and S3, comparing the first vehicle running data with the second vehicle running data, and extracting the vehicle with the difference in the first vehicle running data and the second vehicle running data as the abnormal charging vehicle. The method and the system can effectively identify the vehicles with abnormal charging and reduce the loss.
Description
Technical Field
The invention relates to the technical field of charging systems, in particular to a vehicle-mounted charging abnormity identification method and device, electronic equipment and a storage medium.
Background
Currently, road traffic charging is based on that a special charging system is established to acquire a vehicle driving path, so that the vehicle driving path is taken as a charging basis. However, in the actual establishment of the traffic toll collection system, due to design limitations, there is no way to completely identify various unexpected situations or device tampering by human intention, and the inevitable occurrence of the system is difficult to perceive in terms of some malicious fee evasion behaviors. Resulting in a loss of charge.
Disclosure of Invention
The invention aims to provide a vehicle-mounted charging abnormity identification method, a vehicle-mounted charging abnormity identification device, electronic equipment and a storage medium.
The technical scheme adopted by the invention for solving the technical problems is as follows: a vehicle-mounted charging abnormity identification method is constructed, and the method comprises the following steps:
s1, acquiring road traffic big data through a road traffic management system to acquire all first vehicle driving data according to the road traffic big data;
s2, acquiring charge big data through a vehicle charge system to acquire all second vehicle running data according to the charge big data;
s3, comparing the first vehicle running data with the second vehicle running data, and extracting the vehicle with the difference in the first vehicle running data and the second vehicle running data as the abnormal charging vehicle.
Preferably, in the vehicle-mounted charging abnormality identification method according to the present invention, in the step S1, the road traffic big data is acquired by the road traffic management system to acquire all the first vehicle travel data thereof according to the road traffic big data; the method comprises the following steps:
and acquiring video monitoring information of the vehicle through a video monitoring system in the road traffic management system so as to acquire first vehicle running data corresponding to the vehicle according to the video monitoring information.
Preferably, in the vehicle-mounted charging abnormality identification method according to the present invention, the acquiring the first vehicle driving data corresponding to the vehicle according to the video monitoring information includes:
and acquiring the driving path of the vehicle according to the generation time and the generation position of the video monitoring information and the road network information of the road network system so as to acquire the first vehicle driving data.
Preferably, in the vehicle-mounted charging abnormality recognition method according to the present invention, in the step S2, the charging big data is acquired by the vehicle charging system to acquire all the second vehicle travel data thereof based on the charging big data; the method comprises the following steps:
and acquiring the running track of the vehicle according to the charging big data, and taking the running track of the vehicle as second vehicle running data of the vehicle.
Preferably, in the vehicle-mounted charging abnormality recognition method according to the present invention, in the step S3, the comparing the first vehicle travel data and the second vehicle travel data includes:
acquiring corresponding vehicle information according to the first vehicle running data so as to acquire corresponding second vehicle running data according to the vehicle information;
and comparing the first vehicle running data and the second vehicle running data corresponding to the vehicle information.
Preferably, in the vehicle-mounted charging abnormality recognition method according to the present invention, in the step S3, the comparing the first vehicle travel data and the second vehicle travel data includes:
acquiring corresponding vehicle information according to the second vehicle running data so as to acquire corresponding first vehicle running data according to the vehicle information;
and comparing the second vehicle running data and the first vehicle running data corresponding to the vehicle information.
Preferably, in the vehicle-mounted charging abnormality recognition method of the present invention, the vehicle information includes a license plate.
The present invention also constructs a vehicle-mounted charging abnormality recognition apparatus including:
the first data acquisition unit is used for acquiring road traffic big data through a road traffic management system so as to acquire all first vehicle driving data according to the road traffic big data;
a second data acquisition unit for acquiring charge big data through a vehicle charge system to acquire all second vehicle running data thereof according to the charge big data; (ii) a
And the judging unit is used for comparing the first vehicle running data with the second vehicle running data and extracting the vehicle with the difference between the first vehicle running data and the second vehicle running data meeting the preset condition as the abnormal charging vehicle.
The present invention also provides a computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the vehicle charging abnormality identification method according to any one of the above.
The invention also features an electronic device including a memory and a processor;
the memory is used for storing a computer program;
the processor is used for executing the computer program to realize the vehicle charging abnormity identification method.
The invention discloses a vehicle-mounted charging abnormity identification method, a vehicle-mounted charging abnormity identification device, electronic equipment and a storage medium. The method has the following beneficial effects: the abnormal vehicle charging can be effectively identified, and the loss is reduced.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a flowchart of a vehicle charging abnormality recognition method according to an embodiment of the present invention;
fig. 2 is a logic block diagram of an embodiment of the vehicle-mounted charging abnormality recognition apparatus according to the present invention.
Detailed Description
For a more clear understanding of the technical features, objects and effects of the present invention, embodiments of the present invention will now be described in detail with reference to the accompanying drawings.
As shown in fig. 1, in a first embodiment of the vehicle-mounted charging abnormality identification method of the present invention, the method includes the following steps: s1, acquiring road traffic big data through a road traffic management system to acquire all first vehicle driving data according to the road traffic big data; specifically, the corresponding road traffic big data is obtained based on the road traffic management system which is mature at present. It is generally understood that the road traffic management system is a system mature in municipalities at the time applied to road traffic state monitoring, which is generally a mature system that has been currently constructed. Wherein the road traffic management system may be obtained in administrative level regionalization. For example, for a road traffic management system corresponding to a certain city, first vehicle travel data, which is all vehicle travel data in the road traffic management system corresponding to the city, is acquired.
And S2, acquiring the charge big data through a vehicle charge system so as to acquire all second vehicle running data according to the charge big data. Specifically, the charge amount data may be acquired based on the corresponding vehicle charge system, and all the second vehicle travel data may be acquired from the charge amount data. Vehicle toll systems it is also understood that systems are currently relatively sophisticated for charging for special road segments. Mature systems are also generally understood. Currently, the vehicle charging system may also be divided based on administrative level areas. Such as a vehicle toll system for a city. It is to be understood that it may also be a system for charging a city for a particular vehicle based on a certain road segment. For example, a certain section of high speed, a certain section of bridge.
S3, comparing the first vehicle running data with the second vehicle running data, and extracting the vehicle with the difference between the first vehicle running data and the second vehicle running data as a vehicle with abnormal charge. Specifically, the first vehicle running data and the second vehicle running data may be compared, and the vehicle with the difference between the two data may be acquired as the vehicle with abnormal charge. The difference can be understood that the driving path of the vehicle in the toll collection system is different from the traffic path obtained by fitting based on the road traffic big data. For example, in the road traffic big data, that is, the vehicle passes through a part of intersection, the driving path of the vehicle obtained by fitting based on the passing intersection is different from the toll collection path of the vehicle obtained in the toll collection system, and in this case, it can be determined that the vehicle may have a toll collection abnormality, and the vehicle toll collection needs to be confirmed.
Optionally, in the step S1, the road traffic big data is obtained by the road traffic management system, so as to obtain all the first vehicle driving data according to the road traffic big data; the method comprises the following steps: the method comprises the steps that video monitoring information of a vehicle is obtained through a video monitoring system in a road traffic management system, and first vehicle running data corresponding to the vehicle are obtained according to the video monitoring information. Specifically, the first vehicle driving data of the road traffic management system may be video monitoring information of all vehicles acquired by a video monitoring system in the current road traffic management system, and the driving path of the vehicle is fitted based on the video information of each vehicle. In this data fitting process it is also possible to obtain data information that is strongly related to the charging system. For example, the vehicle travel data is closer to the toll address.
Optionally, the obtaining of the first vehicle driving data corresponding to the vehicle according to the video monitoring information includes: and acquiring the driving path of the vehicle according to the generation time and the generation position of the video monitoring information and the road network information of the road network system so as to acquire the first vehicle driving data. Specifically, the driving path of the vehicle is fitted based on the time and the position of the generation of the video monitoring data of the vehicle, and the first vehicle driving data is obtained by obtaining the actual passing path. For example, for a certain vehicle, what intersection the vehicle has passed at a certain time point on a certain day is obtained, and the traveling path of the vehicle is obtained based on the information of each intersection, that is, the first vehicle traveling data of the vehicle is obtained correspondingly.
Optionally, in step S2, the charging big data is obtained by the vehicle charging system, so as to obtain all the second vehicle driving data thereof according to the charging big data; the method comprises the following steps: and acquiring the running track of the vehicle according to the charge big data, and taking the running track of the vehicle as second vehicle running data of the vehicle. Specifically, the charging big data records the driving data of the charging vehicle, and the data can be acquired based on the vehicle-mounted charging terminal. It can be understood that the server or the cloud platform in the vehicle charging system acquires the vehicle driving track based on the vehicle-mounted terminal corresponding to the vehicle. Wherein, in the charging big data, it only records the charging route of the vehicle.
Optionally, in the step S3, the comparing the first vehicle driving data and the second vehicle driving data includes: acquiring corresponding vehicle information according to the first vehicle running data so as to acquire corresponding second vehicle running data according to the vehicle information; and comparing the first vehicle running data and the second vehicle running data corresponding to the vehicle information. Specifically, the vehicle information may be acquired based on data in a road traffic management system, and the vehicle information may be a license plate number. And comparing the acquired corresponding second vehicle running data in the vehicle charging system on the basis of the acquired vehicle information.
Optionally, in the step S3, the comparing the first vehicle traveling data and the second vehicle traveling data includes: acquiring corresponding vehicle information according to the second vehicle running data so as to acquire corresponding first vehicle running data according to the vehicle information; and comparing the second vehicle running data and the first vehicle running data corresponding to the vehicle information. Specifically, the corresponding vehicle information may be obtained based on the charging data in the charging system, and the vehicle information may be license plate information. And based on the first vehicle obtained from the toll system
As shown in fig. 2, the vehicle-mounted charging abnormality recognition device according to the present invention includes:
a first data obtaining unit 110, configured to obtain road traffic big data through a road traffic management system, so as to obtain all first vehicle driving data according to the road traffic big data;
a second data obtaining unit 120 for obtaining charge big data through a vehicle charge system to obtain all second vehicle running data thereof according to the charge big data; (ii) a
A determination unit 130, configured to compare the first vehicle driving data and the second vehicle driving data, and extract a vehicle with a difference between the first vehicle driving data and the second vehicle driving data as a vehicle with abnormal charging.
Specifically, the corresponding road traffic big data is obtained based on the road traffic management system which is mature at present. It is generally understood that the road traffic management system is a system mature in municipalities at the time applied to road traffic state monitoring, which is generally a mature system that has been currently constructed. Wherein the road traffic management system may be obtained in administrative level regionalization. For example, for a road traffic management system corresponding to a certain city, first vehicle travel data, which is all vehicle travel data in the road traffic management system corresponding to the city, is acquired. The charge big data from which all the second vehicle travel data is acquired may be acquired based on the vehicle charge system. Vehicle toll systems it is also understood that systems are currently relatively sophisticated for charging for special road segments. Mature systems are also generally understood. Currently, the vehicle charging system may also be divided based on administrative level areas. For example a vehicle toll system for a city. It is to be understood that it may also be a system for charging a city for a particular vehicle based on a certain road segment. For example, a section of high speed, a section of bridge. The first vehicle running data and the second vehicle running data can be compared, and the vehicle with the difference between the first vehicle running data and the second vehicle running data is obtained as the vehicle with abnormal charging. The difference can be understood as that the driving path of the vehicle in the toll collection system is different from the traffic path obtained by fitting based on the road traffic big data. For example, in the road traffic big data, that is, the running path of the vehicle obtained by fitting the road traffic big data through a part of intersections is different from the toll collection path of the vehicle obtained in the toll collection system, it can be determined that the vehicle may have a toll collection abnormality and the vehicle toll collection needs to be confirmed.
In addition, an electronic device of the present invention includes a memory and a processor; the memory is used for storing a computer program; the processor is used for executing a computer program to realize the vehicle charging abnormity identification method. In particular, according to an embodiment of the present invention, the processes described above with reference to the flowcharts may be implemented as a computer software program. For example, embodiments of the invention include a computer program product comprising a computer program embodied on a computer-readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such embodiments, the computer program may be downloaded and installed by an electronic device and executed to perform the above-described functions defined in the methods of embodiments of the present invention. The electronic equipment can be a terminal such as a notebook, a desktop, a tablet computer, a smart phone and the like, and can also be a server.
In addition, a computer storage medium of the present invention has stored thereon a computer program that, when executed by a processor, implements the vehicle-mounted charging abnormality recognition method of any one of the above. In particular, it should be noted that the computer readable medium of the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device.
It is to be understood that the foregoing examples, while indicating the preferred embodiments of the invention, are given by way of illustration and description, and are not to be construed as limiting the scope of the invention; it should be noted that, for those skilled in the art, the above technical features can be freely combined, and several changes and modifications can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention; therefore, all equivalent changes and modifications made within the scope of the claims of the present invention should be covered by the claims of the present invention.
Claims (10)
1. A vehicle-mounted charging abnormity identification method is characterized by comprising the following steps:
s1, acquiring road traffic big data through a road traffic management system to acquire all first vehicle driving data according to the road traffic big data;
s2, acquiring charge big data through a vehicle charge system to acquire all second vehicle running data according to the charge big data;
s3, comparing the first vehicle running data with the second vehicle running data, and extracting the vehicle with the difference in the first vehicle running data and the second vehicle running data as the abnormal-charge vehicle.
2. The vehicle-mounted charging abnormality recognition method according to claim 1, wherein in the step S1, the road traffic big data is acquired by a road traffic management system to acquire all of the first vehicle travel data thereof according to the road traffic big data; the method comprises the following steps:
and acquiring video monitoring information of the vehicle through a video monitoring system in the road traffic management system so as to acquire first vehicle running data corresponding to the vehicle according to the video monitoring information.
3. The vehicle-mounted charging abnormity identification method according to claim 2, wherein the step of obtaining the first vehicle driving data corresponding to the vehicle according to the video monitoring information comprises the following steps:
and acquiring the driving path of the vehicle according to the generation time and the generation position of the video monitoring information and the road network information of the road network system so as to acquire the first vehicle driving data.
4. The vehicle-mounted charging abnormality recognition method according to claim 1, wherein in the step S2, the charging big data is acquired by a vehicle charging system to acquire all of second vehicle travel data thereof based on the charging big data; the method comprises the following steps:
and acquiring the running track of the vehicle according to the charge big data, and taking the running track of the vehicle as second vehicle running data of the vehicle.
5. The vehicle-mounted charging abnormality recognition method according to claim 1, wherein the comparing the first vehicle travel data and the second vehicle travel data in the step S3 includes:
acquiring corresponding vehicle information according to the first vehicle running data so as to acquire corresponding second vehicle running data according to the vehicle information;
and comparing the first vehicle running data and the second vehicle running data corresponding to the vehicle information.
6. The vehicle-mounted charging abnormality recognition method according to claim 1, wherein in the step S3, the comparing the first vehicle travel data and the second vehicle travel data includes:
acquiring corresponding vehicle information according to the second vehicle running data so as to acquire corresponding first vehicle running data according to the vehicle information;
and comparing the second vehicle running data and the first vehicle running data corresponding to the vehicle information.
7. The vehicle-mounted charging abnormality recognition method according to claim 1, wherein the vehicle information includes a license plate.
8. An on-vehicle charging abnormality recognition device characterized by comprising:
the first data acquisition unit is used for acquiring road traffic big data through a road traffic management system so as to acquire all first vehicle driving data according to the road traffic big data;
a second data acquisition unit for acquiring charge big data through a vehicle charge system to acquire all second vehicle running data thereof according to the charge big data; (ii) a
And the judging unit is used for comparing the first vehicle running data with the second vehicle running data and extracting the vehicle with the difference of the first vehicle running data and the second vehicle running data meeting the preset condition as the abnormal charging vehicle.
9. A computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the vehicle charging abnormality identification method according to any one of claims 1 to 7.
10. An electronic device comprising a memory and a processor;
the memory is used for storing a computer program;
the processor is used for executing the computer program to realize the vehicle charging abnormity identification method according to any one of claims 1-7.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210720691.7A CN115271751A (en) | 2022-06-23 | 2022-06-23 | Vehicle-mounted charging abnormity identification method and device, electronic equipment and storage medium |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202210720691.7A CN115271751A (en) | 2022-06-23 | 2022-06-23 | Vehicle-mounted charging abnormity identification method and device, electronic equipment and storage medium |
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| CN115271751A true CN115271751A (en) | 2022-11-01 |
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| CN202210720691.7A Pending CN115271751A (en) | 2022-06-23 | 2022-06-23 | Vehicle-mounted charging abnormity identification method and device, electronic equipment and storage medium |
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