CN111369801B - Vehicle identification method, device, equipment and storage medium - Google Patents
Vehicle identification method, device, equipment and storage medium Download PDFInfo
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- CN111369801B CN111369801B CN201910794628.6A CN201910794628A CN111369801B CN 111369801 B CN111369801 B CN 111369801B CN 201910794628 A CN201910794628 A CN 201910794628A CN 111369801 B CN111369801 B CN 111369801B
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Abstract
The application provides a vehicle identification method, a device, equipment and a storage medium, wherein the method comprises the following steps: acquiring a driving track of each vehicle in a plurality of vehicles, wherein the driving track comprises driving information of the vehicle on each driving point in N driving points, each driving information comprises a driving time point, vehicle information and driver information, the vehicle information belonging to each driving point on the same driving track is the same, and the driver information belonging to each driving point on the same driving track is the same; and if the driving tracks with the same vehicle information have the same M driving time points, determining that the vehicle corresponding to the driving track with the same vehicle information is a suspected fake-licensed vehicle, and determining the fake-licensed vehicle in the suspected fake-licensed vehicle according to the vehicle information and/or the driver information in the driving track of the suspected fake-licensed vehicle. The fake-licensed vehicle identification method and device can accurately identify fake-licensed vehicles and improve identification accuracy of fake-licensed vehicles.
Description
Technical Field
The present application relates to vehicle technologies, and in particular, to a vehicle identification method, apparatus, device, and storage medium.
Background
With the development and progress of society, vehicles have become essential devices in people's life and work. The user may use the vehicle for travel, or the user may use the vehicle for transportation of goods, and so on. However, an illegal person may modify a vehicle illegally to modify the vehicle into a fake-licensed vehicle, i.e., a fake-licensed vehicle, which refers to a vehicle provided with a genuine license plate obtained in an illegal manner. Thus, identification of the fake-licensed vehicle is required.
In the prior art, a face image of a driver driving a vehicle can be acquired, the face image of the driver is compared with a face image of a registered owner of the vehicle, and when the face image of the driver is determined to be inconsistent with the face image of the registered owner of the vehicle, the current vehicle can be determined to be a fake-licensed vehicle.
However, in the prior art, since there is a situation that a driver driving a current vehicle may be a user renting the vehicle, a way of comparing a face image of the driver with a face image of a registered owner of the vehicle may cause the vehicle to be misjudged as a fake-licensed vehicle; thus, the manner in which the fake-licensed vehicle is identified is not accurate.
Content of application
The embodiment of the application provides a vehicle identification method, a device, equipment and a storage medium, which are used for solving the problem of poor accuracy of the identification of the current fake-licensed vehicle.
In a first aspect, an embodiment of the present application provides a vehicle identification method, including:
acquiring a driving track of each vehicle in a plurality of vehicles, wherein the driving track comprises driving information of the vehicle on each driving point in N driving points, N is a positive integer greater than or equal to 1, each driving information comprises a driving time point, vehicle information and driver information, the vehicle information belonging to each driving point on the same driving track is the same, and the driver information belonging to each driving point on the same driving track is the same;
if the driving tracks with the same vehicle information have the same M driving time points, determining that the vehicle corresponding to the driving tracks with the same vehicle information is a suspected fake-licensed vehicle, wherein M is a positive integer which is greater than or equal to 1 and less than or equal to N;
and determining the fake-licensed vehicles in the suspected fake-licensed vehicles according to the vehicle information and/or the driver information in the driving track of the suspected fake-licensed vehicles.
In one possible embodiment, the acquiring the driving track of each of the plurality of vehicles includes:
acquiring the running time point of each vehicle at each running point, and vehicle information and driver information corresponding to the vehicle;
determining the running information of each vehicle at each running point according to the running time point of each vehicle at each running point, and the vehicle information and the driver information corresponding to the vehicle;
according to the running information with the same driver information and the same vehicle information, the running track of the vehicle with the same driver information and the same vehicle information is generated according to the time sequence of the running time points in the running information.
In one possible embodiment, the obtaining the vehicle information and the driver information of each vehicle includes:
acquiring a vehicle image and a driver image of each of the vehicles;
and carrying out vehicle identification on the vehicle image of each vehicle to obtain vehicle information of each vehicle, and carrying out face identification on the driver image of each vehicle to obtain driver information of each vehicle.
In one possible embodiment, the vehicle information includes license plate information, or the vehicle information includes license plate information and at least one of the following information: license plate color, license plate size, vehicle brand, vehicle color, vehicle model;
the driver information comprises a face recognition identification of the driver;
the travel information further includes at least one of the following information: the vehicle driving method comprises a driving point mark and a driving direction, wherein the driving time point is the time when the vehicle passes through the driving point, and the driving direction is the driving direction when the vehicle passes through the driving point.
In one possible embodiment, before acquiring the travel time point of each vehicle at each travel point, and the vehicle information and the driver information corresponding to the vehicle, the method further includes:
acquiring indication information, wherein the indication information is used for indicating a travel time range and/or a travel point range, and the indication information is preset or sent by a user;
and determining vehicles corresponding to the travel time range and/or the travel point range from a preset first database, wherein the first database comprises vehicle information, driver information and travel time points of a plurality of vehicles in different travel time ranges and/or different travel points.
In one possible embodiment, determining a fake-licensed vehicle in the suspected fake-licensed vehicles according to vehicle information and/or driver information in a driving track of the suspected fake-licensed vehicles includes:
according to a preset second database, wherein the second database comprises vehicle registration information and/or driver registration information of vehicles, when it is determined that the vehicle information in the driving track of the suspected fake-licensed vehicle is different from the vehicle registration information of the vehicle corresponding to the driving track in the second database, and/or when it is determined that the driver information in the driving track of the suspected fake-licensed vehicle is different from the driver registration information of the vehicle corresponding to the driving track in the second database, the suspected fake-licensed vehicle is determined to be a fake-licensed vehicle.
In one possible embodiment, after determining a fake-licensed vehicle of the suspected fake-licensed vehicles, the method further comprises:
and generating and displaying warning information, wherein the warning information is used for indicating the fake-licensed vehicle.
In a second aspect, an embodiment of the present application provides a vehicle identification device, including:
the vehicle information acquisition module is used for acquiring a driving track of each vehicle in a plurality of vehicles, wherein the driving track comprises driving information of the vehicle on each driving point in N driving points, N is a positive integer greater than or equal to 1, each driving information comprises a driving time point, vehicle information and driver information, the vehicle information belonging to each driving point on the same driving track is the same, and the driver information belonging to each driving point on the same driving track is the same;
the system comprises a first processing module, a second processing module and a third processing module, wherein the first processing module is used for determining that a vehicle corresponding to a driving track with the same vehicle information is a suspected fake-licensed vehicle if the driving track with the same vehicle information has the same M driving time points, and M is a positive integer which is greater than or equal to 1 and less than or equal to N;
and the second processing module is used for determining the fake-licensed vehicles in the suspected fake-licensed vehicles according to the vehicle information and/or the driver information in the driving track of the suspected fake-licensed vehicles.
In a possible implementation manner, the obtaining module is configured to:
acquiring the running time point of each vehicle at each running point, and vehicle information and driver information corresponding to the vehicle;
determining the running information of each vehicle at each running point according to the running time point of each vehicle at each running point, and the vehicle information and the driver information corresponding to the vehicle;
according to the running information with the same driver information and the same vehicle information, the running track of the vehicle with the same driver information and the same vehicle information is generated according to the time sequence of the running time points in the running information.
In a possible implementation manner, the obtaining module is configured to:
acquiring a vehicle image and a driver image of each of the vehicles;
and carrying out vehicle identification on the vehicle image of each vehicle to obtain vehicle information of each vehicle, and carrying out face identification on the driver image of each vehicle to obtain driver information of each vehicle.
In one possible embodiment, the vehicle information includes license plate information, or the vehicle information includes license plate information and at least one of the following information: license plate color, license plate size, vehicle brand, vehicle color, vehicle model;
the driver information comprises a face recognition identification of the driver;
the travel information further includes at least one of the following information: the vehicle driving method comprises a driving point mark and a driving direction, wherein the driving time point is the time when the vehicle passes through the driving point, and the driving direction is the driving direction when the vehicle passes through the driving point.
In a possible implementation manner, the obtaining module is further configured to:
acquiring indication information, wherein the indication information is used for indicating a travel time range and/or a travel point range, and the indication information is preset or sent by a user;
and determining vehicles corresponding to the travel time range and/or the travel point range from a preset first database, wherein the first database comprises vehicle information, driver information and travel time points of a plurality of vehicles in different travel time ranges and/or different travel points.
In a possible implementation, the second processing module is configured to:
according to a preset second database, wherein the second database comprises vehicle registration information and/or driver registration information of vehicles, when it is determined that the vehicle information in the driving track of the suspected fake-licensed vehicle is different from the vehicle registration information of the vehicle corresponding to the driving track in the second database, and/or when it is determined that the driver information in the driving track of the suspected fake-licensed vehicle is different from the driver registration information of the vehicle corresponding to the driving track in the second database, the suspected fake-licensed vehicle is determined to be a fake-licensed vehicle.
In a possible implementation, the apparatus further includes a generation module configured to:
and after the fake-licensed vehicles in the suspected fake-licensed vehicles are determined, generating and displaying warning information, wherein the warning information is used for indicating the fake-licensed vehicles.
In a third aspect, an embodiment of the present application provides a vehicle identification apparatus, including: at least one processor and memory;
the memory stores computer-executable instructions;
the at least one processor executes computer-executable instructions stored by the memory to cause the at least one processor to perform the vehicle identification method as described above in the first aspect and various possible implementations of the first aspect.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, where computer-executable instructions are stored, and when a processor executes the computer-executable instructions, the vehicle identification method according to the first aspect and various possible implementation manners of the first aspect is implemented.
In the vehicle identification method, the apparatus, the device, and the storage medium provided in this embodiment, by obtaining a travel track of each of a plurality of vehicles, where the travel track includes travel information of the vehicle at each of N travel points, N is a positive integer greater than or equal to 1, each of the travel information includes a travel time point, vehicle information, and driver information, the vehicle information belonging to each of the travel points on the same travel track is the same, and the driver information belonging to each of the travel points on the same travel track is the same; if the driving tracks with the same vehicle information have the same M driving time points, determining that the vehicle corresponding to the driving tracks with the same vehicle information is a suspected fake-licensed vehicle, wherein M is a positive integer which is greater than or equal to 1 and less than or equal to N; the fake-licensed vehicles in the suspected fake-licensed vehicles are determined according to the vehicle information and/or the driver information in the driving tracks of the suspected fake-licensed vehicles, the fake-licensed vehicles are determined by comparing a plurality of driving tracks with the same vehicle information and determining the fake-licensed vehicles if the same driving time points exist, and then the fake-licensed vehicles are determined from the suspected fake-licensed vehicles, so that the fake-licensed vehicles can be accurately identified, and the identification accuracy of the fake-licensed vehicles is improved.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a schematic flowchart of a vehicle identification method according to an embodiment of the present application;
FIG. 2 is a schematic flow chart diagram illustrating a vehicle identification method according to another embodiment of the present application;
FIG. 3 is a schematic flow chart diagram illustrating a vehicle identification method according to another embodiment of the present application;
FIG. 4 is a schematic flow chart illustrating a vehicle identification method according to yet another embodiment of the present application;
fig. 5 is a schematic structural diagram of a vehicle identification device according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a vehicle identification device according to another embodiment of the present application;
fig. 7 is a schematic hardware structure diagram of a vehicle identification device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
A fake-licensed vehicle refers to a vehicle to which a real license plate obtained in an illegal manner is set. The use of a fake-licensed vehicle severely impacts vehicle management and therefore requires the identification of the fake-licensed vehicle. The existing fake-licensed vehicle identification method is to obtain a face image of a driver driving a vehicle through a monitoring device, compare the face image of the driver with a face image of a registered vehicle owner of the vehicle, and determine that the current vehicle is a fake-licensed vehicle when the face image of the driver is inconsistent with the face image of the registered vehicle owner of the vehicle. However, this identification method may erroneously identify the rented vehicle as a fake-licensed vehicle, and the identification result is inaccurate.
According to the fake-licensed vehicle identification method and device, a plurality of running tracks with the same vehicle information are compared, if the same running time points exist, the fake-licensed vehicle is determined from the suspected fake-licensed vehicles, the fake-licensed vehicle can be accurately identified, and the identification accuracy of the fake-licensed vehicle is improved.
Fig. 1 is a schematic flowchart of a vehicle identification method according to an embodiment of the present application. As shown in fig. 1, the method includes:
s101, obtaining a running track of each vehicle in a plurality of vehicles, wherein the running track comprises running information of the vehicle on each running point in N running points, N is a positive integer greater than or equal to 1, each piece of running information comprises a running time point, vehicle information and driver information, the vehicle information belonging to each running point on the same running track is the same, and the driver information belonging to each running point on the same running track is the same.
In this embodiment, the manner of acquiring the driving track of the vehicle may be determined according to actual requirements, and is not limited herein. For example, a driving point of the vehicle during driving can be recorded by a positioning device mounted on the vehicle, so as to obtain a driving track of the vehicle; the driving track of the vehicle can be obtained by analyzing the driving process of the vehicle recorded by a vehicle data recorder installed on the vehicle in combination with the map information of the driving area; or a vehicle passing through the gate is recorded by a gate monitoring device installed on the road, and the driving track of the vehicle is generated by the data of the vehicle recorded by the gate monitoring device; in addition, the driving track of the vehicle may be obtained in other manners, which are not limited herein.
The travel time point is a time when the vehicle passes the travel point. The vehicle information may include, but is not limited to, at least one of license plate information, vehicle color information, vehicle model information, vehicle brand information, vehicle identification, and the like. The driver information may include, but is not limited to, at least one of a face recognition identification of the driver, credential information of the driver, and the like.
The travel track is a track formed by travel points where the vehicle information and the driver information are the same. If any one of the vehicle information and the driver information is different, a different trajectory is formed. For example, a travel point on which the driver a drives the vehicle P and a travel point on which the driver a drives the vehicle Q form two different travel trajectories, respectively. The travel point on which the driver a drives the vehicle P and the travel point on which the driver B drives the vehicle P form two different travel tracks, respectively.
S102, if the driving tracks with the same vehicle information have the same M driving time points, determining that the vehicle corresponding to the driving tracks with the same vehicle information is a suspected fake-licensed vehicle, wherein M is a positive integer which is greater than or equal to 1 and less than or equal to N.
In this embodiment, the value of M may be determined according to actual requirements, and is not limited herein. For example, M may be set to 1,2,3, etc. Every two of all the driving tracks with the same vehicle information can be compared respectively to determine whether the M driving time points are the same. The specific implementation manner for determining whether the two driving tracks have the same driving time point may be selected according to actual requirements, and is not limited herein. For example, the driving time points of the driving points recorded in the two driving tracks may be compared, and whether the two driving tracks have the same driving time point and the same number of driving time points may be determined according to a strategy that the two driving time points with an interval smaller than a certain threshold are the same driving time point; or counting the starting time point and the ending time point of each driving track to obtain a driving time period corresponding to each driving track, and if the driving time periods have mutually overlapped parts and the overlapped parts are greater than a certain threshold value, determining that the two driving tracks have M identical driving time points.
Therefore, if at least two tracks with the same M travel time points exist in a plurality of travel tracks with the same vehicle information, at least one of the travel tracks is represented by the running of the fake-licensed vehicle, and the vehicle corresponding to the travel track with the same vehicle information can be determined to be a suspected fake-licensed vehicle.
For example, M is set to 2, assuming that the travel track H and the travel track I have the same vehicle information, if the license plate numbers are the same, the travel track H has 30 travel points, the travel track I has 40 travel points, each travel point corresponds to one travel time point, the travel time points of the travel track H are respectively compared with the travel time points of the travel track I, it is obtained that 3 identical travel time points exist in the travel track H and the travel track I, since 3 is greater than M, it is determined that a fake-licensed vehicle exists in the vehicle corresponding to the travel track H and the vehicle corresponding to the travel track I, and both the vehicle corresponding to the travel track H and the vehicle corresponding to the travel track I are determined as the pseudo-fake-licensed vehicles. And then further identifying which vehicles in the suspected fake-licensed vehicles are fake-licensed vehicles and which vehicles are vehicles with real license plates.
S103, determining the fake-licensed vehicles in the suspected fake-licensed vehicles according to vehicle information and/or driver information in the driving track of the suspected fake-licensed vehicles.
In this embodiment, the vehicle registration information and/or the driver registration information of the vehicle in the database may be compared with the vehicle information and/or the driver information in the driving trajectory of the suspected fake-licensed vehicle to determine the fake-licensed vehicle; or comparing the inspection record or the maintenance record of the vehicle in the historical data with the vehicle information and/or the driver information in the driving track of the suspected fake-licensed vehicle to determine the fake-licensed vehicle; or vehicle information and/or driver information in the driving track of the suspected fake-licensed vehicle is sent to an auditor, and the auditor performs manual auditing on the vehicle to determine the fake-licensed vehicle; in addition, other implementations are possible and not limited herein.
And when the vehicle information and/or the driver information in the running track of a suspected fake-licensed vehicle does not accord with the vehicle registration information and/or the driver registration letter of the vehicle, determining that the suspected fake-licensed vehicle is the fake-licensed vehicle. For example, if the face recognition identifier in the driving track of a suspected fake-licensed vehicle is different from the face registration identifier corresponding to the license plate in the database, the suspected fake-licensed vehicle is determined to be a fake-licensed vehicle.
In the embodiment, by acquiring a driving track of each of a plurality of vehicles, the driving track includes driving information of the vehicle at each of N driving points, where N is a positive integer greater than or equal to 1, each driving information includes a driving time point, vehicle information, and driver information, the vehicle information attributed to each driving point on the same driving track is the same, and the driver information attributed to each driving point on the same driving track is the same; if the driving tracks with the same vehicle information have the same M driving time points, determining that the vehicle corresponding to the driving tracks with the same vehicle information is a suspected fake-licensed vehicle, wherein M is a positive integer which is greater than or equal to 1 and less than or equal to N; the fake-licensed vehicles in the suspected fake-licensed vehicles are determined according to the vehicle information and/or the driver information in the driving tracks of the suspected fake-licensed vehicles, the fake-licensed vehicles are determined by comparing a plurality of driving tracks with the same vehicle information and determining the suspected fake-licensed vehicles if the same driving time points exist, the fake-licensed vehicles are determined from the suspected fake-licensed vehicles, the fake-licensed vehicles can be accurately identified according to the driving tracks, and the identification accuracy of the fake-licensed vehicles is improved.
Fig. 2 is a schematic flowchart of a vehicle identification method according to another embodiment of the present application. The present embodiment describes in detail a specific implementation process of acquiring a travel track of each of a plurality of vehicles. As shown in fig. 2, the method includes:
s201, acquiring the running time point of each vehicle at each running point, and the vehicle information and the driver information corresponding to the vehicle.
In this embodiment, the driving time point of the vehicle at each driving point, and the vehicle information and the driver information corresponding to the vehicle may be acquired from a database or recorded data of a gate monitoring device installed on a road.
Alternatively, the vehicle information may include, but is not limited to, license plate information and the driver information may include, but is not limited to, a facial recognition identification of the driver. Further, the vehicle information may include license plate information and at least one of the following information: license plate color, license plate size, vehicle brand, vehicle color, vehicle model.
Optionally, the driving information includes at least one of the following information: the vehicle driving method comprises a driving point mark and a driving direction, wherein the driving time point is the time when the vehicle passes through the driving point, and the driving direction is the driving direction when the vehicle passes through the driving point. The driving point identifier may be a position coordinate of a driving point, a preset driving point number, or the like, and is not limited herein. One driving point corresponds to one driving direction. The driving direction is used for representing the driving direction of the vehicle when the vehicle passes through the driving point, so that the driving track of the vehicle is determined by combining the driving direction.
Optionally, S201 may include:
acquiring a vehicle image and a driver image of each of the vehicles;
and carrying out vehicle identification on the vehicle image of each vehicle to obtain vehicle information of each vehicle, and carrying out face identification on the driver image of each vehicle to obtain driver information of each vehicle.
In the present embodiment, the vehicle image and the driver image of the vehicle may be acquired by a mount monitoring device, a monitoring camera, or the like. The driver image is an image of a driver on the vehicle during the driving process of the vehicle. Vehicle identification can be performed on vehicle images acquired by image identification methods such as Scale-invariant feature transform (SIFT) algorithm, Speeded Up Robust Features (SURF), neural network algorithm, and the like, so as to obtain vehicle information of each vehicle, and the image identification method is not limited herein.
The face recognition algorithm such as a face recognition algorithm based on Principal Component Analysis (PCA), a face recognition algorithm based on a local feature analysis method, or a neural network algorithm may be used to perform face recognition on the driver image of each vehicle, obtain driver information of each vehicle, determine a face recognition identifier of the driver of the vehicle, and the face recognition algorithm is not limited herein.
S202, determining the running information of each vehicle at each running point according to the running time point of each vehicle at each running point, and the vehicle information and the driver information corresponding to the vehicle.
And S203, generating the running tracks of the vehicles with the same driver information and the same vehicle information according to the running information with the same driver information and the same vehicle information and the time sequence of the running time points in the running information.
In this embodiment, the driving information of the vehicle having the same driver information and the same vehicle information may be grouped into a set, and the corresponding driving track may be determined according to the driving time point, the driving point, and the driving direction in the set. For example, the running information with the same face recognition identifier and license plate number may form a set, or the running information with the same face recognition identifier, license plate number, vehicle color information, and vehicle model information may form a set, so as to obtain the corresponding running track.
In the present embodiment, for the travel information of the vehicle whose driver information is the same and whose vehicle information is the same, all the travel points are sorted by the travel time point, and then the travel locus of the vehicle is generated in the order of the travel points.
And S204, if the driving tracks with the same vehicle information have the same M driving time points, determining that the vehicle corresponding to the driving tracks with the same vehicle information is a suspected fake-licensed vehicle, wherein M is a positive integer which is greater than or equal to 1 and less than or equal to N.
In this embodiment, S204 is similar to S102 in the embodiment of fig. 1, and is not described here again.
S205, determining the fake-licensed vehicles in the suspected fake-licensed vehicles according to vehicle information and/or driver information in the driving track of the suspected fake-licensed vehicles.
In this embodiment, S205 is similar to S202 in the embodiment of fig. 2, and is not described herein again.
The method includes the steps of obtaining the running time point of each vehicle at each running point, and the vehicle information and the driver information corresponding to the vehicle, determining the running information of each vehicle at each running point, generating the running tracks of the vehicles with the same driver information and the same vehicle information according to the running information with the same driver information and the same vehicle information and the time sequence of the running time points in the running information, obtaining the running tracks of the same driver and the same vehicle, identifying the fake-licensed vehicles according to the running tracks, forming one running track by the running information with the same driver information and the same vehicle information, preventing the running tracks of different vehicles from being fused together, and improving the identification accuracy of the fake-licensed vehicles.
The following description will take a scene of identifying a taxi with a fake-licensed car as an example. The taxis are usually vehicles with the same brand, the same model and the same color, and the license plate of the existing taxi R is assumed to be a real license plate, and the license plate of the taxi S is the license plate number of the applied taxi R, that is, the taxi S is a fake-licensed car, and the license plate of the taxi R is the license plate number of the taxi S. If the taxi R and the taxi S run in the same time range, and if a running track is formed only according to the running information with the same vehicle information, the running information of the taxi R and the taxi S is fused into one running track, so that an error running track is generated, and subsequent fake-licensed vehicle identification cannot be carried out. In the embodiment, the driving information with the same vehicle information and the same driver information is formed into one driving track, so that the taxi R corresponds to one driving track, and the taxi S corresponds to the other driving track, therefore, when the driving tracks are compared in the following, the same driving time point can be found between the two vehicles, so that the two vehicles are accurately determined as suspected fake-licensed vehicles, and then the taxi R is further identified as a fake-licensed vehicle. Therefore, in the present embodiment, the accuracy of recognizing the fake-licensed vehicle can be improved by determining the travel locus of the vehicle having the same driver information and the same vehicle information from the travel information of the vehicle having the same driver information and the same vehicle information.
The following description will be further made by taking a scenario in which the owner borrows the vehicle for use by other persons. Assuming that the vehicle owner X borrows the vehicle W for the driver Y to drive, the vehicle owner X and the driver Y drive the vehicle W to run in different time periods respectively in one day. According to the embodiment, the driving information with the same driver information and the same vehicle information forms one driving track, the driving information of the vehicle W driven by the vehicle owner X forms one driving track, the driving information of the vehicle W driven by the vehicle driver Y forms another driving track, and when the driving tracks are compared subsequently, the two driving tracks do not have the same driving time point because the vehicle W is driven by only one person at the same time, so that the two driving tracks cannot be mistakenly judged as the suspected fake-licensed vehicle. Therefore, in the embodiment, the condition that the borrowed vehicle is mistakenly identified as the fake-licensed vehicle can be avoided by forming the driving track by the driving information with the same driver information and the same vehicle information and comparing different driving tracks, and the identification accuracy of the fake-licensed vehicle is improved.
Optionally, after S201, the method may further include:
and carrying out data preprocessing on the running time point of each vehicle at each running point and the vehicle information and the driver information corresponding to the vehicle so as to eliminate the vehicle information, the driver information and the running time point which do not meet the preset requirement.
In this embodiment, the preset requirement may include, but is not limited to, at least one of no missing license plate number, no missing vehicle brand information, no missing driver's face recognition mark, no missing driving direction in the driving information, and the like, and is not limited herein. The specific implementation manner of the data preprocessing corresponding to the preset requirement may be various, and is not limited herein. For example, if the preset requirement is that no license plate number is missing and no license plate number is damaged, the data preprocessing can be to search for vehicles with no license plate number or no license plate number damage and delete corresponding vehicle information; if the preset requirement is that no license plate number is missing and no face identification of the driver is missing, the data preprocessing can delete corresponding vehicle information for searching vehicles without license plate number missing or without face identification of the driver being identified. The influence of invalid data on the identification process can be prevented through data preprocessing, and the identification efficiency is improved.
Fig. 3 is a schematic flowchart of a vehicle identification method according to another embodiment of the present application. The present embodiment describes in detail the concrete implementation process of acquiring the vehicle information, the driver information, and the travel time point at each travel point of each vehicle. As shown in fig. 3, the method includes:
s301, acquiring indication information, wherein the indication information is used for indicating a travel time range and/or a travel point range.
In this embodiment, the indication information is preset, or the indication information is sent by the user. For example, preset instruction information may be acquired from a specified position, or instruction information input by a user on an input interface may be acquired. The driving time range may be indicated by the starting time point and the ending time point, or by the starting time point and a preset time period, which is not limited herein. The range of the driving points may be driving points within a certain preset area range, or driving points within a certain area range selected by a user, and is not limited herein.
When the indication information is input by the user, the data of the time range and the boundary bayonet range input by the user can be checked, whether the data meet the corresponding data format requirement is judged, if not, the user is prompted to re-input, and if so, S302 is executed.
S302, determining vehicles corresponding to the travel time range and/or the travel point range from a preset first database, wherein the first database comprises vehicle information, driver information and travel time points of a plurality of vehicles in different travel time ranges and/or different travel points.
In the present embodiment, the first database is a database for storing vehicle information, driver information, and travel time points of a plurality of vehicles over different travel time ranges and/or different travel points. For example, the driving data of the vehicle collected by the gate monitoring device may be saved in the first database. The information of the vehicle corresponding to the travel time range and/or the travel point range may be found from a preset first database.
S303, acquiring the running time point of each vehicle at each running point, and the vehicle information and the driver information corresponding to the vehicle.
In this embodiment, S303 is similar to S201 in the embodiment of fig. 2, and is not described herein again.
S304, determining the running information of each vehicle at each running point according to the running time point of each vehicle at each running point, and the vehicle information and the driver information corresponding to the vehicle.
In this embodiment, S304 is similar to S202 in the embodiment of fig. 2, and is not described herein again.
And S305, generating the running tracks of the vehicles with the same driver information and the same vehicle information according to the time sequence of the running time points in the running information according to the running information with the same driver information and the same vehicle information.
In this embodiment, S305 is similar to S203 in the embodiment of fig. 2, and is not described herein again.
S306, if the driving tracks with the same vehicle information have the same M driving time points, determining that the vehicle corresponding to the driving tracks with the same vehicle information is a suspected fake-licensed vehicle, wherein M is a positive integer which is greater than or equal to 1 and less than or equal to N.
In this embodiment, S306 is similar to S102 in the embodiment of fig. 1, and is not described here again.
S307, determining the fake-licensed vehicles in the suspected fake-licensed vehicles according to vehicle information and/or driver information in the driving track of the suspected fake-licensed vehicles.
In this embodiment, S307 is similar to S103 in the embodiment of fig. 1, and is not described here again.
The fake-licensed vehicle identification method and the fake-licensed vehicle identification device can identify fake-licensed vehicles in a specified area or specified time through the travel time range and the travel point range, and are convenient for a user to identify fake-licensed vehicles for specific vehicles according to requirements.
Fig. 4 is a schematic flowchart of a vehicle identification method according to still another embodiment of the present application. The embodiment describes in detail a specific implementation process for determining a fake-licensed vehicle in a suspected fake-licensed vehicle according to vehicle information and/or driver information in a driving track of the suspected fake-licensed vehicle. As shown in fig. 4, the method includes:
s401, a driving track of each vehicle in a plurality of vehicles is obtained, the driving track comprises driving information of the vehicle on each driving point in N driving points, N is a positive integer greater than or equal to 1, each driving information comprises a driving time point, vehicle information and driver information, the vehicle information belonging to each driving point on the same driving track is the same, and the driver information belonging to each driving point on the same driving track is the same.
In this embodiment, S401 is similar to S101 in the embodiment of fig. 1, and is not described here again.
S402, if the driving tracks with the same vehicle information have the same M driving time points, determining that the vehicle corresponding to the driving tracks with the same vehicle information is a suspected fake-licensed vehicle, wherein M is a positive integer which is greater than or equal to 1 and less than or equal to N.
In this embodiment, S402 is similar to S102 in the embodiment of fig. 1, and is not described here again.
And S403, according to a preset second database, determining that the suspected fake-licensed vehicle is the fake-licensed vehicle when the vehicle information in the driving track of the suspected fake-licensed vehicle is different from the vehicle registration information of the vehicle corresponding to the driving track in the second database and/or determining that the driver information in the driving track of the suspected fake-licensed vehicle is different from the driver registration information of the vehicle corresponding to the driving track in the second database.
In the present embodiment, the second database is a database that holds vehicle registration information and/or driver registration information of the vehicle. The vehicle registration information may include, but is not limited to, at least one of a license plate number, a license plate color, vehicle model information, vehicle brand information, vehicle color information, a vehicle device number, and the like, and the driver registration information includes, but is not limited to, face recognition information and/or identity information of an owner of the vehicle, which is not limited herein.
The fake-licensed vehicle is an illegal vehicle, and the registration information of the fake-licensed vehicle does not exist in the second database. Therefore, by comparing the vehicle information in the driving track of the suspected fake-licensed vehicle with the corresponding vehicle registration information in the second database, and/or by comparing the driver information in the driving track of the suspected fake-licensed vehicle with the corresponding driver registration information in the second database, the driving track of the fake-licensed vehicle can be determined from the driving track of the suspected fake-licensed vehicle, and the fake-licensed vehicle can be determined.
For example, assuming that a suspected fake-licensed vehicle has two driving tracks, namely a driving track H and a driving track I, respectively, the driver information of the driving track H is a first face identification, and the driver information of the driving track I is a second face identification, the driver registration information of the license plate number corresponding to the suspected fake-licensed vehicle can be searched in the second database, and if the driver registration information in the second database is found to be the first face identification, the vehicle corresponding to the driving track H is a vehicle with a real license plate, and the vehicle corresponding to the driving track I is a fake-licensed vehicle. If the found driver registration information in the second database is the second face identification mark, the vehicle corresponding to the driving track I is a vehicle with a real license plate, and the vehicle corresponding to the driving track H is a fake-license vehicle. The process of identifying the fake-licensed vehicle through the vehicle registration information in the second database is similar to the above process, and is not described herein again.
According to the method and the device, the driving track corresponding to the fake-licensed vehicle can be determined from the driving tracks corresponding to the suspected fake-licensed vehicles according to the vehicle registration information and/or the driver registration information of the vehicles in the second database, and then the fake-licensed vehicle can be accurately identified.
Optionally, after S403, the method may further include:
and generating and displaying warning information, wherein the warning information is used for indicating the fake-licensed vehicle.
In this embodiment, after the fake-licensed vehicle is identified, warning information may be generated and displayed, where the warning information may include, but is not limited to, at least one of a number plate number of the fake-licensed vehicle, a running track of the fake-licensed vehicle, vehicle color information of the fake-licensed vehicle, vehicle model information, vehicle brand information, a driver's face recognition identifier, and the like. The warning information can be used for indicating the fake-licensed vehicle so that related personnel or equipment can identify, arrange, capture and the like the fake-licensed vehicle.
Fig. 5 is a schematic structural diagram of a vehicle identification device according to an embodiment of the present application. As shown in fig. 5, the vehicle recognition device 50 includes: an acquisition module 501, a first processing module 502 and a second processing module 503.
The method includes obtaining a driving track of each vehicle in a plurality of vehicles, where the driving track includes driving information of the vehicle at each of N driving points, where N is a positive integer greater than or equal to 1, each driving information includes a driving time point, vehicle information, and driver information, and the vehicle information belonging to each driving point on the same driving track is the same, and the driver information belonging to each driving point on the same driving track is the same.
The first processing module 502 is configured to determine that a vehicle corresponding to a driving track with the same vehicle information is a suspected fake-licensed vehicle if the driving track with the same vehicle information has the same M driving time points, where M is a positive integer greater than or equal to 1 and less than or equal to N.
A second processing module 503, configured to determine a fake-licensed vehicle in the suspected fake-licensed vehicle according to vehicle information and/or driver information in a driving track of the suspected fake-licensed vehicle.
In the embodiment, by acquiring a driving track of each of a plurality of vehicles, the driving track includes driving information of the vehicle at each of N driving points, where N is a positive integer greater than or equal to 1, each driving information includes a driving time point, vehicle information, and driver information, the vehicle information attributed to each driving point on the same driving track is the same, and the driver information attributed to each driving point on the same driving track is the same; if the driving tracks with the same vehicle information have the same M driving time points, determining that the vehicle corresponding to the driving tracks with the same vehicle information is a suspected fake-licensed vehicle, wherein M is a positive integer which is greater than or equal to 1 and less than or equal to N; the fake-licensed vehicles in the suspected fake-licensed vehicles are determined according to the vehicle information and/or the driver information in the driving tracks of the suspected fake-licensed vehicles, the fake-licensed vehicles are determined by comparing a plurality of driving tracks with the same vehicle information and determining the fake-licensed vehicles if the same driving time points exist, and then the fake-licensed vehicles are determined from the suspected fake-licensed vehicles, so that the fake-licensed vehicles can be accurately identified, and the identification accuracy of the fake-licensed vehicles is improved.
Fig. 6 is a schematic structural diagram of a vehicle identification device according to still another embodiment of the present application. As shown in fig. 6, the vehicle identification apparatus 50 provided in this embodiment may further include, on the basis of the vehicle identification apparatus 50 provided in the embodiment shown in fig. 5: a generating module 504.
Optionally, the obtaining module 501 is configured to:
acquiring the running time point of each vehicle at each running point, and vehicle information and driver information corresponding to the vehicle;
determining the running information of each vehicle at each running point according to the running time point of each vehicle at each running point, and the vehicle information and the driver information corresponding to the vehicle;
according to the running information with the same driver information and the same vehicle information, the running track of the vehicle with the same driver information and the same vehicle information is generated according to the time sequence of the running time points in the running information.
Optionally, the obtaining module 501 is configured to:
acquiring a vehicle image and a driver image of each of the vehicles;
and carrying out vehicle identification on the vehicle image of each vehicle to obtain vehicle information of each vehicle, and carrying out face identification on the driver image of each vehicle to obtain driver information of each vehicle.
Optionally, the vehicle information includes license plate information, or the vehicle information includes license plate information and at least one of the following information: license plate color, license plate size, vehicle brand, vehicle color, vehicle model;
the driver information comprises a face recognition identification of the driver;
the travel information further includes at least one of the following information: the vehicle driving method comprises a driving point mark and a driving direction, wherein the driving time point is the time when the vehicle passes through the driving point, and the driving direction is the driving direction when the vehicle passes through the driving point.
Optionally, the obtaining module 501 is further configured to:
acquiring indication information, wherein the indication information is used for indicating a travel time range and/or a travel point range, and the indication information is preset or sent by a user;
and determining vehicles corresponding to the travel time range and/or the travel point range from a preset first database, wherein the first database comprises vehicle information, driver information and travel time points of a plurality of vehicles in different travel time ranges and/or different travel points.
Optionally, the second processing module 503 is configured to:
according to a preset second database, wherein the second database comprises vehicle registration information and/or driver registration information of vehicles, when it is determined that the vehicle information in the driving track of the suspected fake-licensed vehicle is different from the vehicle registration information of the vehicle corresponding to the driving track in the second database, and/or when it is determined that the driver information in the driving track of the suspected fake-licensed vehicle is different from the driver registration information of the vehicle corresponding to the driving track in the second database, the suspected fake-licensed vehicle is determined to be a fake-licensed vehicle.
Optionally, the generating module 504 is configured to:
and after the fake-licensed vehicles in the suspected fake-licensed vehicles are determined, generating and displaying warning information, wherein the warning information is used for indicating the fake-licensed vehicles.
The vehicle identification device provided by the embodiment of the application can be used for executing the method embodiment, the implementation principle and the technical effect are similar, and the embodiment is not repeated herein.
Fig. 7 is a schematic hardware structure diagram of a vehicle identification device according to an embodiment of the present application. As shown in fig. 7, the present embodiment provides a vehicle recognition device 70 including: at least one processor 701 and a memory 702. The vehicle identification device 70 further includes a communication section 703. The processor 701, the memory 702, and the communication section 703 are connected by a bus 704.
In particular implementations, the at least one processor 701 executes computer-executable instructions stored by the memory 702 to cause the at least one processor 701 to perform the vehicle identification method as described above.
For a specific implementation process of the processor 701, reference may be made to the above method embodiments, which implement principles and technical effects similar to each other, and details of this embodiment are not described herein again.
In the embodiment shown in fig. 7, it should be understood that the Processor may be a Central Processing Unit (CPU), other general purpose processors, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in the incorporated application may be directly implemented by a hardware processor, or may be implemented by a combination of hardware and software modules in the processor.
The memory may comprise high speed RAM memory and may also include non-volatile storage NVM, such as at least one disk memory.
The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, the buses in the figures of the present application are not limited to only one bus or one type of bus.
The application also provides a computer readable storage medium, wherein the computer readable storage medium stores computer executable instructions, and when a processor executes the computer executable instructions, the vehicle identification method is realized.
The computer-readable storage medium may be implemented by any type of volatile or non-volatile memory device or combination thereof, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk. Readable storage media can be any available media that can be accessed by a general purpose or special purpose computer.
An exemplary readable storage medium is coupled to the processor such the processor can read information from, and write information to, the readable storage medium. Of course, the readable storage medium may also be an integral part of the processor. The processor and the readable storage medium may reside in an Application Specific Integrated Circuits (ASIC). Of course, the processor and the readable storage medium may also reside as discrete components in the apparatus.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.
Claims (12)
1. A vehicle identification method, characterized in that the method comprises:
acquiring a driving track of each vehicle in a plurality of vehicles, wherein the driving track comprises driving information of the vehicle on each driving point in N driving points, N is a positive integer greater than or equal to 1, each driving information comprises a driving time point, vehicle information and driver information, the vehicle information belonging to each driving point on the same driving track is the same, and the driver information belonging to each driving point on the same driving track is the same;
respectively comparing every two of all driving tracks with the same vehicle information, and determining whether the driving tracks are the same as the two driving tracks; comparing the running time points of the running points recorded in the two running tracks, and determining whether the two running tracks have the same running time points and the same number of the running time points according to a strategy that the two running time points with the interval smaller than a certain threshold are the same running time points;
or counting the starting time point and the ending time point of each driving track to obtain a driving time period corresponding to each driving track, and if the driving time periods have mutually overlapped parts and the overlapped parts are greater than a certain threshold value, determining that the two driving tracks have M identical driving time points;
if the driving tracks with the same vehicle information have the same M driving time points, determining that the vehicle corresponding to the driving tracks with the same vehicle information is a suspected fake-licensed vehicle, wherein M is a positive integer which is greater than or equal to 1 and less than or equal to N;
and determining the fake-licensed vehicles in the suspected fake-licensed vehicles according to the vehicle information and/or the driver information in the driving track of the suspected fake-licensed vehicles.
2. The method of claim 1, wherein said obtaining a travel trajectory for each of a plurality of vehicles comprises:
acquiring the running time point of each vehicle at each running point, and vehicle information and driver information corresponding to the vehicle;
determining the running information of each vehicle at each running point according to the running time point of each vehicle at each running point, and the vehicle information and the driver information corresponding to the vehicle;
according to the running information with the same driver information and the same vehicle information, the running track of the vehicle with the same driver information and the same vehicle information is generated according to the time sequence of the running time points in the running information.
3. The method of claim 1, wherein the vehicle information comprises license plate information, or wherein the vehicle information comprises license plate information and at least one of: license plate color, license plate size, vehicle brand, vehicle color, vehicle model;
the driver information comprises a face recognition identification of the driver;
the travel information further includes at least one of the following information: the vehicle driving method comprises a driving point mark and a driving direction, wherein the driving time point is the time when the vehicle passes through the driving point, and the driving direction is the driving direction when the vehicle passes through the driving point.
4. The method according to claim 2, wherein before acquiring the travel time point of each vehicle at each travel point, and the vehicle information and the driver information corresponding to the vehicle, the method further comprises:
acquiring indication information, wherein the indication information is used for indicating a travel time range and/or a travel point range, and the indication information is preset or sent by a user;
and determining vehicles corresponding to the travel time range and/or the travel point range from a preset first database, wherein the first database comprises vehicle information, driver information and travel time points of a plurality of vehicles in different travel time ranges and/or different travel points.
5. The method according to any one of claims 1 to 4, wherein determining a fake-licensed vehicle of the suspected fake-licensed vehicles from vehicle information and/or driver information in a driving trajectory of the suspected fake-licensed vehicles comprises:
according to a preset second database, wherein the second database comprises vehicle registration information and/or driver registration information of vehicles, when it is determined that the vehicle information in the driving track of the suspected fake-licensed vehicle is different from the vehicle registration information of the vehicle corresponding to the driving track in the second database, and/or when it is determined that the driver information in the driving track of the suspected fake-licensed vehicle is different from the driver registration information of the vehicle corresponding to the driving track in the second database, the suspected fake-licensed vehicle is determined to be a fake-licensed vehicle.
6. A vehicle identification device characterized by comprising:
the vehicle information acquisition module is used for acquiring a driving track of each vehicle in a plurality of vehicles, wherein the driving track comprises driving information of the vehicle on each driving point in N driving points, N is a positive integer greater than or equal to 1, each driving information comprises a driving time point, vehicle information and driver information, the vehicle information belonging to each driving point on the same driving track is the same, and the driver information belonging to each driving point on the same driving track is the same;
the first processing module is used for respectively comparing every two driving tracks with the same vehicle information, comparing the driving time points of the driving points recorded in the two driving tracks, and determining whether the two driving tracks have the same driving time points and the same number of the driving time points according to a strategy that the two driving time points with the interval smaller than a certain threshold are the same driving time points; or counting the starting time point and the ending time point of each driving track to obtain a driving time period corresponding to each driving track, and if the driving time periods have mutually overlapped parts and the overlapped parts are greater than a certain threshold value, determining that the two driving tracks have M identical driving time points;
if the driving tracks with the same vehicle information have the same M driving time points, determining that the vehicle corresponding to the driving tracks with the same vehicle information is a suspected fake-licensed vehicle, wherein M is a positive integer which is greater than or equal to 1 and less than or equal to N;
and the second processing module is used for determining the fake-licensed vehicles in the suspected fake-licensed vehicles according to the vehicle information and/or the driver information in the driving track of the suspected fake-licensed vehicles.
7. The apparatus of claim 6, wherein the obtaining module is configured to:
acquiring the running time point of each vehicle at each running point, and vehicle information and driver information corresponding to the vehicle;
determining the running information of each vehicle at each running point according to the running time point of each vehicle at each running point, and the vehicle information and the driver information corresponding to the vehicle;
according to the running information with the same driver information and the same vehicle information, the running track of the vehicle with the same driver information and the same vehicle information is generated according to the time sequence of the running time points in the running information.
8. The apparatus of claim 6, wherein the vehicle information comprises license plate information, or wherein the vehicle information comprises license plate information and at least one of: license plate color, license plate size, vehicle brand, vehicle color, vehicle model;
the driver information comprises a face recognition identification of the driver;
the travel information further includes at least one of the following information: the vehicle driving method comprises a driving point mark and a driving direction, wherein the driving time point is the time when the vehicle passes through the driving point, and the driving direction is the driving direction when the vehicle passes through the driving point.
9. The apparatus of claim 7, wherein the obtaining module is further configured to:
acquiring indication information, wherein the indication information is used for indicating a travel time range and/or a travel point range, and the indication information is preset or sent by a user;
and determining vehicles corresponding to the travel time range and/or the travel point range from a preset first database, wherein the first database comprises vehicle information, driver information and travel time points of a plurality of vehicles in different travel time ranges and/or different travel points.
10. The apparatus according to any one of claims 6-9, wherein the second processing module is configured to:
according to a preset second database, wherein the second database comprises vehicle registration information and/or driver registration information of vehicles, when it is determined that the vehicle information in the driving track of the suspected fake-licensed vehicle is different from the vehicle registration information of the vehicle corresponding to the driving track in the second database, and/or when it is determined that the driver information in the driving track of the suspected fake-licensed vehicle is different from the driver registration information of the vehicle corresponding to the driving track in the second database, the suspected fake-licensed vehicle is determined to be a fake-licensed vehicle.
11. A vehicle identification apparatus characterized by comprising: at least one processor and memory;
the memory stores computer-executable instructions;
the at least one processor executing the computer-executable instructions stored by the memory causes the at least one processor to perform the vehicle identification method of any of claims 1-5.
12. A computer-readable storage medium having stored thereon computer-executable instructions which, when executed by a processor, implement the vehicle identification method according to any one of claims 1 to 5.
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| CN112017444A (en) * | 2020-08-28 | 2020-12-01 | 上海依图网络科技有限公司 | Fake-licensed vehicle detection method and device, medium and system thereof |
| CN113160565B (en) * | 2021-04-14 | 2022-12-30 | 北京掌行通信息技术有限公司 | Fake-licensed vehicle identification method and device, storage medium and terminal |
| CN114140780A (en) * | 2021-11-19 | 2022-03-04 | 杭州海康威视数字技术股份有限公司 | Abnormal vehicle detection method, device and equipment |
| CN114882448B (en) * | 2022-04-01 | 2023-10-31 | 北京卓视智通科技有限责任公司 | Vehicle monitoring method and electronic equipment |
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