CN116129653B - Bayonet vehicle detection method, device, equipment and storage medium - Google Patents
Bayonet vehicle detection method, device, equipment and storage medium Download PDFInfo
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- CN116129653B CN116129653B CN202310405022.5A CN202310405022A CN116129653B CN 116129653 B CN116129653 B CN 116129653B CN 202310405022 A CN202310405022 A CN 202310405022A CN 116129653 B CN116129653 B CN 116129653B
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- G08—SIGNALLING
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- G08G1/00—Traffic control systems for road vehicles
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Abstract
The invention discloses a method, a device, equipment and a storage medium for detecting a bayonet vehicle, wherein the method comprises the following steps: acquiring traffic flow information acquired by each bayonet in a target area in the last unit time; establishing an association relation between a target detection bayonet and at least one auxiliary detection bayonet according to the traffic flow information; and distributing the vehicle information acquired by the target detection bayonet in the current unit time to a detection server of the target detection bayonet and a detection server of the corresponding auxiliary detection bayonet, so that the detection server of the auxiliary detection bayonet assists the target detection bayonet to execute the vehicle detection task in the current unit time. According to the invention, the traffic flow information is used as the target detection bayonet to match the corresponding auxiliary detection bayonet, so that the operation pressure of the target detection bayonet is reduced, the operation capability of the detection server in the area is reasonably configured, and the efficiency of detecting the vehicles in the area is improved.
Description
Technical Field
The present invention relates to the field of detection technologies of bayonet vehicles, and in particular, to a method, an apparatus, a device, and a storage medium for detecting a bayonet vehicle.
Background
With the rapid development of modern society economy and popularization of cities, automobiles are an important transportation means, and the number of automobiles is increased in a blowout manner. The increase of the number of automobiles brings convenience to people and also causes a series of traffic violation running problems.
At present, a plurality of vehicle detection bayonets are generally arranged at a plurality of positions of a road section, and vehicle information such as vehicle monitoring videos and vehicle running speeds is collected, so that running states and characteristics of each vehicle are extracted and analyzed. However, as urban vehicles have proliferated, the data processing burden of the detection server conventionally provided with each vehicle detection port has gradually increased, so that the vehicle detection efficiency is low and the time delay is large; on the one hand, the detection servers of the vehicle detection bayonets in the busy road sections are often in overload operation, and the detection servers of the vehicle detection bayonets in the other road sections are often in idle or low-load operation, so that the operation resources are not effectively utilized; on the other hand, detection servers disposed at different vehicle detection bays generally have different computing capabilities due to different installation timings. Therefore, how to improve the detection efficiency of the vehicle in the area is a technical problem to be solved.
The foregoing is provided merely for the purpose of facilitating understanding of the technical solutions of the present invention and is not intended to represent an admission that the foregoing is prior art.
Disclosure of Invention
The invention mainly aims to provide a method, a device, equipment and a storage medium for detecting a bayonet vehicle, and aims to solve the technical problem of low detection efficiency of the existing bayonet vehicle.
To achieve the above object, the present invention provides a bayonet vehicle detection method, the method comprising the steps of:
acquiring traffic flow information acquired by each bayonet in a target area in the last unit time;
establishing an association relation between a target detection bayonet and at least one auxiliary detection bayonet according to the traffic flow information;
and distributing the vehicle information acquired by the target detection bayonet in the current unit time to a detection server of the target detection bayonet and a detection server of the corresponding auxiliary detection bayonet, so that the detection server of the auxiliary detection bayonet assists the target detection bayonet to execute the vehicle detection task in the current unit time.
Optionally, each of the bayonets is configured with a traffic flow collecting device, and the traffic flow information is the number of vehicles passing through the bayonets in a unit time collected by the traffic flow collecting device corresponding to each of the bayonets in the target area.
Optionally, before the step of establishing the association between the target detection bayonet and at least one auxiliary detection bayonet according to the traffic flow information, the method further includes:
determining a target detection bayonet needing auxiliary detection and an auxiliary detection bayonet providing auxiliary detection according to traffic flow information acquired by each bayonet in the last unit time;
the ratio of the traffic flow information acquired in unit time by the target detection bayonets to the traffic flow information during full load detection is ranked as a preset percentage in all bayonets;
wherein the auxiliary detection bayonet is a bayonet other than the target detection bayonet.
Optionally, establishing an association relationship between the target detection bayonet and at least one auxiliary detection bayonet according to the traffic flow information, which specifically includes:
determining a traffic flow detection gap value according to traffic flow information of a target detection bayonet and traffic flow information during full load detection;
determining a traffic flow detection margin value according to traffic flow information of the auxiliary detection bayonet and traffic flow information during full load detection;
establishing an association relation between a target detection bayonet and at least one auxiliary detection bayonet according to the traffic flow detection notch value and the traffic flow detection margin value; the difference value of the sum of the traffic flow detection gap value of the target detection bayonet and the traffic flow detection margin value of the corresponding auxiliary detection bayonet is within a preset numerical range.
Optionally, after the step of establishing the association between the target detection bayonet and at least one auxiliary detection bayonet according to the traffic flow information, the method further includes:
according to the traffic flow detection gap value of the target detection bayonet and the traffic flow detection margin value of the auxiliary detection bayonet, adjusting the preset percentage so as to ensure that the target detection bayonet to be subjected to auxiliary detection and the auxiliary detection bayonet for providing auxiliary detection are determined according to the adjusted preset percentage in the next unit time;
wherein, the step of adjusting the preset percentage specifically comprises:
adjusting a preset percentage according to the ratio of the sum of the traffic flow detection margin values of the auxiliary detection bayonets to the traffic flow detection notch value of the target detection bayonets; when the ratio is greater than 1, the preset percentage is increased, and when the ratio is less than 1, the preset percentage is decreased.
Optionally, the step of distributing the vehicle information collected by the target detection bayonet in the current unit time to the detection server of the target detection bayonet and the detection server of the corresponding auxiliary detection bayonet specifically includes: and distributing the vehicle information acquired by the target detection bayonet in the current unit to a detection server of the target detection bayonet and a detection server of the corresponding auxiliary detection bayonet according to the ratio of the vehicle flow information during full load detection of the target detection bayonet to the vehicle flow detection margin value of the auxiliary detection bayonet.
Optionally, the method further comprises:
determining an initial influence distance radius;
when the situation that the traffic flow information acquired by the target detection bayonet in continuous unit time is increased is detected, increasing the influence distance radius, selecting the target detection bayonet outside the influence distance radius range, and establishing an association relation of the auxiliary detection bayonet;
when detecting that the traffic flow information acquired by the target detection bayonet in continuous unit time is reduced, reducing the influence distance radius, selecting the target detection bayonet outside the influence distance radius range, and establishing an association relation of the auxiliary detection bayonet.
In addition, in order to achieve the above object, the present invention also provides a bayonet vehicle detection device including:
the acquisition module is used for acquiring traffic flow information acquired by each bayonet in the target area in the last unit time;
the establishing module is used for establishing the association relation between the target detection bayonet and at least one auxiliary detection bayonet according to the traffic flow information;
the auxiliary detection module is used for distributing the vehicle information acquired by the target detection bayonet in the current unit time to the detection server of the target detection bayonet and the detection server of the corresponding auxiliary detection bayonet, so that the detection server of the auxiliary detection bayonet assists the target detection bayonet to execute the vehicle detection task in the current unit time.
In addition, in order to achieve the above object, the present invention also provides a bayonet vehicle detecting apparatus, the apparatus comprising: the system comprises a memory, a processor and a bayonet vehicle detection program stored in the memory and capable of running on the processor, wherein the bayonet vehicle detection program realizes the steps of the bayonet vehicle detection method when being executed by the processor.
In addition, in order to achieve the above object, the present invention also provides a storage medium having stored thereon a bayonet vehicle detection program which, when executed by a processor, implements the steps of the bayonet vehicle detection method described above.
The embodiment of the invention provides a method, a device, equipment and a storage medium for detecting a bayonet vehicle, wherein the method comprises the following steps: acquiring traffic flow information acquired by each bayonet in a target area in the last unit time; establishing an association relation between a target detection bayonet and at least one auxiliary detection bayonet according to the traffic flow information; and distributing the vehicle information acquired by the target detection bayonet in the current unit time to a detection server of the target detection bayonet and a detection server of the corresponding auxiliary detection bayonet, so that the detection server of the auxiliary detection bayonet assists the target detection bayonet to execute the vehicle detection task in the current unit time. According to the invention, the traffic flow information is used as the target detection bayonet to match the corresponding auxiliary detection bayonet, so that the operation pressure of the target detection bayonet is reduced, the operation capability of the detection server in the area is reasonably configured, and the efficiency of detecting the vehicles in the area is improved.
Drawings
FIG. 1 is a schematic diagram of a device structure of a hardware operating environment according to an embodiment of the present invention;
fig. 2 is a flowchart of an embodiment of a method for detecting a vehicle in a bayonet according to the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, fig. 1 is a schematic diagram of an apparatus structure of a hardware running environment according to an embodiment of the present invention.
As shown in fig. 1, the apparatus may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
It will be appreciated by those skilled in the art that the arrangement of the apparatus shown in fig. 1 is not limiting and may include more or fewer components than shown, or certain components may be combined, or a different arrangement of components.
As shown in fig. 1, an operating system, a network communication module, a user interface module, and a bayonet vehicle detection program may be included in the memory 1005 as one type of computer storage medium.
In the terminal shown in fig. 1, the network interface 1004 is mainly used for connecting to a background server and performing data communication with the background server; the user interface 1003 is mainly used for connecting a client (user side) and performing data communication with the client; and the processor 1001 may be configured to call a bayonet vehicle detection program stored in the memory 1005 and perform the following operations:
acquiring traffic flow information acquired by each bayonet in a target area in the last unit time;
establishing an association relation between a target detection bayonet and at least one auxiliary detection bayonet according to the traffic flow information;
and distributing the vehicle information acquired by the target detection bayonet in the current unit time to a detection server of the target detection bayonet and a detection server of the corresponding auxiliary detection bayonet, so that the detection server of the auxiliary detection bayonet assists the target detection bayonet to execute the vehicle detection task in the current unit time.
The specific embodiment of the present invention applied to the device is basically the same as each embodiment of the following method for detecting a vehicle using a bayonet, and will not be described herein.
The embodiment of the invention provides a method for detecting a vehicle at a bayonet, and referring to fig. 2, fig. 2 is a schematic flow chart of the embodiment of the method for detecting the vehicle at the bayonet.
In this embodiment, the method for detecting a vehicle in a bayonet comprises the following steps:
step S100: acquiring traffic flow information acquired by each bayonet in a target area in the last unit time;
step S200: establishing an association relation between a target detection bayonet and at least one auxiliary detection bayonet according to the traffic flow information;
step S300: and distributing the vehicle information acquired by the target detection bayonet in the current unit time to a detection server of the target detection bayonet and a detection server of the corresponding auxiliary detection bayonet, so that the detection server of the auxiliary detection bayonet assists the target detection bayonet to execute the vehicle detection task in the current unit time.
It is easy to understand that in this embodiment, each of the bayonets is configured with a traffic flow collecting device, and the traffic flow information is the number of vehicles passing through the bayonets in a unit time collected by the traffic flow collecting device corresponding to each of the bayonets in the target area.
In a preferred embodiment, before the step of establishing the association between the target detection bayonet and the at least one auxiliary detection bayonet according to the traffic flow information, the method further includes: determining a target detection bayonet needing auxiliary detection and an auxiliary detection bayonet providing auxiliary detection according to traffic flow information acquired by each bayonet in the last unit time; the ratio of the traffic flow information acquired in unit time by the target detection bayonets to the traffic flow information during full load detection is ranked as a preset percentage in all bayonets; wherein the auxiliary detection bayonet is a bayonet other than the target detection bayonet.
On the basis, establishing an association relation between a target detection bayonet and at least one auxiliary detection bayonet according to the traffic flow information, and specifically comprising the following steps: determining a traffic flow detection gap value according to traffic flow information of a target detection bayonet and traffic flow information during full load detection; determining a traffic flow detection margin value according to traffic flow information of the auxiliary detection bayonet and traffic flow information during full load detection; establishing an association relation between a target detection bayonet and at least one auxiliary detection bayonet according to the traffic flow detection notch value and the traffic flow detection margin value; the difference value of the sum of the traffic flow detection gap value of the target detection bayonet and the traffic flow detection margin value of the corresponding auxiliary detection bayonet is within a preset numerical range.
In this embodiment, after the step of establishing the association between the target detection port and at least one auxiliary detection port according to the traffic flow information, the method further includes: and adjusting the preset percentage according to the traffic flow detection gap value of the target detection bayonet and the traffic flow detection margin value of the auxiliary detection bayonet so as to ensure that the target detection bayonet to be subjected to auxiliary detection and the auxiliary detection bayonet for providing auxiliary detection are determined according to the adjusted preset percentage in the next unit time.
Wherein, the step of adjusting the preset percentage specifically comprises: adjusting a preset percentage according to the ratio of the sum of the traffic flow detection margin values of the auxiliary detection bayonets to the traffic flow detection notch value of the target detection bayonets; when the ratio is greater than 1, the preset percentage is increased, and when the ratio is less than 1, the preset percentage is decreased.
Therefore, the preset percentage of the target detection bayonet and the auxiliary detection bayonet can be adjusted and determined through the ratio of the sum of the traffic flow detection margin values of the auxiliary detection bayonet and the traffic flow detection notch value of the target detection bayonet, so that the ratio of the target detection bayonet and the auxiliary detection bayonet is optimized, and the detection efficiency of the bayonet vehicle in the whole area range is improved.
Therefore, the step of distributing the vehicle information collected by the target detection checkpoint in the current unit time to the detection server of the target detection checkpoint and the detection server of the corresponding auxiliary detection checkpoint in this embodiment specifically includes: and distributing the vehicle information acquired by the target detection bayonet in the current unit to a detection server of the target detection bayonet and a detection server of the corresponding auxiliary detection bayonet according to the ratio of the vehicle flow information during full load detection of the target detection bayonet to the vehicle flow detection margin value of the auxiliary detection bayonet.
In another embodiment, the method further comprises: determining an initial influence distance radius; when the situation that the traffic flow information acquired by the target detection bayonet in continuous unit time is increased is detected, increasing the influence distance radius, selecting the target detection bayonet outside the influence distance radius range, and establishing an association relation of the auxiliary detection bayonet; when detecting that the traffic flow information acquired by the target detection bayonet in continuous unit time is reduced, reducing the influence distance radius, selecting the target detection bayonet outside the influence distance radius range, and establishing an association relation of the auxiliary detection bayonet.
Therefore, the influence of traffic flow caused by connectivity among roads is avoided by introducing the influence distance radius, the influence caused by the roads is considered when the auxiliary detection bayonets corresponding to the target detection bayonets are selected, the auxiliary detection bayonets with smaller connectivity are selected and established as far as possible for the target detection bayonets, and the detection efficiency of the bayonet vehicles in the whole area range is improved.
In the embodiment, the vehicle detection method for the bayonet is provided, and the vehicle flow information is used as the auxiliary detection bayonet corresponding to the target detection bayonet, so that the operation pressure of the target detection bayonet is reduced, the operation capability of the detection server in the area is reasonably configured, and the vehicle detection efficiency of the bayonet in the area is improved.
The invention also provides a bayonet vehicle detection device, which comprises:
the acquisition module is used for acquiring traffic flow information acquired by each bayonet in the target area in the last unit time;
the establishing module is used for establishing the association relation between the target detection bayonet and at least one auxiliary detection bayonet according to the traffic flow information;
the auxiliary detection module is used for distributing the vehicle information acquired by the target detection bayonet in the current unit time to the detection server of the target detection bayonet and the detection server of the corresponding auxiliary detection bayonet, so that the detection server of the auxiliary detection bayonet assists the target detection bayonet to execute the vehicle detection task in the current unit time.
The vehicle detection device for the bayonet is provided, and the vehicle flow information is used as an auxiliary detection bayonet corresponding to the target detection bayonet in a matching way, so that the operation pressure of the target detection bayonet is reduced, the operation capacity of the detection server in the area range is reasonably configured, and the vehicle detection efficiency of the bayonet in the area range is improved.
Other embodiments or specific implementations of the bayonet vehicle detection device of the present invention may refer to the above method embodiments, and will not be described herein.
In addition, the invention also provides a bayonet vehicle detection device, the bayonet vehicle detection apparatus comprises a memory, a processor, and a bayonet vehicle detection program stored on the memory and executable on the processor, wherein: the bayonet vehicle detection program, when executed by the processor, implements the bayonet vehicle detection method according to the embodiments of the present invention.
The specific implementation manner of the bayonet vehicle detection device is basically the same as the above embodiments of the bayonet vehicle detection method, and will not be repeated here.
Furthermore, the present invention also proposes a readable storage medium comprising a computer readable storage medium having a bayonet vehicle detection program stored thereon. The readable storage medium may be a Memory 1005 in the terminal of fig. 1, or may be at least one of a ROM (Read-Only Memory)/RAM (Random Access Memory ), a magnetic disk, and an optical disk, and the readable storage medium includes several instructions for causing a bayonet vehicle detection device having a processor to perform the bayonet vehicle detection method according to the embodiments of the present invention.
The specific implementation of the detection program for the bayonet vehicle in the readable storage medium is substantially the same as the above embodiments of the detection method for the bayonet vehicle, and will not be described herein.
It is appreciated that in the description herein, reference to the terms "one embodiment," "another embodiment," "other embodiments," or "first through nth embodiments," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as described above, comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (8)
1. A method of bayonet vehicle detection, the method comprising the steps of:
acquiring traffic flow information acquired by each bayonet in a target area in the last unit time;
according to the traffic flow information, establishing an association relationship between a target detection bayonet and at least one auxiliary detection bayonet, specifically including:
determining a traffic flow detection gap value according to traffic flow information of a target detection bayonet and traffic flow information during full load detection;
determining a traffic flow detection margin value according to traffic flow information of the auxiliary detection bayonet and traffic flow information during full load detection;
establishing an association relation between a target detection bayonet and at least one auxiliary detection bayonet according to the traffic flow detection notch value and the traffic flow detection margin value; the difference value of the sum of the traffic flow detection gap value of the target detection bayonet and the traffic flow detection margin value of the corresponding auxiliary detection bayonet is within a preset numerical range;
according to the traffic flow detection gap value of the target detection bayonet and the traffic flow detection margin value of the auxiliary detection bayonet, adjusting the preset percentage so as to ensure that the target detection bayonet to be subjected to auxiliary detection and the auxiliary detection bayonet for providing auxiliary detection are determined according to the adjusted preset percentage in the next unit time;
wherein, the step of adjusting the preset percentage specifically comprises:
adjusting a preset percentage according to the ratio of the sum of the traffic flow detection margin values of the auxiliary detection bayonets to the traffic flow detection notch value of the target detection bayonets; increasing the preset percentage when the ratio is greater than 1, and decreasing the preset percentage when the ratio is less than 1;
and distributing the vehicle information acquired by the target detection bayonet in the current unit time to a detection server of the target detection bayonet and a detection server of the corresponding auxiliary detection bayonet, so that the detection server of the auxiliary detection bayonet assists the target detection bayonet to execute the vehicle detection task in the current unit time.
2. The method for detecting a vehicle in a vehicle communication system according to claim 1, wherein each of the vehicle communication systems is provided with a traffic flow collection device, and the traffic flow information is the number of vehicles passing through the vehicle communication system per unit time collected by the traffic flow collection device corresponding to each of the vehicle communication systems in the target area.
3. The bayonet vehicle detection method of claim 1, wherein prior to the step of establishing an association of a target detection bayonet with at least one auxiliary detection bayonet based on the traffic flow information, the method further comprises:
determining a target detection bayonet needing auxiliary detection and an auxiliary detection bayonet providing auxiliary detection according to traffic flow information acquired by each bayonet in the last unit time;
the ratio of the traffic flow information acquired in unit time by the target detection bayonets to the traffic flow information during full load detection is ranked as a preset percentage in all bayonets;
wherein the auxiliary detection bayonet is a bayonet other than the target detection bayonet.
4. The method for detecting a vehicle in a vehicle entrance according to claim 1, wherein the step of distributing the vehicle information collected by the target detection entrance in the current unit time to the detection server of the target detection entrance and the detection server of the corresponding auxiliary detection entrance, specifically comprises: and distributing the vehicle information acquired by the target detection bayonet in the current unit to a detection server of the target detection bayonet and a detection server of the corresponding auxiliary detection bayonet according to the ratio of the vehicle flow information during full load detection of the target detection bayonet to the vehicle flow detection margin value of the auxiliary detection bayonet.
5. The bayonet vehicle detection method of claim 4, wherein the method further comprises:
determining an initial influence distance radius;
when the situation that the traffic flow information acquired by the target detection bayonet in continuous unit time is increased is detected, increasing the influence distance radius, selecting the target detection bayonet outside the influence distance radius range, and establishing an association relation of the auxiliary detection bayonet;
when detecting that the traffic flow information acquired by the target detection bayonet in continuous unit time is reduced, reducing the influence distance radius, selecting the target detection bayonet outside the influence distance radius range, and establishing an association relation of the auxiliary detection bayonet.
6. A bayonet vehicle detection device, characterized in that it comprises:
the acquisition module is used for acquiring traffic flow information acquired by each bayonet in the target area in the last unit time;
the establishing module is used for establishing the association relation between the target detection bayonet and at least one auxiliary detection bayonet according to the traffic flow information, and specifically comprises the following steps:
determining a traffic flow detection gap value according to traffic flow information of a target detection bayonet and traffic flow information during full load detection;
determining a traffic flow detection margin value according to traffic flow information of the auxiliary detection bayonet and traffic flow information during full load detection;
establishing an association relation between a target detection bayonet and at least one auxiliary detection bayonet according to the traffic flow detection notch value and the traffic flow detection margin value; the difference value of the sum of the traffic flow detection gap value of the target detection bayonet and the traffic flow detection margin value of the corresponding auxiliary detection bayonet is within a preset numerical range;
according to the traffic flow detection gap value of the target detection bayonet and the traffic flow detection margin value of the auxiliary detection bayonet, adjusting the preset percentage so as to ensure that the target detection bayonet to be subjected to auxiliary detection and the auxiliary detection bayonet for providing auxiliary detection are determined according to the adjusted preset percentage in the next unit time;
wherein, the step of adjusting the preset percentage specifically comprises:
adjusting a preset percentage according to the ratio of the sum of the traffic flow detection margin values of the auxiliary detection bayonets to the traffic flow detection notch value of the target detection bayonets; increasing the preset percentage when the ratio is greater than 1, and decreasing the preset percentage when the ratio is less than 1;
the auxiliary detection module is used for distributing the vehicle information acquired by the target detection bayonet in the current unit time to the detection server of the target detection bayonet and the detection server of the corresponding auxiliary detection bayonet, so that the detection server of the auxiliary detection bayonet assists the target detection bayonet to execute the vehicle detection task in the current unit time.
7. A bayonet vehicle detection apparatus, characterized in that it comprises: memory, a processor and a bayonet vehicle detection program stored on the memory and executable on the processor, which when executed by the processor, implements the steps of the bayonet vehicle detection method according to any one of claims 1 to 5.
8. A storage medium having stored thereon a bayonet vehicle detection program which, when executed by a processor, implements the steps of the bayonet vehicle detection method according to any one of claims 1 to 5.
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