CN113112798B9

CN113112798B9 - Vehicle overload detection method, system and storage medium

Info

Publication number: CN113112798B9
Application number: CN202110384133.3A
Authority: CN
Inventors: 苏庆裕
Original assignee: Individual
Current assignee: Individual
Priority date: 2021-04-09
Filing date: 2021-04-09
Publication date: 2023-04-07
Anticipated expiration: 2041-04-09
Also published as: CN113112798B; CN113112798A

Abstract

The embodiment of the application provides a vehicle overload detection method, a vehicle overload detection system and a storage medium, relates to the technical field of overload detection, and aims to solve the problem of low vehicle overload detection efficiency in the prior art. The method specifically comprises the following steps: the data processor acquires weight data; the weight data is used to characterize a vehicle weight of a monitored area of the pathway weighing apparatus detected by the weighing apparatus at a first time; the data processor receives a first image from the first snapshot device, the first image is an image acquired by the first snapshot device at a second moment, and the time difference between the first moment and the second moment is less than a first preset time length; the monitoring area is in the visual field range of the first capturing device, or the distance between the monitoring area and the visual field range of the first capturing device is smaller than a first preset distance; the data processor determines whether the vehicle in the first image is overloaded based on the weight data and the first image.

Description

Vehicle overload detection method, system and storage medium

Technical Field

The application relates to the technical field of overload detection, in particular to a method, a system and a storage medium for detecting vehicle overload.

Background

The vehicle overload has huge potential safety hazard, which not only can damage the road surface and break the bridge, but also can cause tire burst, deviation, brake or steering failure, vehicle turnover and the like of the vehicle due to serious overload. Therefore, overload detection for the vehicle is crucial.

At present, the overload detection of the vehicle is usually completed by manual detection, weight-based charging and the like. However, the above-mentioned method basically determines whether the vehicle is overloaded by weighing the weight of the workers one by one. Therefore, the required detection time is long, traffic jam is easy to cause, and the working efficiency cannot be effectively guaranteed.

Disclosure of Invention

The application provides a vehicle overload detection method, a vehicle overload detection system and a storage medium, which are used for solving the problem of low vehicle overload detection efficiency in the prior art.

In order to achieve the purpose, the following technical scheme is adopted in the application:

in a first aspect, the present application provides a vehicle overload detection method, which is applied to a vehicle detection device comprising a weighing device and a data processor, wherein the weighing device is connected with the data processor; the method comprises the following steps: the data processor acquires weight data; the weight data being indicative of a vehicle weight of a monitored area of the weighing apparatus detected by the weighing apparatus at a first time; the data processor receives a first image from the first snapshot device, the first image is an image acquired by the first snapshot device at a second moment, and the time difference between the first moment and the second moment is less than a first preset time length; the monitoring area is in the visual field range of the first capturing device, or the distance between the monitoring area and the visual field range of the first capturing device is smaller than a first preset distance; the data processor determines whether the vehicle in the first image is overloaded based on the weight data and the first image.

According to the vehicle overrun detection method, the weight data of the vehicle are determined through the weighing device, the first image is determined through the first capturing device, and whether the vehicle is overloaded or not is determined according to the weight data and the first image. Through laying the weighing-appliance on the road, but automatic weighing has avoided the artifical participation when overload detects, has reduced the cost of labor. Whether overload exists or not is determined according to the weight data and the first image, so that misjudgment caused by manual participation is avoided, the accuracy of overrun judgment is improved, and the working efficiency is improved.

In design, the step of "the data processor determining whether the vehicle in the first image is overloaded based on the weight data and the first image" comprises: identifying the first image to determine a vehicle type of the vehicle; determining that the vehicle is overloaded when the weight data is greater than a load threshold corresponding to the vehicle type; and determining that the vehicle is not overloaded when the weight data is less than or equal to the load threshold corresponding to the vehicle type.

As can be seen from the above, the specific overload determination method is determined according to the weight data and the magnitude of the load threshold. The method avoids the manual acquisition of the specific data of the vehicle type corresponding to the load threshold value, saves time, and further improves the overrun detection efficiency.

In the design, in the case that it is determined that the vehicle is overloaded and the vehicle type is a truck, the vehicle overrun detection method further includes: the data processor sends a control signal to the second snapshot device, the control signal is used for starting the second snapshot device, the monitoring area is in the visual field range of the second snapshot device, or the distance between the monitoring area and the visual field range of the second snapshot device is smaller than a second preset distance; the first capturing device is used for capturing an image of a vehicle driving away from the first capturing device, and the second capturing device is used for capturing an image of a vehicle approaching the second capturing device; or the first capturing device is used for capturing an image of a vehicle close to the first capturing device, and the second capturing device is used for capturing an image of the vehicle moving away from the second capturing device; the data processor acquires a second image; the second image is an image acquired by the second snapshot device at a third moment, and the time difference between the first moment and the third moment is less than a second preset time length; the data processor determines identification information from the first image and the second image, the identification information being used to uniquely identify the vehicle.

According to the method, under the condition that the vehicle is determined to be overloaded and the type of the vehicle is the truck, the second image is obtained, and the unique identification vehicle corresponding to the overload is finally determined through the first image and the second image, so that the accuracy of the overrun judgment is further improved, and the error is reduced.

In design, the vehicle overload detection method further comprises the step that the data processor sends prompt information to the display so as to display the prompt information; the prompt message is used to characterize the vehicle overload.

Therefore, the data processor sends the prompt information to the display, and the display displays the prompt information to play a role in warning so as to reduce the occurrence frequency of the over-limit behaviors.

In design, the vehicle overload detection method further comprises the step that the data processor sends prompt information to the background server.

As can be seen from the above, the data processor sends the prompt message to the backend server, and the backend server stores or uses it for other purposes. By storing the prompt information, traceable raw data is provided for subsequent follow-up over-limit behavior processing.

In a second aspect, a vehicle overload detection system is provided, where the vehicle overload detection system includes a vehicle detection device and at least one snapshot device, the vehicle detection device is connected to the snapshot device, and the vehicle detection device is configured to execute the vehicle detection method in the first aspect.

In a third aspect, a data processor is provided, comprising: a processor; a memory for storing the processor-executable instructions; wherein the processor is configured to execute instructions to implement the vehicle over-limit detection method as provided in the first aspect above.

In a fourth aspect, the present application provides a computer-readable storage medium comprising instructions. The instructions, when executed on the computer, cause the computer to perform the vehicle over-limit detection method as provided in the first aspect above.

In a fifth aspect, the present application provides a computer program product, which when run on a computer, causes the computer to perform the vehicle over-limit detection method as provided in the first aspect above.

It should be noted that all or part of the above computer instructions may be stored on the first computer readable storage medium. The first computer readable storage medium may be packaged with the processor of the access network terminal device, or may be packaged separately from the processor of the access network terminal device, which is not limited in this application.

For the descriptions of the second, third, fourth and fifth aspects in this application, reference may be made to the detailed description of the first aspect; in addition, for the beneficial effects described in the second aspect, the third aspect, the fourth aspect and the fifth aspect, reference may be made to the beneficial effect analysis of the first aspect, and details are not repeated here.

In the present application, the above names do not limit the terminal devices or the functional modules themselves, and in actual implementation, the terminal devices or the functional modules may appear by other names. As long as the functions of the respective terminal devices or functional modules are similar to those of the present application, they fall within the scope of the claims of the present application and their equivalents.

These and other aspects of the present application will be more readily apparent from the following description.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.

FIG. 1 is a schematic diagram of a vehicle overload detection system according to an embodiment of the present disclosure;

FIG. 2 is a schematic diagram of a vehicle overload detection scenario according to an embodiment of the present application;

FIG. 3 is a second schematic diagram of a vehicle overload detection system according to an embodiment of the present application;

FIG. 4 is a schematic flow chart of a vehicle overload detection method according to an embodiment of the present application;

FIG. 5 is a second flowchart illustrating a vehicle overload detection method according to an embodiment of the present application;

fig. 6 is a third flowchart illustrating a vehicle overload detection method according to an embodiment of the present application;

FIG. 7 is a fourth flowchart illustrating a method for detecting vehicle overload according to an embodiment of the present disclosure;

FIG. 8 is a block diagram of a data processor according to an embodiment of the present application;

fig. 9 is a schematic structural diagram of a computer program product of a detection method according to an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present application, and 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.

It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described herein as "exemplary" or "e.g.," is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present relevant concepts in a concrete fashion.

For the convenience of clearly describing the technical solutions of the embodiments of the present application, in the embodiments of the present application, the terms "first", "second", and the like are used to distinguish the same items or similar items with basically the same functions and actions, and those skilled in the art can understand that the terms "first", "second", and the like are not limited in number or execution order.

Based on the consideration of the potential safety hazard of vehicle transportation, vehicle overload always is the key concern problem of traffic control, and vehicle overload causes great life threat to drivers and surrounding vehicles and personnel. Therefore, detection of vehicle overload is also crucial.

At present, the detection of vehicle overload is usually realized by combining manual detection, weighing charge, high-speed pre-detection, factory precision detection and the like. The manual detection mode needs professional staff to go on the road for detection and on-site judgment, so that the working efficiency is low and traffic jam is easily caused; the weighing charging mode needs to weigh one by one, which can cause the phenomenon of vehicle congestion; the high-speed pre-inspection and factory fine inspection are combined, the detection process is complex, the personnel and equipment investment is large, and the phenomena of vehicle escape and fee evasion are serious. All the above methods have various disadvantages, and the detection efficiency is low.

In view of the above problems, the vehicle overrun detection method provided in the embodiment of the present application is applicable to vehicle overload detection. When a vehicle drives into a preset overload detection station, a first image is obtained through first snapshot equipment, and weight data are obtained through weighing equipment. Based on the first image and the weight data, it is determined whether the vehicle is overloaded.

The vehicle overrun detection method provided by the embodiment of the application can be suitable for a vehicle overrun detection system. Fig. 1 shows one configuration of the vehicle overrun detection system. As shown in fig. 1, the system includes a vehicle detection device 1 and at least one capturing apparatus 2, and the vehicle detection device 1 and the capturing apparatus 2 are connected.

The vehicle detection device 1 is used for executing a vehicle overrun detection method. Wherein, the vehicle detection device 1 comprises a weighing apparatus 11 and a data processor 12; the weighing device 11 and the data processor 12 communicate by wire or wirelessly.

The weighing device 11 is used to detect the weight of the vehicle passing through the monitoring area of the weighing device at a first moment.

The data processor 12 may be a server, a server cluster composed of a plurality of servers, or a cloud computing service center, for example: various personal computers, notebook computers, smart phones, tablet computers, control cabinets and other computing equipment. In practical applications, the data processor 12 may also be integrated in one computing device, or may be located in two computing devices independent of each other.

In the scenario that the data processor 12 is connected to one weighing device 11, the data processor 12 and the weighing device 11 may be integrated into one device, or may be located in two devices independent of each other, and the embodiment of the present application does not limit the positional relationship between the data processor 12 and the weighing device 11.

The capturing device 2 is a device for acquiring images, and is generally a bayonet capturing device and an electric alarm capturing device. Illustratively, the capturing apparatus 2 includes a first capturing apparatus 21 and a second capturing apparatus 22.

In a scene that the vehicle detection device 1 is connected with the capturing device 2, the vehicle detection device 1 and the capturing device 2 may be integrated in one device or may be located in two devices that are independent of each other.

Illustratively, the weighing apparatus 11 includes load cells, vehicle detectors, front and rear coils, and the like. The weighing sensor comprises a flat plate type weighing sensor, a narrow strip type weighing sensor and a quartz type weighing sensor. As shown in FIG. 2, the weighing device 11 is laid on a highway and when a vehicle enters the XXX detection station according to the signboard, the vehicle runs in a monitoring area (comprising the weighing device) at the speed appointed by the signboard. When the front rear coil and the vehicle detector detect that the vehicle enters, the weighing sensor is triggered to measure the weight of the vehicle, and weight data are obtained.

The weighing device 11 adopts a seamless splicing technology, and full-section detection is performed after splicing is completed. And when the detection result meets the preset requirement, putting the test card into practical use. In order to improve the weighing accuracy, the flat weighing sensor with higher accuracy is selected as the weighing sensor, and when a vehicle rapidly passes through the weighing device, accurate measurement is realized. Meanwhile, a large amount of original weight data are accumulated through the weighing device 11, and a mathematical model is established according to the original weight data so as to realize effective weighing under special conditions (such as large axle base randomness, elastic tires, uneven speed and the like).

Illustratively, the capturing device 2 includes a capturing machine, a fill-in light, a signal detector, a signal machine, and the like. The snapshot machine can be a bayonet snapshot machine or an electric police snapshot machine. The bayonet snapshot machine is used for shooting all vehicle images in the way, and the electric alarm snapshot machine is used for shooting specific vehicle images according to the control information of the data processor.

Meanwhile, the electric police snapshot machine is also used for taking a snapshot under the condition that the behavior characteristics of the vehicle are inconsistent with the target behavior characteristics (such as violation of traffic signal light indication, sheltering or polluting motor vehicle license plates, reverse driving, violation of regulation for overtaking, stopping according to the regulation, avoidance of pedestrians, continuous driving on overtaking lanes and the like). Usually, 3 images are shot, and information such as signal lamp states, stop line positions, illegal lanes, license plate numbers of illegal vehicles, license plate colors, vehicle body colors, vehicle types, illegal time, places, vehicle speeds, driving directions and the like in a shooting scene can be clearly displayed.

Illustratively, as shown in fig. 2, the capturing apparatus 2 is provided with a first capturing apparatus 21 and a second capturing apparatus 22 near an entrance and an exit of a detection station on a highway, respectively. The first capturing device 21 is a bayonet capturing machine, and the second capturing device 22 is an electric alarm capturing machine. If the distance between the vehicles entering the detection station and the detection station is designed to be 80m, if the distance between every two vehicles is 8 m, the 18 m vehicles can pass about 3 vehicles in the detection station; about 6 vehicles can pass through the 5 m vehicle in the detection station. The design can effectively control traffic flow, and traffic lights are convenient to control. The application does not limit the number of the snapshot devices entering the distance between the detection station and the detection station, and can flexibly select the snapshot devices according to practical application.

Further, as shown in fig. 3, the vehicle overrun detection system further includes a display 3.

The display 3 is used for acquiring prompt information and displaying the prompt information, and the prompt information is used for representing vehicle overload.

In this step, the display 3 acquires prompt information sent by the data processor 12 in the vehicle overrun detection device 1, and displays the prompt information, wherein the prompt information is used for representing vehicle overload. The prompt information comprises a license plate number, vehicle overload weight data, overload time and the like. In a specific embodiment, as shown in fig. 2, a display 3 is disposed on the highway, and when an overload occurs, the display 3 performs scrolling playing on the data of the license plate number, the data of the vehicle overload weight, the overload time, and the like included in the prompt message. Therefore, the vehicle driver can know the prompt information in time, and the warning effect is achieved.

Further, as shown in fig. 3, the vehicle overrun detection system further includes a background server 4.

The background server 4 is used for acquiring prompt information, and the prompt information is used for representing vehicle overload.

Illustratively, the background server 4 acquires prompt information sent by the data processor 12 in the vehicle overrun detection device 1, records data including a license plate number, vehicle overload weight data, overload time and the like included in the prompt information, and uploads the data to a third-party platform. The third-party platform comprises a data aggregation platform, a service processing platform, a work management platform and a video management platform. Overload information can be determined in the third-party platform according to screening conditions (such as license plate numbers, detection sites, starting time and the like). The overload information may be directly linked to the integrated processing platform. After the overload event is associated to the comprehensive processing platform, the comprehensive processing platform can track the subsequent progress of the overload event according to the overload information, remind the overload event to execute a related process, and finally finish all the overload events. Meanwhile, the third-party platform and the comprehensive processing platform can be the same platform or multiple platforms to execute corresponding functions, and the application is not limited to this.

Further, as shown in fig. 2, the vehicle overrun detection system further includes a signboard.

The signboard comprises a distance signboard, a lane signboard, a special lane signboard, a speed limit signboard and the like. The signboard can be set according to actual needs, and the application is not limited to this.

Illustratively, as shown in fig. 2, distance signboards are arranged at positions 1km, 500m and 300m away from the XXX detection station in the B direction at the road A in advance. The distance signboard is used for prompting that an overload detection station exists in front of the distance signboard, the goods vehicle must drive in, and otherwise, the goods vehicle belongs to violation behaviors.

And a lane signboard is further arranged at an entrance of the XXX detection station to prompt lane driving according to the type of the vehicle. If the vehicle is not driven according to the lane-dividing signboard, the high-definition face shooting machine arranged by the snapshot equipment is combined to shoot the violation behaviors such as non-lane driving or reverse lane driving, and the violation behaviors of the vehicle are judged.

And a special lane signboard is arranged 100m before the vehicle enters the non-stop XXX detection station and is used for prompting that the vehicle is not allowed to run straight and must enter an overload detection special lane. And if the vehicle is not driven according to the special lane signboard, judging that the vehicle generates violation behaviors.

And a speed limit signboard is also arranged after the vehicle enters the special lane for detecting the non-stop XXX, and the vehicle is warned to keep the running speed below 50km/h (or 40 km/h). And if the vehicle is not driven according to the speed-limiting signboard, judging whether the vehicle has violation behaviors.

The following describes a vehicle overrun detection method provided in the embodiments of the present application with reference to specific embodiments, and the methods provided in the embodiments can be applied to the vehicle overrun detection device in the vehicle overrun detection system shown in fig. 1 or fig. 3.

FIG. 4 is a flow chart illustrating a detection method for a vehicle over-limit detection device, wherein the vehicle over-limit detection device includes a weighing apparatus and a data processor, according to an exemplary embodiment. As shown in fig. 4, the method may include steps 401-403:

step 401, the data processor obtains weight data.

The weight data is used to characterize the vehicle weight of the monitored area of the approach weighing apparatus detected by the weighing apparatus at a first time.

In this step, the data processor obtains weight data from the weighing device. The weight data is data measured by the weighing apparatus when the vehicle is travelling to the weighing apparatus in the monitoring area at a first moment in time. In a specific embodiment, the vehicle weight data is 28000 kilograms. The first moment can be the moment when the vehicle contacts the weighing device, or the moment when the vehicle wheel leaves the weighing device, and can be customized according to actual use, which is not limited in the present application.

Step 402, the data processor receives a first image from a first capture device.

The first image is an image acquired by the first snapshot device at the second moment, and the time difference between the first moment and the second moment is less than a first preset duration.

The monitoring area is in the visual field range of the first capturing device, or the distance between the monitoring area and the visual field range of the first capturing device is smaller than a first preset distance.

In this step, the first image is image information of the vehicle.

For example, the first image may capture information about a direction of a head of the vehicle, and may also capture information about a direction of a tail of the vehicle.

If the first image is captured to be the information of the direction of the head of the vehicle, the first capturing device captures the information of the vehicle close to the first capturing device. The second moment corresponding to the vehicle which is captured by the first capturing device and close to the first capturing device can be earlier than the first moment corresponding to weighing of the weighing device, can also be later than the first moment, and can also be synchronous with the first moment.

If the first image captures the tail direction information of the vehicle, the first capturing device captures the information of the vehicle driving away from the first capturing device. The second moment when the first capturing device captures the vehicle running away from the first capturing device can be earlier than the first moment or later than the first moment, and can be synchronous with the first moment.

Meanwhile, the visual field range of the first snapshot device can completely cover the whole monitoring area, and can also only cover the area of the weighing device, or the distance between the first snapshot device and the monitoring area is smaller than a first preset distance, so long as all complete information of the first image shot by the first snapshot device is ensured, and the method is not limited by the application. In a specific embodiment, the first capturing device is a bayonet capturing machine.

The execution sequence of step 401 and step 402 is not limited in the present application, and step 401 may be executed first and then step 402 may be executed, or step 402 may be executed first and then step 401 may be executed, or step 401 and step 402 may be executed simultaneously.

Step 403, the data processor determines whether the vehicle in the first image is overloaded based on the weight data and the first image.

In this step, the data processor determining whether the vehicle in the first image is overloaded according to the weight data and the first image specifically includes the following steps:

as shown in fig. 5, step 403 includes steps 4031-4032.

Step 4031, the data processor identifies the first image to determine a vehicle type of the vehicle.

In this step, the data processor acquires a first image from the first capturing device and acquires weight data from the weighing device. The data processor identifies the first image through an image processing method, analyzes information contained in the first image, and obtains specific information such as the license plate number, the license plate color, the body color, the vehicle type, the number of axles and the like of the vehicle. By scaling the first image equally, the length, width, height of the vehicle can also be obtained.

The vehicle type may be determined according to the number of axles included in the first image, or may be determined according to other information included in the first image, which is not limited in the present application. The method for judging the type of the vehicle according to the axle comprises the following steps: the number of the wheels from the head to the tail or from the tail to the head is several rows of the axles. The types of vehicles can be divided into two-axle trucks, three-axle trucks, four-axle trucks, five-axle motor trains, six-axle and above-six motor trains and the like according to the axle. In a particular embodiment, the vehicle type in the first image is determined to be a three-axle truck.

4032, when the weight data is greater than the load threshold corresponding to the vehicle type, the data processor determines that the vehicle is overloaded; the data processor determines that the vehicle is not overloaded if the weight data is less than or equal to a load threshold corresponding to the vehicle type.

In this step, after the vehicle type is determined, the load threshold corresponding to each vehicle type can be determined. For example, a two-axle truck may have a total truck mass limit of 18000 kilograms; the total weight limit value of the three-axle truck is 25000 kilograms; the total mass limit value of the train and goods of the three-axle train is 27000 kg; a truck having a total truck mass of more than 31000 kilograms; the total mass limit value of the four-axle automobile train is 36000 kg; the total mass limit value of the train and goods of the five-axis automobile train is 43000 kg; the total mass limit of the train of six or more than six automobiles is 49000 kg, wherein the driving shaft of the tractor is single-shaft, and the total mass limit of the train is 46000 kg.

After the vehicle type and the load threshold value corresponding to the vehicle type are determined, whether the current vehicle is overloaded or not can be judged. And if the weight data of the current vehicle is less than or equal to the load threshold value, determining that the current vehicle is not overloaded. Combining steps 401 and 4031, it is determined that the vehicle type is a three-axle truck, and the load threshold of the three-axle truck is 25000 kilograms. And if the weight data of the current three-axle truck is 28000 kilograms and is larger than the load threshold 25000 kilograms, the current vehicle is determined to be overloaded.

After the length, width, height data and vehicle type of the vehicle are obtained, the length, width, height data may be compared with length, width, height data corresponding to the vehicle type to determine whether the vehicle is out of limit.

In the case where it is determined that the vehicle is overloaded and the vehicle type is a truck, as shown in fig. 6, step 4032 further includes steps 40321-40323:

step 40321, the data processor sends a control signal to the second capturing device.

The control signal is used to activate the second capturing device.

The monitoring area is in the visual field range of the second snapshot device, or the distance between the monitoring area and the visual field range of the second snapshot device is smaller than a second preset distance.

In this step, if it is determined that the vehicle is overloaded and the vehicle type is a truck, if only the first image is acquired, the vehicle information may be incomplete. Such as: the semitrailer on the highway is usually 2 sets of license plates, one set is hung on the head of the semitrailer, and one set is hung on the trailer. If only the first image is acquired, only the license plate number of the head of the vehicle or the license plate number of the tail of the vehicle can be acquired, and the other license plate number which is inconsistent with the first image cannot be acquired. To avoid this, the data processor sends a control signal to the second snap-shot device in case it is determined that there is overload behavior and the vehicle type is a truck. The control signal is used for controlling the second capturing device to capture the second image.

For example, the captured second image may be information about the direction of the head of the vehicle, and may also be information about the direction of the tail of the vehicle.

If the first image captures the direction information of the head of the vehicle, the second image captures the direction information of the tail of the vehicle; at the moment, the first capturing device captures information of a vehicle close to the first capturing device, and the second capturing device captures information of the vehicle moving away from the first capturing device.

If the first image captures the tail direction information of the vehicle, the second image captures the head direction information of the vehicle; at the moment, the first capturing device captures information of a vehicle driving away from the first capturing device, and the second capturing device captures information of a vehicle approaching the first capturing device.

Meanwhile, the visual field range of the second snapshot device can completely cover the whole monitoring area, and can also only cover the area of the weighing device, or the distance between the second snapshot device and the monitoring area is smaller than a second preset distance, so long as it is ensured that the second snapshot device shoots all complete information of the second image, and the method and the device are not limited in the application. In a specific embodiment, the second capturing device is an electric alarm capturing machine.

Step 40322, the data processor acquires a second image.

The second image is an image acquired by the second capturing device at a third moment, and the time difference between the first moment and the third moment is less than a second preset time.

In this step, the second image is captured by snapping after the vehicle is determined to be out of limit, so that the third time corresponding to the second image is later than the first time and the second time, and the time difference between the third time and the first time is less than a second preset time. The second preset time is set to ensure validity and accuracy of the second image acquired at the third moment.

Step 40323, the data processor determines the identification information from the first image and the second image.

The identification information is used to uniquely identify the vehicle.

In this step, as can be seen from the above, the first image may be the license plate number of the vehicle head, and the number can also be the license plate number of the tail of the vehicle. The second image can be the license plate number of the head of the vehicle and can also be the license plate number of the tail of the vehicle. The license plate numbers corresponding to the first image and the second image are respectively obtained from different positions of the vehicle. Therefore, when the vehicle is a trailer or a semi-trailer, the unique identification vehicle can be determined according to the first image and the second image, so that the problem of misjudgment is avoided, and the reliability of overload judgment is improved.

Further, as shown in fig. 7, after the step 40323, the method for detecting vehicle overload further includes:

step 404a, the data processor sends the prompt information to the display so as to display the prompt information.

The prompt message is used to characterize the vehicle overload.

In this step, the data processor may send the prompt message to a display, and the display displays the prompt message. For details, reference is made to the description of the display portion of the vehicle over-limit detection system.

Further, as shown in fig. 7, the vehicle overload detection method further includes:

and step 404b, the data processor sends prompt information to the background server.

In this step, the data processor may send a prompt message to the background server. In a specific embodiment, the data processor sends the prompt message to the background server. The details are described with reference to the background server portion of the vehicle over-limit detection system.

The detection method provided by the application is suitable for the scene of vehicle overload on the expressway. When the vehicle enters the overload detection station according to the signboard, weight data are obtained through the weighing equipment; and obtaining a first image through first snapshot equipment. Determining whether the first image is out of limit based on the weight data. And under the condition that the vehicle type is determined to be a truck, sending control information to a second snapshot device to obtain a second image, and determining the unique identification vehicle according to the first image and the second image. By the detection mode, the detection pressure caused by insufficient workers is solved, and the detection precision is higher; meanwhile, the method is simple and easy to operate, low in learning cost and wide in applicability.

The scheme provided by the embodiment of the application is introduced from the perspective of the method. In order to implement the above functions, it includes a hardware structure and/or a software module for performing each function. Those of skill in the art will readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

Fig. 8 is a schematic structural diagram of a data processor according to an embodiment of the present application, where the data processor may include: at least two processors 81, a memory 82, a communication interface 83, and a communication bus 84.

The following specifically introduces each component of the overload detection apparatus for terminal device with reference to fig. 8:

the processor 81 is a control center of the overload detection apparatus for the terminal device, and may be a single processor or a collective term for multiple processing elements. For example, the processor 81 is a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement embodiments of the present application, such as: one or more DSPs, or one or more Field Programmable Gate Arrays (FPGAs).

In a particular implementation, processor 81 may include one or more CPUs, such as CPU0 and CPU1 shown in FIG. 8, as one embodiment. Also, as an embodiment, the terminal equipment overload detecting device may include a plurality of processors, such as the processor 81 and the processor 85 shown in fig. 8. Each of these processors may be a Single-core processor (Single-CPU) or a Multi-core processor (Multi-CPU). A processor herein may refer to one or more terminal devices, circuits, and/or processing cores for processing data (e.g., computer program instructions).

The Memory 82 may be a Read-Only Memory (ROM) or other types of static storage terminal devices that can store static information and instructions, a Random Access Memory (RAM) or other types of dynamic storage terminal devices that can store information and instructions, or an Electrically Erasable Programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), compact disk Read-Only Memory (CD-ROM) or other optical disk storage, optical disk storage (including Compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), magnetic disk storage media or other magnetic storage terminal devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to such. The memory 82 may be self-contained and overload-detected with the processor 81 via the communication bus 84. The memory 82 may also be integrated with the processor 81.

In particular implementations, memory 82 is used to store data and execute software programs of the present application. The processor 81 may perform various functions of the air conditioner by running or executing software programs stored in the memory 82 and calling data stored in the memory 82.

The communication interface 83 is a device such as any transceiver, and is used for communicating with other terminal devices or communication Networks, such as a Radio Access Network (RAN), a Wireless Local Area Network (WLAN), a terminal device, and a cloud. The communication interface 83 may include an acquisition unit implementing an acquisition function and a transmission unit implementing a transmission function.

The communication bus 84 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (enhanced Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 8, but this is not intended to represent only one bus or type of bus.

Another embodiment of the present application further provides a computer-readable storage medium, which stores instructions that, when executed on a computer, cause the computer to perform the method shown in the above method embodiment.

In some embodiments, the disclosed methods may be implemented as computer program instructions encoded on a computer-readable storage medium in a machine-readable format or encoded on other non-transitory media or articles of manufacture.

Fig. 9 schematically illustrates a conceptual partial view of a computer program product provided by an embodiment of the present application, the computer program product comprising a computer program for executing a computer process on a computing terminal device.

In one embodiment, the computer program product is provided using a signal bearing medium 910. The signal bearing medium 910 may include one or more program instructions that, when executed by one or more processors, may provide the functions or portions of the functions described above with respect to fig. 2. Thus, for example, referring to the embodiment shown in fig. 2, one or more features of steps 301-302 may be undertaken by one or more instructions associated with the signal bearing medium 910. Further, the program instructions in FIG. 9 also describe example instructions.

In some examples, the signal bearing medium 910 may comprise a computer readable medium 911 such as, but not limited to, a hard disk drive, a Compact Disc (CD), a Digital Video Disc (DVD), a digital tape, a memory, a read-only memory (ROM), a Random Access Memory (RAM), or the like.

In some embodiments, signal bearing medium 910 may comprise a computer recordable medium 912, such as, but not limited to, memory, read/write (R/W) CD, R/W DVD, and the like.

In some implementations, the signal bearing medium 910 may include a communication medium 913, such as, but not limited to, a digital and/or analog communication medium (e.g., a fiber optic cable, a waveguide, a wired communications link, a wireless communication link, etc.).

The signal bearing medium 910 may be conveyed by a wireless form of communication medium 913. The one or more program instructions may be, for example, computer-executable instructions or logic-implementing instructions.

In some examples, a data writing apparatus, such as that described with respect to fig. 2, may be configured to provide various operations, functions, or actions in response to one or more program instructions via the computer-readable medium 911, the computer-recordable medium 912, and/or the communication medium 913.

Through the above description of the embodiments, it is clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be completed by different functional modules according to needs, that is, the internal structure of the device may be divided into different functional modules to complete the above-described full-classification part or part of the functions.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, a module or a unit may be divided into only one logic function, and may be implemented in other ways, for example, a plurality of units or components may be combined or integrated into another apparatus, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication overload detection may be through some interfaces, indirect coupling or communication overload detection of devices or units, and may be in an electrical, mechanical or other form.

Units described as separate parts may or may not be physically separate, and parts displayed as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed to a plurality of different places. The purpose of the scheme of the embodiment can be realized by selecting a part of or a whole classification part unit according to actual needs.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present application, or portions thereof that contribute to the prior art per se, or the whole classification part or portions thereof, may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a terminal device (which may be a single chip, a chip, etc.) or a processor (processor) to execute the whole classification part or some steps of the methods of the embodiments of the present application. And the foregoing storage the medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

The above is only an embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions within the technical scope of the present disclosure should be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A vehicle overload detection method is applied to a vehicle detection device comprising a weighing device and a data processor, wherein the weighing device is connected with the data processor; the method is characterized by comprising the following steps:

the data processor acquiring weight data; the weight data is used for representing the weight of the vehicle passing through a monitoring area of the weighing equipment, which is detected by the weighing equipment at a first moment;

the data processor receives a first image from first capturing equipment, wherein the first image is an image acquired by the first capturing equipment at a second moment, and the time difference between the first moment and the second moment is less than a first preset time length; the distance between the monitoring area and the visual field range of the first snapshot device is smaller than a first preset distance;

the data processor determining whether a vehicle in the first image is overloaded based on the weight data and the first image;

when the vehicle is determined to be overloaded and the vehicle type is a truck, the data processor sends a control signal to second capturing equipment, and the control signal is used for starting the second capturing equipment; the distance between the monitoring area and the visual field range of the second snapshot device is smaller than a second preset distance; the first capturing device is used for capturing an image of a vehicle driving away from the first capturing device, and the second capturing device is used for capturing an image of a vehicle approaching the second capturing device;

the data processor acquiring a second image; the second image is an image acquired by the second snapshot device at a third moment, and the time difference between the first moment and the third moment is less than a second preset time length;

the data processor determines identification information according to the first image and the second image, wherein the identification information is used for uniquely identifying the vehicle.

2. The vehicle overload detection method of claim 1, wherein the data processor determining whether the vehicle in the first image is overloaded based on the weight data and the first image comprises:

identifying the first image to determine a vehicle type of the vehicle;

determining that the vehicle is overloaded when the weight data is greater than a load threshold corresponding to the vehicle type; determining that the vehicle is not overloaded when the weight data is less than or equal to a load threshold corresponding to the vehicle type.

3. The vehicle overload detection method according to claim 1 or 2, further comprising:

the data processor sends prompt information to a display so as to display the prompt information; the prompt message is used for representing vehicle overload.

4. The vehicle overload detection method according to claim 1 or 2, further comprising:

and the data processor sends prompt information to a background server.

5. A vehicle overload detection system, comprising a vehicle detection device and at least one snapshot apparatus, the vehicle detection device being connected with the snapshot apparatus,

the vehicle detection device is used for executing the vehicle overload detection method of any one of the preceding claims 1-4.

6. The vehicle overload detection system of claim 5, further comprising a display;

the display is used for acquiring prompt information and displaying the prompt information, and the prompt information is used for representing vehicle overload.

7. The vehicle overload detection system of claim 5, further comprising a backend server;

the background server is used for acquiring prompt information, and the prompt information is used for representing vehicle overload.

8. A data processor, comprising:

a processor;

a memory for storing the processor-executable instructions;

wherein the processor is configured to execute the instructions to implement the vehicle overload detection method of any one of claims 1-4.

9. A computer-readable storage medium comprising instructions that, when executed by a data processor, cause the data processor to perform the vehicle overload detection method of any one of claims 1-4.