Information collection method, device, electronic device and readable storage medium

Abstract

The present application discloses an information collection method, device, electronic device and readable storage medium, belonging to the technical field of information processing. Among them, the method includes: at at least one sampling moment, obtaining the detection value of each pressure sensing detection unit in the pressure sensing detection unit array, the pressure sensing detection unit array is arranged in the target area, and the detection value is associated with the pressure value; determining the pressure sensing information of the target area according to the detection value; analyzing the pressure sensing information to obtain the target information of the target area, and the target information includes traffic flow information. The present application can improve the accuracy of traffic flow statistics.

Description

Technical Field

[0001] This application belongs to the technical field of information processing, and particularly relates to an information collection method, device, electronic device, and readable storage medium. Background Art

[0002] Traffic flow collection is widely applied in scenarios such as highways, urban arterial roads, shopping malls, stations, scenic spots, etc.

[0003] In the prior art, traffic flow data is usually obtained by analyzing and identifying video images captured by cameras installed at high places. However, cameras are prone to situations such as missed detection, misdetection, or unclear captured images that are difficult to detect due to factors such as angles and light, resulting in low accuracy of traffic flow statistics. Summary of the Invention

[0004] The purpose of the embodiments of this application is to provide an information collection method, device, electronic device, and readable storage medium, which can solve the problem of low accuracy of traffic flow statistics.

[0005] In a first aspect, the embodiments of this application provide an information collection method, including:

[0006] At at least one sampling moment, obtain the detection value of each pressure sensing detection unit in the pressure sensing detection unit array, where the pressure sensing detection unit array is arranged in the target area, and the detection value is associated with the pressure value;

[0007] Determine the pressure sensing information of the target area according to the detection value;

[0008] Analyze the pressure sensing information to obtain the target information of the target area, where the target information includes traffic flow information.

[0009] In a second aspect, the embodiments of this application provide an information collection device, including:

[0010] A first acquisition module, configured to obtain the detection value of each pressure sensing detection unit in the pressure sensing detection unit array at at least one sampling moment, where the pressure sensing detection unit array is arranged in the target area, and the detection value is associated with the pressure value;

[0011] A first determination module, configured to determine the pressure sensing information of the target area according to the detection value;

[0012] An analysis module, configured to analyze the pressure sensing information to obtain the target information of the target area, where the target information includes traffic flow information.

[0013] In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program or instruction stored on the memory and executable on the processor. When the program or instruction is executed by the processor, the steps of the method described in the first aspect are implemented.

[0014] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0015] In a fifth aspect, an embodiment of the present application provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the method described in the first aspect.

[0016] In the embodiment of the present application, through the pressure-sensing detection array provided on the ground, the pressure senses the vehicles passing through the target area, and can relatively accurately and completely obtain the associated information of the vehicles passing through the target area. Compared with the related art in which the traffic flow information is collected by a camera installed at a high place, the method provided by the embodiment of the present application does not have the problems of vehicle occlusion or false detection due to sunlight, and improves the accuracy of traffic flow statistics. Description of the Drawings

[0017] Figure 1 is a flowchart of an information collection method provided by an embodiment of the present application;

[0018] Figure 2a is one of the schematic diagrams of a pressure-sensing image provided by an embodiment of the present application;

[0019] Figure 2b is another schematic diagram of a pressure-sensing image provided by an embodiment of the present application;

[0020] Figure 2c is yet another schematic diagram of a pressure-sensing image provided by an embodiment of the present application;

[0021] Figure 2d is still another schematic diagram of a pressure-sensing image provided by an embodiment of the present application;

[0022] Figure 3 is a structural block diagram of an information collection device provided by an embodiment of the present application;

[0023] Figure 4 is a structural block diagram of an electronic device provided by an embodiment of the present application. Detailed Embodiments

[0024] Next, the technical solutions in the embodiments of the present application will be clearly described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art belong to the scope of protection of the present application.

[0025] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are usually of the same type, and the number of objects is not limited. For example, the first object can be one or multiple. In addition, "and / or" in the specification and claims means at least one of the connected objects, and the character " / " generally indicates an "or" relationship between the associated objects before and after.

[0026] Next, in conjunction with the accompanying drawings, the information collection provided by the embodiments of the present application will be described in detail through specific embodiments and their application scenarios.

[0027] Please refer to Figure 1 , Figure 1 which is a schematic flowchart of an information collection method provided by an embodiment of the present application.

[0028] As Figure 1 shown, the information collection method includes the following steps:

[0029] Step 101, at at least one sampling moment, obtain the detection value of each pressure sensing detection unit in the pressure sensing detection unit array, the pressure sensing detection unit array is disposed in the target area, and the detection value is associated with the pressure value.

[0030] If the area for traffic flow statistics is a closed or semi-closed area, such as a scenic area, a shopping mall, a station, etc., the target area can be located at the entrance and exit of the above-mentioned closed or semi-closed area, such as the entrance and exit of a parking lot. If the area for traffic flow statistics is a road, such as a highway, an urban arterial road, etc., the target area can be set according to the position where traffic flow statistics are actually required. Exemplarily, the target area can be located at any position on a main section of a certain highway, or can be an entrance and exit of a certain highway, such as a highway toll station or a highway interchange hub, etc., which can be determined according to the actual situation and will not be specifically limited here.

[0031] The pressure sensing detection unit array includes a plurality of pressure sensing detection units, and the plurality of pressure sensing detection units can be set as a rectangular array, a circular array or other pattern arrays according to actual needs. The pressure sensing detection unit array can be directly disposed on the ground of the target area, or can be carried by a pressure sensing panel or a carpet and then disposed on the ground of the target area. Specifically, it can be determined according to the actual situation and is not specifically limited herein.

[0032] The at least one sampling moment can be determined in advance, and can be a directly determined sampling moment, such as 08:00:00, 08:00:01, 08:00:02 ···, or can be a sampling moment determined according to a preset sampling start moment and a sampling time interval. For example, the sampling start moment is 08:00:00 and the sampling time interval is 1 / 70 second, or 70 times are collected per second.

[0033] In specific implementation, when the vehicle is traveling on the target area, its tires will contact at least one pressure sensing detection unit in the pressure sensing detection array. Based on the weight of the vehicle, the vehicle will apply pressure to the pressure sensing detection unit contacted by the tire, and the pressed pressure sensing detection unit can detect a detection value related to the pressure value. The detection value can be a pressure value. Exemplarily, when the pressure sensing detection unit is a pressure sensor, the detection value is a pressure value. The detection value can be other numerical values linearly related to the pressure value, such as a capacitance value, a resistance value, etc. Exemplarily, when the pressure sensing detection unit is a piezoresistive detection unit, the detection value is a resistance value. In specific implementation, the linear relationship between the resistance value and the pressure value can be determined based on the detection principle of piezoresistive detection. If necessary, the resistance value can also be converted into a pressure value.

[0034] Step 102: Determine the pressure sensing information of the target area according to the detection value.

[0035] Since the detection value is generated based on the pressure applied by the vehicle to the target area, the pressure sensing information determined according to the detection value can reflect the sensing situation of the target area for the traveling vehicle.

[0036] The pressure sensing information can include the associated information of the detection value, such as the magnitude of the detection value, the detection time of the detection value, etc. The pressure sensing information can also include the associated information of the pressure sensing detection unit corresponding to the detection value, such as the identification information of the pressure sensing detection unit, the position information of the pressure sensing detection unit in the pressure sensing detection array, etc. The pressure sensing information can also include the information associated with both the detection value and the pressure sensing detection unit.

[0037] The pressure sensing information may be in the form of data. Exemplarily, it may be a detection value in numerical form, the position of a pressure sensing detection unit in coordinate form, the identifier of a pressure sensing detection unit in character form, etc. The pressure sensing information may also be in the form of an image. Exemplarily, based on the shape and boundary of the target area, the shape and boundary of a pressure sensing image are correspondingly formed, and then the color is used to distinguish the pressure sensing detection units that are pressed and those that are not, or the color depth is used to represent the magnitude of the detection value, etc.

[0038] It can be understood that the implementation manner of the pressure sensing information is not limited to this, and it can be determined according to the actual situation specifically, and no specific limitation is made here.

[0039] Step 103: Analyze the pressure sensing information to obtain the target information of the target area, where the target information includes traffic flow information.

[0040] In specific implementation, optionally, by analyzing the pressure sensing information, information such as the driving path or tire marks of a vehicle in the target area can be obtained, and then the traffic flow information in the target area can be determined based on this information. It should be noted that the target information may also include other information of the target area. Optionally, the target information may also include other information associated with the vehicles driving in the target area, such as driving direction, driving speed, load, etc., and no specific limitation is made here.

[0041] In the embodiment of the present application, through a pressure sensing detection array provided on the ground, the pressure senses the vehicles passing through the target area, and the associated information of the vehicles passing through the target area can be obtained more accurately and completely. Compared with the related art where traffic flow information is collected by a camera installed at a high place, problems such as vehicle occlusion or misdetection due to sunlight can be avoided, and the accuracy of traffic flow statistics is improved.

[0042] Optionally, step 102 includes:

[0043] According to the detection value obtained at the first sampling moment and the position of each pressure sensing detection unit in the pressure sensing detection unit array, determine the pressure sensing image of the target area at the first sampling moment, where the first sampling moment is any sampling moment among the at least one sampling moment;

[0044] Based on the pressure sensing images of the target area at each sampling moment, generate a pressure sensing image sequence of the target area, where the pressure sensing information includes the pressure sensing image sequence.

[0045] In this embodiment, at each sampling moment, the detection value of each pressure sensing detection unit can be obtained, and the detection value is associated with the position of the pressure sensing detection unit in the pressure sensing detection array. In this way, based on the above two pieces of information, a pressure sensing image can be drawn at each sampling moment. The pressure sensing image includes the current sampling moment, and the pressure sensing footprint corresponding to the tire of the vehicle in the target area can be regarded as an "image frame" containing the vehicle tire footprint collected at the current sampling moment.

[0046] Exemplarily, at the first sampling moment, the tire of the vehicle traveling in the target area contacts the target area, and pressure can be applied to the pressure sensing detection units corresponding to the contact area. The pressurized pressure sensing detection units can obtain the current detection value. Since the contact areas between the vehicle tire and the pressure sensing detection units at different positions are different, the detection values obtained by the pressure sensing detection units at different positions are different. After obtaining the detection value corresponding to the first sampling moment, based on the arrangement of the pressure sensing detection units in the pressure sensing detection array, black dots are drawn at the positions of the pressurized pressure sensing detection units, and the gray levels of the black dots are determined according to the magnitudes of the detection values. White dots are drawn at the positions of the non-pressurized pressure sensing detection units. In this way, a pressure sensing image can be drawn, and a schematic diagram of the pressure sensing image can be as Figures 2a to 2d shown.

[0047] Based on the pressure sensing images of the target area at each sampling moment, the above-mentioned multiple pressure sensing images can be arranged in time sequence to obtain a pressure sensing image sequence, which can be regarded as a "video picture" containing the vehicle tire footprint collected at a continuous plurality of sampling moments. Exemplarily, as Figures 2a to 2d shown, the pressure sensing images corresponding to four sampling moments of 08:00:00, 08:00:01, 08:00:02, and 08:00:03 are respectively. As the vehicle in the target area moves, the positions of the tire footprints in the pressure sensing image corresponding to each sampling moment are different. Combining these four pressure sensing images can form a video picture containing four image frames, so that information such as the number of vehicles in the target area, the moving trajectories of each vehicle, and the moving directions can be analyzed.

[0048] In an alternative embodiment, step 103 includes:

[0049] Identify the tire footprints in the pressure sensing image sequence and obtain the footprint features of each tire footprint;

[0050] Based on the footprint features of the tire footprints, determine the tire footprints of the same vehicle as the tire footprints of the same vehicle;

[0051] According to the number of tire footprints in the pressure sensing image sequence and the corresponding relationship between each tire footprint and the vehicle, determine the traffic flow information of the target area.

[0052] In specific implementation, image and video processing technologies in related technologies can be used to identify the tire imprints in the pressure-sensitive image sequence, such as OpenCV, etc. By using such open-source image processing software and customizing the parameters and templates of image processing based on the contour features or texture features of the tire imprints before processing, the tire imprints in the pressure-sensitive image sequence can be identified, and then the imprint features of each tire imprint can be extracted. It should be noted that the specific implementation manners of processing the pressure-sensitive image and the pressure-sensitive image sequence can refer to the descriptions in related technologies and will not be elaborated here.

[0053] Based on the imprint features of the tire, it can be determined whether there are the same tire imprints in the current time period, and these same tire imprints can be regarded as the tire imprints of the same vehicle.

[0054] Optionally, the imprint features include at least one of an imprint orientation, an imprint motion time sequence, an imprint texture feature, an imprint size feature, and an imprint pressure feature. The imprint orientation can represent the driving direction of the tire, and the imprint orientations corresponding to the tires of the same vehicle are usually the same or similar. The imprint motion time sequence can represent the driving direction of the tire and the time sequence of the contact between the tire and the pressure-sensitive detection unit on the target area, and the imprint motion time sequences corresponding to the tires of the same vehicle are usually the same. The imprint texture feature can represent the relevant information of the tire tread, pattern, lines, etc. The tire tread, pattern, lines, etc. can represent the type of the tire, the wear condition of the tire, etc. According to the type of the tire, the vehicle model can be further determined. According to the wear condition of the tire, different vehicles with different usage conditions can be further distinguished among vehicles of the same model, or the front wheels or rear wheels of the vehicle can also be distinguished, etc., to assist in determining whether they are the tire imprints corresponding to the same vehicle. The imprint size feature can represent information such as the width of the tire imprint and whether it is a dual tire, so as to further determine the vehicle model, etc. The imprint pressure feature can represent the pressure application information of the tire imprint, so as to further determine the load information of the vehicle, to assist in determining whether they are the tire imprints corresponding to the same vehicle.

[0055] In specific implementation, in an optional implementation manner, the imprint features include imprint orientation, imprint movement timing sequence, imprint texture features, imprint size features, and imprint pressure features. Different tire imprints in different driving directions can be distinguished according to the imprint orientation and imprint movement timing sequence. Then, for tire imprints in the same driving direction, it can be further determined whether there are the same tire imprints. Exemplarily, in one way, for tire imprints in the same driving direction, the imprint texture features of any two tire imprints can be compared first, and multiple tire imprints with matching imprint texture features can be classified into the same category; then, further classification can be made according to the imprint size features of each category of tire imprints. In another way, for tire imprints in the same driving direction, the imprint size features of any two tire imprints can be compared first, and multiple tire imprints with matching imprint size features can be classified into the same category; then, further classification can be made according to the imprint texture features of each category of tire imprints. Finally, the classification is further verified and refined according to the imprint pressure features to obtain the final classification result of the tire imprints, and the tire imprints classified into the same category are determined to be the tire imprints of the same vehicle.

[0056] According to the above classification result of the tire imprints, the number of vehicles driving on the target area can be determined, and thus the traffic flow information in the target area can be obtained. Exemplarily, for a four-wheel motor vehicle, if the same four tire imprints are identified in the same pressure-sensitive image, they may be the tire imprints corresponding to the four tires of the same vehicle. When counting the traffic flow information subsequently, these four tire imprints are counted as one vehicle or one vehicle trip. Further, if the same multiple tire imprints are identified in the pressure-sensitive images corresponding to multiple sampling moments in a sampling period, it can be determined whether they are of the same vehicle by combining the orientation of the tire imprints and the spacing between the tire imprints, so as to avoid double counting or omission.

[0057] In an optional implementation manner, before determining the same tire imprints as the tire imprints of the same vehicle based on the imprint features of the tire imprints, the method further includes:

[0058] Obtain the target tire imprints within a preset time period in the pressure-sensitive image sequence;

[0059] Determining the same tire imprints as the tire imprints of the same vehicle based on the imprint features of the tire imprints includes:

[0060] Based on the imprint features of the target tire imprints, determine the same target tire imprints as the tire imprints of the same vehicle.

[0061] The difference between this embodiment and the above - mentioned embodiment is that the traffic volume in the target area is separately counted in different time periods. That is to say, in the above - mentioned embodiment, if the same vehicle enters the shopping mall twice in two different time periods, the vehicle is recorded as one trip in the traffic volume statistics. However, in this embodiment, the vehicle is recorded as two trips in the traffic volume statistics. Specifically, one trip is recorded in the first time period and one trip is recorded in the second time period. In this way, the actual vehicle flow situation can be counted, and the accuracy of traffic volume statistics can be further improved.

[0062] In an alternative embodiment, the footprint feature includes at least one of the footprint orientation and the footprint movement time sequence; after determining the same tire footprint as the tire footprint of the same vehicle based on the footprint feature of the tire footprint, the method further includes:

[0063] Determine the moving direction of the vehicle corresponding to the first tire footprint according to at least one of the footprint orientation and the footprint movement time sequence of the first tire footprint, where the first tire footprint is any tire footprint in the pressure - sensitive image sequence;

[0064] Determine the traffic volume information in the first direction in the target area according to the moving direction of each vehicle, where the first direction is any direction in which the vehicle moves.

[0065] In this embodiment, the traffic volume is separately counted based on the moving direction of the vehicles in the target area. Exemplarily, the traffic volume of vehicles entering the scenic area and leaving the scenic area is separately counted. In this way, the special prevention and control requirements for traffic volume statistics in shopping malls, scenic areas, etc. can be met. When specifically implemented, the moving direction of the vehicle can be judged based on the moving direction of the same tire footprint in the pressure - sensitive image sequence or the orientation of the tire footprint, and then the corresponding traffic volume can be counted.

[0066] In the embodiments of the present application, optionally, the target information further includes vehicle information. The vehicle information may include the type information of the vehicle. Specifically, it can be further analyzed based on the footprint feature of the above - mentioned tire footprint. For example, the type of the vehicle can be judged according to the number of the same tire footprints corresponding to the same vehicle, whether it is a tricycle, a sedan, a motorcycle, a long - haul truck, etc.; or for another example, according to the size, texture or tire spacing of different tire footprints. By judging the type information of the vehicle, the traffic volume can be counted separately for different types of vehicles, and the flexibility and comprehensiveness of the application of traffic volume information can be further improved.

[0067] The vehicle information may also include the loading information of the vehicle. Optionally, the target information further includes overweight warning information. Analyzing the pressure sensing information to obtain the target information includes: according to the detected value, when at least one of the detected values meets the preset overweight condition, obtaining the overweight warning information used to characterize that the vehicle in the target area is overweight.

[0068] In specific implementation, the preset overweight condition may be that at least one of the detected values is greater than a preset threshold. By presetting a preset threshold corresponding to an upper loading amount, the preset threshold is of the same type as the detected value. When it is detected that at least one of the detected values is greater than the preset threshold, it can be determined that there is an overloaded vehicle in the currently traveling vehicles. Further, according to the position of the pressure sensing detection unit corresponding to the detected value exceeding the preset threshold, the specific overloaded vehicle is determined to further analyze information such as the vehicle type. The implementation manner of determining the specific overloaded vehicle can refer to the relevant description in the above implementation manner. It can be understood that the preset overweight condition may also be other conditions, which can be specifically determined according to the actual situation and are not specifically limited herein.

[0069] Exemplarily, when it is detected that at least one of the detected values is greater than the preset threshold, the pressure sensing detection unit corresponding to the detected value greater than the preset threshold can be determined, which is denoted as the target pressure sensing detection unit herein. Then, according to the detected value of the target detection unit and the detected values of the pressure sensing detection units around the target pressure sensing detection unit, the target pressure sensing information can be determined, and the target pressure sensing information is analyzed to determine the specific overloaded vehicle.

[0070] For ease of understanding, an example of the embodiment of the present application is described as follows:

[0071] 1) Lay a pressure sensing detection panel / carpet at the entrance and exit of the scenic area parking lot. The pressure sensing detection panel / carpet is provided with a plurality of pressure sensing detection units distributed in an array, and each pressure sensing detection unit can detect a detected value linearly related to the pressure value when being pressed.

[0072] 2) When the vehicle is driving on the pressure sensing detection panel / carpet, the pressure sensing detection units in contact with the vehicle tires can detect the corresponding detected values. The central processor of the pressure sensing detection panel / carpet can summarize the detected values of all pressure sensing detection units at each sampling moment based on the array distribution of the pressure sensing detection units to correspondingly draw the pressure sensing image at each sampling moment and further form a pressure sensing image sequence.

[0073] 3) Using OpenCV, by customizing parameters and image templates, analyze the pressure-sensitive images and the sequence of pressure-sensitive images obtained in 2) to identify the tire imprints in the sequence of pressure-sensitive images and obtain the imprint features of the tire imprints. The imprint features include: imprint orientation, imprint movement time sequence, imprint texture feature, imprint size feature, and imprint pressure feature.

[0074] 4) Based on the imprint features in 3), determine the tire imprints that are the same as each other, and determine the same tire imprints as the tire imprints of the same vehicle, and record a vehicle trip. In addition, the current time can also be recorded, and according to the imprint orientation and / or the imprint movement time sequence, record the driving direction of the vehicle (entering the parking lot or leaving the parking lot).

[0075] 5) Accumulate the "one vehicle trip" information obtained in 4) within a preset time period to obtain the traffic flow information of the parking lot, as well as the number of vehicles entering and the number of vehicles leaving.

[0076] It should be noted that for the information collection method provided in the embodiments of the present application, the execution subject can be an information collection device, or a control module in the information collection device for executing the information collection method. In the embodiments of the present application, taking the information collection device as the execution subject of the information collection method as an example, the information collection device provided in the embodiments of the present application is described.

[0077] See Figure 3 , Figure 3 which is one of the structural diagrams of the information collection device provided in the embodiments of the present application.

[0078] As Figure 3 shown, the information collection device 300 includes:

[0079] A first acquisition module 301, configured to acquire the detection value of each pressure-sensitive detection unit in the pressure-sensitive detection unit array at at least one sampling moment. The pressure-sensitive detection unit array is disposed in a target area, and the detection value is associated with a pressure value;

[0080] A first determination module 302, configured to determine the pressure-sensitive information of the target area according to the detection value;

[0081] An analysis module 303, configured to analyze the pressure-sensitive information to obtain the target information of the target area, where the target information includes traffic flow information.

[0082] Optionally, the first determination module 302 includes:

[0083] A first determination unit, configured to determine a pressure-sensitive image of the target area at the first sampling moment according to the detected value obtained at the first sampling moment and the position of each pressure-sensitive detection unit in the pressure-sensitive detection unit array, where the first sampling moment is any one of the at least one sampling moment;

[0084] A generation unit, configured to generate a pressure-sensitive image sequence of the target area based on the pressure-sensitive images of the target area at each sampling moment, where the pressure-sensitive information includes the pressure-sensitive image sequence.

[0085] Optionally, the analysis module 303 includes:

[0086] An identification unit, configured to identify tire imprints in the pressure-sensitive image sequence and obtain the imprint characteristics of each tire imprint;

[0087] A second determination unit, configured to determine tire imprints of the same vehicle as the same tire imprints based on the imprint characteristics of the tire imprints;

[0088] A third determination unit, configured to determine the traffic flow information of the target area according to the number of tire imprints in the pressure-sensitive image sequence and the corresponding relationship between each tire imprint and the vehicle.

[0089] Optionally, the information acquisition device 300 further includes:

[0090] A second acquisition module, configured to acquire target tire imprints within a preset time period in the pressure-sensitive image sequence;

[0091] The second determination unit is specifically configured to:

[0092] Determine tire imprints of the same vehicle as the same target tire imprints based on the imprint characteristics of the target tire imprints.

[0093] Optionally, the imprint characteristics include at least one of an imprint orientation, an imprint movement time sequence, an imprint texture feature, an imprint size feature, and an imprint pressure feature.

[0094] Optionally, the imprint characteristics include at least one of an imprint orientation and an imprint movement time sequence;

[0095] The information acquisition device 300 further includes:

[0096] A second determination module, configured to determine the movement direction of the vehicle corresponding to the first tire imprint according to at least one of the imprint orientation and the imprint movement time sequence of the first tire imprint, where the first tire imprint is any tire imprint in the pressure-sensitive image sequence;

[0097] A third determination module, configured to determine the traffic flow information in a first direction within the target area according to the moving direction of each vehicle, where the first direction is any direction in which the vehicle moves.

[0098] Optionally, the target information further includes overweight warning information;

[0099] The analysis module 303 includes:

[0100] An analysis unit, configured to obtain overweight warning information for characterizing that the vehicles in the target area are overweight when at least one of the detection values meets a preset overweight condition according to the detection values.

[0101] The information collection device 300 can implement each process of the corresponding method embodiment, and achieve the same beneficial effects. To avoid repetition, it will not be elaborated here. Figure 1 The information collection device 300 can implement each process of the corresponding method embodiment, and achieve the same beneficial effects. To avoid repetition, it will not be elaborated here.

[0102] The embodiment of the present application further provides an electronic device. Please refer to Figure 4 , the electronic device 400 may include a processor 401, a memory 402, and a computer program 4021 stored in the memory 402 and executable on the processor 401. When the computer program 4021 is executed by the processor 401, it can implement Figure 1 any step in the corresponding method embodiment and achieve the same beneficial effects, which will not be elaborated here.

[0103] The embodiment of the present application further provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, it implements each process of the above information collection method embodiment, and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0104] Wherein, the processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disc, etc.

[0105] The embodiment of the present application further provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor, and the processor is configured to run a program or instruction to implement each process of the above information collection method embodiment, and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0106] It should be understood that the chip mentioned in the embodiment of the present application may also be referred to as a system-on-chip, system chip, chip system, or system-on-chip, etc.

[0107] It should be noted that in this text, the term "including", "comprising", or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or device that includes a series of elements includes not only those elements but also other elements not explicitly listed, or elements that are inherent to such process, method, article, or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article, or device that includes such element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the reverse order according to the functions involved. For example, the described methods may be performed in an order different from that described, and various steps may be added, omitted, or combined. Additionally, the features described with reference to certain examples may be combined in other examples.

[0108] Through the description of the above embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions for causing a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in various embodiments of the present application.

[0109] The embodiments of the present application have been described above in conjunction with the accompanying drawings. However, the present application is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present application, those of ordinary skill in the art can also make many forms without departing from the purpose of the present application and the scope protected by the claims, and all of them fall within the protection scope of the present application.

Claims

1. An information collection method, characterized in that, Comprising: At at least one sampling moment, obtaining the detection value of each pressure sensing unit in the pressure sensing unit array, where the pressure sensing unit array is disposed in the target area, and the detection value is associated with the pressure value; Determining the pressure sensing information of the target area according to the detection value; Analyzing the pressure sensing information to obtain the target information of the target area, where the target information includes traffic flow information; The determining the pressure sensing information of the target area according to the detection value includes: According to the detection value obtained at the first sampling moment and the position of each pressure sensing unit in the pressure sensing unit array, determining the pressure sensing image of the target area at the first sampling moment, where the first sampling moment is any one of the at least one sampling moment; Generating a pressure sensing image sequence of the target area based on the pressure sensing images of the target area at each sampling moment, where the pressure sensing information includes the pressure sensing image sequence; The analyzing the pressure sensing information to obtain the target information of the target area includes: Identifying the tire marks in the pressure sensing image sequence and obtaining the mark features of each tire mark; Based on the mark features of the tire marks, determining the tire marks with the same features as the tire marks of the same vehicle; Determining the traffic flow information of the target area according to the number of tire marks in the pressure sensing image sequence and the corresponding relationship between each tire mark and the vehicle.

2. The method according to claim 1, characterized in that, Before the determining the tire marks with the same features as the tire marks of the same vehicle based on the mark features of the tire marks, the method further includes: Obtaining the target tire marks within a preset time period in the pressure sensing image sequence; The determining the tire marks with the same features as the tire marks of the same vehicle based on the mark features of the tire marks includes: Based on the mark features of the target tire marks, determining the target tire marks with the same features as the tire marks of the same vehicle.

3. The method according to claim 1, characterized in that, The mark features include at least one of mark orientation, mark movement timing, mark texture feature, mark size feature, and mark pressure feature.

4. The method according to claim 1, characterized in that, The mark features include at least one of mark orientation and mark movement timing; After the determining the tire marks with the same features as the tire marks of the same vehicle based on the mark features of the tire marks, the method further includes: Determining the moving direction of the vehicle corresponding to the first tire mark according to at least one of the mark orientation and mark movement timing of the first tire mark, where the first tire mark is any one of the tire marks in the pressure sensing image sequence; Determining the traffic flow information in the first direction in the target area according to the moving direction of each vehicle, where the first direction is any direction in which the vehicle moves.

5. The method according to claim 1, wherein The target information further includes overweight warning information; The analyzing the pressure sensing information to obtain the target information of the target area includes: According to the detection value, when at least one of the detection values meets a preset overweight condition, obtaining overweight warning information for characterizing vehicle overweight in the target area.

6. An information collection device, characterized in that, Comprising: A first acquisition module, configured to acquire, at at least one sampling moment, the detection values of each pressure sensing unit in the pressure sensing unit array, where the pressure sensing unit array is disposed in a target area, and the detection values are associated with pressure values; A first determination module, configured to determine the pressure sensing information of the target area according to the detection values; An analysis module, configured to analyze the pressure sensing information to obtain target information of the target area, where the target information includes traffic flow information; The first determination module includes: A first determination unit, configured to determine a pressure sensing image of the target area at a first sampling moment according to the detection values acquired at the first sampling moment and the positions of each pressure sensing unit in the pressure sensing unit array, where the first sampling moment is any one of the at least one sampling moment; A generation unit, configured to generate a pressure sensing image sequence of the target area based on the pressure sensing images of the target area at each sampling moment, where the pressure sensing information includes the pressure sensing image sequence; The analysis module includes: An identification unit, configured to identify tire imprints in the pressure sensing image sequence and acquire the imprint features of each tire imprint; A second determination unit, configured to determine the tire imprints of the same vehicle as the tire imprints of the same vehicle based on the imprint features of the tire imprints; A third determination unit, configured to determine the traffic flow information of the target area according to the number of tire imprints in the pressure sensing image sequence and the corresponding relationship between each tire imprint and the vehicle.

7. An electronic device, characterized in that, It includes a processor, a memory, and a program or instruction stored on the memory and executable on the processor. When the program or instruction is executed by the processor, the steps of the method according to any one of claims 1-5 are implemented.

8. A readable storage medium, characterized in that, The program or instruction is stored on the readable storage medium. When the program or instruction is executed by the processor, the steps of the method according to any one of claims 1-5 are implemented.

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