Vehicle information identification methods and devices, storage media and electronic devices

Abstract

This application discloses a method, apparatus, storage medium, and electronic device for identifying vehicle information. The method includes: acquiring a vehicle departure trigger sequence, wherein the vehicle departure trigger sequence is a sequence in which a weighing sensor array is sequentially triggered by the vehicle; searching among multiple sample vehicles for a sample vehicle whose trigger sequence matches the vehicle departure trigger sequence, wherein the trigger sequence of each of the multiple sample vehicles is a sequence in which the weighing sensor array is sequentially triggered by each of the sample vehicles; and, if a target sample vehicle matching the vehicle is found, determining the vehicle information of the target sample vehicle as the vehicle information of the vehicle to be dispatched. This application solves the problem of high computational resource consumption in related vehicle information identification methods.

Description

Technical Field

[0001] This application relates to the field of vehicle identification, and more specifically, to a method and apparatus for identifying vehicle information, a storage medium, and an electronic device. Background Technology

[0002] To reduce safety hazards caused by overloaded freight vehicles and avoid traffic congestion due to low weighing efficiency during manual on-site vehicle weighing, a non-site enforcement system based on dynamic weighing can be used to dynamically weigh vehicles. This system ensures that vehicle weight measurement, license plate capture, matching, and data uploading are completed during normal vehicle movement. The dynamic weighing system within this system can include: a weighing sensor array installed on the road surface (e.g., strip sensors, wheel spoke sensors), and vehicle identification sensors (e.g., inductive loop detectors).

[0003] Currently, when there are vehicles waiting to be dispatched, the off-site law enforcement system can calculate the number of axles of the vehicle waiting to be dispatched, divide the vehicle into axles, and calculate the axle spacing based on the sensor trigger information of the vehicle waiting to be dispatched, thereby obtaining the vehicle information of the vehicle waiting to be dispatched.

[0004] Therefore, the above-mentioned method for identifying vehicle information of vehicles waiting to depart suffers from the problem of high computational resource consumption. Summary of the Invention

[0005] This application provides a method and apparatus for identifying vehicle information, a storage medium, and an electronic device, to at least solve the problems of complex judgment steps / conditions and high resource consumption in related technologies for identifying vehicle information.

[0006] According to one aspect of the embodiments of this application, a method for identifying vehicle information is provided, comprising: acquiring a vehicle departure trigger sequence, wherein the vehicle departure trigger sequence is a sequence in which a weighing sensor array is triggered sequentially by the vehicle departure; identifying a sample vehicle among a plurality of sample vehicles whose trigger sequence matches the vehicle departure trigger sequence, wherein the trigger sequence of each of the plurality of sample vehicles is a sequence in which the weighing sensor array is triggered sequentially by each of the sample vehicles; and, if it is confirmed that there is a target sample vehicle that matches the vehicle departure, determining the vehicle information of the target sample vehicle as the vehicle information of the vehicle departure.

[0007] In an exemplary embodiment, after obtaining the vehicle departure trigger sequence, the method further includes: detecting the integrity of the vehicle departure trigger sequence to obtain an integrity detection result; and if the integrity detection result indicates that the vehicle departure trigger sequence is incomplete, setting a target flag bit to a predetermined value, wherein the target flag bit is a flag bit used to indicate the integrity of the vehicle departure.

[0008] In one exemplary embodiment, identifying a sample vehicle whose trigger sequence matches the trigger sequence to be dispatched from among a plurality of sample vehicles includes: determining the sequence length of the trigger sequence to be dispatched to obtain a first sequence length; identifying sample vehicles whose trigger sequence length is not less than the first sequence length as sample vehicles to be matched; and identifying sample vehicles whose trigger sequence matches the trigger sequence to be dispatched from among the sample vehicles to be matched.

[0009] In one exemplary embodiment, identifying a sample vehicle whose trigger sequence matches the trigger sequence to be dispatched among a plurality of sample vehicles includes: determining the sequence similarity to each sample vehicle based on the trigger sequence to be dispatched and the trigger sequence of each sample vehicle; and identifying the sample vehicle whose trigger sequence matches the trigger sequence to be dispatched based on the sequence similarity to each sample vehicle.

[0010] In an exemplary embodiment, determining the sequence similarity to each sample vehicle based on the vehicle-to-departure trigger sequence and the trigger sequence of each sample vehicle includes: performing dynamic time warping analysis on the vehicle-to-departure trigger sequence and the trigger sequence of each sample vehicle to determine the sequence deviation between the vehicle-to-departure trigger sequence and the trigger sequence of each sample vehicle, thereby obtaining the sequence deviation corresponding to each sample vehicle, wherein the sequence deviation corresponding to each sample vehicle is negatively correlated with the sequence similarity corresponding to each sample vehicle.

[0011] In an exemplary embodiment, the step of identifying a sample vehicle whose trigger sequence matches the trigger sequence to be dispatched based on the sequence similarity corresponding to each sample vehicle includes: identifying the sample vehicle with the highest corresponding sequence similarity as a candidate sample vehicle; and identifying the candidate sample vehicle as a sample vehicle that matches the vehicle to be dispatched if the sequence similarity corresponding to the candidate sample vehicle is greater than or equal to a target similarity threshold.

[0012] In one exemplary embodiment, after confirming that a sample vehicle whose trigger sequence matches the vehicle to be dispatched trigger sequence among a plurality of sample vehicles, the method further includes: if it is confirmed that no sample vehicle matches the vehicle to be dispatched, outputting the vehicle to be dispatched trigger sequence to a target data file.

[0013] According to another aspect of the embodiments of this application, a vehicle information identification device is also provided, comprising: an acquisition unit, configured to acquire a vehicle departure trigger sequence of a vehicle to be dispatched, wherein the vehicle departure trigger sequence is a sequence in which a weighing sensor array is triggered sequentially by the vehicle to be dispatched; a matching unit, configured to identify a sample vehicle among a plurality of sample vehicles whose trigger sequence matches the vehicle departure trigger sequence, wherein the trigger sequence of each of the plurality of sample vehicles is a sequence in which the weighing sensor array is triggered sequentially by each of the sample vehicles; and a determination unit, configured to, when it is confirmed that there is a target sample vehicle that matches the vehicle to be dispatched, determine the vehicle information of the target sample vehicle as the vehicle information of the vehicle to be dispatched.

[0014] In one exemplary embodiment, the apparatus further includes: a detection unit, configured to detect the integrity of the vehicle departure trigger sequence after acquiring the vehicle departure trigger sequence, and obtain an integrity detection result; and a setting unit, configured to set a target flag bit to a predetermined value when the integrity detection result indicates that the vehicle departure trigger sequence is incomplete, wherein the target flag bit is a flag bit used to indicate the integrity of the vehicle departure.

[0015] In an exemplary embodiment, the matching unit includes: a first determining module, configured to determine the sequence length of the trigger sequence to be dispatched, thereby obtaining a first sequence length; a second determining module, configured to determine sample vehicles whose trigger sequence length is not less than the first sequence length as sample vehicles to be matched; and a first searching module, configured to search for sample vehicles whose trigger sequence matches the trigger sequence to be dispatched from the sample vehicles to be matched.

[0016] In one exemplary embodiment, the matching unit includes: a third determining module, configured to determine the sequence similarity to each sample vehicle based on the vehicle-to-departure trigger sequence and the trigger sequence of each sample vehicle; and a second searching module, configured to search for sample vehicles whose trigger sequences match the vehicle-to-departure trigger sequence based on the sequence similarity to each sample vehicle.

[0017] In an exemplary embodiment, the third determining unit includes: a fourth determining module, configured to perform dynamic time warping analysis on the vehicle-to-departure trigger sequence and the trigger sequence of each sample vehicle, determine the sequence deviation between the vehicle-to-departure trigger sequence and the trigger sequence of each sample vehicle, and obtain the sequence deviation corresponding to each sample vehicle, wherein the sequence deviation corresponding to each sample vehicle is negatively correlated with the sequence similarity corresponding to each sample vehicle.

[0018] In an exemplary embodiment, the second search module includes: a first determining submodule, configured to determine the sample vehicle with the highest corresponding sequence similarity as a candidate sample vehicle; and a second determining submodule, configured to determine the candidate sample vehicle as a sample vehicle matching the vehicle to be searched if the sequence similarity with the candidate sample vehicle is greater than or equal to a target similarity threshold.

[0019] In one exemplary embodiment, the apparatus further includes an output unit, configured to output the vehicle-to-depart trigger sequence to a target data file after searching for a sample vehicle whose trigger sequence matches the vehicle-to-depart trigger sequence among a plurality of sample vehicles, if no sample vehicle matching the vehicle-to-depart is found.

[0020] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer-readable storage medium, and the computer program is configured to execute the above-described vehicle information identification method when running.

[0021] According to another aspect of the embodiments of this application, an electronic device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the vehicle information identification method through the computer program.

[0022] In this embodiment, a method is adopted to match the trigger sequence of the vehicle to be dispatched with the trigger sequence of a sample vehicle. The trigger sequence of the vehicle to be dispatched is obtained, where the trigger sequence is the sequence in which the weighing sensor array is triggered sequentially by the vehicle to be dispatched. A sample vehicle whose trigger sequence matches the trigger sequence of the vehicle to be dispatched is found among multiple sample vehicles, where the trigger sequence of each sample vehicle is the sequence in which the weighing sensor array is triggered sequentially by each sample vehicle. When a target sample vehicle matching the vehicle to be dispatched is found, its vehicle information is determined as the vehicle information of the vehicle to be dispatched. Since the vehicle information is determined based on the matching result between the trigger sequence of the vehicle to be dispatched and the trigger sequence of the sample vehicle, there is no need to calculate the number of axes, sub-axles, and axle spacing. This reduces the operations required to calculate vehicle information, achieving the technical effect of reducing computational resource consumption and increasing dispatch speed. This solves the problem of high computational resource consumption in related vehicle information identification methods. Attached Figure Description

[0023] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0024] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a schematic diagram of the hardware environment of an optional vehicle information identification method according to an embodiment of this application;

[0026] Figure 2 This is a flowchart illustrating an optional vehicle information identification method according to an embodiment of this application;

[0027] Figure 3 This is a schematic diagram of an optional vehicle information identification method according to an embodiment of this application;

[0028] Figure 4 This is a flowchart illustrating an optional vehicle information identification method according to an embodiment of this application;

[0029] Figure 5 This is a structural block diagram of an optional electronic device according to an embodiment of this application. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0031] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0032] According to one aspect of the embodiments of this application, a method for identifying vehicle information is provided. Optionally, in this embodiment, the above-described vehicle information identification method can be applied to, for example... Figure 1 The hardware environment shown consists of a weighing sensor 102 and a server 104. Figure 1 As shown, server 104 is connected to load cell 102 via a network and can be used to provide services (such as application services) to smart devices or clients installed on smart devices. A database can be set up on the server or independently to provide data storage services to server 104. Load cell 102 can be, but is not limited to, strain gauges, narrow strip sensors, shaft assembly scales, etc.

[0033] The vehicle information identification method of this application embodiment can be executed by server 104, by weighing sensor 102, or by both server 104 and weighing sensor 102. Alternatively, the weighing sensor 102 can execute the vehicle information identification method of this application embodiment by a client installed on it.

[0034] Taking the vehicle information recognition method in this embodiment as an example, which is executed by server 104, Figure 2 This is a flowchart illustrating an optional vehicle information identification method according to an embodiment of this application, such as... Figure 2 As shown, the process of this method may include the following steps:

[0035] Step S202: Obtain the vehicle departure trigger sequence of the vehicle to be dispatched, wherein the vehicle departure trigger sequence is the sequence in which the weighing sensor array is triggered sequentially by the vehicle to be dispatched.

[0036] The vehicle information identification method in this embodiment can be applied to scenarios where vehicles leave a weighing area equipped with a weighing sensor array. The weighing sensors in the aforementioned weighing sensor array can be weighing sensors located on the highway, or they can be strain sensors, narrow strip sensors, axle array scales, etc.

[0037] In related technologies, when a vehicle is waiting to be dispatched, the server can calculate and determine vehicle information such as model, axle type, number of axles, and axle spacing based on information such as axle count, axle spacing, etc., resulting in a significant consumption of computing resources. To reduce the consumption of computing resources for calculating vehicle information, this solution can obtain the information by querying and comparing it with a pre-obtained standard library. If the comparison is successful, there is no need to perform the above calculation of vehicle information, thus minimizing resource consumption.

[0038] The weighing area may include at least one lane, and each lane may be equipped with a weighing sensor array (e.g., a narrow strip array). The weighing sensor array may contain multiple weighing sensors (e.g., two weighing sensors). Weighing sensors belonging to the same array may be arranged in parallel or non-parallel arrangements, for example, staggered left and right rows. This embodiment does not limit the arrangement of the weighing sensor array.

[0039] When a vehicle passes over the weighing sensor array, the weighing sensors it passes over are triggered, and the weighing sensors can record the detected weighing-related information. The weighing-related information may include, but is not limited to, at least one of the following: weight information detected by the weighing sensor, position information detected by the weighing sensor, trigger time information detected by the weighing sensor, etc., but this embodiment does not limit this.

[0040] It should be noted that when the load cell is a deformable load cell (e.g., a narrow strip), the process of detecting weight information by the load cell can involve first acquiring the deformation of the load cell, and then calculating the weight information of the vehicle passing through the load cell based on the deformation. After collecting the weighing-related information, each load cell can upload the collected weighing-related information to the server in real time, or it can simultaneously report the weighing-related information of at least one vehicle to the server at regular intervals. This embodiment does not limit this approach.

[0041] The server can receive weighing-related information uploaded by the weighing sensor array. This weighing-related information is sensor-level information. Based on this information, the server can determine whether vehicle separation is needed, whether vehicle dispatch is required, and perform different processing operations according to different scenarios.

[0042] When a vehicle meets the departure conditions, the server can first obtain the trigger sequence of the vehicle to be dispatched, that is, the departure trigger sequence, which is the sequence in which the weighing sensor array is triggered sequentially by the vehicle to be dispatched. Here, the departure conditions are the conditions that the vehicle must meet when it departs, which may include, but are not limited to, at least one of the following: the rear-mounted vehicle control coil is turned off; there is a 3-axle connection at the end of the vehicle; and the following vehicle is identified.

[0043] The aforementioned vehicle departure trigger sequence can be determined by the weighing-related information detected by the weighing sensors. The server can determine the order in which each weighing sensor in the weighing sensor array is triggered by the vehicle to be departed, based on the reception time of the weighing-related information matching the vehicle, thus obtaining the vehicle departure trigger sequence. The obtained vehicle departure trigger sequence is the sequence in which the weighing sensor array is triggered sequentially by the vehicle to be departed.

[0044] Step S204: Among multiple sample vehicles, identify the sample vehicle whose trigger sequence matches the trigger sequence of the vehicle to be dispatched. The trigger sequence of each sample vehicle is the sequence in which the weighing sensor array is triggered sequentially by each sample vehicle.

[0045] For a fixed sensor layout, the triggering order of the sensors is fixed when each specific vehicle type passes through the weighing area normally. Based on this, in this embodiment, the standard triggering order for multiple vehicle types is obtained beforehand through simulation or actual testing; that is, triggering sequences for multiple sample vehicles are obtained, where each sample vehicle's triggering sequence is the sequence in which the weighing sensor array is triggered sequentially by each sample vehicle. Optionally, each sample vehicle's triggering sequence may also include a forward triggering sequence and a reverse triggering sequence for each sample vehicle. The triggering sequences of multiple sample vehicles and other relevant information can be recorded in a standard library.

[0046] After obtaining the trigger sequence for the vehicle to be dispatched, the server can search among multiple sample vehicles for a sample vehicle whose trigger sequence matches the trigger sequence for the vehicle to be dispatched. For example, the server can match the trigger sequence for the vehicle to be dispatched with the trigger sequence corresponding to a sample vehicle. When the matching result shows that the similarity between the trigger sequence for the vehicle to be dispatched and the trigger sequence of a certain sample vehicle reaches a preset requirement, the sample vehicle is identified as the sample vehicle that matches the trigger sequence for the vehicle to be dispatched.

[0047] Step S206: If it is determined that there is a target sample vehicle that matches the vehicle to be dispatched, the vehicle information of the target sample vehicle is determined as the vehicle information of the vehicle to be dispatched.

[0048] Optionally, the standard library may contain the following information corresponding to each sample vehicle: vehicle type, number of axles, the corresponding sequence of sensors triggered when the vehicle travels in the forward / reverse direction through the weighing area (i.e., forward trigger sequence and reverse trigger sequence), and the number of vehicle axles corresponding to each trigger when passing normally (i.e., axle-by-axle result).

[0049] If a target sample vehicle matching the vehicle to be dispatched can be identified, the server can use a standard library or other methods to determine the vehicle information of the target sample vehicle as the vehicle information of the vehicle to be dispatched. For example, the model, number of axles, and axle information of the sample vehicle can be assigned to the current vehicle to be dispatched, and the task can be terminated.

[0050] If no matching target vehicle is identified, the system can determine whether the vehicle is driving abnormally (e.g., circling around an S-shape) based on its trigger sequence. Then, based on whether the driving is abnormal, the corresponding algorithm can be used to calculate the number of axles and axle division of the vehicle. Furthermore, the current trigger sequence can be logged for later analysis.

[0051] Through the above steps, the vehicle dispatch trigger sequence of the vehicle to be dispatched is obtained, wherein the vehicle dispatch trigger sequence is the sequence in which the weighing sensor array is triggered sequentially by the vehicle to be dispatched; among multiple sample vehicles, a sample vehicle whose trigger sequence matches the vehicle dispatch trigger sequence is found, wherein the trigger sequence of each sample vehicle is the sequence in which the weighing sensor array is triggered sequentially by each sample vehicle; when a target sample vehicle matching the vehicle to be dispatched is found, the vehicle information of the target sample vehicle is determined as the vehicle information of the vehicle to be dispatched. This solves the problem of high computational resource consumption in the vehicle information identification methods of related technologies, reduces computational resource consumption, and improves the dispatch speed.

[0052] It is understood that the solution in this application is a subsequent implementation step after vehicle allocation is completed. Therefore, in one exemplary embodiment, a method of vehicle allocation is provided, including:

[0053] When the execution conditions are met, multiple trajectories are determined based on the trigger position corresponding to each trigger information in the trigger information group, wherein each trigger information is the trigger information of the weighing sensor in the weighing area being triggered;

[0054] Based on the trajectory characteristics of each of the plurality of trajectories, at least one trajectory group is determined, wherein each trajectory group contains at least one of the plurality of trajectories.

[0055] Vehicle sorting is performed based on the at least one trajectory group to obtain at least one vehicle, wherein the at least one trajectory group corresponds one-to-one with the at least one vehicle;

[0056] For any vehicle that meets the departure conditions, determine the correspondence between the vehicle's departure signal and vehicle information to complete the vehicle allocation process.

[0057] The execution conditions include at least one of the following: obtaining a vehicle allocation signal from the vehicle allocation sensor, and the number of pending trigger information reaching a target number threshold, wherein the pending trigger information is trigger information to be placed into an existing trajectory.

[0058] Preferably, determining at least one trajectory group based on the trajectory characteristics of each of the plurality of trajectories includes:

[0059] Acquire multiple pending trigger information, wherein each pending trigger information is a trigger information to be placed into multiple existing trajectories, and the trigger information group includes the multiple pending trigger information and the trigger information in the multiple existing trajectories;

[0060] Based on the trigger position corresponding to each pending trigger information, each pending trigger information is matched with the multiple existing trajectories;

[0061] If each pending trigger information matches a corresponding existing trajectory, the updated multiple existing trajectories are obtained, wherein the updated multiple existing trajectories are the multiple trajectories.

[0062] Preferably, determining at least one trajectory group based on the trajectory characteristics of each of the plurality of trajectories further includes:

[0063] If there is a pending trigger information in the plurality of pending trigger information that does not match a corresponding existing trajectory, a clustering operation is performed on all the trigger information in the trigger information group to obtain the plurality of trajectories, wherein each of the plurality of trajectories corresponds to a first cluster obtained by clustering.

[0064] Preferably, determining at least one trajectory group based on the trajectory characteristics of each of the plurality of trajectories includes:

[0065] Based on the first trajectory feature of each trajectory, a first trajectory among the plurality of trajectories is determined, wherein the first trajectory is the trajectory corresponding to a vehicle with two wheels, each first trajectory is a first trajectory group, and the first trajectory feature includes at least one of the following: trajectory pressure maximum value, trajectory trigger number, trajectory trigger width;

[0066] The other trajectories are double-traversed along the first direction according to the second trajectory features to obtain the second trajectory group. The other trajectories are the trajectories other than the first trajectory among the multiple trajectories. The second trajectory features include at least one of the following: trajectory width, trajectory position, trajectory direction, trajectory speed, trajectory start and end time. The at least one trajectory group includes all the first trajectory groups and all the second trajectory groups. The first direction is the direction from one end of the other trajectory to the other end of the other trajectory.

[0067] Preferably, determining at least one trajectory group based on the trajectory characteristics of each of the plurality of trajectories includes:

[0068] The multiple trajectories are double-traversed along the second direction according to the second trajectory feature to obtain the at least one trajectory group, wherein the second trajectory feature includes at least one of the following: trajectory width, trajectory position, trajectory direction, trajectory speed, trajectory start and end time, and the second direction is the direction from one end of the multiple trajectories to the other end of the multiple trajectories.

[0069] Preferably, the plurality of trajectories are double-traversed along the second direction according to the second trajectory features to obtain the at least one trajectory group, including:

[0070] Based on the trajectory positions of the second trajectory and the third trajectory, the horizontal spacing between the second trajectory and the third trajectory is determined, wherein the second trajectory and the third trajectory are the currently traversed trajectories;

[0071] The overlap time between the second trajectory and the third trajectory is determined based on the start and end times of the second trajectory and the start and end times of the third trajectory.

[0072] If the horizontal spacing is within the first spacing range, the trajectory width of the second trajectory and the trajectory width of the third trajectory are both within the first width range, and the overlap time is greater than or equal to the first time threshold, then the second trajectory and the third trajectory are determined as the first sub-trajectory group.

[0073] If the second trajectory and the third trajectory are the same trajectory, and the trajectory width of the second trajectory is within the range of the second width, the second trajectory is determined as the second sub-trajectory group;

[0074] When the width of the second trajectory and the width of the third trajectory are both within the range of the third width, the second trajectory and the third trajectory are determined as a third sub-trajectory group;

[0075] When the width of the second trajectory and the width of the third trajectory are both within the fourth width range, and the lateral spacing is within the second spacing range, the second trajectory and the third trajectory are determined as the fourth sub-trajectory group.

[0076] In one exemplary embodiment, after obtaining the departure trigger sequence of the vehicle to be dispatched, the above method further includes:

[0077] S11, check the integrity of the vehicle dispatch trigger sequence and obtain the integrity check result;

[0078] S12, if the integrity detection result indicates that the trigger sequence of the vehicle to be dispatched is incomplete, the target flag bit is set to a predetermined value, wherein the target flag bit is a flag bit used to indicate the integrity of the vehicle to be dispatched.

[0079] Incomplete trigger sequences for vehicles awaiting dispatch can affect the matching results between these sequences and the trigger sequences of sample vehicles. For example, if the trigger sequence for a vehicle awaiting dispatch is 1234, while the server records the trigger sequence for sample vehicle A as 123456 and the trigger sequence for sample vehicle B as 123457, the incomplete trigger sequence for the vehicle awaiting dispatch will prevent the server from determining whether the vehicle awaiting dispatch is sample vehicle A or sample vehicle B based on its trigger sequence.

[0080] Therefore, in this embodiment, after obtaining the departure trigger sequence of the vehicle to be dispatched, the server can check the integrity of the obtained departure trigger sequence and obtain an integrity check result. If the integrity check result indicates that the departure trigger sequence is complete, the server can search for sample vehicles whose trigger sequences match the departure trigger sequence among multiple sample vehicles, thereby reducing the resource consumption of the process of determining the vehicle information of the vehicle to be dispatched.

[0081] If the trigger sequence for the vehicle to be dispatched is incomplete, it may be impossible to find a sample vehicle whose trigger sequence matches the trigger sequence for the vehicle to be dispatched among multiple sample vehicles. Therefore, in this embodiment, when the integrity detection result indicates that the trigger sequence for the vehicle to be dispatched is incomplete, the target flag can be set to a predetermined value. The target flag is a flag used to indicate the integrity of the vehicle to be dispatched.

[0082] Optionally, the target flag can be a vehicle assignment error flag, which can be set to 1 when an incomplete vehicle dispatch trigger sequence is detected. Each vehicle to be dispatched (e.g., a pre-built vehicle) has a corresponding vehicle assignment error flag, which can be a flag stored on the server corresponding to each vehicle to be dispatched. When a vehicle assignment error occurs, this vehicle assignment error flag is set to 1; if no vehicle assignment error occurs, the vehicle assignment error flag is set to 0. Therefore, the integrity of the vehicles to be dispatched can be determined based on this vehicle assignment error flag.

[0083] In this embodiment, the integrity of the trigger sequence of the vehicle to be dispatched is checked before trigger sequence matching, and vehicles with incomplete trigger sequences are marked. This can reduce unnecessary resource consumption and speed up the process of determining the vehicle information of the vehicle to be dispatched.

[0084] In one exemplary embodiment, finding a sample vehicle whose trigger sequence matches the trigger sequence to be dispatched among a plurality of sample vehicles includes:

[0085] S21, determine the sequence length of the trigger sequence to be dispatched, and obtain the first sequence length;

[0086] S22, identify the sample vehicles whose trigger sequence length is not less than the first sequence length as the sample vehicles to be matched;

[0087] S23, find the sample vehicles whose trigger sequence matches the trigger sequence of the vehicle to be dispatched from the sample vehicles to be matched.

[0088] This embodiment simplifies the process of determining the sample vehicle to be dispatched by matching the trigger sequence of the selected sample vehicle with the vehicle to be dispatched, thereby improving the efficiency of vehicle dispatch.

[0089] In one exemplary embodiment, finding a sample vehicle whose trigger sequence matches the trigger sequence to be dispatched among a plurality of sample vehicles includes:

[0090] S31, Based on the trigger sequence of the vehicle to be dispatched and the trigger sequence of each sample vehicle, determine the sequence similarity with each sample vehicle;

[0091] S32, based on the sequence similarity to each sample vehicle, find sample vehicles whose trigger sequence matches the trigger sequence to be dispatched.

[0092] Because vehicles of the same model will generate sufficiently similar vehicle trigger sequences when passing through the same weighing sensor array, even if their speed and state (e.g., whether they are empty or overloaded) change, the sample vehicle matching the vehicle to be dispatched can be determined based on the sequence similarity between the trigger sequence of the vehicle to be dispatched and the trigger sequence of the sample vehicle.

[0093] The server can first determine the trigger sequence of the vehicle to be dispatched and the sequence similarity with the trigger sequence of each sample vehicle. The determined sequence similarity is the sequence similarity corresponding to each sample vehicle. Then, based on the sequence similarity corresponding to each sample vehicle, the server can find the sample vehicles whose trigger sequences match the trigger sequence of the vehicle to be dispatched.

[0094] When identifying sample vehicles whose trigger sequence matches the vehicle dispatch trigger sequence, the difference between each sample vehicle and the one with the smallest difference that is less than a threshold can be calculated, and the sample vehicle sequence corresponding to this smallest difference can be used as the vehicle dispatch trigger sequence. This embodiment does not impose any limitations on this.

[0095] For example, with a similarity threshold of 90%, the server can identify the sample vehicle corresponding to the trigger sequence that has a 95% similarity to the trigger sequence to be dispatched as the sample vehicle that matches the trigger sequence to be dispatched.

[0096] This embodiment improves the accuracy of identifying sample vehicles by finding a matching sample vehicle based on the trigger sequence of the vehicle to be dispatched and the sequence similarity with the trigger sequence of each sample vehicle.

[0097] In one exemplary embodiment, determining the sequence similarity to each sample vehicle based on the vehicle dispatch trigger sequence and the trigger sequence of each sample vehicle includes:

[0098] S41, Perform dynamic time warping analysis on the vehicle dispatch trigger sequence and the trigger sequence of each sample vehicle to determine the sequence deviation between the vehicle dispatch trigger sequence and the trigger sequence of each sample vehicle, and obtain the sequence deviation corresponding to each sample vehicle. The sequence deviation corresponding to each sample vehicle is negatively correlated with the sequence similarity corresponding to each sample vehicle.

[0099] In this embodiment, sequence similarity can be characterized by sequence deviation. There is a negative correlation between sequence similarity and sequence deviation; that is, the higher the sequence similarity, the smaller the sequence deviation, and vice versa. The server can perform DTW (Dynamic Time Warping) analysis on the trigger sequence to be dispatched and the trigger sequence of each sample vehicle to determine the sequence deviation between the trigger sequence to be dispatched and the trigger sequence of each sample vehicle, thereby obtaining the sequence deviation corresponding to each sample vehicle.

[0100] Here, the DTW algorithm can be applied to compare the similarity of two time series. This algorithm is not sensitive to sequence stretching, compression, or even omissions. In this embodiment, the DTW algorithm is used to compare the similarity of two discrete trigger sequences, that is, to compare the similarity between the vehicle-to-depart trigger sequence and the trigger sequence of each sample vehicle. The comparison can be based on the sensor's row number, column number, sensor number, and several discrete features or combinations thereof.

[0101] For example, by checking whether a series of triggering features (such as the number of sensor trigger rows) given by the sensor array when the vehicle passes through the weighing area are close enough to a pre-recorded standard sequence, it can be determined whether the current vehicle model is consistent with the vehicle model corresponding to the standard sequence. If they are close enough (the sequence distance is less than a set threshold), it can be determined that the current vehicle model is consistent with the vehicle model corresponding to the standard sequence.

[0102] Since calculating the sequence deviation between the vehicle to be dispatched and each sample vehicle consumes a lot of time, in order to reduce the time consumption of calculating the above sequence deviation, the sequence deviation between the vehicle to be dispatched and each sample vehicle can be calculated in parallel to speed up the calculation.

[0103] It should be noted that the process of determining the sequence deviation between the trigger sequence to be dispatched and the trigger sequence of each sample vehicle can be achieved not only by using the dynamic time warping algorithm described above, but also by using the variance between the sequence deviation between the trigger sequence to be dispatched and the trigger sequence of each sample vehicle. This embodiment does not limit this method.

[0104] In this embodiment, by performing dynamic time warping analysis on the trigger sequence of the vehicle to be dispatched and the trigger sequence of each sample vehicle, the sequence deviation between the trigger sequence of the vehicle to be dispatched and the trigger sequence of each sample vehicle can be determined, thereby improving the accuracy of determining the sequence similarity corresponding to each sample vehicle.

[0105] In one exemplary embodiment, finding sample vehicles whose trigger sequences match the trigger sequence to be dispatched, based on the sequence similarity corresponding to each sample vehicle, includes:

[0106] S51, the sample vehicle with the highest sequence similarity is determined as the candidate sample vehicle;

[0107] S52, if the sequence similarity to the candidate sample vehicle is greater than or equal to the target similarity threshold, the candidate sample vehicle is determined as the sample vehicle that matches the vehicle to be output.

[0108] In this embodiment, after determining the sequence similarity between the vehicle to be dispatched and each sample vehicle, the sample vehicle with the highest sequence similarity can be identified as a candidate sample vehicle. Then, it is determined whether the sequence similarity between the candidate sample vehicle and the candidate sample vehicle is greater than or equal to the target similarity threshold, thereby determining whether the candidate sample vehicle is a sample vehicle that matches the vehicle to be dispatched.

[0109] Optionally, if the sequence similarity to the candidate sample vehicle is less than the target similarity threshold, it can be determined that there is no sample vehicle matching the vehicle to be dispatched. The following situations may lead to no sample vehicle matching the vehicle to be dispatched: the vehicle to be dispatched has a special model and is not included in the standard library; the vehicle to be dispatched exhibits abnormal driving behavior when passing through the weighing area, such as swerving in an S-shape or driving diagonally. In this case, the vehicle information can be determined and the dispatch operation performed according to the conventional vehicle dispatch method; this embodiment does not limit this. In addition, an error message can be reported to the backend server to promptly remind relevant personnel to handle the situation. The aforementioned prompt message can be a voice prompt or a pop-up prompt; this embodiment does not limit the type of prompt.

[0110] In this embodiment, by finding the sample vehicle with the highest sequence similarity and determining whether the sequence similarity between the sample vehicle and the vehicle to be dispatched exceeds a set similarity threshold, it is possible to determine whether the sample vehicle is a matching sample vehicle for the vehicle to be dispatched. This can improve the accuracy of identifying the sample vehicle that matches the vehicle to be dispatched, thereby improving the accuracy of identifying the vehicle information of the vehicle to be dispatched.

[0111] In one exemplary embodiment, after searching among multiple sample vehicles for a sample vehicle whose trigger sequence matches the trigger sequence to be dispatched, the method further includes:

[0112] S61, if no sample vehicle matching the vehicle to be dispatched is found, the vehicle dispatching trigger sequence is output to the target data file.

[0113] In this embodiment, after searching for a sample vehicle whose trigger sequence matches the vehicle to be dispatched trigger sequence among multiple sample vehicles, if no sample vehicle matching the vehicle to be dispatched is found, the vehicle to be dispatched trigger sequence can be output to the target data file so that relevant personnel can perform data analysis to determine the reason for the non-match (e.g., vehicle model not recorded, vehicle abnormal driving). Different processing is performed for different reasons. For example, if the vehicle model is not recorded, it can be improved by continuously supplementing the standard library. If the vehicle is abnormally driving and has been billed normally, it is ignored. Otherwise, abnormal billing is recorded.

[0114] In this embodiment, when no matching sample vehicle is found, the trigger sequence for the vehicle to be dispatched is output to the target data file, which facilitates the improvement of the sample library and thus improves the dispatch efficiency of this type of vehicle in the future.

[0115] The vehicle information identification method in this application embodiment is explained below with reference to optional examples. The vehicle information identification method in this optional example can be applied to multi-channel narrow strips with single / multi-row layouts, laterally spaced stress / strain sensor arrays, and other types of sensor arrays capable of providing trigger positions perpendicular to the driving direction and with sufficient spatial resolution. Due to this characteristic, for dynamic weighing scenarios involving multi-sensor fusion, different sensor subsystems can share the vehicle identification logic described in this solution.

[0116] The overall approach of this optional example is as follows: when the vehicle dispatch conditions are met, determine the vehicle to be dispatched, search for sample vehicles in the standard library based on the trigger sequence of the vehicle to be dispatched, find the model with the highest similarity to the sequence and greater than the set threshold, and use this model as the model of the current vehicle to be dispatched. At the same time, the number of axles and the axle distribution of the vehicle can also be obtained directly from the table without recalculation.

[0117] Combination Figure 3 As shown, the process for determining vehicle model and axle using a standard trigger sequence in this optional example may include the following steps:

[0118] Step S302, Begin.

[0119] Step S304: Sensor sequence integrity detection passed.

[0120] After the vehicle meets the departure conditions, it receives a trigger sequence for trigger sequence integrity check. If the check passes, proceed to step S308; otherwise, proceed to step S306.

[0121] Step S306: Set the vehicle error flag to position 1.

[0122] If the vehicle is deemed to have made a wrong departure signal or a wrong vehicle assignment, the corresponding flag is set to 1 and the process is returned, and step S326 is executed.

[0123] Step S308: Calculate the current trigger sequence length N.

[0124] Step S310: Determine whether the length of the current sequence is greater than N.

[0125] Traverse the standard library and select sequences with a length greater than or equal to N. If the length of the current sequence is greater than N, then execute step S312.

[0126] In step S312, the DTW algorithm calculates the deviation between the two sequences.

[0127] Perform DTW analysis sequentially, calculate and record sequence bias.

[0128] Step S314: Find the minimum deviation.

[0129] After completing the traversal, find the standard library sample with the smallest deviation.

[0130] Step S316: Determine whether the minimum deviation is less than the set threshold.

[0131] If the deviation is less than the set threshold, it proves that the two sequences are close enough. The vehicle model, number of axles, and axle information corresponding to the sample are assigned to the current vehicle, and step S326 is executed. Otherwise, step S318 is executed.

[0132] Step S318: Determine abnormal driving.

[0133] The trigger sequence is used to determine whether the anomaly is due to abnormal driving. This step might be triggered because the vehicle model is unique and not included in the standard library, or because the vehicle's driving behavior was abnormal when passing through the weighing area, such as swerving in an S-shape or driving at an angle. The former can be addressed by continuously adding to the standard library, while the latter can be resolved using conventional algorithms.

[0134] Step S320: Calculate the number of axes.

[0135] The current number of axles of the vehicle is calculated using a conventional algorithm.

[0136] Step S322: Calculate the axis splitting results.

[0137] The results of the biaxial calculation are then calculated using a conventional algorithm.

[0138] Step S324: Record the trigger sequence to the log.

[0139] Record the current trigger sequence in the log for later analysis.

[0140] Step S326, End.

[0141] Mission complete.

[0142] With this optional example, the vehicle model / axle type / number of axles / axle spacing results are obtained by querying and comparing with a pre-existing standard library, eliminating the need to calculate the number of axles, axle spacing, and axle distance, thus consuming fewer resources and speeding up vehicle dispatch.

[0143] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0144] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM (Read-Only Memory) / RAM (Random Access Memory), magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0145] According to another aspect of the embodiments of this application, a vehicle information identification device for implementing the above-described vehicle information identification method is also provided. Figure 4 This is a structural block diagram of an optional vehicle information recognition device according to an embodiment of this application, such as... Figure 4 As shown, the device may include:

[0146] The acquisition unit 402 is used to acquire the vehicle departure trigger sequence of the vehicle to be dispatched, wherein the vehicle departure trigger sequence is the sequence in which the weighing sensor array is triggered sequentially by the vehicle to be dispatched;

[0147] The matching unit 404, connected to the acquisition unit 402, is used to identify the sample vehicle whose trigger sequence matches the trigger sequence to be dispatched among multiple sample vehicles. The trigger sequence of each sample vehicle among the multiple sample vehicles is the sequence in which the weighing sensor array is triggered sequentially by each sample vehicle.

[0148] The determining unit 406, connected to the matching unit 404, is used to determine the vehicle information of the target sample vehicle as the vehicle information of the vehicle to be dispatched when it is confirmed that there is a target sample vehicle that matches the vehicle to be dispatched.

[0149] It should be noted that the acquisition unit 402 in this embodiment can be used to execute the above step S202, the matching unit 404 in this embodiment can be used to execute the above step S204, and the determination unit 406 in this embodiment can be used to execute the above step S206.

[0150] The above modules are used to obtain the vehicle dispatch trigger sequence, which is the sequence in which the weighing sensor array is triggered sequentially by the vehicle to be dispatched. A sample vehicle whose trigger sequence matches the vehicle dispatch trigger sequence is searched among multiple sample vehicles, where the trigger sequence for each sample vehicle is the sequence in which the weighing sensor array is triggered sequentially by each sample vehicle. When a target sample vehicle matching the vehicle to be dispatched is found, the vehicle information of the target sample vehicle is determined as the vehicle information of the vehicle to be dispatched. This solves the problem of high computational resource consumption in vehicle information identification methods in related technologies, reduces resource consumption during the identification process, and improves the speed of the identification process.

[0151] In one exemplary embodiment, the above-described apparatus further includes:

[0152] The detection unit is used to detect the integrity of the vehicle departure trigger sequence after acquiring the vehicle departure trigger sequence, and obtain the integrity detection result.

[0153] The setting unit is used to set the target flag bit to a predetermined value when the integrity detection result indicates that the trigger sequence of the vehicle to be dispatched is incomplete. The target flag bit is a flag bit used to indicate the integrity of the vehicle to be dispatched.

[0154] In one exemplary embodiment, the matching unit includes:

[0155] The first determining module is used to determine the sequence length of the trigger sequence to be dispatched, and to obtain the first sequence length;

[0156] The second determining module is used to determine sample vehicles whose trigger sequence length is the first sequence length as sample vehicles to be matched.

[0157] The first search module is used to find sample vehicles whose trigger sequences match the trigger sequence to be dispatched from the sample vehicles to be matched.

[0158] In one exemplary embodiment, the matching unit includes:

[0159] The third determination module is used to determine the sequence similarity to each sample vehicle based on the trigger sequence to be dispatched and the trigger sequence of each sample vehicle.

[0160] The second search module is used to find sample vehicles whose trigger sequences match the trigger sequences to be dispatched, based on the sequence similarity to each sample vehicle.

[0161] In one exemplary embodiment, the third determining unit includes:

[0162] The fourth determination module is used to perform dynamic time warping analysis on the trigger sequence of the vehicle to be dispatched and the trigger sequence of each sample vehicle, determine the sequence deviation between the trigger sequence of the vehicle to be dispatched and the trigger sequence of each sample vehicle, and obtain the sequence deviation corresponding to each sample vehicle. The sequence deviation corresponding to each sample vehicle is negatively correlated with the sequence similarity corresponding to each sample vehicle.

[0163] In one exemplary embodiment, the second lookup module includes:

[0164] The first determination submodule is used to determine the sample vehicle with the highest corresponding sequence similarity as the candidate sample vehicle;

[0165] The second determination submodule is used to determine the candidate sample vehicle as the sample vehicle that matches the vehicle to be output when the sequence similarity corresponding to the candidate sample vehicle is greater than or equal to the target similarity threshold.

[0166] In one exemplary embodiment, the above-described apparatus further includes:

[0167] The output unit is used to find a sample vehicle whose trigger sequence matches the trigger sequence of the vehicle to be dispatched among multiple sample vehicles, and if no sample vehicle matching the trigger sequence is found, output the trigger sequence of the vehicle to be dispatched to the target data file.

[0168] It should be noted that the examples and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the content disclosed in the above embodiments. It should also be noted that the above modules, as part of a device, can operate in environments such as... Figure 1 The hardware environment shown can be implemented through software or hardware, and the hardware environment includes the network environment.

[0169] According to another aspect of the embodiments of this application, a storage medium is also provided. Optionally, in this embodiment, the storage medium can be used to execute program code for the vehicle information identification method described above in the embodiments of this application.

[0170] Optionally, in this embodiment, the storage medium may be located on at least one of the network devices in the network shown in the above embodiment.

[0171] Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps:

[0172] S1, obtain the vehicle departure trigger sequence of the vehicle to be dispatched, wherein the vehicle departure trigger sequence is the sequence in which the weighing sensor array is triggered sequentially by the vehicle to be dispatched;

[0173] S2, find the sample vehicle whose trigger sequence matches the trigger sequence of the vehicle to be dispatched among multiple sample vehicles, wherein the trigger sequence of each sample vehicle among the multiple sample vehicles is the sequence in which the weighing sensor array is triggered sequentially by each sample vehicle.

[0174] S3, if a target sample vehicle matching the vehicle to be dispatched is found, the vehicle information of the target sample vehicle is determined as the vehicle information of the vehicle to be dispatched.

[0175] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments, and will not be repeated in this embodiment.

[0176] Optionally, in this embodiment, the storage medium may include, but is not limited to, various media capable of storing program code, such as USB flash drives, ROMs, RAMs, portable hard drives, magnetic disks, or optical disks.

[0177] According to another aspect of the embodiments of this application, an electronic device for implementing the above-described vehicle information identification method is also provided. The electronic device may be a server, a terminal, or a combination thereof.

[0178] Figure 5 This is a structural block diagram of an optional electronic device according to an embodiment of this application, such as... Figure 5 As shown, it includes a processor 502, a communication interface 504, a memory 506, and a communication bus 508. The processor 502, communication interface 504, and memory 506 communicate with each other via the communication bus 508.

[0179] Memory 506 is used to store computer programs;

[0180] When processor 502 executes a computer program stored in memory 506, it performs the following steps:

[0181] S1, obtain the vehicle departure trigger sequence of the vehicle to be dispatched, wherein the vehicle departure trigger sequence is the sequence in which the weighing sensor array is triggered sequentially by the vehicle to be dispatched;

[0182] S2, find the sample vehicle whose trigger sequence matches the trigger sequence of the vehicle to be dispatched among multiple sample vehicles, wherein the trigger sequence of each sample vehicle among the multiple sample vehicles is the sequence in which the weighing sensor array is triggered sequentially by each sample vehicle.

[0183] S3, if a target sample vehicle matching the vehicle to be dispatched is found, the vehicle information of the target sample vehicle is determined as the vehicle information of the vehicle to be dispatched.

[0184] Optionally, in this embodiment, the communication bus can be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. This communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, Figure 5 The symbol is represented by a single thick line, but this does not indicate that there is only one bus or one type of bus. The communication interface is used for communication between the aforementioned electronic device and other devices.

[0185] The memory may include RAM, or non-volatile memory, such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0186] As an example, the memory 506 described above may include, but is not limited to, the acquisition unit 402, the matching unit 404, and the determination unit 408 of the vehicle information recognition device. Furthermore, it may include, but is not limited to, other module units of the vehicle information recognition device described above, which will not be elaborated upon in this example.

[0187] The processors mentioned above can be general-purpose processors, including but not limited to: CPU (Central Processing Unit), NP (Network Processor), etc.; they can also be DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0188] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments, and will not be repeated here. The sequence numbers of the embodiments in this application are merely for description and do not represent the superiority or inferiority of the embodiments.

[0189] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for identifying vehicle information, characterized in that, include: Obtain the vehicle departure trigger sequence of the vehicle to be dispatched, wherein the vehicle departure trigger sequence is a sequence in which the weighing sensor array is triggered sequentially by the vehicle to be dispatched; Among multiple sample vehicles, identify the sample vehicle whose trigger sequence matches the trigger sequence to be dispatched, wherein the trigger sequence of each of the multiple sample vehicles is the sequence in which the weighing sensor array is triggered sequentially by each of the sample vehicles; If it is confirmed that there is a target sample vehicle that matches the vehicle to be dispatched, the vehicle information of the target sample vehicle is determined as the vehicle information of the vehicle to be dispatched. The standard library includes the following information corresponding to each sample vehicle: vehicle type, number of axles, the corresponding sequence of sensor triggers when the vehicle travels forward / backward through the weighing area, and the number of vehicle axles corresponding to each trigger when passing normally. The method further includes: if it is confirmed that there is a target sample vehicle that matches the vehicle to be dispatched, the vehicle information of the target sample vehicle is assigned to the vehicle to be dispatched by searching the standard library. The vehicle information of the target sample vehicle includes: vehicle type, number of axles, and axle information.

2. The method according to claim 1, characterized in that, After obtaining the vehicle departure trigger sequence, the method further includes: The integrity of the vehicle departure trigger sequence is checked to obtain the integrity check result; If the integrity detection result indicates that the vehicle to be dispatched trigger sequence is incomplete, the target flag bit is set to a predetermined value, wherein the target flag bit is a flag bit used to indicate the integrity of the vehicle to be dispatched.

3. The method according to claim 1, characterized in that, The step of identifying sample vehicles whose trigger sequence matches the trigger sequence to be dispatched among multiple sample vehicles includes: Determine the sequence length of the trigger sequence to be dispatched, and obtain the first sequence length; Vehicles whose trigger sequence length is not less than the length of the first sequence are identified as vehicles to be matched. Identify sample vehicles whose trigger sequences match the trigger sequence of the vehicle to be dispatched from the sample vehicles to be matched.

4. The method according to claim 1, characterized in that, The step of identifying sample vehicles whose trigger sequence matches the trigger sequence to be dispatched among multiple sample vehicles includes: Based on the vehicle dispatch trigger sequence and the trigger sequence of each sample vehicle, determine the sequence similarity to each sample vehicle; Based on the sequence similarity to each sample vehicle, the sample vehicles whose trigger sequences match the trigger sequences to be dispatched are identified.

5. The method according to claim 4, characterized in that, The step of determining the sequence similarity to each sample vehicle based on the trigger sequence to be dispatched and the trigger sequence of each sample vehicle includes: Dynamic time warping analysis is performed on the vehicle-to-departure trigger sequence and the trigger sequence of each sample vehicle to determine the sequence deviation between the vehicle-to-departure trigger sequence and the trigger sequence of each sample vehicle, thereby obtaining the sequence deviation corresponding to each sample vehicle. The sequence deviation corresponding to each sample vehicle is negatively correlated with the sequence similarity corresponding to each sample vehicle.

6. The method according to claim 4, characterized in that, The step of identifying sample vehicles whose trigger sequences match the pending dispatch trigger sequence based on the sequence similarity to each sample vehicle includes: The sample vehicle with the highest sequence similarity is identified as the candidate sample vehicle; If the sequence similarity to the candidate sample vehicle is greater than or equal to the target similarity threshold, the candidate sample vehicle is determined as a sample vehicle that matches the vehicle to be dispatched.

7. The method according to any one of claims 1 to 6, characterized in that, After identifying a sample vehicle whose trigger sequence matches the trigger sequence to be dispatched among multiple sample vehicles, the method further includes: If it is confirmed that there is no sample vehicle that matches the vehicle to be dispatched, the vehicle to be dispatched trigger sequence is output to the target data file.

8. A vehicle information identification device, characterized in that, include: The acquisition unit is used to acquire the vehicle departure trigger sequence of the vehicle to be dispatched, wherein the vehicle departure trigger sequence is a sequence in which the weighing sensor array is triggered sequentially by the vehicle to be dispatched; A matching unit is used to identify a sample vehicle whose trigger sequence matches the trigger sequence to be dispatched among a plurality of sample vehicles, wherein the trigger sequence of each sample vehicle among the plurality of sample vehicles is the sequence in which the weighing sensor array is triggered sequentially by each sample vehicle. The determining unit is used to determine the vehicle information of the target sample vehicle as the vehicle information of the vehicle to be dispatched when it is confirmed that there is a target sample vehicle that matches the vehicle to be dispatched. The standard library includes the following information corresponding to each sample vehicle: vehicle type, number of axles, the corresponding sequence of sensor triggers when the vehicle passes through the weighing area in the forward / reverse direction, and the number of vehicle axles corresponding to each trigger when passing normally. The device is also used to: when it is confirmed that there is a target sample vehicle that matches the vehicle to be dispatched, assign the vehicle information of the target sample vehicle to the vehicle to be dispatched by searching the standard library. The vehicle information of the target sample vehicle includes: vehicle type, number of axles, and axle information.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein the program, when executed, performs the method of any one of claims 1 to 7.

10. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to execute the method of any one of claims 1 to 7 through the computer program.

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