A fusion method of ETC toll lane transaction and plate recognition based on time sequence queue

Abstract

The technical solution of the present invention is to provide a method for integrating ETC toll lane transactions and license plate recognition based on a time series queue, which is characterized in that it includes the following steps: installing two sets of license plate recognition equipment in each ETC toll lane; establishing a hash table for storing the traffic relationship buffer of vehicles passing through the current ETC toll lane; constructing an empty transaction time series queue, a front license plate recognition time series queue, and a rear license plate recognition time series queue; receiving matched vehicle data; and performing matching judgment. The method for integrating ETC toll lane transactions and license plate recognition based on a time series queue disclosed by the present invention effectively improves the processing capability and matching efficiency of data analysis, and effectively filters the traffic data of the ETC toll lane that is normally matched, so that the highway audit work can focus on the traffic data of vehicles with abnormal traffic and abnormal transactions, greatly improving the efficiency of highway vehicle audits.

Description

Technical Field

[0001] The invention belongs to the field of intelligent transportation and relates to a data entry and retrieval method, in particular to a matching method of toll lane transactions and plate recognition based on a time sequence queue. Background Art

[0002] On January 1, 2020, the national highway toll station cancellation project was completed and opened to traffic. The national highway network was completed, and the integrated operation and smooth traffic were basically realized. ETC toll lanes mainly rely on the processing of information recorded in the pass medium to achieve unattended automatic transaction passage. Highway operators use the comparison of license plate recognition data, view information and ETC toll transaction data as an important means of highway toll audit. However, some drivers take risks in pursuit of maximizing economic benefits, using means such as duplicate license plates, passing through checkpoints, and changing pass media to evade or underpay tolls, which poses new challenges to toll audits.

[0003] At present, the ETC toll lane system on highways mainly uses DSRC 5.8G wireless microwave communication technology to transmit data with the on-board unit OBU to realize the reading and billing of vehicle passage information and generate ETC toll transaction data. This data mainly records the passage medium passing through the ETC lane and the vehicle and billing information recorded by the medium (hereinafter referred to as "ETC transaction timing data").

[0004] At the same time, the ETC toll lane system is deployed and installed with a digital high-definition license plate recognition and perception system (hereinafter referred to as the license plate recognition equipment), which captures and perceives the vehicles actually passing through the ETC toll lanes through license plate recognition, and captures video and image data of passing vehicles (hereinafter referred to as "license plate recognition data").

[0005] There are the following difficulties in the key technologies of data matching and association:

[0006] 1) The vehicle information recorded in the ETC transaction time series data is all recorded in the ETC device when the ETC device is processed, and there is no direct correlation with the actual passing vehicles;

[0007] 2) The perception ability of the card recognition equipment is greatly affected by weather, environment, and human interference, and there are certain false perceptions and omissions. Because the association matching rate is low only based on the card recognition time;

[0008] 3) When installing and arranging the license plate recognition equipment, it is often blocked by the vehicles in front and behind, resulting in perception omissions and interference with data matching and association. Summary of the invention

[0009] The purpose of the present invention is to efficiently and quickly achieve the matching association between toll lane transactions and license plate recognition data, thereby improving the difficulties of highway audit business.

[0010] In order to achieve the above object, the technical solution of the present invention is to provide a method for integrating ETC toll lane transaction and plate recognition based on a time sequence queue, which is characterized by comprising the following steps:

[0011] Step 1, two sets of license plate recognition devices are installed in each ETC toll lane. The first license plate recognition device along the driving direction is used to sense the front license plate information of the vehicle, and the second license plate recognition device along the driving direction is used to sense the rear license plate information of the vehicle. When a vehicle passes through the first license plate recognition device, front license plate recognition timing data Vh is generated, and when a vehicle passes through the second license plate recognition device, rear license plate recognition timing data Vt is generated. The front license plate recognition timing data Vh and the rear license plate recognition timing data Vt are used to describe whether the current vehicle is the first vehicle that passes through the first license plate recognition device or the second license plate recognition device in the current ETC toll lane within the current time period;

[0012] After a vehicle completes a transaction through the ETC toll lane system in each ETC toll lane, ETC transaction time series data T is generated. The ETC transaction time series data T describes whether the current vehicle is the first vehicle to complete a transaction through the ETC toll lane system in the current ETC toll lane within the current time period.

[0013] Based on the license plate and the front plate recognition time series data Vh, rear plate recognition time series data Vt and ETC transaction time series data T of the same vehicle, the vehicle passage data PR is constructed for each vehicle to carry the passage data association relationship of the vehicle passing through the ETC toll lane;

[0014] Step 2: Establish a hash table to store the traffic relationship of vehicles passing through the current ETC toll lane. Define the hash table as the vehicle cache. The license plate number is used as the key in the hash table, and the ETC transaction time series data T, the front plate recognition time series data Vh, and the rear plate recognition time series data Vt of the same license plate number are used as the value;

[0015] Step 3: construct an empty transaction time series queue, a front plate recognition time series queue, and a rear plate recognition time series queue to store ETC transaction time series data T, front plate recognition time series data Vh, and rear plate recognition time series data Vt, and realize the association fault tolerance of ETC transaction time series data and plate recognition data through the error threshold of the continuous time series in the queue;

[0016] Step 4: Receive ETC transaction timing data, vehicle head plate recognition timing data, and vehicle tail plate recognition timing data as matched vehicle data and put them into transaction timing queue, vehicle head plate recognition timing queue, and vehicle tail plate recognition timing queue;

[0017] Step 5: If there is vehicle traffic data in the vehicle cache that matches the matched vehicle data in the transaction timing queue, the front license plate recognition timing queue or the rear license plate recognition timing queue, it is determined that the timing error between the vehicle traffic data in the vehicle cache and the matched vehicle data is within the fault tolerance threshold, and the data in the transaction timing queue, the front license plate recognition timing queue or the rear license plate recognition timing queue that has the same license plate as the matched vehicle data is directly matched to the vehicle cache; after the matching is completed, recursively process the vehicles that have not been matched in the previous sequence;

[0018] Step 6: If there is no vehicle traffic data in the vehicle cache that matches the matched vehicle data in the transaction timing queue, the front license plate recognition timing queue, or the rear license plate recognition timing queue, and the current matched vehicle data is the tail of the transaction timing queue, the front license plate recognition timing queue, or the rear license plate recognition timing queue, construct the vehicle traffic data based on the current matched vehicle data and put it into the vehicle cache;

[0019] Step 7: If there is no vehicle traffic data in the vehicle cache that matches the matched vehicle data in the transaction timing queue, the front license plate recognition timing queue, or the rear license plate recognition timing queue, and the current matched vehicle data is not the tail of the transaction timing queue, the front license plate recognition timing queue, or the rear license plate recognition timing queue, the timing relationship matching process is performed;

[0020] If the matched vehicle data is the ETC transaction timing data T, the data to be matched are the front plate recognition timing data Vh and the rear plate recognition timing data Vt; if the matched vehicle data is the front plate recognition timing data Vh, the data to be matched are the ETC transaction timing data T and the rear plate recognition timing data Vt; if the matched vehicle data is the rear plate recognition timing data Vt, the data to be matched are the ETC transaction timing data T and the front plate recognition timing data Vh; the matched vehicle data are uniformly referred to by the matched data T1, the vehicle passage data PR1 in the vehicle cache is matched with the matched data T1, and the data to be matched are uniformly referred to by the to-be-matched data Vh1, then the timing relationship matching process includes the following steps:

[0021] Step 701, determine the previous data T0 of the matched data T1 in the transaction timing queue, the front plate recognition timing queue or the rear plate recognition timing queue. If there is no vehicle traffic data matching the data T0 in the vehicle cache, recursively process forward until data matching the vehicle traffic data in the vehicle cache is found in the transaction timing queue, the front plate recognition timing queue or the rear plate recognition timing queue, define the matched vehicle traffic data as vehicle traffic data PR0, and proceed to the next step;

[0022] Step 702: determine the data T2 after the matched data T1 in the transaction timing queue, the front plate recognition timing queue or the rear plate recognition timing queue. If there is no vehicle traffic data matching the data T2 in the vehicle cache, recursively process until data matching the vehicle traffic data in the vehicle cache is found in the transaction timing queue, the front plate recognition timing queue or the rear plate recognition timing queue. Define the matched vehicle traffic data as vehicle traffic data PR2 and proceed to the next step.

[0023] If the vehicle traffic data PR2 cannot be obtained, the processing is suspended and the process returns to step 5;

[0024] Step 703, determine whether there is other time series data Vhx between the ETC transaction time series data T, the front plate recognition time series data Vh or the rear plate recognition time series data Vt corresponding to the to-be-matched data Vh1 in the vehicle passage data PR0 and the ETC transaction time series data T, the front plate recognition time series data Vh or the rear plate recognition time series data Vt corresponding to the to-be-matched data Vh1 in the vehicle passage data PR2: If there is other time series data Vhx, then the ETC transaction time series data T, the front plate recognition time series data Vh or the rear plate recognition time series data Vt corresponding to the matched data T1 in the vehicle passage data PR1=T 1. The ETC transaction timing data T, the front plate recognition timing data Vh or the rear plate recognition timing data Vt corresponding to the timing data Vhx in the vehicle passage data PR1 are equal to Vhx; if there is no other timing data Vhx, then the ETC transaction timing data T, the front plate recognition timing data Vh or the rear plate recognition timing data Vt corresponding to the matched data T1 in the vehicle passage data PR1 are equal to T1, and the ETC transaction timing data T, the front plate recognition timing data Vh or the rear plate recognition timing data Vt corresponding to the timing data Vhx in the vehicle passage data PR1 are equal to null; after the matching is completed, return to step 5.

[0025] Preferably, in step 1, if the current vehicle is the vehicle that has completed the Mth transaction in the L lane at the current time D, the ETC transaction timing data T = LDM; if the current vehicle is the Mth license plate recognition by the first license plate recognition device in the L lane at the current time D, the vehicle front license plate recognition timing data Vh = LDM; if the current vehicle is the Mth license plate recognition by the second license plate recognition device in the L lane at the current time D, the vehicle front license plate recognition timing data Vt = LDM.

[0026] Preferably, in step 2, a bidirectional ordered linked list is used to design the transaction timing queue, the front plate recognition timing queue, and the rear plate recognition timing queue.

[0027] The method for integrating ETC toll lane transactions and license plate recognition based on time-series queues disclosed in the present invention effectively improves the processing capability and matching efficiency of data analysis, and effectively filters the traffic data normally matched by the ETC toll lanes, so that the highway audit work can focus on the traffic data of vehicles with abnormal traffic and abnormal transactions, greatly improving the efficiency of highway vehicle audits. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a schematic diagram of the installation layout of the ETC toll lane sign recognition equipment;

[0029] Figure 2 A schematic diagram of lane abstraction queue and timing fault tolerance;

[0030] Figure 3 For direct matching schematic diagram;

[0031] Figure 4 It shows before timing matching;

[0032] Figure 5 The timing relationship matching process is illustrated. DETAILED DESCRIPTION

[0033] The present invention will be further described below in conjunction with specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms fall within the scope limited by the appended claims of the application equally.

[0034] The method for integrating ETC toll lane transactions and sign recognition based on a time sequence queue disclosed in this embodiment specifically includes the following contents:

[0035] 1) Installation layout of brand recognition equipment:

[0036] like Figure 1 As shown, two sets of license plate recognition devices are installed in the ETC toll lane. The first license plate recognition device along the driving direction is used to sense the front license plate information of the vehicle, and the second license plate recognition device along the driving direction is used to sense the rear license plate information of the vehicle. The present invention can effectively reduce the phenomenon of missed shots caused by close occlusion of vehicles in the same direction by adding rear license plate recognition.

[0037] 2) Data Timing Design

[0038] The design of the time series constrains the uniqueness of the order within the same time and space, and will not cause matching errors due to changes in device clocks and inconsistencies in clock benchmarks.

[0039] An ETC vehicle passes through an ETC toll lane system at a specific time to complete a transaction. This process can be described in terms of time series: at time D (in hours), the Mth vehicle passes through the L lane, that is, the ETC transaction time series data T = LDM. The front license plate recognition time series data of the same vehicle can also be described as: at time D, the Mth license plate recognition in the L lane, that is, the front license plate recognition time series data Vh = LDM. The rear license plate recognition time series data of the same vehicle can also be described as: at time D, the Mth license plate recognition in the L lane, that is, the rear license plate recognition time series data Vt = LDM.

[0040] The ETC transaction time series data T, the front plate recognition time series data Vh and the rear plate recognition time series data Vt are the traffic data. Based on the license plate, the vehicle traffic data is constructed for each vehicle to carry the traffic data association relationship of the vehicle passing through the ETC toll lane. The code is shown as follows:

[0041] class PassRelation{

[0042] public string T;

[0043] public string Vh;

[0044] public string Vt;

[0045] }

[0046] For example, at 10:00 on October 1, 2022, the ETC transaction time series data completed by the first and second vehicles in the L lane can be recorded in order as L20221001100001 and L20221001100002, and the front license plate recognition time series data Vh and the rear license plate recognition time series data can also be recorded in order as L20221001100001 and L20221001100002, that is:

[0047] PR1={T:L20221001100001,Vh:L20221001100001,Vt:L20221001100001};

[0048] PR2={T:L20221001100002,Vh:L20221001100002,Vt:L20221001100002};

[0049] PR1 and PR2 are the vehicle traffic data of the first vehicle and the second vehicle respectively.

[0050] 3) Lane timing queue design and fault tolerance:

[0051] The perception process of the card recognition device and the ETC transaction process are independent of each other, and the timing of a single data cannot be used as a direct relationship between the ETC transaction and the card recognition data.

[0052] For example, if the vehicle with license plate Beijing A0001 is the second vehicle sensed by the front and rear license plate recognition in the L lane at 0:00 on October 1, 2022, then the front license plate recognition time series data Vh = rear license plate recognition time series data Vt = L20221001000002. If the same vehicle is the first transaction in the L lane at 0:00 on October 1, 2022, then the ETC transaction time series data T = L20221001000001, that is, the vehicle traffic data PR1 of the vehicle with license plate Beijing A0001 is expressed as: PR1 = {T: L20221001000001, Vh: L20221001000002, Vt: L20221001000002}.

[0053] Therefore, a bidirectional ordered linked list is used to design the toll lane time series queue to carry the time series data of ETC transactions and license plate recognition in continuous time, and the error threshold of the continuous time series in the queue is used to achieve the association fault tolerance of ETC transaction time series data and license plate recognition data. Figure 2 As shown, the transaction of 0001 and the license plate recognition of 0002 can still be matched as a transaction pass for the same vehicle.

[0054] An ETC toll lane has ETC transaction time series data, vehicle head plate recognition time series data, and vehicle tail plate recognition time series data at the same time. That is, an ETC toll lane needs three ordered bidirectional linked lists and one hash table to be abstracted. The three ordered bidirectional linked lists are used to record ETC transaction time series data, vehicle head plate recognition time series data, and vehicle tail plate recognition time series data, respectively, and are defined as transaction time series queue, vehicle head plate recognition time series queue, and vehicle tail plate recognition time series queue. One hash table is used to store the vehicle traffic relationship cache (hereinafter referred to as "vehicle cache") of the current ETC toll lane, with the license plate number as the key and the ETC transaction time series data T, vehicle head plate recognition time series data Vh, and vehicle tail plate recognition time series data Vt of the same license plate number as the value. Multiple lanes are constructed in the hash table container using lane identifiers as keys.

[0055]

[0056]

[0057]

[0058] 4) The matching method based on the time sequence queue includes the following steps:

[0059] Step 1: Construct an empty transaction timing queue, a front plate recognition timing queue, and a rear plate recognition timing queue.

[0060] Step 2: Receive ETC transaction timing data, vehicle front plate recognition timing data, and vehicle rear plate recognition timing data as matched vehicle data and put them into the transaction timing queue, vehicle front plate recognition timing queue, and vehicle rear plate recognition timing queue.

[0061] Step 3: If there is vehicle traffic data in the vehicle cache that matches the matched vehicle data in the transaction timing queue, the front license plate recognition timing queue, or the rear license plate recognition timing queue, it is determined that the timing error between the vehicle traffic data in the vehicle cache and the matched vehicle data is within the fault tolerance threshold, such as Figure 3 As shown, directly match the data with the same license plate as the matched vehicle data in the transaction time sequence queue, the front license plate recognition time sequence queue or the rear license plate recognition time sequence queue to the vehicle cache. After the matching is completed, try to recursively process the vehicles that have not been matched in the previous sequence of vehicles.

[0062] Step 4: If there is no vehicle traffic data in the vehicle cache that matches the matched vehicle data in the transaction timing queue, the front license plate recognition timing queue or the rear license plate recognition timing queue, and the current matched vehicle data is at the end of the transaction timing queue, the front license plate recognition timing queue or the rear license plate recognition timing queue, the vehicle traffic data is constructed based on the current matched vehicle data and placed in the vehicle cache.

[0063] Step 5: If there is no vehicle traffic data in the vehicle cache that matches the matched vehicle data in the transaction timing queue, the front license plate recognition timing queue or the rear license plate recognition timing queue, and the current matched vehicle data is not the end of the transaction timing queue, the front license plate recognition timing queue or the rear license plate recognition timing queue, the timing relationship matching process is performed.

[0064] If the matched vehicle data is the ETC transaction timing data T, the data that needs to be matched are the front plate recognition timing data Vh and the rear plate recognition timing data Vt; if the matched vehicle data is the front plate recognition timing data Vh, the data that needs to be matched are the ETC transaction timing data T and the rear plate recognition timing data Vt; if the matched vehicle data is the rear plate recognition timing data Vt, the data that needs to be matched are the ETC transaction timing data T and the front plate recognition timing data Vh. In any case, the matched vehicle data is uniformly referred to as the matched data T1, the vehicle traffic data pr1 in the vehicle cache is matched with the matched data T1, and the data that needs to be matched is uniformly referred to as the to-be-matched data Vh1, then the timing relationship matching process includes the following steps:

[0065] Step 501, determine the previous data T0 of the matched data T1 in the transaction timing queue, the front plate recognition timing queue or the rear plate recognition timing queue. If there is no vehicle passage data matching the data T0 in the vehicle cache, recursively process forward until data matching the vehicle passage data in the vehicle cache is found in the transaction timing queue, the front plate recognition timing queue or the rear plate recognition timing queue, and define the matched vehicle passage data as vehicle passage data pr0, and proceed to the next step.

[0066] Step 502, determine the data T2 after the matched data T1 in the transaction timing queue, the front plate recognition timing queue or the rear plate recognition timing queue. If there is no vehicle passage data matching the data T2 in the vehicle cache, recursively process until data matching the vehicle passage data in the vehicle cache is found in the transaction timing queue, the front plate recognition timing queue or the rear plate recognition timing queue, define the matched vehicle passage data as vehicle passage data pr2, and proceed to the next step.

[0067] If the vehicle traffic data pr2 cannot be obtained, the processing is suspended and the process returns to step 3.

[0068] Step 503, determine whether there is other time series data Vhx between the ETC transaction time series data T, the front plate recognition time series data Vh or the rear plate recognition time series data Vt corresponding to the to-be-matched data Vh1 in the vehicle passage data pr0 and the ETC transaction time series data T, the front plate recognition time series data Vh or the rear plate recognition time series data Vt corresponding to the to-be-matched data Vh1 in the vehicle passage data pr2: If there is other time series data Vhx, then the ETC transaction time series data T, the front plate recognition time series data Vh or the rear plate recognition time series data Vt corresponding to the to-be-matched data T1 in the vehicle passage data pr1 Data Vt=T1, ETC transaction time series data T, vehicle head plate recognition time series data Vh or vehicle tail plate recognition time series data Vt=Vhx in vehicle traffic data pr1 corresponding to time series data Vhx; if there is no other time series data Vhx, then ETC transaction time series data T, vehicle head plate recognition time series data Vh or vehicle tail plate recognition time series data Vt=T1 in vehicle traffic data pr1 corresponding to matched data T1, ETC transaction time series data T, vehicle head plate recognition time series data Vh or vehicle tail plate recognition time series data Vt=null in vehicle traffic data pr1 corresponding to time series data Vhx. After matching is completed, return to step 3.

Claims

1. A method for integrating ETC toll lane transactions and sign recognition based on time series queues, characterized in that: The following steps are involved: Step 1, two sets of license plate recognition devices are installed in each ETC toll lane. The first license plate recognition device along the driving direction is used to sense the front license plate information of the vehicle, and the second license plate recognition device along the driving direction is used to sense the rear license plate information of the vehicle. When a vehicle passes through the first license plate recognition device, front license plate recognition timing data Vh is generated, and when a vehicle passes through the second license plate recognition device, rear license plate recognition timing data Vt is generated. The front license plate recognition timing data Vh and the rear license plate recognition timing data Vt are used to describe whether the current vehicle is the first vehicle that passes through the first license plate recognition device or the second license plate recognition device in the current ETC toll lane within the current time period; After a vehicle completes a transaction through the ETC toll lane system in each ETC toll lane, ETC transaction time series data T is generated. The ETC transaction time series data T describes whether the current vehicle is the first vehicle to complete a transaction through the ETC toll lane system in the current ETC toll lane within the current time period. Based on the license plate and the front plate recognition time series data Vh, rear plate recognition time series data Vt and ETC transaction time series data T of the same vehicle, the vehicle passage data PR is constructed for each vehicle to carry the passage data association relationship of the vehicle passing through the ETC toll lane; Step 2: Establish a hash table to store the traffic relationship of vehicles passing through the current ETC toll lane. Define the hash table as the vehicle cache. The license plate number is used as the key in the hash table, and the ETC transaction time series data T, the front plate recognition time series data Vh, and the rear plate recognition time series data Vt of the same license plate number are used as the value; Step 3: construct an empty transaction time series queue, a front plate recognition time series queue, and a rear plate recognition time series queue to store ETC transaction time series data T, front plate recognition time series data Vh, and rear plate recognition time series data Vt, and realize the association fault tolerance of ETC transaction time series data and plate recognition data through the error threshold of the continuous time series in the queue; Step 4: Receive ETC transaction timing data, vehicle head plate recognition timing data, and vehicle tail plate recognition timing data as matched vehicle data and put them into transaction timing queue, vehicle head plate recognition timing queue, and vehicle tail plate recognition timing queue; Step 5: If there is vehicle traffic data in the vehicle cache that matches the matched vehicle data in the transaction timing queue, the front license plate recognition timing queue or the rear license plate recognition timing queue, it is determined that the timing error between the vehicle traffic data in the vehicle cache and the matched vehicle data is within the fault tolerance threshold, and the data in the transaction timing queue, the front license plate recognition timing queue or the rear license plate recognition timing queue that has the same license plate as the matched vehicle data is directly matched to the vehicle cache; after the matching is completed, recursively process the vehicles that have not been matched in the previous sequence; Step 6: If there is no vehicle traffic data in the vehicle cache that matches the matched vehicle data in the transaction timing queue, the front license plate recognition timing queue, or the rear license plate recognition timing queue, and the current matched vehicle data is the tail of the transaction timing queue, the front license plate recognition timing queue, or the rear license plate recognition timing queue, construct the vehicle traffic data based on the current matched vehicle data and put it into the vehicle cache; Step 7: If there is no vehicle traffic data in the vehicle cache that matches the matched vehicle data in the transaction timing queue, the front license plate recognition timing queue, or the rear license plate recognition timing queue, and the current matched vehicle data is not the tail of the transaction timing queue, the front license plate recognition timing queue, or the rear license plate recognition timing queue, the timing relationship matching process is performed; If the matched vehicle data is the ETC transaction timing data T, the data to be matched are the front plate recognition timing data Vh and the rear plate recognition timing data Vt; if the matched vehicle data is the front plate recognition timing data Vh, the data to be matched are the ETC transaction timing data T and the rear plate recognition timing data Vt; if the matched vehicle data is the rear plate recognition timing data Vt, the data to be matched are the ETC transaction timing data T and the front plate recognition timing data Vh; the matched vehicle data are uniformly referred to by the matched data T1, the vehicle passage data PR1 in the vehicle cache is matched with the matched data T1, and the data to be matched are uniformly referred to by the to-be-matched data Vh1, then the timing relationship matching process includes the following steps: Step 701, determine the previous data T0 of the matched data T1 in the transaction timing queue, the front plate recognition timing queue or the rear plate recognition timing queue. If there is no vehicle traffic data matching the data T0 in the vehicle cache, recursively process forward until data matching the vehicle traffic data in the vehicle cache is found in the transaction timing queue, the front plate recognition timing queue or the rear plate recognition timing queue, define the matched vehicle traffic data as vehicle traffic data PR0, and proceed to the next step; Step 702: determine the data T2 after the matched data T1 in the transaction timing queue, the front plate recognition timing queue or the rear plate recognition timing queue. If there is no vehicle traffic data matching the data T2 in the vehicle cache, recursively process until data matching the vehicle traffic data in the vehicle cache is found in the transaction timing queue, the front plate recognition timing queue or the rear plate recognition timing queue. Define the matched vehicle traffic data as vehicle traffic data PR2 and proceed to the next step. If the vehicle traffic data PR2 cannot be obtained, the processing is suspended and the process returns to step 5; Step 703, determine whether there is other time series data Vhx between the ETC transaction time series data T, the front plate recognition time series data Vh or the rear plate recognition time series data Vt corresponding to the to-be-matched data Vh1 in the vehicle passage data PR0 and the ETC transaction time series data T, the front plate recognition time series data Vh or the rear plate recognition time series data Vt corresponding to the to-be-matched data Vh1 in the vehicle passage data PR2: If there is other time series data Vhx, then the ETC transaction time series data T, the front plate recognition time series data Vh or the rear plate recognition time series data Vt corresponding to the matched data T1 in the vehicle passage data PR1=T 1. The ETC transaction timing data T, the front plate recognition timing data Vh or the rear plate recognition timing data Vt corresponding to the timing data Vhx in the vehicle passage data PR1 are equal to Vhx; if there is no other timing data Vhx, then the ETC transaction timing data T, the front plate recognition timing data Vh or the rear plate recognition timing data Vt corresponding to the matched data T1 in the vehicle passage data PR1 are equal to T1, and the ETC transaction timing data T, the front plate recognition timing data Vh or the rear plate recognition timing data Vt corresponding to the timing data Vhx in the vehicle passage data PR1 are equal to null; after the matching is completed, return to step 5.

2. The method for integrating ETC toll lane transaction and license plate recognition based on time sequence queue as claimed in claim 1, characterized in that: In step 1, if the current vehicle is the vehicle that has completed the Mth transaction in the L lane at the current time D, the ETC transaction timing data T = LDM; if the current vehicle is the Mth license plate recognition by the first license plate recognition device in the L lane at the current time D, the vehicle front license plate recognition timing data Vh = LDM; if the current vehicle is the Mth license plate recognition by the second license plate recognition device in the L lane at the current time D, the vehicle front license plate recognition timing data Vt = LDM.

3. The method for integrating ETC toll lane transaction and license plate recognition based on time sequence queue as claimed in claim 1, characterized in that: In step 2, a bidirectional ordered linked list is used to design the transaction timing queue, the front plate recognition timing queue, and the rear plate recognition timing queue.

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