ETC abnormal condition identification intelligent early warning system

Abstract

The invention relates to the technical field of ETC intelligent early warning, and discloses an ETC abnormal condition identification intelligent early warning system. According to the system, ETC related data including vehicle passing records, transaction amount and payment states, vehicle driving speed data and real-time road information are collected through a data acquisition unit, and the collected data are denoised through a data processing unit. The data processing unit is used for transmitting data, calculating real-time traffic flow, vehicle passing transaction success rate, vehicle passing time, average transaction amount and charging processing response time, carrying out license plate recognition and passing record data consistency check, and the abnormity recognition unit is used for carrying out ETC abnormity recognition based on data transmitted by the data processing unit and transmitting abnormal information to the early warning unit; the early warning unit generates corresponding early warning information and exception handling measures based on an exception detection result, summarizes and sends the early warning information and the exception handling measures to the information display unit, and the information display unit displays the early warning information and the exception handling measures on the visual terminal for information reminding and exception condition improvement.

Description

Technical Field

[0001] The present invention relates to the technical field of ETC intelligent early warning, and in particular to an ETC abnormal situation identification intelligent early warning system. Background Art

[0002] The ETC electronic toll collection system is a traffic management system that uses wireless communication, sensing technology and automatic identification technology to enable vehicles to automatically complete toll collection when passing through toll stations without having to stop or slow down. The use of ETC can reduce the waiting time of vehicles at toll stations, improve overall traffic flow, and reduce congestion. Therefore, timely identification of abnormal situations within the system, such as traffic surges, transaction failures, etc., can ensure that relevant departments can take prompt measures to prevent the problem from further expanding.

[0003] Currently, most electronic toll collection systems may have delays in identifying and warning of abnormal situations and are unable to respond in real time, reducing system efficiency. Summary of the invention

[0004] 1. Technical issues to be resolved In view of the deficiencies in the prior art, the present invention provides an ETC abnormal situation identification intelligent early warning system, which collects data related to the ETC system in real time through a data acquisition unit, including vehicle passage records, transaction amounts and payment statuses, vehicle speed data and real-time road information; a data processing unit denoises the above-collected data, and calculates real-time traffic flow, vehicle transaction success rate, vehicle passage time, average transaction amount and toll processing response time, and performs a consistency check between license plate recognition and passage record data; an abnormality identification unit identifies ETC abnormalities based on data transmitted by the data processing unit, and transmits the abnormal information to an early warning unit; the early warning unit generates corresponding early warning information and abnormality handling measures based on the results of abnormality detection, and summarizes and sends them to an information display unit; the information display unit displays the early warning information and abnormality handling measures on a visual terminal for information reminders and abnormal situation improvements; and by timely early warning responses to ETC-related abnormal information and taking corresponding solutions, the working efficiency of the ETC system is improved and the above-mentioned problems are solved.

[0005] (II) Technical solution To achieve the above-mentioned object, the present invention provides the following technical solutions: an ETC abnormal situation identification intelligent early warning system, comprising a data acquisition unit, a data processing unit, an abnormality identification unit, an early warning unit and an information display unit; The data acquisition unit is responsible for collecting data related to the ETC system in real time, including vehicle pass records, transaction amounts and payment status, vehicle speed data and real-time road information, and transmitting the vehicle pass records, transaction amounts and payment status, vehicle speed data and real-time road information to the data processing unit; The data processing unit performs denoising on the vehicle pass record, transaction amount and payment status, vehicle speed data and real-time road information, calculates the real-time traffic flow, vehicle transaction success rate, vehicle pass time, average transaction amount and toll processing response time, and performs a consistency check between license plate recognition and pass record data. The processed vehicle pass record, transaction amount and payment status, vehicle speed data and real-time road information are sent to the abnormality recognition unit; The abnormality identification unit performs ETC abnormality identification based on the data transmitted by the data processing unit, and transmits the abnormality information to the early warning unit; The early warning unit generates corresponding early warning information and abnormality handling measures based on the results of abnormality detection, and summarizes and sends them to the information display unit; The information display unit displays the warning information and abnormality handling measures on the visualization terminal for information reminder and abnormal situation improvement.

[0006] Preferably, the formula used by the data processing unit to denoise the collected data is as follows: ; In the formula, Indicates at a point in time The denoised data value, Indicates at a point in time The original data value at is the window radius of the Gaussian filter, indicating the range of points used, and is the current point The number of data points before and after, Represents the standard deviation of the Gaussian distribution and controls the width of the Gaussian function. represents the base of natural logarithm, which is 2.71828, Indicates a counting subscript.

[0007] Preferably, the formula for calculating the real-time traffic flow by the data processing unit is as follows: ; In the formula, Indicates real-time traffic flow, Indicates the time period The total number of vehicles passing through the measuring point within Indicates the length of the observation period.

[0008] Preferably, the formula used by the data processing unit to calculate the vehicle transaction success rate is as follows: ; In the formula, Indicates the success rate of vehicle transactions. Indicates the vehicle that has successfully completed the payment during the transaction. Indicates the total number of vehicles traded, regardless of whether the transaction was successful or failed.

[0009] Preferably, the formula used by the data processing unit to calculate the vehicle travel time is as follows: ; In the formula, Indicates the vehicle travel time. Indicates the time when the vehicle arrives at the toll booth. Indicates the time when the vehicle leaves the toll booth.

[0010] Preferably, the formula used by the data processing unit to calculate the average transaction amount is as follows: ; In the formula, represents the average transaction amount, Represents the sum of the amounts of all successful transactions. Indicates the total number of vehicles that have completed payment.

[0011] Preferably, the formula used by the data processing unit to calculate the charging processing response time is as follows: ; In the formula, Indicates the charging processing response time. Represents the sum of response times of all transactions, Indicates the total number of vehicles that have completed payment.

[0012] Preferably, the formula for the data processing unit to perform the consistency check of license plate recognition and traffic record data is as follows: ; In the formula, Indicates the matching result, 1 indicates a successful match, and 0 indicates a failed match. Indicates the recognized license plate number. Indicates the license plate number in the traffic record. Indicates the timestamp of license plate recognition, Indicates the timestamp of the vehicle's passage record. Indicates the time error, which is 5 seconds and is used to determine whether the timestamp is within a reasonable range.

[0013] Preferably, the abnormality identification unit performs ETC abnormality identification based on the data transmitted by the data processing unit, and the abnormality identification method is as follows: When real-time traffic flow Traffic abnormality occurs when the traffic increases or decreases by more than 20% compared to the historical average, or when the traffic exceeds 80% or is lower than 80% of the historical average for 5 consecutive minutes. When the vehicle passes the transaction success rate If the rate is lower than 90%, it is considered as an abnormal ETC transaction; When the vehicle passes If the time exceeds 30 seconds, it is considered as abnormal vehicle traffic; When the average transaction amount When the rate of change exceeds plus or minus 15%, the amount transaction is considered abnormal; When charging is processed response time If it exceeds 5 seconds, it is considered as ETC response abnormality; When the license plate recognition is inconsistent with the traffic record and the difference between the recognition results exceeds 1 character, the license plate recognition is determined to be abnormal.

[0014] Preferably, the early warning unit generates corresponding early warning information and abnormality handling measures based on the results of abnormality detection as follows: When the real-time traffic flow is abnormal, the system will send SMS to the traffic management center to conduct on-site inspection and dispatch traffic; When ETC transactions are abnormal, the system opens a backup payment channel for normal transaction payment; When vehicles pass abnormally, the system will send staff to conduct on-site inspections of the equipment operating status at toll booths and crossings via SMS; When the amount of transaction is abnormal, the system will review the transaction records to confirm the reason for the fluctuation of the transaction amount. If it is a false alarm, the system parameters will be adjusted; When ETC responds abnormally, the system checks the server and network status and performs system optimization; When the license plate recognition is inconsistent with the traffic record, the system verifies the inconsistent record, performs manual review, and updates the license plate database.

[0015] Compared with the prior art, the present invention provides an ETC abnormal situation identification intelligent early warning system, which has the following beneficial effects: The present invention collects data related to the ETC system in real time through a data acquisition unit, including vehicle pass records, transaction amounts and payment status, vehicle speed data and real-time road information. The data processing unit denoises the above-collected data, and calculates real-time traffic flow, vehicle transaction success rate, vehicle pass time, average transaction amount and toll processing response time, and performs a consistency check between license plate recognition and pass record data. The abnormality recognition unit performs ETC abnormality recognition based on data transmitted by the data processing unit, and transmits the abnormal information to the early warning unit. The early warning unit generates corresponding early warning information and abnormality handling measures based on the results of the abnormality detection, and summarizes and sends them to the information display unit. The information display unit displays the early warning information and abnormality handling measures on a visual terminal for information reminders and abnormal situation improvements. By timely early warning responses to ETC-related abnormal information and taking corresponding solutions, the work efficiency of the ETC system is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] In view of the fact that most current electronic toll collection systems may have delays in identifying and warning abnormal situations, and cannot respond in real time, which reduces the system's working efficiency, an ETC abnormal situation identification intelligent warning system is proposed. Figure 1 , the system includes a data acquisition unit, a data processing unit, an abnormality identification unit, an early warning unit and an information display unit; The data collection unit is equipped with high-precision sensors and cameras to automatically record the vehicle's passage records. These sensors can obtain the vehicle's passage time, license plate information and vehicle type in real time. At the same time, through the interface with the payment gateway, the data collection unit can monitor the transaction amount and payment status in real time to ensure the timeliness and accuracy of the transaction. In addition, with the help of GPS and the vehicle communication system, the collection unit can obtain the vehicle's driving speed data and real-time road information connected to the traffic management center, such as traffic flow, road conditions and weather conditions. These data are quickly transmitted to the data processing unit through the 5G network, forming an efficient and real-time data collection ecosystem, providing a solid data foundation for subsequent abnormal identification and traffic management decisions; The data processing unit removes noise from the above collected data, calculates real-time traffic flow, vehicle transaction success rate, vehicle travel time, average transaction amount and toll processing response time, and performs consistency check between license plate recognition and traffic record data, including: The data denoising formula is as follows: ; The original data may contain a lot of irrelevant or erroneous information. De-noising can effectively reduce the impact of these noises on the anomaly detection algorithm and reduce the occurrence of false positives and false negatives. In the formula, Indicates at a point in time The denoised data value, Indicates at a point in time The original data value at is the window radius of the Gaussian filter, indicating the range of points used, and is the current point The number of data points before and after, Represents the standard deviation of the Gaussian distribution and controls the width of the Gaussian function. represents the base of natural logarithm, which is 2.71828, Indicates the count subscript. By removing the noise in the data, the overall data trend is more obvious, which makes the subsequent trend analysis, pattern recognition and prediction work more accurate, thereby improving the analysis ability of key indicators such as traffic flow and transaction status; The formula for calculating real-time traffic flow is as follows: ; Abnormal changes in traffic, such as sudden decrease or increase, may indicate potential traffic accidents or other emergencies. Through real-time monitoring, the system can quickly issue warnings to help relevant departments respond quickly and reduce losses caused by accidents. In the formula, Indicates real-time traffic flow, Indicates the time period The total number of vehicles passing through the measuring point within Indicates the length of the observation period. Real-time traffic flow data provides a basis for subsequent traffic pattern analysis and prediction. By comparing and analyzing historical data with real-time data, peak hours and traffic trends can be identified to provide support for future traffic planning. The formula for calculating the vehicle transaction success rate is as follows: ; By monitoring the transaction success rate, potential problems in the system can be discovered in a timely manner, such as payment system failures, equipment failures, etc., so as to carry out targeted maintenance and optimization. In the formula, Indicates the success rate of vehicle transactions. Indicates the vehicle that has successfully completed the payment during the transaction. Indicates the total number of vehicles traded, regardless of whether the transaction is successful or failed. A low transaction success rate may indicate security risks or fraud. By monitoring the transaction success rate, the system can identify abnormal transactions in a timely manner, take corresponding security measures, and reduce risks. The formula for calculating vehicle travel time is as follows: ; The length of travel time directly affects the toll collection efficiency. By monitoring the travel time, managers can promptly discover efficiency problems at toll stations, optimize the toll collection process, and reduce the waiting time of vehicles at toll stations. In the formula, Indicates the vehicle travel time. Indicates the time when the vehicle arrives at the toll booth. Indicates the time when the vehicle leaves the toll booth; The formula for calculating the average transaction amount is as follows: ; By monitoring the average transaction amount, we can evaluate the rationality and economic benefits of the charging policy and adjust the charging standards in a timely manner to achieve the best economic benefits. In the formula, represents the average transaction amount, Represents the sum of the amounts of all successful transactions. Indicates the total number of vehicles that have completed payment. By analyzing the relationship between the average transaction amount and the transaction volume, future revenue can be predicted more accurately, and reasonable budgeting and financial planning can be carried out; The formula for calculating the charge processing response time is as follows: ; By monitoring the response time of charging processing, we can timely discover the bottleneck and delay problems of the system, make targeted optimizations, and improve the overall system efficiency. In the formula, Indicates the charging processing response time. Represents the sum of response times of all transactions, Indicates the total number of vehicles that have completed payment. By analyzing the response time data, resources can be reasonably allocated to ensure that there is sufficient equipment and personnel support during peak hours, thereby improving the service capacity of the toll station; The formula for checking the consistency of license plate recognition and traffic record data is as follows: ; By comparing the license plate recognition results with the traffic record data, the problem of inconsistent information can be discovered and corrected in time, and the accuracy and reliability of the system data can be improved. In the formula, Indicates the matching result, 1 indicates a successful match, and 0 indicates a failed match. Indicates the recognized license plate number. Indicates the license plate number in the traffic record. Indicates the timestamp of license plate recognition, Indicates the timestamp of the vehicle's passage record. Indicates the time error, which is 5 seconds. It is used to determine whether the timestamp is within a reasonable range. The consistency check helps to identify incorrect charging information in a timely manner, avoid incorrect charging due to inconsistent license plate information, and safeguard the legitimate rights and interests of users; The abnormality identification unit performs ETC abnormality identification based on the data transmitted by the data processing unit. The abnormality identification method is as follows: When real-time traffic flow Traffic abnormality occurs when the traffic increases or decreases by more than 20% compared to the historical average, or when the traffic exceeds 80% or is lower than 80% of the historical average for 5 consecutive minutes. When the vehicle passes the transaction success rate If the rate is lower than 90%, it is considered as an abnormal ETC transaction; When the vehicle passes If the time exceeds 30 seconds, it is considered as abnormal vehicle traffic; When the average transaction amount When the rate of change exceeds plus or minus 15%, the amount transaction is considered abnormal; When charging is processed response time If it exceeds 5 seconds, it is considered as ETC response abnormality; When the license plate recognition is inconsistent with the traffic record and the difference between the recognition results exceeds 1 character, the license plate recognition is judged to be abnormal; The early warning unit generates corresponding early warning information and abnormal handling measures based on the results of abnormal detection as follows: When the real-time traffic flow is abnormal, the system will send SMS to the traffic management center to conduct on-site inspection and dispatch traffic; When ETC transactions are abnormal, the system opens a backup payment channel for normal transaction payment; When vehicles pass abnormally, the system will send staff to conduct on-site inspections of the equipment operating status at toll booths and crossings via SMS; When the amount of transaction is abnormal, the system will review the transaction records to confirm the reason for the fluctuation of the transaction amount. If it is a false alarm, the system parameters will be adjusted; When ETC responds abnormally, the system checks the server and network status and performs system optimization; When the license plate recognition is inconsistent with the traffic record, the system verifies the inconsistent record, conducts manual review, and updates the license plate database; The information display unit displays the warning information and abnormal handling measures from the warning unit in a user-friendly form on the visual terminal. The terminal uses a high-resolution display and an intuitive graphical user interface, and uses dynamic information display and visual analysis charts to highlight key data. In addition, the information display unit also has a touch interaction function, allowing operators to perform rapid retrieval and in-depth analysis to enhance understanding and response to abnormal situations.

[0019] Through the application of the above system, timely early warning responses are made to ETC-related abnormal information, and corresponding solutions are taken, thus improving the working efficiency of the ETC system.

[0020] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An ETC abnormal situation identification intelligent early warning system, characterized by: It includes a data collection unit, a data processing unit, an abnormality identification unit, an early warning unit and an information display unit; The data acquisition unit is responsible for collecting data related to the ETC system in real time, including vehicle pass records, transaction amounts and payment status, vehicle speed data and real-time road information, and transmitting the vehicle pass records, transaction amounts and payment status, vehicle speed data and real-time road information to the data processing unit; The data processing unit performs denoising on the vehicle pass record, transaction amount and payment status, vehicle speed data and real-time road information, calculates the real-time traffic flow, vehicle transaction success rate, vehicle pass time, average transaction amount and toll processing response time, and performs a consistency check between license plate recognition and pass record data. The processed vehicle pass record, transaction amount and payment status, vehicle speed data and real-time road information are sent to the abnormality recognition unit; The abnormality identification unit performs ETC abnormality identification based on the data transmitted by the data processing unit, and transmits the abnormality information to the early warning unit; The early warning unit generates corresponding early warning information and abnormality handling measures based on the results of abnormality detection, and summarizes and sends them to the information display unit; The information display unit displays the warning information and abnormality handling measures on the visualization terminal for information reminder and abnormal situation improvement.

2. The ETC abnormal situation identification intelligent early warning system according to claim 1 is characterized by: The formula used by the data processing unit to denoise the collected data is as follows: ； In the formula, Indicates at a point in time The denoised data value, Indicates at a point in time The original data value at is the window radius of the Gaussian filter, indicating the range of points used, and is the current point The number of data points before and after, Represents the standard deviation of the Gaussian distribution and controls the width of the Gaussian function. represents the base of natural logarithm, which is 2.71828, Indicates a counting subscript.

3. The ETC abnormal situation identification intelligent early warning system according to claim 2 is characterized by: The formula for calculating the real-time traffic flow by the data processing unit is as follows: ； In the formula, Indicates real-time traffic flow, Indicates the time period The total number of vehicles passing through the measuring point within Indicates the length of the observation period.

4. The ETC abnormal situation identification intelligent early warning system according to claim 3 is characterized by: The formula for calculating the vehicle transaction success rate by the data processing unit is as follows: ； In the formula, Indicates the success rate of vehicle transactions. Indicates the vehicle that has successfully completed the payment during the transaction. Indicates the total number of vehicles traded, regardless of whether the transaction was successful or failed.

5. The ETC abnormal situation identification intelligent early warning system according to claim 4 is characterized by: The formula for calculating the vehicle travel time by the data processing unit is as follows: ； In the formula, Indicates the vehicle travel time. Indicates the time when the vehicle arrives at the toll booth. Indicates the time when the vehicle leaves the toll booth.

6. The ETC abnormal situation identification intelligent early warning system according to claim 5 is characterized by: The formula for calculating the average transaction amount by the data processing unit is as follows: ； In the formula, represents the average transaction amount, Represents the sum of the amounts of all successful transactions. Indicates the total number of vehicles that have completed payment.

7. The ETC abnormal situation identification intelligent early warning system according to claim 6 is characterized by: The formula for calculating the charging processing response time by the data processing unit is as follows: ； In the formula, Indicates the charge processing response time. Represents the sum of response times of all transactions, Indicates the total number of vehicles that have completed payment.

8. The ETC abnormal situation identification intelligent early warning system according to claim 7 is characterized by: The formula for the data processing unit to perform the consistency check of license plate recognition and traffic record data is as follows: ； In the formula, Indicates the matching result, 1 indicates a successful match, and 0 indicates a failed match. Indicates the recognized license plate number. Indicates the license plate number in the traffic record. Indicates the timestamp of license plate recognition, Indicates the timestamp of the vehicle's passage record. Indicates the time error, which is 5 seconds and is used to determine whether the timestamp is within a reasonable range.

9. The ETC abnormal situation identification intelligent early warning system according to claim 8 is characterized by: The abnormality identification unit performs ETC abnormality identification based on the data transmitted by the data processing unit. The abnormality identification method is as follows: When real-time traffic flow Traffic abnormality occurs when the traffic increases or decreases by more than 20% compared to the historical average, or when the traffic exceeds 80% or is lower than 80% of the historical average for 5 consecutive minutes. When the vehicle passes the transaction success rate If the rate is lower than 90%, it is considered as an abnormal ETC transaction; When the vehicle passes If the time exceeds 30 seconds, it is considered as abnormal vehicle traffic; When the average transaction amount When the rate of change exceeds plus or minus 15%, the transaction amount is considered abnormal; When charging is processed response time If it exceeds 5 seconds, it is considered as ETC response abnormality; When the license plate recognition is inconsistent with the traffic record and the difference between the recognition results exceeds 1 character, the license plate recognition is determined to be abnormal.

10. The ETC abnormal situation identification intelligent early warning system according to claim 9, characterized in that: The warning unit generates corresponding warning information and abnormality handling measures based on the results of abnormality detection as follows: When the real-time traffic flow is abnormal, the system will send SMS to the traffic management center to conduct on-site inspection and dispatch traffic; When ETC transactions are abnormal, the system opens a backup payment channel for normal transaction payment; When vehicles pass abnormally, the system will send staff to conduct on-site inspections of the equipment operating status at toll booths and crossings via SMS; When the amount of transaction is abnormal, the system will review the transaction records to confirm the reason for the fluctuation of the transaction amount. If it is a false alarm, the system parameters will be adjusted; When ETC responds abnormally, the system checks the server and network status and performs system optimization; When the license plate recognition is inconsistent with the traffic record, the system verifies the inconsistent record, performs manual review, and updates the license plate database.

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