ETC special condition data processing method based on multi-service demand data

Abstract

The invention relates to the technical field of intelligent traffic systems, and discloses an ETC special situation data processing method based on multi-service demand data. A multi-service data storage module, an ETC special condition data acquisition module, an ETC special condition data analysis module, an ETC special condition data processing module, an ETC special condition data control module, an ETC special condition data evaluation module, a system data maintenance module and a system data monitoring module are established, the multi-service data storage module is used for storing data, and the ETC special condition data acquisition module is responsible for acquiring data; the ETC special situation data analysis module carries out data calculation, the ETC special situation data processing module carries out data classification processing and data correction optimization on the calculated data, the ETC special situation data control module carries out decision making and execution on the processed data, and the ETC special situation data evaluation module carries out feedback and evaluation on a processing result. The system data maintenance module regularly maintains and updates the multi-service data storage module, and the system data monitoring module monitors and manages the whole system.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent transportation systems, and in particular to an ETC special situation data processing method based on multi-service demand data. Background Art

[0002] Although ETC (Electronic Parking Toll Collection System) has brought many conveniences to our lives, the current system still has some obvious defects. Especially in terms of abnormal data correction, due to heavy rain, fog, insufficient light at night, etc., the visibility of the highway decreases, which directly affects the detection accuracy of the ETC license plate recognition equipment. Although the existing technology proposes an ETC gantry data correction method based on multi-source traffic data fusion, it still faces the problem of difficulty in abnormal data correction in actual operation.

[0003] In bad weather conditions, such as heavy rain and fog, visibility is significantly reduced, which can cause the license plate recognition equipment in the ETC system to be unable to accurately capture vehicle information. Similarly, insufficient light at night can also have a negative impact on the detection capabilities of the equipment. These factors combined make the ETC system prone to abnormal data during data collection and processing, which in turn affects the operating efficiency and accuracy of the entire system.

[0004] Although existing technologies attempt to correct ETC gantry data by fusing multi-source traffic data to improve detection accuracy, this method still faces many challenges in practical applications. For example, the coordination and integration between different data sources is difficult, and there is still room for improvement in terms of real-time and accuracy. Therefore, how to effectively solve the problem of abnormal data correction has become a technical problem that the current ETC system urgently needs to overcome. Summary of the invention

[0005] 1. Technical issues to be resolved In view of the shortcomings of the prior art, the present invention provides an ETC special situation data processing method based on multi-business demand data, which has the advantage of simple abnormal data correction and solves the problem of difficulty in correcting abnormal data of ETC license plate recognition equipment due to reduced visibility in the prior art.

[0006] (II) Technical solution To achieve the above object, the present invention provides the following technical solution: an ETC special situation data processing method based on multi-service demand data, comprising the following steps: Step 1: Establish a multi-service data storage module, an ETC special situation data collection module, an ETC special situation data analysis module, an ETC special situation data processing module, an ETC special situation data control module, an ETC special situation data evaluation module, a system data maintenance module and a system data monitoring module; Step 2: Store multi-business data and ETC special situation data through a multi-business data storage module; Step 3: In the ETC special situation data collection module, ETC special situation data, environmental impact data and vehicle data are obtained through the interaction between the vehicle-mounted unit and the ETC gantry system, sensor detection and database query; Step 4: Perform data calculation in the ETC special situation data analysis module; Step 5: In the ETC special situation data processing module, the calculated data is classified and processed and the data correction and optimization is performed; Step 6: In the ETC special situation data control module, make decisions and execute them based on the processed data; Step 7: Feedback and evaluate the processing results in the ETC special situation data evaluation module; Step 8: The system data maintenance module regularly maintains and updates the multi-service data storage module; Step 9: The system data monitoring module monitors and manages the entire system.

[0007] Preferably, the ETC special situation data collection module classifies and numbers the acquired ETC special situation data, environmental impact data and vehicle data, and transmits the numbered data to the ETC special situation data analysis module through the network for calculation.

[0008] Preferably, the ETC special situation data includes recording and counting the number of license plates correctly identified after abnormal data correction and the total number of license plate recognition attempts under abnormal conditions, and numbering the data, the number of license plates correctly identified after abnormal data correction and the total number of license plate recognition attempts under abnormal conditions are numbered respectively. , .

[0009] Preferably, the environmental impact data includes recording and counting all data on the impact of weather changes on ETC identification of vehicles at toll stations, and numbering the data. The environmental impact data number is , , ,… .

[0010] Preferably, the automobile data includes recording and counting the number of false recognitions when only a single camera device is used for recognition mode and the number of false recognitions when a multimodal recognition technology combining radio frequency and camera device is used, and the data are numbered, and the number of false recognitions when only a single camera device is used for recognition mode and the number of false recognitions when a multimodal recognition technology combining radio frequency and camera device is used are numbered as , .

[0011] Preferably, the ETC special situation data analysis module includes an environmental parameter impact unit, a multimodal license plate recognition unit and an abnormal state data correction unit, and the environmental parameter impact unit calculates the environmental parameter impact data possibility index according to the environmental impact data. The multimodal license plate recognition unit calculates the multimodal license plate recognition index according to the automobile data. The abnormal state data correction unit calculates the abnormal state data correction index according to the ETC special situation data. The environmental parameter impact unit, the multimodal license plate recognition unit and the data correction unit under abnormal conditions are connected to the ETC special situation data processing module through a network.

[0012] Preferably, the environmental parameter impact unit calculates the environmental parameter impact data possibility index according to the environmental impact data , and its calculation formula is: ; In the formula, Indicates the possibility index of environmental parameters affecting data, , , ,… Indicates environmental impact data, represents the actual measured value of the i-th environmental impact data, represents the weight coefficient of the i-th environmental parameter, and n represents the total number of environmental impact data considered.

[0013] Preferably, the multimodal license plate recognition unit calculates a multimodal license plate recognition index based on the vehicle data. , and its calculation formula is: ; In the formula, represents the multimodal license plate recognition index, , They represent the number of false positives when only a single camera is used for recognition and the number of false positives when a multi-modal recognition technology combining radio frequency and camera is used. , They represent the total number of recognitions when only a single camera recognition mode is used and the total number of recognitions when a multi-modal recognition technology combining radio frequency and camera is used. Represents the single-mode error rate, that is, the error rate when only a single camera device mode is used. It indicates the multimodal error recognition rate, that is, the error recognition rate when using multimodal recognition technology combining radio frequency and camera equipment.

[0014] Preferably, the abnormal state data correction unit calculates the abnormal state data correction index according to the ETC special situation data. , and its calculation formula is: ; In the formula, Indicates the data correction index under abnormal conditions, , They represent the number of correctly recognized license plates after abnormal data correction and the total number of license plate recognition attempts under abnormal conditions, respectively.

[0015] Preferably, the ETC special situation data processing module calculates the environmental parameter impact data probability index , Multimodal License Plate Recognition Index and data correction index under abnormal conditions Carry out data classification processing and data correction optimization, and in the ETC special situation data processing module, the environmental parameters affect the data possibility index Multimodal License Plate Recognition Index To establish an ETC gantry operation monitoring platform, real-time monitoring of gantry equipment status information, road section abnormal events, early warning statistics, real-time alarm push, use chart data to present abnormal trends of each road section, and the ETC special situation data processing module corrects the index according to the data under abnormal conditions. , using flat map points to present specific alarm information.

[0016] Compared with the prior art, the present invention provides an ETC special situation data processing method based on multi-service demand data, which has the following beneficial effects: 1. The present invention calculates the likelihood index of environmental parameters affecting data , which helps to accurately quantify the impact of environmental factors on ETC license plate recognition equipment, so as to make targeted corrections and optimizations during data processing. When it is lower than 0.85, the ETC special situation data processing module can dynamically adjust the resource allocation of the ETC system and increase the computing resources for image processing when visibility is low to improve recognition accuracy, thereby solving the problem in the prior art that it is difficult to correct abnormal data in the ETC license plate recognition equipment due to reduced visibility.

[0017] 2. The present invention calculates the multi-modal license plate recognition index , which can quantify the improvement of multimodal recognition technology in reducing the number of false recognitions compared to single-modal recognition technology, thus proving the advantage of multimodal recognition technology in improving the accuracy of license plate recognition. It reflects that under different environmental conditions, multimodal recognition technology is more stable and reliable than single-modal recognition technology, which helps to improve the stability and reliability of the ETC system in complex environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0019] 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.

[0020] See also Figure 1 , an ETC special situation data processing method based on multi-business demand data, comprising the following steps: Step 1: Establish a multi-service data storage module, an ETC special situation data collection module, an ETC special situation data analysis module, an ETC special situation data processing module, an ETC special situation data control module, an ETC special situation data evaluation module, a system data maintenance module and a system data monitoring module; Step 2: Store multi-business data and ETC special situation data through a multi-business data storage module; Step 3: In the ETC special situation data collection module, ETC special situation data, environmental impact data and vehicle data are obtained through the interaction between the vehicle-mounted unit and the ETC gantry system, sensor detection and database query; Step 4: Perform data calculation in the ETC special situation data analysis module; Step 5: In the ETC special situation data processing module, the calculated data is classified and processed and the data correction and optimization is performed; Step 6: In the ETC special situation data control module, make decisions and execute them based on the processed data; Step 7: Feedback and evaluate the processing results in the ETC special situation data evaluation module to continuously optimize the data processing method and improve the processing efficiency; Step 8: The system data maintenance module regularly maintains and updates the multi-business data storage module to ensure the accuracy and completeness of the data; Step 9: The system data monitoring module monitors and manages the entire system to ensure the stable operation and security of the system.

[0021] The ETC special situation data collection module classifies and numbers the acquired ETC special situation data, environmental impact data and vehicle data, and transmits the numbered data to the ETC special situation data analysis module through the network for calculation.

[0022] The ETC special situation data includes recording and counting the number of license plates correctly identified after abnormal data correction and the total number of license plate recognition attempts under abnormal conditions, and numbering the data. The number of license plates correctly identified after abnormal data correction and the total number of license plate recognition attempts under abnormal conditions are numbered respectively. , .

[0023] Environmental impact data includes recording and counting all data on the impact of weather changes on ETC identification of vehicles at toll stations, and numbering the data. The environmental impact data number is , , ,… .

[0024] The automobile data includes recording and counting the number of false recognitions when only a single camera device is used for recognition mode and the number of false recognitions when a multi-modal recognition technology combining radio frequency and camera device is used, and the data is numbered. The number of false recognitions when only a single camera device is used for recognition mode and the number of false recognitions when a multi-modal recognition technology combining radio frequency and camera device is used are numbered as , .

[0025] The ETC special situation data analysis module includes an environmental parameter impact unit, a multi-modal license plate recognition unit and an abnormal state data correction unit. The environmental parameter impact unit calculates the environmental parameter impact data possibility index based on the environmental impact data. The multimodal license plate recognition unit calculates the multimodal license plate recognition index according to the automobile data. The abnormal state data correction unit calculates the abnormal state data correction index according to the ETC special situation data. The environmental parameter impact unit, the multimodal license plate recognition unit and the data correction unit under abnormal conditions are connected to the ETC special situation data processing module through a network.

[0026] The environmental parameter impact unit calculates the environmental parameter impact data possibility index based on the environmental impact data , and its calculation formula is: ; In the formula, Indicates the possibility index of environmental parameters affecting data, , , ,… Indicates environmental impact data, represents the actual measured value of the i-th environmental impact data, represents the weight coefficient of the ith environmental parameter (such as visibility, weather conditions), and n represents the total number of environmental impact data considered.

[0027] Advantages: By calculating the probability index of environmental parameters affecting data , which helps to accurately quantify the impact of environmental factors on ETC license plate recognition equipment, so as to make targeted corrections and optimizations during data processing. When it is lower than 0.85, the ETC special situation data processing module can dynamically adjust the resource allocation of the ETC system and increase the computing resources for image processing when visibility is low to improve recognition accuracy, thereby solving the problem in the prior art that it is difficult to correct abnormal data in the ETC license plate recognition equipment due to reduced visibility.

[0028] The multimodal license plate recognition unit calculates the multimodal license plate recognition index based on the car data , and its calculation formula is: ; In the formula, represents the multimodal license plate recognition index, , They represent the number of false positives when only a single camera is used for recognition and the number of false positives when a multi-modal recognition technology combining radio frequency and camera is used. , They represent the total number of recognitions when only a single camera recognition mode is used and the total number of recognitions when a multi-modal recognition technology combining radio frequency and camera is used. Represents the single-mode error rate, that is, the error rate when only a single camera device mode is used. It indicates the multimodal error recognition rate, that is, the error recognition rate when using multimodal recognition technology combining radio frequency and camera equipment.

[0029] The advantage is: by calculating the multimodal license plate recognition index , which can quantify the improvement of multimodal recognition technology in reducing the number of false recognitions compared to single-modal recognition technology, thus proving the advantage of multimodal recognition technology in improving the accuracy of license plate recognition. It reflects that under different environmental conditions, multimodal recognition technology is more stable and reliable than single-modal recognition technology, which helps to improve the stability and reliability of the ETC system in complex environments.

[0030] The data correction unit under abnormal conditions calculates the data correction index under abnormal conditions based on the ETC special situation data. , and its calculation formula is: ; In the formula, Indicates the data correction index under abnormal conditions, , They represent the number of correctly recognized license plates after abnormal data correction and the total number of license plate recognition attempts under abnormal conditions, respectively.

[0031] The advantage is: by calculating the data correction index under abnormal conditions , can quantify the effect of anomaly correction technology, thereby improving the accuracy of overall data processing. This index can reflect the accuracy of the system's recognition technology under abnormal conditions and help improve the performance of the ETC system in complex environments.

[0032] The ETC special situation data processing module will calculate the environmental parameters that affect the data probability index , Multimodal License Plate Recognition Index and data correction index under abnormal conditions Carry out data classification processing and data correction optimization, and in the ETC special situation data processing module, the environmental parameters affect the data possibility index Multimodal License Plate Recognition Index To establish an ETC gantry operation monitoring platform, real-time monitoring of gantry equipment status information, road section abnormal events, early warning statistics, real-time alarm push, use chart data to present abnormal trends of each road section, and the ETC special situation data processing module corrects the index according to the data under abnormal conditions. , using plane map points to present specific warning information to solve the problem of difficulty in correcting abnormal data of ETC license plate recognition equipment due to reduced visibility in the existing technology.

[0033] 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. A method for processing ETC special situation data based on multi-service demand data, characterized in that: The following steps are involved: Step 1: Establish a multi-service data storage module, an ETC special situation data collection module, an ETC special situation data analysis module, an ETC special situation data processing module, an ETC special situation data control module, an ETC special situation data evaluation module, a system data maintenance module and a system data monitoring module; Step 2: Store multi-business data and ETC special situation data through a multi-business data storage module; Step 3: In the ETC special situation data collection module, ETC special situation data, environmental impact data and vehicle data are obtained through the interaction between the vehicle-mounted unit and the ETC gantry system, sensor detection and database query; Step 4: Perform data calculation in the ETC special situation data analysis module; Step 5: In the ETC special situation data processing module, the calculated data is classified and processed and the data correction and optimization is performed; Step 6: In the ETC special situation data control module, make decisions and execute them based on the processed data; Step 7: Feedback and evaluate the processing results in the ETC special situation data evaluation module; Step 8: The system data maintenance module regularly maintains and updates the multi-service data storage module; Step 9: The system data monitoring module monitors and manages the entire system.

2. The ETC special situation data processing method based on multi-service demand data according to claim 1, characterized in that: The ETC special situation data acquisition module classifies and numbers the acquired ETC special situation data, environmental impact data and vehicle data, and transmits the numbered data to the ETC special situation data analysis module through the network for calculation.

3. The ETC special situation data processing method based on multi-service demand data according to claim 2 is characterized in that: The ETC special situation data includes recording and counting the number of license plates correctly identified after abnormal data correction and the total number of license plate recognition attempts under abnormal conditions, and numbering the data. The number of license plates correctly identified after abnormal data correction and the total number of license plate recognition attempts under abnormal conditions are numbered respectively. , .

4. The ETC special situation data processing method based on multi-service demand data according to claim 2 is characterized in that: The environmental impact data includes recording and counting all data that are affected by weather changes in the ETC recognition of vehicles at toll stations, and numbering the data. The environmental impact data number is , , ,… .

5. The ETC special situation data processing method based on multi-service demand data according to claim 2 is characterized in that: The automobile data includes recording and counting the number of false recognitions when only a single camera device is used for recognition mode and the number of false recognitions when a multi-modal recognition technology combining radio frequency and camera device is used, and the data are numbered. The number of false recognitions when only a single camera device is used for recognition mode and the number of false recognitions when a multi-modal recognition technology combining radio frequency and camera device is used are numbered as , .

6. The ETC special situation data processing method based on multi-service demand data according to claim 1 is characterized in that: The ETC special situation data analysis module includes an environmental parameter impact unit, a multi-modal license plate recognition unit and an abnormal state data correction unit. The environmental parameter impact unit calculates the environmental parameter impact data possibility index according to the environmental impact data. The multimodal license plate recognition unit calculates the multimodal license plate recognition index according to the automobile data. The abnormal state data correction unit calculates the abnormal state data correction index according to the ETC special situation data. The environmental parameter impact unit, the multimodal license plate recognition unit and the data correction unit under abnormal conditions are connected to the ETC special situation data processing module through a network.

7. The ETC special situation data processing method based on multi-service demand data according to claim 6 is characterized in that: The environmental parameter impact unit calculates the environmental parameter impact data possibility index according to the environmental impact data , and its calculation formula is: ； In the formula, Indicates the possibility index of environmental parameters affecting data, , , ,… Indicates environmental impact data, represents the actual measured value of the i-th environmental impact data, represents the weight coefficient of the i-th environmental parameter, and n represents the total number of environmental impact data considered.

8. The ETC special situation data processing method based on multi-service demand data according to claim 6 is characterized by: The multimodal license plate recognition unit calculates a multimodal license plate recognition index based on the automobile data , and its calculation formula is: ； In the formula, represents the multimodal license plate recognition index, , They represent the number of false positives when only a single camera is used for recognition and the number of false positives when a multi-modal recognition technology combining radio frequency and camera is used. , They represent the total number of recognitions when only a single camera recognition mode is used and the total number of recognitions when a multi-modal recognition technology combining radio frequency and camera is used. Represents the single-mode error rate, that is, the error rate when only a single camera device mode is used. It indicates the multimodal error recognition rate, that is, the error recognition rate when using multimodal recognition technology combining radio frequency and camera equipment.

9. The ETC special situation data processing method based on multi-service demand data according to claim 6, characterized in that: The abnormal state data correction unit calculates the abnormal state data correction index according to the ETC special situation data , and its calculation formula is: ； In the formula, Indicates the data correction index under abnormal conditions, , They represent the number of correctly recognized license plates after abnormal data correction and the total number of license plate recognition attempts under abnormal conditions, respectively.

10. The ETC special situation data processing method based on multi-service demand data according to claim 9, characterized in that: The ETC special situation data processing module calculates the environmental parameter impact data possibility index , Multimodal License Plate Recognition Index and data correction index under abnormal conditions Carry out data classification processing and data correction optimization, and in the ETC special situation data processing module, the environmental parameters affect the data possibility index Multimodal License Plate Recognition Index To establish an ETC gantry operation monitoring platform, real-time monitoring of gantry equipment status information, road section abnormal events, early warning statistics, real-time alarm push, use chart data to present abnormal trends of each road section, and the ETC special situation data processing module corrects the index according to the data under abnormal conditions. , using flat map points to present specific alarm information.

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