CN117314124B - Intelligent management system and method for expressway toll service - Google Patents

Intelligent management system and method for expressway toll service Download PDF

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CN117314124B
CN117314124B CN202311596312.9A CN202311596312A CN117314124B CN 117314124 B CN117314124 B CN 117314124B CN 202311596312 A CN202311596312 A CN 202311596312A CN 117314124 B CN117314124 B CN 117314124B
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service
information
business
department
station
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CN117314124A (en
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彭驰
何炜
陈九龙
翟波
陆翔莺
王骏驰
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Sichuan Expressway Co ltd
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Sichuan Expressway Co ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06311—Scheduling, planning or task assignment for a person or group
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/583—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
    • G06F16/5846—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using extracted text
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/587—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using geographical or spatial information, e.g. location
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06313—Resource planning in a project environment
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/10—Office automation; Time management
    • G06Q10/103—Workflow collaboration or project management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/26—Government or public services

Abstract

The embodiment of the application provides an intelligent management system and method for expressway toll service, and relates to the field of vehicle management. The system comprises: the login module is used for identifying a site to which a login user belongs; the station management module is used for acquiring station information of stations aiming at business departments, materials and processing personnel; the service management module is used for associating the acquired service information to be processed into a service template so as to acquire a service list; performing service distribution on each service department based on the service list, and determining an execution strategy of each service department according to the station information, so that the distributed service is processed based on the execution strategy, wherein the execution strategy is used for indicating distribution of materials and processing personnel; and the in-station auditing module is used for executing the auditing task aiming at the charging business and displaying and processing the business distribution information of the corresponding charging business when the auditing task is abnormal. The method and the device solve the problem that the processing efficiency of the conventional expressway charge management technology is low.

Description

Intelligent management system and method for expressway toll service
Technical Field
The invention relates to the technical field of vehicle management, in particular to an intelligent management system and method for expressway toll service.
Background
Currently, for intelligent management of highway tolling, many new technologies, such as Electronic Toll Collection (ETC), are emerging on the market, in which an electronic tag is installed on a vehicle, then a radio frequency reader reads the electronic tag, and information such as a passing distance, a passing time, a vehicle type and the like is obtained through the electronic tag, and finally a passing cost is calculated according to the obtained information. The electronic toll collection technology deducts fees through a bank card bound by an electronic tag, and the vehicle does not need to park, insert the card or pay the fees on site, thereby realizing automatic toll collection.
Although the prior art improves the level of intellectualization of highway tolling to some extent, these techniques only improve the tolling link in the highway tolling process. In other links in the charging process, such as fund examination, personnel handover, material management and the like, a paper registration form is still used in most of the management forms, and the management forms have the problems of large registration form number, large repeated workload, complex registration form storage and the like. In particular, when the ETC recognition is wrong or the license plate recognition is wrong, the phenomena of missed collection and wrong collection may occur, and the passing charge may deviate. The prior art faces the problems, and measures adopted are still a manual auditing mode, and all license plates and ETC information of a time period are screened by taking the time period as an index, but the mode clearly greatly increases labor cost and takes a long time. Therefore, the current highway toll management technology has low processing efficiency.
Disclosure of Invention
In order to solve the above prior art problems, the present invention provides an intelligent management system and method for highway toll service, which are used for solving the technical problem of low processing efficiency of the current highway toll management technology.
According to an aspect of the embodiments of the present application, there is provided an intelligent management system for highway toll service, the system including:
the login module is used for identifying a site to which a login user belongs;
the station management module is connected with the login module and is used for acquiring station information of the station for business departments, materials and processing personnel;
the service management module is connected with the station management module and is used for associating the acquired service information to be processed with a preset service template so as to acquire a service list; performing service distribution on each service department based on the service list, and determining an execution strategy of each service department according to the station information, so that the distributed service is processed based on the execution strategy, wherein the execution strategy is used for indicating distribution of materials and processing personnel;
and the in-station checking module is connected with the service management module and is used for executing checking tasks aiming at the charging service and displaying and processing service distribution information of the corresponding charging service when the result of the checking tasks is abnormal.
In one possible implementation, the station management module includes:
the department structure unit is used for acquiring the configuration information of the business department from the login user and associating the configuration information of the business department to a preset department configuration template so as to acquire the station information of the business department;
the material management unit is connected with the department structure unit and is used for managing material information of materials, wherein the material information comprises material states;
the personnel management unit is connected with the material management unit and the department structure unit and is used for determining personnel allocation strategies and allocating the processing personnel of each business department based on the personnel allocation strategies so as to obtain station information for the processing personnel.
In one possible implementation, the service management module includes:
a service list unit, configured to associate the service information to be processed to a preset service template, so as to obtain a service list;
the charging class handover unit is connected with the service list unit and the material management unit and is used for determining a service department associated with the service list, distributing corresponding service to the determined service department based on the service list and identifying the corresponding service state as a to-be-completed state;
Assigning a corresponding department working period to the determined business department;
based on the station information aiming at the materials, corresponding materials are distributed to the determined business departments, and a delivery instruction is sent to the material management unit, so that the material management unit identifies the material state corresponding to the distributed materials as a delivery state after responding to the delivery instruction.
In one possible implementation manner, the charging shift handover unit is further configured to, before detecting that a currently working service department reaches an end time of a department working period, check a material corresponding to the currently working service department, and send a warehousing instruction to the material management unit, so that the material corresponding to the currently working service department is updated from a warehouse-out state to a warehouse-in state after responding to the warehousing instruction by the material management unit;
when the current working business department is detected to reach the end time, the business state corresponding to the current working business department is updated in the business list to be the finished state, and the next business department to be worked is controlled to process the corresponding business.
In one possible implementation, the service management module further includes:
And the executive log unit is connected with the charging executive handover unit and is used for carrying out work log record on the currently working business department based on a preset log template.
In one possible implementation, the service management module further includes:
the toll collector handover personnel unit is connected with the toll collector handover personnel unit and is used for distributing materials corresponding to the business departments for the processing personnel of the business departments and determining the personnel working time period of the processing personnel;
when the fact that the currently working processor reaches the end time of the working period of the processor is detected, transmitting handover information to the next processor to be worked, wherein the handover information is used for indicating the next processor to be worked to start working and carrying the material information distributed by the currently working processor.
In one possible implementation, the in-station auditing module includes an auditing task unit;
the examination task unit is used for selecting license plate images of other sites in a preset period from a license plate database aiming at examination tasks of the charging business;
matching license plate images acquired by a website to which the login user belongs in an inspection time period with the selected license plate images by utilizing a pre-established retrieval model so as to determine the travel information of each vehicle in the inspection time period based on a matching result;
Calculating a corresponding theoretical charging value based on the journey information;
and comparing the theoretical charging value with the actual charging value of the vehicle, and determining the vehicle corresponding to the inconsistent comparison result when the comparison result is inconsistent so as to display service distribution information corresponding to the charging service of the vehicle, wherein the service distribution information comprises the station information and the corresponding processor information of the vehicle when the vehicle enters the expressway.
In one possible implementation, the in-station auditing module further includes a retrieval model construction unit connected with the auditing task unit;
the search model is formed by combining a fuzzy logic operator and a deep neural network, wherein the deep neural network comprises a convolution layer, an average pooling layer and a full connection layer which are arranged in a cascading sequence;
the retrieval model construction unit is used for inputting license plate images of sites to which the login user belongs and the selected license plate images into the fuzzy logic operator to perform exclusive OR operation, so that the output result of the fuzzy logic operator is used as the input of the deep neural network to output the characteristic values of the input license plate images, and the characteristic values are used for obtaining the matching result for the license plate images through comparison.
In a possible implementation manner, the search model building unit is further configured to build the fuzzy logic operator through formula (1):
（1）
wherein,for the fuzzy logic operator, +.>For the number of channels>For channel weight->The feature map is obtained by convolution operation of the input license plate image;
constructing the deep neural network by the formula (2):
（2）
wherein,for the output of the deep neural network, +.>Is biased;
the bias is obtained by equation (3):
（3）
wherein,summing for each channel for said profile, ++>Summing for each channel weight in the convolutional layer and the fully-connected layer.
According to another aspect of the embodiments of the present application, there is provided an intelligent management method for highway toll service, including:
identifying a site to which a login user belongs;
acquiring station information of the station aiming at business departments, materials and processing personnel;
correlating the acquired service information to be processed to a preset service template to acquire a service list;
performing service distribution on each service department based on the service list, and determining an execution strategy of each service department according to the station information, so that the distributed service is processed based on the execution strategy, wherein the execution strategy is used for indicating distribution of materials and processing personnel;
And executing the examination task aiming at the charging business, and displaying and processing the business distribution information of the corresponding charging business when the examination task is abnormal.
The method has the advantages that the login module is used for identifying the site to which the login user belongs, the station management module is used for acquiring the station information of the site aiming at the business departments, the materials and the processing personnel, and then the service management module is used for associating the acquired business information to be processed with a preset business template so as to acquire a business list; and carrying out service distribution on each service department based on the service list, determining an execution strategy of each service department according to the station service information, and processing the distributed service based on the execution strategy, wherein the execution strategy is used for indicating distribution of materials and processing personnel, so that an inspection task for charging service is executed through an in-station inspection module, and service distribution information corresponding to the charging service is displayed and processed when the result of the inspection task is abnormal, thus, intelligent management is realized by managing various information in a digital form, meanwhile, rapid configuration of service data is realized by configuring a service template, the condition of large repeated workload is avoided, and the processing efficiency of expressway charging service management is improved. And aiming at the fund examination link in the charging process, the automatic examination is realized, the labor cost is greatly reduced, the service distribution information corresponding to the abnormal charging service can be rapidly acquired through the service configuration of the service management module, the processing time is reduced, and the correction of missed collection and erroneous collection is realized, so that the technical problem of lower processing efficiency of the conventional expressway charging management technology is solved.
Drawings
Fig. 1 is a schematic structural diagram of an intelligent management system for highway toll service according to an embodiment of the present application;
fig. 2 is a schematic flow chart of an intelligent management method for highway toll service according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
Example 1:
fig. 1 is a schematic structural diagram of an intelligent management system for highway toll service according to an embodiment of the present application, where the system 100 includes:
a login module 101, configured to identify a site to which a login user belongs;
the station management module 102 is connected to the login module 101 and is used for acquiring station information of the station for business departments, materials and processing personnel;
the service management module 103 is connected to the station management module 102 and is used for associating the acquired service information to be processed with a preset service template to obtain a service list; performing service distribution on each service department based on the service list, and determining an execution strategy of each service department according to the station information, so that the distributed service is processed based on the execution strategy, wherein the execution strategy is used for indicating distribution of materials and processing personnel;
And the in-station auditing module 104 is connected with the service management module 103 and is used for executing the auditing task aiming at the charging service and displaying and processing the service distribution information of the corresponding charging service when the auditing task is abnormal.
In the application, the login module is connected with the user terminal, so that the user terminal performs identity verification on a user (i.e. a login user) through the login module so as to verify whether the user is a staff member, and can execute subsequent system operation when the user is verified to be the staff member. The station management module is used for managing station information such as processing personnel, business departments, materials and the like, realizing the management of various information in a digital form and realizing intelligent management. The business management module is used for distributing the business to be processed to each business department and distributing the processing personnel and materials of each business department to realize the processing of the business distributed to the business management module. By configuring the service template, the method and the device realize quick generation of the service list, avoid the condition of large processing capacity of repeated workload in the prior art, and improve the processing efficiency. The in-station checking module is used for checking the charging business, and can quickly extract business distribution information of the corresponding business when checking abnormality, such as business departments, processing personnel, stations and the like for each working period, so as to be convenient for realizing correction of missed receipts and misplaces by combining the distribution of factors such as business departments, processing personnel, materials and the like for each business in the business management module.
In a preferred embodiment, the data information in the management system is stored and managed in the form of structured data, so that the operation is convenient, and the processing efficiency of the system is improved.
The intelligent management system for highway toll service provided by the embodiment identifies a site to which a login user belongs through a login module, acquires station information of the site for service departments, materials and processing personnel through a station management module, and then associates the acquired service information to be processed into a preset service template through the service management module to acquire a service list; and carrying out service distribution on each service department based on the service list, determining an execution strategy of each service department according to the station service information, and processing the distributed service based on the execution strategy, wherein the execution strategy is used for indicating distribution of materials and processing personnel, so that an inspection task for charging service is executed through an in-station inspection module, and service distribution information corresponding to the charging service is displayed and processed when the result of the inspection task is abnormal, thus, intelligent management is realized by managing various information in a digital form, meanwhile, rapid configuration of service data is realized by configuring a service template, the condition of large repeated workload is avoided, and the processing efficiency of expressway charging service management is improved. And aiming at the fund examination link in the charging process, the automatic examination is realized, the labor cost is greatly reduced, the service distribution information corresponding to the abnormal charging service can be rapidly acquired through the service configuration of the service management module, the processing time is reduced, and the correction of missed collection and erroneous collection is realized, so that the technical problem of lower processing efficiency of the conventional expressway charging management technology is solved.
In some embodiments, the station management module comprises:
the department structure unit is used for acquiring the configuration information of the business department from the login user and associating the configuration information of the business department to a preset department configuration template so as to acquire the station information of the business department;
the material management unit is connected with the department structure unit and is used for managing material information of materials, wherein the material information comprises material states;
the personnel management unit is connected with the material management unit and the department structure unit and is used for determining personnel allocation strategies and allocating the processing personnel of each business department based on the personnel allocation strategies so as to obtain station information for the processing personnel.
The station management module is composed of a personnel management unit, a department structure unit and a material management unit. The personnel management unit is used for managing basic information of the processing personnel, including information such as 'name', 'team', 'identity', 'mobile phone number', 'identity card number', 'state', and distribution of business departments. The department structure unit is responsible for managing each business department. The material management unit is responsible for managing materials of the site, including 'flashlight', 'seal of day' and the like.
In this embodiment, the user accesses the service management module, and first sets each service department of the site through the department structure unit, so as to obtain service department configuration information, such as "service one group", "service two group", and the like. In this embodiment, the department configuration template is provided with common information, so that the user can import the configuration information of the business department into the department configuration template, and the station information about the business department can be obtained quickly, thereby improving the data processing efficiency. The material management unit is used for checking the material of the site so as to manage material information such as material states (such as ex-warehouse state and warehouse-in state), material types, material quantity and the like. And then, the personnel management unit performs department allocation on the processing personnel based on personnel allocation strategies, the personnel allocation strategies can be determined by a plurality of personnel allocation strategies stored in the unit in a week, the personnel allocation applicability is improved, the processing efficiency of the system is improved, and the operation is convenient.
In some embodiments, the service management module comprises:
a service list unit, configured to associate the service information to be processed to a preset service template, so as to obtain a service list;
The charging class handover unit is connected with the service list unit and the material management unit and is used for determining a service department associated with the service list, distributing corresponding service to the determined service department based on the service list and identifying the corresponding service state as a to-be-completed state;
assigning a corresponding department working period to the determined business department;
based on the station information aiming at the materials, corresponding materials are distributed to the determined business departments, and a delivery instruction is sent to the material management unit, so that the material management unit identifies the material state corresponding to the distributed materials as a delivery state after responding to the delivery instruction.
In this embodiment, the user enters the service management module, and fills in the service to be processed through the service list unit, so as to obtain the service information to be processed. By configuring a plurality of service templates, the configuration of the service list is completed rapidly, and repeated work in the management process is reduced. And then, carrying out service distribution on the service departments according to the service list through the charging class handover unit.
Specifically, the service distribution step for the service department includes: selecting a service department, distributing the service to be completed in the service list, and enabling the service to be distributed in the service list to be changed from a to-be-distributed state to a to-be-completed state; assigning a department working period to the selected business department; distributing corresponding materials for the selected business departments, wherein after distribution, the corresponding material states in the material management unit are changed from the in-warehouse state to the out-warehouse state; and carrying out work time period arrangement on the corresponding processing personnel of each business department. Therefore, the embodiment realizes the intelligent management of the service by carrying out service distribution aiming at the service department, and improves the efficiency of service processing.
In some embodiments, the charging shift handover unit is further configured to, before detecting that the currently working business department reaches the end time of the department working period, check the material corresponding to the currently working business department, and send a warehousing instruction to the material management unit, so that the material corresponding to the currently working business department is updated from a warehouse-out state to a warehouse-in state after responding to the warehousing instruction by the material management unit;
when the current working business department is detected to reach the end time, the business state corresponding to the current working business department is updated in the business list to be the finished state, and the next business department to be worked is controlled to process the corresponding business.
In this embodiment, when the currently working business department arrives, the receiving business department is notified in advance, and the materials in the currently working business department are checked, and the materials are put in storage after being checked, and the corresponding materials in the materials management unit are changed from the in-storage state to the put-in-storage state. Then, when the currently working business department arrives, the corresponding business state is identified in the business list to be changed from the to-be-completed state to the completed state, the accepted business department starts working, and the working state is changed from off-duty to on-duty. Therefore, the embodiment realizes the work handover between the business departments by aiming at the control and the configuration processing of the current working business departments and the receiving business departments, does not need manual processing, and improves the intellectualization and the processing efficiency.
In some embodiments, the service management module further comprises:
the toll collector handover personnel unit is connected with the toll collector handover personnel unit and is used for distributing materials corresponding to the business departments for the processing personnel of the business departments and determining the personnel working time period of the processing personnel;
when the fact that the currently working processor reaches the end time of the working period of the processor is detected, transmitting handover information to the next processor to be worked, wherein the handover information is used for indicating the next processor to be worked to start working and carrying the material information distributed by the currently working processor.
In this embodiment, the task in each business department is refined by the toll collector handing-over personnel unit, such as the distribution of each piece of material and the working period of each processing personnel. When the current working processor needs to change the work, the receiver is informed in advance and the material is delivered, but the material state corresponding to the material is not changed and is not put in storage, and the storage operation is carried out after the whole work of the business department is needed to be completed. Therefore, the embodiment combines the service distribution of each service department and the distribution of materials, processing personnel and the like in the service department, realizes automatic management and processing of the service, and greatly reduces the management cost.
Based on the above embodiments, in some embodiments, the service management module further includes:
and the executive log unit is connected with the charging executive handover unit and is used for carrying out work log record on the currently working business department based on a preset log template.
In this embodiment, the working log unit is configured to record the working log, so that the working handover between the business department and the processing personnel is facilitated, meanwhile, the loss of working data under the fault condition such as handover failure is avoided, and the risk of system operation is reduced.
In some embodiments, the in-station auditing module includes an auditing task unit;
the examination task unit is used for selecting license plate images of other sites in a preset period from a license plate database aiming at examination tasks of the charging business;
matching license plate images acquired by a website to which the login user belongs in an inspection time period with the selected license plate images by utilizing a pre-established retrieval model so as to determine the travel information of each vehicle in the inspection time period based on a matching result;
calculating a corresponding theoretical charging value based on the journey information;
and comparing the theoretical charging value with the actual charging value of the vehicle, and determining the vehicle corresponding to the inconsistent comparison result when the comparison result is inconsistent so as to display service distribution information corresponding to the charging service of the vehicle, wherein the service distribution information comprises the station information and the corresponding processor information of the vehicle when the vehicle enters the expressway.
At present, for fund examination, when ETC recognition is wrong or license plate recognition is wrong, missed collection and wrong collection phenomena can occur, and at the moment, the passing charge can generate deviation. In this regard, the present embodiment sets a timed audit task by the audit task unit, with the set parameter being audit interval time to automatically perform audit for a charged service. The uncertainty behind the data is built by using a fuzzy rule through combining a fuzzy logic and a deep neural network image retrieval mode, so that the rapid retrieval of large-scale license plate images is realized, manual retrieval is replaced, the pairing of high-efficiency license plates is realized, and the fund errors caused by missed receipts and incorrect receipts are corrected rapidly.
In the method, the license plate database is constructed, so that data intercommunication among sites is realized, the processing efficiency of the system is improved, and automatic management is realized.
Based on the above embodiments, in some embodiments, the in-station auditing module further includes a retrieval model construction unit connected with the auditing task unit;
the search model is formed by combining a fuzzy logic operator and a deep neural network, wherein the deep neural network comprises a convolution layer, an average pooling layer and a full connection layer which are arranged in a cascading sequence;
The retrieval model construction unit is used for inputting license plate images of sites to which the login user belongs and the selected license plate images into the fuzzy logic operator to perform exclusive OR operation, so that the output result of the fuzzy logic operator is used as the input of the deep neural network to output the characteristic values of the input license plate images, and the characteristic values are used for obtaining the matching result for the license plate images through comparison.
Based on the above embodiments, in some embodiments, the search model building unit is further configured to build the fuzzy logic operator by formula (1):
（1）
wherein,for the fuzzy logic operator, +.>For the number of channels>For channel weight->The feature map is obtained by convolution operation of the input license plate image;
constructing the deep neural network by the formula (2):
（2）
wherein,for the output of the deep neural network, +.>Is biased;
the bias is obtained by equation (3):
（3）
wherein,summing for each channel for said profile, ++>Summing for each channel weight in the convolutional layer and the fully-connected layer.
It should be noted that, the search model is composed of a fuzzy logic operator and a deep neural network, and the combination mode of the two algorithms is to fuzzify the operation of each neuron. The deep neural network comprises a convolution layer, an average pooling layer and a full connection layer, and the fuzzy logic operator is an exclusive or operation. Further, the output of the deep neural network is used as the output result of the search model, namely, the characteristic value of the input license plate image is output, for example, the characteristic value is a hash value. And then, comparing the hash value of the license plate image acquired by the local site to which the login user belongs with hash values of license plate images acquired by other sites to generate a matching pair of the license plate image of the local site and the corresponding license plate image in the other sites, namely a matching result, so that the site of the vehicle when entering the expressway, namely the entering site, is acquired based on the matching pair. Further, according to the information of the site (namely the out site) and the in site, the journey information of each vehicle in the examination time period of the site is calculated, so that a theoretical charging value is calculated, and the theoretical charging value is compared with an actual charging value to screen out abnormal vehicle information. Meanwhile, the information of the corresponding processing personnel when the vehicle enters the expressway is acquired through the inbound point information corresponding to the charging service, so that the correction of missed and wrong collection of the expressway cost is realized.
Example 2:
fig. 2 is a flow chart of an intelligent management method for highway toll service according to an embodiment of the present application, where the method includes steps S201 to S205.
S201, identifying a site to which the login user belongs.
S202, acquiring station information of the station aiming at business departments, materials and processing personnel.
S203, the acquired service information to be processed is associated to a preset service template to acquire a service list.
S204, carrying out service distribution on each service department based on the service list, and determining an execution strategy of each service department according to the station service information, so that the distributed service is processed based on the execution strategy, wherein the execution strategy is used for indicating distribution of materials and processing personnel.
S205, executing the examination task for the charging business, and displaying and processing the business distribution information of the corresponding charging business when the examination task is abnormal.
In some embodiments, step S202 includes:
acquiring service department configuration information from the login user, and associating the service department configuration information into a preset department configuration template to obtain station information for the service department;
Managing material information of the material, wherein the material information comprises material states;
and determining a personnel allocation strategy, and allocating the processing personnel of each business department based on the personnel allocation strategy so as to obtain the station information for the processing personnel.
In some embodiments, the method comprises:
the service information is associated to a preset service template to obtain a service list;
determining a service department associated with the service list, distributing corresponding service to the determined service department based on the service list, and identifying the corresponding service state as a state to be completed;
assigning a corresponding department working period to the determined business department;
based on the station information aiming at the materials, corresponding materials are distributed to the determined business departments, and a delivery instruction is sent to the material management unit, so that the material management unit identifies the material state corresponding to the distributed materials as a delivery state after responding to the delivery instruction.
In some embodiments, step S204 includes:
before detecting that a currently working business department reaches the end time of a department working period, checking materials corresponding to the currently working business department, and sending a warehousing instruction to the material management unit, so that the materials corresponding to the currently working business department are updated from a warehouse-out state to a warehouse-in state after responding to the warehousing instruction by the material management unit;
When the current working business department is detected to reach the end time, the business state corresponding to the current working business department is updated in the business list to be the finished state, and the next business department to be worked is controlled to process the corresponding business.
In some embodiments, the method comprises:
and carrying out work log record on the currently working business department based on a preset log template.
In some embodiments, the method comprises:
distributing materials corresponding to the business departments for the processing personnel of each business department, and determining the personnel working time period of each processing personnel;
when the fact that the currently working processor reaches the end time of the working period of the processor is detected, transmitting handover information to the next processor to be worked, wherein the handover information is used for indicating the next processor to be worked to start working and carrying the material information distributed by the currently working processor.
In some embodiments, step S205 includes:
aiming at the examination task of the charging business, selecting license plate images of other sites in a preset period from a license plate database;
matching license plate images acquired by a website to which the login user belongs in an inspection time period with the selected license plate images by utilizing a pre-established retrieval model so as to determine the travel information of each vehicle in the inspection time period based on a matching result;
Calculating a corresponding theoretical charging value based on the journey information;
and comparing the theoretical charging value with the actual charging value of the vehicle, and determining the vehicle corresponding to the inconsistent comparison result when the comparison result is inconsistent so as to display service distribution information corresponding to the charging service of the vehicle, wherein the service distribution information comprises the station information and the corresponding processor information of the vehicle when the vehicle enters the expressway.
In some embodiments, step S205 includes:
the search model is formed by combining a fuzzy logic operator and a deep neural network, and the deep neural network comprises a convolution layer, an average pooling layer and a full-connection layer which are arranged in cascade sequencing;
and inputting license plate images of sites to which the login user belongs and the selected license plate images into the fuzzy logic operator for exclusive OR operation, so that an output result of the fuzzy logic operator is used as input of the deep neural network to output characteristic values of the input license plate images, and the characteristic values are used for obtaining a matching result aiming at the license plate images through comparison.
In some embodiments, step S205 includes:
constructing the fuzzy logic operator by the formula (1):
（1）
Wherein,for the fuzzy logic operator, +.>For the number of channels>For channel weight->The feature map is obtained by convolution operation of the input license plate image;
constructing the deep neural network by the formula (2):
（2）
wherein,for the output of the deep neural network, +.>Is biased;
the bias is obtained by equation (3):
（3）
wherein,summing for each channel for said profile, ++>Summing for each channel weight in the convolutional layer and the fully-connected layer.
According to the intelligent management method for the expressway toll service, the station information of a service department, materials and processing personnel of a station is acquired by identifying the station to which a login user belongs, and then the acquired service information to be processed is associated to a preset service template to acquire a service list; and carrying out service distribution on each service department based on the service list, determining an execution strategy of each service department according to the station service information, and processing the distributed service based on the execution strategy, wherein the execution strategy is used for indicating distribution of materials and processing personnel so as to execute a checking task aiming at charging service, and displaying and processing service distribution information of the charging service when the result of the checking task is abnormal. And aiming at the fund examination link in the charging process, the automatic examination is realized, the labor cost is greatly reduced, the service distribution information corresponding to the abnormal charging service can be rapidly acquired through the service configuration of the service management module, the processing time is reduced, and the correction of missed collection and erroneous collection is realized, so that the technical problem of lower processing efficiency of the conventional expressway charging management technology is solved.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.

Claims (7)

1. An intelligent management system for highway toll service, comprising:
the login module is used for identifying a site to which a login user belongs;
the station management module is connected with the login module and is used for acquiring station information of the station for business departments, materials and processing personnel;
the service management module is connected with the station management module and is used for associating the acquired service information to be processed with a preset service template so as to acquire a service list; performing service distribution on each service department based on the service list, and determining an execution strategy of each service department according to the station information, so that the distributed service is processed based on the execution strategy, wherein the execution strategy is used for indicating distribution of materials and processing personnel;
the in-station auditing module is connected with the service management module and is used for executing auditing tasks aiming at the charging service and displaying and processing service distribution information of the corresponding charging service when the auditing tasks are abnormal;
Wherein the in-station auditing module comprises an auditing task unit;
the examination task unit is used for selecting license plate images of other sites in a preset period from a license plate database aiming at examination tasks of the charging business;
matching license plate images acquired by a website to which the login user belongs in an inspection time period with the selected license plate images by utilizing a pre-established retrieval model so as to determine the travel information of each vehicle in the inspection time period based on a matching result;
calculating a corresponding theoretical charging value based on the journey information;
comparing the theoretical charging value with the actual charging value of the vehicle, and determining the vehicle corresponding to the inconsistent comparison result when the comparison result is inconsistent so as to display service distribution information corresponding to charging service of the vehicle, wherein the service distribution information comprises station information and corresponding processor information of the vehicle when the vehicle enters a highway;
the in-station auditing module further comprises a retrieval model construction unit connected with the auditing task unit; the search model is formed by combining a fuzzy logic operator and a deep neural network, and the deep neural network comprises a convolution layer, an average pooling layer and a full-connection layer which are arranged in cascade sequencing;
The retrieval model construction unit is used for inputting license plate images of sites to which the login user belongs and the selected license plate images into the fuzzy logic operator to perform exclusive OR operation, so that an output result of the fuzzy logic operator is used as input of the deep neural network to output characteristic values of the input license plate images, and the characteristic values are used for obtaining a matching result for the license plate images through comparison;
the search model construction unit is further configured to construct the fuzzy logic operator by equation (1):
（1）
wherein,for the fuzzy logic operator, +.>For the number of channels>For channel weight->The feature map of the input license plate image after convolution operation is +.>For the convolutional layer and the fully connected layer +.>The channel weight of each channel is determined,is->Feature maps of the individual channels;
constructing the deep neural network by the formula (2):
（2）
wherein,for the output of the deep neural network, +.>Is biased;
the bias is obtained by equation (3):
（3）
wherein,summing for each channel for said profile, ++>Summing for each channel weight in the convolutional layer and the fully-connected layer.
2. The intelligent management system for highway tolling traffic according to claim 1, wherein said station management module comprises:
the department structure unit is used for acquiring the configuration information of the business department from the login user and associating the configuration information of the business department to a preset department configuration template so as to acquire the station information of the business department;
the material management unit is connected with the department structure unit and is used for managing material information of materials, wherein the material information comprises material states;
the personnel management unit is connected with the material management unit and the department structure unit and is used for determining personnel allocation strategies and allocating the processing personnel of each business department based on the personnel allocation strategies so as to obtain station information for the processing personnel.
3. The intelligent management system for highway tolling traffic according to claim 2, wherein said traffic management module comprises:
a service list unit, configured to associate the service information to be processed to a preset service template, so as to obtain a service list;
the charging class handover unit is connected with the service list unit and the material management unit and is used for determining a service department associated with the service list, distributing corresponding service to the determined service department based on the service list and identifying the corresponding service state as a to-be-completed state;
Assigning a corresponding department working period to the determined business department;
based on the station information aiming at the materials, corresponding materials are distributed to the determined business departments, and a delivery instruction is sent to the material management unit, so that the material management unit identifies the material state corresponding to the distributed materials as a delivery state after responding to the delivery instruction.
4. The intelligent management system for highway toll service according to claim 3, wherein the toll class handover unit is further configured to, before detecting that a currently operated service department reaches an end time of a department operation period thereof, check a material corresponding to the currently operated service department, and send a warehousing instruction to the material management unit, so that the material corresponding to the currently operated service department is updated from a warehouse-out state to a warehouse-in state after responding to the warehousing instruction by the material management unit;
when the current working business department is detected to reach the end time, the business state corresponding to the current working business department is updated in the business list to be the finished state, and the next business department to be worked is controlled to process the corresponding business.
5. The intelligent management system for highway tolling traffic according to claim 4, wherein said traffic management module further comprises:
And the executive log unit is connected with the charging executive handover unit and is used for carrying out work log record on the currently working business department based on a preset log template.
6. The intelligent management system for highway tolling traffic according to claim 3, wherein said traffic management module further comprises:
the toll collector handover personnel unit is connected with the toll collector handover personnel unit and is used for distributing materials corresponding to the business departments for the processing personnel of the business departments and determining the personnel working time period of the processing personnel;
when the fact that the currently working processor reaches the end time of the working period of the processor is detected, transmitting handover information to the next processor to be worked, wherein the handover information is used for indicating the next processor to be worked to start working and carrying the material information distributed by the currently working processor.
7. An intelligent management method for highway toll service is characterized by comprising the following steps:
identifying a site to which a login user belongs;
acquiring station information of the station aiming at business departments, materials and processing personnel;
correlating the acquired service information to be processed to a preset service template to acquire a service list;
Performing service distribution on each service department based on the service list, and determining an execution strategy of each service department according to the station information, so that the distributed service is processed based on the execution strategy, wherein the execution strategy is used for indicating distribution of materials and processing personnel;
executing the examination task for the charging business, and when the examination task is abnormal, displaying and processing the business distribution information of the corresponding charging business, wherein the business distribution information comprises the following steps: aiming at the examination task of the charging business, selecting license plate images of other sites in a preset period from a license plate database; matching license plate images acquired by a website to which the login user belongs in an inspection time period with the selected license plate images by utilizing a pre-established retrieval model so as to determine the travel information of each vehicle in the inspection time period based on a matching result; calculating a corresponding theoretical charging value based on the journey information; comparing the theoretical charging value with the actual charging value of the vehicle, and determining the vehicle corresponding to the inconsistent comparison result when the comparison result is inconsistent so as to display service distribution information corresponding to charging service of the vehicle, wherein the service distribution information comprises station information and corresponding processor information of the vehicle when the vehicle enters a highway; the retrieval model is formed by combining a fuzzy logic operator and a deep neural network, the deep neural network comprises a convolution layer, an average pooling layer and a full connection layer which are arranged in a cascading sequence, a license plate image of a site to which the login user belongs and the selected license plate image are input into the fuzzy logic operator to carry out exclusive OR operation, an output result of the fuzzy logic operator is used as input of the deep neural network to output a characteristic value of the input license plate image, and the characteristic value is used for obtaining a matching result aiming at the license plate image through comparison;
Wherein the fuzzy logic operator is constructed by equation (1):
（1）
wherein,for the fuzzy logic operator, +.>For the number of channels>For channel weight->The feature map of the input license plate image after convolution operation is +.>For the convolutional layer and the fully connected layer +.>The channel weight of each channel is determined,is->Feature maps of the individual channels;
constructing the deep neural network by the formula (2):
（2）
wherein,for the output of the deep neural network, +.>Is biased;
the bias is obtained by equation (3):
（3）
wherein,summing for each channel for said profile, ++>Summing for each channel weight in the convolutional layer and the fully-connected layer.
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