CN112711619A - Beidou positioning-based highway fee evasion inspection platform - Google Patents
Beidou positioning-based highway fee evasion inspection platform Download PDFInfo
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Abstract
The invention provides a Beidou positioning-based highway fee evasion checking platform, which comprises a big data checking system, a list management system, a work order system and an outfield checking system, wherein the big data checking system, the list management system, the work order system and the outfield checking system are in data interaction with one another; the big data inspection system is used for judging whether the user and the vehicle have payment neglecting behaviors and illegal fee evasion behaviors; the list management system is used for receiving and storing information of users and vehicles with illegal fee evasion behaviors; the work order system is used for generating an inspection work order and processing and feeding back the inspection work order; the outfield inspection system is used for inspecting vehicles on site through the handheld terminal, matching vehicles on site or uploading image information of vehicle license plates, automatically detecting vehicle illegal conditions, enforcing law on illegal vehicles and chasing up lost tolls. According to the invention, through establishing various inspection models to carry out big data analysis, a complete evidence chain is formed, and a basis is provided for mileage charge payment, vehicle management and state list management.
Description
Technical Field
The invention relates to the technical field of highway fee evasion checking, in particular to a highway fee evasion checking platform based on Beidou positioning.
Background
According to the general requirement of the government of the province of Hainan province on 'ban sale prohibition traditional fuel vehicles in the island by stage starting and implementing by sub-fields around 2030', the province of Hainan actively explores and establishes a new collection mode for stabilizing capital sources of highway construction. At present, no toll station is arranged in Hainan province, and a road toll mode of 'four-fee-in-one' is replaced by a mode of collecting additional fuel fee. In recent years, new energy vehicles are vigorously popularized in Hainan province, fuel vehicles are reduced year by year, the basis of dynamic fuel tax accounting is further influenced, the fund source and stability of ordinary road maintenance are further influenced, and effective technical means are urgently needed to realize the innovation and reform of the road toll mode and support the sustainable development of traffic infrastructure aiming at fund gaps in the fields of road construction and maintenance.
The existing checking system of the ETC high-speed electronic toll collection system is developed on the basis of an inland closed road network, a large amount of portal flow data, video card port data and entrance and exit toll station data, and cannot support open road network and Beidou positioning data.
Therefore, there is a need in the art to develop an auditing system that can overcome the above-mentioned technical problems in the prior art.
Disclosure of Invention
The invention aims to provide a highway fee evasion checking platform based on Beidou positioning, which can solve the technical problems that the existing checking system of an ETC high-speed electronic toll collection system carries out fee collection checking based on an inland closed road network, portal flow data, video card port data and entrance and exit toll station data, and the toll collection checking cannot be realized for an open road network without a portal.
The invention provides a Beidou positioning-based highway fee evasion checking platform, which comprises: the system comprises a big data inspection system, a list management system, a work order system and an external field inspection system, wherein the big data inspection system, the list management system, the work order system and the external field inspection system are in data interaction with each other;
the big data inspection system is used for acquiring space data information from the mileage-fee-based operation management platform and a third-party platform, establishing different inspection models, comparing the toll inspection running water with the charging running water generated by the mileage-fee operation management platform, pushing a comparison result to an inspector for judgment and confirmation, and manually judging whether the user and the vehicle have payment missing behaviors and illegal fee evasion behaviors;
the list management system is used for receiving and storing the user and vehicle information of the big data inspection system which judges that illegal fee evasion behaviors exist;
the work order system is used for checking abnormal bills or vehicles according to the big data checking system, generating a checking work order through a work order generating interface, and processing and feeding back the checking work order;
the outfield inspection system is used for receiving the information of the work order system and the name list management system, performing data interaction with a mileage charge operation management platform, inspecting field vehicles through a handheld terminal, matching or uploading vehicle license plate image information, automatically detecting vehicle illegal conditions, performing law enforcement on illegal vehicles, and chasing leaked toll.
Preferably, the system further comprises a fee compensation management system, wherein the fee compensation management system performs data interaction with the work order system, and is used for uniformly managing the inspection fee generated by the inspection work order in the work order system and viewing all the conditions needing fee compensation and the result of user fee compensation.
Preferably, the big data inspection system comprises an inspection model, a travel list inspection, a vehicle model inspection and a terminal inspection,
the inspection model is used for finding cheating vehicles or abnormal vehicles;
the travel itinerary inspection is used for carrying out big data inspection on travel itineraries, carrying out secondary calculation on a charging result through access track data, third party data, road network data and rate data, judging the continuity between the travel itineraries through comparing a calculation result with third party track data and Beidou data, and pushing abnormal travel itineraries to an inspection auditor for manual confirmation if the abnormal travel itineraries are found;
the vehicle type inspection is used for finding vehicles with inconsistent vehicle types by accessing and issuing vehicle data, writing information data by a terminal and identifying the vehicle data by a gate and combining a big data algorithm;
the terminal inspection is used for monitoring abnormal alarm information of the vehicle-mounted terminal and randomly carrying out terminal heartbeat detection, finding out terminal state or heartbeat abnormality, recording abnormal data and entering big data inspection for carrying out inspection model matching.
Preferably, the inspection model comprises a travel itinerary inspection model, a terminal inspection model and an internal employee behavior analysis inspection model,
the travel itinerary inspection model is used for inspecting the amount, mileage, rate, discount, LBS track and video bayonet images of the travel itinerary in multiple dimensions by accessing third-party data and adopting a big data algorithm, so that vehicles suspected of being abnormal in the travel itinerary are found;
the terminal inspection model is used for matching terminal state, heartbeat and terminal written content data transmitted into the terminal inspection model through a big data algorithm so as to find out malicious shielding of the terminal, illegal issuing operation and abnormal behavior of vehicle model inconsistency;
the internal employee behavior analysis and inspection model is used for carrying out big data analysis on vehicle issuing records, abnormal travel itinerary operation logs of the vehicle, additional payment list operation logs and additional payment list operation log data to find that the illegal operation of the internal employees is abnormal.
Preferably, the list management system comprises a suspected abnormal list, a subsidy list, a pursuit list and a key monitoring list,
the suspected abnormal list is a list for judging that suspected fee evasion behaviors exist in the big data inspection system;
the reimbursement list is a list for determining that the vehicles suspected of being in the abnormal list have missed payment or need to be reimbursed;
the surcharge list is a list for surcharge evasion of the users who confirm that vehicles suspected of the abnormal list have illegal evasion and are overdue and not subsidized;
the key monitoring list is a list which needs key monitoring for confirming that vehicles suspected of being abnormal have illegal behaviors.
Preferably, the list management system further comprises a list audit and list removal,
the list audit is used for auditing the vehicles entering the suspected abnormal list and confirming whether the behaviors of the vehicles meet the condition of additional payment or compensation;
the list removing is used for automatically removing the additional payment or the supplementary payment list for the vehicle which has paid the fee, and is used for automatically removing the additional payment list for the vehicle which has paid the fee by the field inspection personnel.
Preferably, the work order system comprises a work order generating module, a work order dispatching module, a work order counting module and a work order auditing module,
the work order generation module generates a work order for automatically calling a work order generation interface on the inspection platform;
the work order dispatching module is set according to the business rules, automatically assigns work orders to the inspectors and requires the inspectors to regularly complete the inspection work orders;
the work order counting module is used for counting the completed rate and the uncompleted rate of different types of inspection work orders;
and the work order auditing module initiates auditing to the superior level according to the auditing flow after the work order is audited, and the work order processing result can take effect after the auditing is passed.
Preferably, the system also comprises a credit management system, the credit management system performs data interaction with the big data inspection system, the work order system, the list management system and the field inspection system,
the credit management system is used for collecting vehicle driving data, vehicle insurance data and user credit account data, analyzing vehicle behaviors, establishing a vehicle credit library, checking identity traits, behavior preference, credit history and performance capability, and removing the work order system and the list management system for users or vehicles with qualified credit and completed subsidy.
Preferably, the system also comprises a user complaint system which performs data interaction with the work order system,
the work order system is also used for receiving the complaint proposed by the user to form a complaint work order;
the user complaint system is used for realizing the management of the whole complaint process for the initiation, processing and auditing of the complaint worksheet and judging whether the complaint proposed by the user is reasonable or not.
Preferably, the outfield inspection system comprises a mobile inspection and a fixed inspection,
the mobile inspection is that the handheld terminal inspects, receives key monitoring lists and subsidizing payment list information through data communication with the inspection platform, matches with on-site vehicles or uploads vehicle license plate images, the system automatically detects vehicle illegal conditions, finds and enforces law enforcement on illegal vehicles, subsidizes escaping toll, can make punishments according to law, and verifies and inputs key monitoring lists on site;
the fixed inspection is an inspection service center which is used for providing field complaint, illegal penalty payment and compensation payment for mileage bill externally, and the user makes a dispute on law enforcement conditions or makes a dispute on a travel bill to perform complaint processing.
Compared with the prior art, the Beidou positioning-based highway fee evasion checking platform has the following beneficial effects:
1. the big data inspection system of the invention acquires spatial data information based on a mileage charge operation management platform and a third-party platform, acquires data through mobile inspection, combines vehicle passing data, utilizes the big data inspection system, performs big data analysis by establishing various inspection models, finds suspicious behavior vehicles, forms a complete evidence chain, provides basis for mileage charge chasing, vehicle management and state list management, and builds a set of closed-loop inspection management system from vehicle fee evasion behavior discovery, evidence generation to fee chasing, violation behavior punishment and credit evaluation.
2. According to the invention, through the big data inspection system, double inspection of toll overtaking and illegal behaviors is realized, credit evaluation and list management of vehicle users and vehicles are realized, vehicle illegal behavior confirmation and toll overtaking are realized through a mobile inspection mode, and accurate identification of road fee evasion and timely overtaking of fee evasion behaviors are realized.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a first schematic diagram of a frame structure of a Beidou positioning-based highway fee evasion checking platform of the invention;
fig. 2 is a second frame structure schematic diagram of the Beidou positioning-based highway fee evasion checking platform of the invention.
Summary of reference numerals:
1. big data checking system 2 and list management system
3. Work order system 4, outfield inspection system
5. Fee compensation management system 6 and credit management system
7. Customer complaint system
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings in conjunction with the following detailed description. It should be understood that the description is intended to be exemplary only, and is not intended to limit the scope of the present invention. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present invention.
As shown in fig. 1 and 2, the highway fee evasion checking platform based on Beidou positioning provided by the invention comprises a big data checking system 1, a list management system 2, a work order system 3 and an external field checking system 4, wherein the big data checking system 1, the list management system 2, the work order system 3 and the external field checking system 4 are in data interaction with each other;
the big data inspection system 1 is used for acquiring space data information from the mileage-fee-based operation management platform and a third-party platform, establishing different inspection models, comparing the toll inspection running water with the charging running water generated by the mileage-fee operation management platform, pushing the comparison result to an inspector for judgment and confirmation, and judging whether the user and the vehicle have payment missing behaviors and illegal fee evasion behaviors;
the list management system 2 is used for receiving and storing the user and vehicle information of the illegal fee evasion behavior judged by the big data inspection system 1;
the work order system 3 is used for checking abnormal bills or vehicles according to the big data checking system 1, generating a checking work order through the work order generating interface, and processing and feeding back the checking work order;
the outfield inspection system 4 is used for receiving information of the work order system 3 and the list management system 2, performing data interaction with a mileage charge operation management platform, inspecting field vehicles through a handheld terminal, matching or uploading vehicle license plate image information, automatically detecting vehicle illegal conditions, performing law enforcement on illegal vehicles, and paying the missed toll.
Aiming at the travel itinerary with data supplementary recording, the big data inspection system 1 adopts an off-line calculation mode to carry out secondary calculation on the running water generated by the charging service, generates the toll inspection running water by combining the charge rate through carrying out calculation on the track running water of the terminal again, compares the charging running water with the toll inspection running water, and finally generates the travel itinerary amount inspection running water to obtain the amount of money required to be compensated; matching mileage charge flow by using an inspection model to obtain a suspected abnormal list, pushing the total amount of the list to inspection and audit personnel for manual check and confirmation, recording the result into a subsidy list, and automatically informing a user of subsidy in a limited time by the system, and calculating a late payment and a late payment according to days without artificial abnormality; if the payment is not paid in due period and the person is confirmed to be abnormal, the late payment is calculated according to the day, the late payment is also transferred to a payment pursuing list to generate a work order, and the subsequent payment pursuing is carried out through mobile inspection; if the user is confirmed to be the key monitoring list user, the result is recorded into the key monitoring list, the key monitoring is carried out on the vehicle through mobile inspection subsequently, meanwhile, a credit system is established in the credit management system 6, the user is punished through the credit system, and the key monitoring list can be removed after the credit of the user is recovered. The platform can find whether the internal staff has abnormal behaviors such as illegal operation and the like by analyzing the operation records of each list.
The big data inspection system 1 comprises an inspection model, a travel list inspection, a vehicle model inspection and a terminal inspection.
The inspection model is different inspection models established by reading data such as money, mileage, track, average speed per hour, driving path, LBS track, video image of video card port and the like of the vehicle travel list, and cheating vehicles or abnormal vehicles can be found according to different inspection models. And the inspection model can be continuously optimized and perfected in the subsequent operation process, and the types of the inspection model are continuously increased. The inspection model mainly comprises a travel itinerary inspection model, a terminal inspection model and an internal employee behavior analysis inspection model.
The AI image recognition technology is adopted for image data conversion of the video card port, so that the image recognition proportion and the accuracy rate are effectively improved; and combining a big data processing engine to form vehicle structural data, and rapidly positioning the target vehicle by analyzing the vehicle characteristics.
The travel itinerary inspection model performs multi-dimensional inspection on data such as money amount, mileage, rate, discount, LBS track, bayonet image and the like of the travel itinerary by accessing third-party data and adopting a big data algorithm, so that vehicles suspected of being abnormal in the travel itinerary are found. For example: vehicle track discontinuity, track loss, whether to maliciously shield signals, etc.
The terminal inspection model is used for matching the terminal state, the heartbeat and terminal written content data transmitted into the terminal inspection model through a big data algorithm so as to find out malicious shielding of the terminal, illegal issuing operation and abnormal behavior of vehicle model inconsistency.
The internal employee behavior analysis and inspection model is used for carrying out big data analysis on vehicle issuing records, abnormal travel itinerary operation logs of the vehicle, additional payment list operation logs and additional payment list operation log data to find that the illegal operation of the internal employees is abnormal.
The travel itinerary inspection is used for carrying out big data inspection on travel itineraries, carrying out secondary calculation on charging results through the access track data, the third party data, the road network data and the rate data, judging the continuity between the travel itineraries through comparing the calculation results and the third party track data with the Beidou data, and pushing abnormal travel itineraries to an inspection auditor for manual confirmation if abnormal travel itineraries are found. For the itinerary with complete data, the big data inspection is performed in a random inspection mode; the data is incomplete, and the big data inspection is performed in a full inspection mode. The travel itinerary inspection mainly comprises travel itinerary amount comparison inspection and track continuity inspection.
The comparison and inspection of the amount of the travel itinerary is to perform inspection charging off-line calculation on the fitting result in combination with the charge rate by accessing the real-time inspection fitting result, so as to generate the passing fee inspection running water. And matching and comparing the toll inspection running water with the charging running water to finally generate the travel bill amount inspection running water.
And the track continuity check is to read the last charging unit or track point of the previous travel list, perform area relevance matching judgment with the first charging unit or track point of the current travel list, judge whether continuous relevance exists or not, namely that the travel list is discontinuous and abnormal, and push the abnormal travel list to an inspector for verification.
The vehicle type inspection is used for discovering vehicles with inconsistent vehicle types by accessing and issuing vehicle data, writing information data by a terminal and identifying the vehicle data by a gate and combining a big data algorithm. The vehicle model inspection mainly comprises the anomalies that vehicle data is inconsistent with an image identification vehicle model, a truck axle type is inconsistent with a charging vehicle model and the like.
The terminal inspection is used for monitoring abnormal alarm information of the vehicle-mounted terminal and randomly carrying out terminal heartbeat detection, finding out terminal state or heartbeat abnormality, recording abnormal data and entering big data inspection for carrying out inspection model matching.
The big data inspection system 1 of the present invention may further include a benefit inspection, which inspects vehicles evading mileage fees by using a benefit policy, and is a high-risk area for evading mileage fees in the future. The method mainly comprises the steps of checking reservation information of port trucks, matching reserved truck paths, managing preferential vehicles, checking port data, checking green traffic, and the like.
The list management system 2 comprises a suspected exception list, a subsidy list, a pursuit list and a key monitoring list, wherein the suspected exception list is a list for judging that suspected fee evasion behaviors exist in the big data inspection system; the additional payment list is a list for confirming that the vehicle suspected of the abnormal list has the missed payment or needs additional payment; the additional payment list is a list for additional payment of the fee evasion of the user who confirms that the vehicle suspected of the abnormal list has illegal fee evasion and is overdue and not paid; the key monitoring list is a list which needs key monitoring for confirming that vehicles suspected to be abnormal have illegal behaviors.
The list management system 2 is a fee evasion checking list which is made by the platform aiming at the users and the vehicles, the users or the vehicles can evade fees in the passing process by methods of damaging the terminals, shielding terminal information and the like by human subjectivity, and the system finds out the fee evasion users and the vehicles through checking and adds the fee evasion users and the vehicles into the list management system 2. The inspection personnel can carry out fee evasion follow-up payment, key monitoring and the like on the user through the status list, so that fee evasion loss is reduced, illegal fee evasion behaviors are mainly attacked, and the status list is an important basis for auditing, key monitoring and field follow-up payment on suspected abnormal vehicles or abnormal vehicles determined by the system; the additional payment list is a list for the system to additionally pay the fee evasion for the user confirming the illegal fee evasion; the additional payment list is the additional payment list caused by the non-human behavior of the system on the vehicle with the missed payment bill.
In addition, the list management system 2 may further include list review and list removal.
The list audit is used for auditing the vehicles entering the suspected abnormal list, confirming whether the behaviors of the vehicles meet the condition of additional payment or compensation, moving the vehicles into the additional payment or compensation list according with the system, synchronously inputting the vehicles into the key monitoring list, and eliminating the suspected abnormal list. If no abnormity is confirmed, the suspected abnormity list is also eliminated.
The list removing is used for automatically removing the additional payment or the supplementary payment list for the vehicle which has paid the fee, and is used for automatically removing the additional payment list for the vehicle which has paid the fee by the field inspection personnel. The inspection personnel inspects the suspected abnormal list to confirm the abnormal vehicles, generates a follow-up or compensation list and a key monitoring list, and removes the suspected abnormal list; the inspection personnel examines the suspected abnormal list to confirm that the vehicles are not abnormal, and removes the suspected abnormal list. The vehicles entering the key monitoring list can be relieved after the credit score is recovered.
The work order system 3 comprises a work order generating module, a work order dispatching module, a work order counting module and a work order auditing module, wherein the work order generating module generates a work order for automatically taking a work order generating interface on an auditing platform; the work order dispatching module is set according to the business rules, automatically assigns work orders to the inspectors and requires the inspectors to periodically complete the inspection work orders; the work order counting module is used for counting the finished rate and unfinished rate of different types of inspection work orders; and the work order auditing module initiates auditing to the superior level according to the auditing flow after the auditing work order is finished, and the work order processing result can take effect after the auditing is passed.
The work order system 3 supports the inspection platform to push and process feedback of suspected abnormal list work orders, supplementary payment work orders and complaint work orders. The system pushes the suspected abnormal list work order to the auditing and auditing personnel, the auditing personnel audit the suspected abnormal list work order, confirm the abnormal travel order to generate the additional payment work order and push the additional payment work order to the additional payment auditing personnel. The compensation payment inspection personnel carry out field compensation payment of the fee evasion through the compensation work order or inform the user to carry out compensation payment of the fee evasion. The system pushes the complaint work order to an inspector, the inspector judges whether the complaint work order is abnormal or not, if the complaint work order is not abnormal, the complaint work order is rejected, a basis is provided, if the complaint work order is abnormal, the complaint work order related bill is replanned and charged, a compensation refund bill is generated, and a user is informed to carry out compensation refund operation after confirmation.
The Beidou positioning-based road fee evasion checking platform can further comprise a fee compensation management system 5, and the fee compensation management system 5 and the work order system 3 are in data interaction. The compensation charge management system 5 is used for uniformly managing the inspection charge generated by the inspection work order in the work order system 3 and checking all the conditions needing compensation charge and the result of user compensation charge. And after the result of the big data inspection is manually confirmed by the inspection personnel, a subsidy payment list and a chasing payment list are generated. The system informs the user to make a compensation payment, and the user makes a compensation payment or makes a compensation payment under the additional payment of the inspection personnel. The compensation is mainly to provide the compensation interface for the APP end, and the user can complete the compensation of the cost through the interface. And calculating the late payment fund by day from the late payment date according to the inspection result of the overdue payment. Calculated as five parts per million per day. For example, referring to the formula for calculating the late fees specified by the motor vehicle toll surcharge collection management temporary in Hainan province: the amount of the late money is the amount of the late money multiplied by 0.5 per mill multiplied by the number of days of the late money.
The Beidou positioning-based road fee evasion checking platform can further comprise a credit management system 6, wherein the credit management system 6 is in data interaction with the big data checking system 1, the work order system 3, the list management system 2 and the field checking system 4. The credit management system 6 is used for collecting vehicle driving data, vehicle insurance data and user credit account data, analyzing vehicle behaviors, establishing a vehicle credit library, checking identity traits, behavior preference, credit history and performance capability, and removing the work order system 3 and the list management system 2 for the users or vehicles with qualified credit and completed subsidy. The vehicle credit pool's score rules refer to sesame credit rules such as: the rule is as follows,
identity traits (15%): the personal basic information and the vehicle basic information which are abundant and reliable enough and are left in the relevant service using process are verified to be qualified through third-party data;
behavioral preference (25%): various behavior preferences and stability during vehicle travel;
credit history (35%): vehicle insurance records and vehicle insurance history, owner credit account and credit account history;
performance capacity (25%): the past mileage bill payment condition and the use of various credit services and the guarantee of timely fulfillment.
The comprehensive evaluation according to the above rules separates 4 credit levels: 600 or more is good, 650 or more is excellent, 700 or more is excellent, and 950 is classified as a capping value. The credit score is below 600 points, the user and the vehicle with the credit value are considered to be general, the user and the vehicle with the credit value are added into the list management system, long-term credit accumulation and evaluation are carried out, and the list management system 2 is removed when the credit value is recovered above 600 points.
The Beidou positioning-based road fee evasion inspection platform can further comprise a user complaint system 7, wherein the user complaint system 7 is in data interaction with the work order system 3, and the work order system 3 is also used for receiving complaints proposed by users to form a complaint work order; the user complaint system 7 is used for realizing the management of the whole complaint process for the complaint initiation, complaint processing and examination of the complaint worksheet and judging whether the complaint proposed by the user is reasonable or not.
The user can submit a complaint demand through a complaint channel (app, customer service telephone and on-site city inspection bureaus) provided by the platform, the platform customer service or inspection staff judges whether the complaint is abnormal or not, normal refund provides refund basis, the inspection work sheet generated by the abnormality is replanned and charged by the inspection staff, a compensation payment work sheet is generated, the user is informed to confirm a processing result, the user can continue to complain in the above mode if the dissimilarity exists in five working days, the user recognition result is defaulted overtime, and a compensation payment flow is entered.
The outfield inspection system 4 comprises mobile inspection and fixed inspection.
The mobile inspection is performed on the handheld terminal and can be realized through the APP or integrated into the handheld terminal. The system automatically detects the illegal condition of the vehicle, finds and enforces law enforcement on illegal vehicles, subsidizes the escaping toll, can make a punishment according to law, and verifies and inputs the key monitoring list on site;
the fixed inspection is an inspection service center which is used for providing field complaint, illegal penalty payment and compensation payment for mileage bill externally, and the user has objection to law enforcement or has objection to travel itinerary, and can carry out complaint processing in the fixed inspection.
It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explaining the principles of the invention and are not to be construed as limiting the invention. Therefore, any modification, equivalent replacement, improvement and the like made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. Further, it is intended that the appended claims cover all such variations and modifications as fall within the scope and boundaries of the appended claims or the equivalents of such scope and boundaries.
Claims (10)
1. The utility model provides a highway fee evasion inspection platform based on big dipper location which characterized in that includes: the system comprises a big data inspection system, a list management system, a work order system and an external field inspection system, wherein the big data inspection system, the list management system, the work order system and the external field inspection system are in data interaction with each other;
the big data inspection system is used for acquiring space data information from the mileage charge operation management platform and a third-party platform, establishing different inspection models, comparing the toll inspection running water with the charging running water generated by the mileage charge operation management platform, then pushing a comparison result to an inspector, and manually judging whether the user and the vehicle have payment omission behaviors and illegal fee evasion behaviors;
the list management system is used for receiving and storing the user and vehicle information of the big data inspection system which judges that illegal fee evasion behaviors exist;
the work order system is used for checking abnormal bills or vehicles according to the big data checking system, generating a checking work order through a work order generating interface, and processing and feeding back the checking work order;
the outfield inspection system is used for receiving the information of the work order system and the name list management system, performing data interaction with a mileage charge operation management platform, inspecting field vehicles through a handheld terminal, matching or uploading vehicle license plate image information, automatically detecting vehicle illegal conditions, performing law enforcement on illegal vehicles, and chasing leaked toll.
2. The Beidou positioning-based road fee evasion checking platform according to claim 1, further comprising a fee compensation management system, wherein the fee compensation management system is in data interaction with the work order system and is used for uniformly managing the checking fee generated by checking the work order in the work order system and checking all conditions needing fee compensation and the result of user fee compensation.
3. The Beidou positioning-based road fee evasion checking platform as recited in claim 1, wherein the big data checking system comprises checking model, itinerary checking, vehicle type checking and terminal checking,
the inspection model is used for finding cheating vehicles or abnormal vehicles;
the travel itinerary inspection is used for carrying out big data inspection on travel itineraries, carrying out secondary calculation on a charging result through access track data, third party data, road network data and rate data, judging the continuity between the travel itineraries through comparing a calculation result with third party track data and Beidou data, and pushing abnormal travel itineraries to an inspection auditor for manual confirmation if the abnormal travel itineraries are found;
the vehicle type inspection is used for finding vehicles with inconsistent vehicle types by accessing and issuing vehicle data, writing information data by a terminal and identifying the vehicle data by a gate and combining a big data algorithm;
the terminal inspection is used for monitoring abnormal alarm information of the vehicle-mounted terminal and randomly carrying out terminal heartbeat detection, finding out terminal state or heartbeat abnormality, recording abnormal data and entering big data inspection for carrying out inspection model matching.
4. The Beidou positioning-based road fee evasion checking platform according to claim 3, wherein the checking model comprises a travel itinerary checking model, a terminal checking model and an internal employee behavior analysis checking model,
the travel itinerary inspection model is used for inspecting the amount, mileage, rate, discount, LBS track and video bayonet images of the travel itinerary in multiple dimensions by accessing third-party data and adopting a big data algorithm, so that vehicles suspected of being abnormal in the travel itinerary are found;
the terminal inspection model is used for matching terminal state, heartbeat and terminal written content data transmitted into the terminal inspection model through a big data algorithm so as to find out malicious shielding of the terminal, illegal issuing operation and abnormal behavior of vehicle model inconsistency;
the internal employee behavior analysis and inspection model is used for carrying out big data analysis on vehicle issuing records, abnormal travel itinerary operation logs of the vehicle, additional payment list operation logs and additional payment list operation log data to find that the illegal operation of the internal employees is abnormal.
5. The Beidou positioning-based highway toll inspection platform according to claim 1, wherein said list management system comprises suspected abnormal list, subsidy list and major monitoring list,
the suspected abnormal list is a list for judging that suspected fee evasion behaviors exist in the big data inspection system;
the reimbursement list is a list for determining that the vehicles suspected of being in the abnormal list have missed payment or need to be reimbursed;
the surcharge list is a list for surcharge evasion of the users who confirm that vehicles suspected of the abnormal list have illegal evasion and are overdue and not subsidized;
the key monitoring list is a list which needs key monitoring for confirming that vehicles suspected of being abnormal have illegal behaviors.
6. The Beidou positioning-based highway fee evasion auditing platform of claim 5, wherein said list management system further comprises list auditing and list removal,
the list audit is used for auditing the vehicles entering the suspected abnormal list and confirming whether the behaviors of the vehicles meet the condition of additional payment or compensation;
the list removing is used for automatically removing the additional payment or the supplementary payment list for the vehicle which has paid the fee, and is used for automatically removing the additional payment list for the vehicle which has paid the fee by the field inspection personnel.
7. The Beidou positioning-based highway fee evasion checking platform of claim 1, wherein said work order system comprises a work order generating module, a work order dispatching module, a work order counting module and a work order auditing module,
the work order generation module is used for providing a work order generation interface to the inspection platform to generate a work order;
the work order dispatching module is set according to the business rules, automatically assigns work orders to the inspectors and requires the inspectors to regularly complete the inspection work orders;
the work order counting module is used for counting the completed rate and the uncompleted rate of different types of inspection work orders;
and the work order auditing module initiates auditing to the superior level according to the auditing flow after the work order is audited, and the work order processing result can take effect after the auditing is passed.
8. The Beidou positioning-based highway fee evasion checking platform according to claim 1, further comprising a credit management system, wherein the credit management system performs data interaction with the big data checking system, the work order system, the list management system and the field check system;
the credit management system is used for collecting vehicle driving data, vehicle insurance data and user credit account data, analyzing vehicle behaviors, establishing a vehicle credit library, checking identity traits, behavior preference, credit history and performance capability, and removing the work order system and the list management system for users or vehicles with qualified credit and completed subsidy.
9. The Beidou positioning-based road fee evasion inspection platform of claim 1, further comprising a user complaint system, wherein the user complaint system is in data interaction with the work order system,
the work order system is also used for receiving the complaint proposed by the user to form a complaint work order;
the user complaint system is used for realizing the management of the whole complaint process for the initiation, processing and auditing of the complaint worksheet and judging whether the complaint proposed by the user is reasonable or not.
10. The Beidou positioning-based road fee evasion checking platform according to claim 5, wherein the outfield checking system comprises a mobile checking and a fixed checking,
the mobile inspection is that the handheld terminal inspects, receives key monitoring lists and subsidizing payment list information through data communication with the inspection platform, matches with on-site vehicles or uploads vehicle license plate images, the system automatically detects vehicle illegal conditions, finds and enforces law enforcement on illegal vehicles, subsidizes escaping toll, can make punishments according to law, and verifies and inputs key monitoring lists on site;
the fixed inspection is an inspection service center which is used for providing field complaint, illegal penalty payment and compensation payment for mileage bill externally, and the user makes a dispute on law enforcement conditions or makes a dispute on a travel bill to perform complaint processing.
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