CN112419526A - Highway toll calibration method and device and storage medium - Google Patents
Highway toll calibration method and device and storage medium Download PDFInfo
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Abstract
The invention provides a method, a device and a storage medium for calibrating highway toll, wherein the method comprises the following steps: acquiring original data; data cleaning; processing data; path fitting reduction; calculating theoretical actual collection; and checking and comparing the theoretical real received data with the split real received data. In addition, a highway toll calibration device and a storage medium are also provided. By the technical scheme provided by the invention, each operation unit of the expressway is helped to integrally master the traffic transaction running condition after the online charging of the road section, the amount of the toll which is actually paid in the road section is accurately estimated, and reliable evidence is provided for the running treatment of possible unreasonable, unfair and unfair disputes; the system automatically calculates theoretical real-time data and compares and checks the theoretical real-time data with the splitting result of the provincial networking settlement center, so that the abnormal splitting condition is quickly found, and the toll loss of the road section is avoided; the calculation process is simple and convenient, too much manual intervention is not needed, the workload of manual one-by-one comparison is saved, and the working efficiency is improved.
Description
Technical Field
The invention relates to the technical field of highway toll calibration, in particular to a highway toll calibration method, a highway toll calibration device and a highway toll calibration storage medium.
Background
With the deepened development of national high-speed networking charging, the provincial Toll station cancels engineering construction, and the national Electronic Toll Collection (ETC) networking is basically completed. Under the environment of national highway large networking, how to accurately grasp the toll charging and splitting of a single road section becomes one of the important concerns of many road section operation units. In the prior art, different road sections realize the expense settlement of the respective road sections through clearing, and clearing settlement services comprise passing transaction clearing settlement and expanding application transaction clearing settlement. The clearing and settlement of the passage transaction comprises the clearing and settlement of the ETC passage transaction, the splitting of other provinces of the provinces of other transactions, the clearing of fees and compensation payment, settlement of funds and reconciliation of the transactions; the expansion application transaction clearing and settlement comprises ETC expansion service transaction clearing, fee returning and payment supplementing clearing and fund settlement. With the increase of the number of vehicles passing ETC and transaction running water, the calculation amount of the score clearing data is large, the data processing is difficult, particularly, the problem of data mismatching easily occurs in inter-provincial splitting, and each link of the data processing is performed manually, so that time and labor are wasted, and the efficiency is low. Meanwhile, for toll road operation units, the operation income mainly comes from the collection of the toll road, the fairness of vehicle toll collection and distribution is only guaranteed, the investment, operation and management of the expressway cannot be met, and each operation unit also hopes to further know the flow of the vehicle toll collection and distribution business and the detailed process of calculation of the distribution result.
Disclosure of Invention
The invention mainly aims to provide a method, a device and a storage medium for highway toll calibration, and aims to solve the problems of difficulty in highway toll calibration, high error probability and low efficiency of the conventional highway toll calibration.
In order to achieve the above object, the present invention provides a highway toll calibration method, including:
acquiring original data; the original data comprises an original traffic transaction flow uploaded on a highway section;
data cleaning, namely performing data cleaning on the original data to obtain cleaned basic data;
data processing, namely grouping and aggregating the basic data according to the pass identification and the license plate number to construct a road network model;
path fitting reduction, namely inputting effective data into the road network model and performing fitting reduction on the road section and the travel of the vehicle;
theoretical real-time collection calculation, namely accumulating real-time collection amount of the charging units of the vehicle running path which is fit and restored to obtain road section theoretical real-time collection data;
and checking and comparing the theoretical real received data with the split real received data, and performing data association comparison on the transaction split real received data obtained by associating with the provincial networking center and the theoretical real received data to form a difference analysis result.
Further, the highway toll calibration method further comprises the following steps:
data difference analysis, namely comparing the presented difference details step by step according to the difference analysis result to obtain a check conclusion;
and generating an evidence chain report, and generating the evidence chain report according to the checking conclusion.
Further, the original traffic flow includes the entrance station traffic flow, the ETC portal billing transaction flow, the exit ETC traffic flow, the exit other transaction flow, the toll station board recognition flow and the ETC portal board recognition flow.
Further, the data cleansing step includes:
receiving the original data;
performing validity check on the key flow information in the original data, and filtering abnormal information and format error data;
establishing a data cleaning rule, wherein the data cleaning rule is used for cleaning data of the data cleaning abnormal type;
and cleaning the data according to the data cleaning rule to obtain cleaned basic data.
Further, the data washing exception type comprises any one or more of repeated running water, waste running water, entry time exception, expired data, delayed data, unformatted running water, repeated transaction, invalid license plate, invalid data, reverse interference, card reading failure and no gantry number.
Further, the road network model is constructed based on provincial path parameters, and the provincial path parameters comprise road network node codes and adjacent node codes.
Further, the vehicle driving path which is fit and restored comprises a driving path of the current road section entering the current road section, a driving path of the current road section entering the non-current road section, a driving path of the non-current road section entering the current road section and a driving path of the path current road section.
Further, the transaction splitting real receiving data comprises correlation confirmation billing data and non-correlation confirmation billing data.
In order to achieve the above object, the present invention further provides an expressway toll calibration apparatus, including a memory and a processor, wherein the memory stores an expressway toll calibration program operable on the processor, and the expressway toll calibration program implements the steps of the expressway toll calibration method when executed by the processor.
Furthermore, the present invention provides a storage medium, which is a computer-readable storage medium, on which an expressway toll calibration program is stored, the expressway toll calibration program being executable by one or more processors to implement the steps of the expressway toll calibration method described above.
The invention provides a method, a device and a storage medium for calibrating highway toll, which are characterized in that data cleaning and data processing are carried out on a traffic transaction flow, theoretical real collection is calculated by path fitting reduction based on a road network model, and the calibration of the highway toll is completed by checking and comparing theoretical real collection data with split real collection data, wherein the benefits comprise:
the first income helps each operating unit of the highway to integrally master the traffic transaction flow condition of the road section after online charging, thereby better mastering the income condition of the road section and providing data support for further management;
the method has the advantages that the second income is that reliable evidence is provided for unreasonable, unfair and unfair dispute streamline treatment which may exist by accurately estimating the traffic flow and toll data of the road section;
income III, the theoretical real-time data is calculated automatically through the system, and the abnormal splitting condition is rapidly found through the difference between the splitting result of the system and the splitting result of the settlement center, so that the toll loss of the road section is avoided;
the profit is four, the calculation process is simple and convenient, too much manual intervention is not needed, the system can automatically realize difference analysis and comparison, a large amount of manual work is saved to remove the workload of comparing one by one, and the working efficiency is improved.
Drawings
Fig. 1 is a schematic flow chart of a highway toll calibration method according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of step S20 in FIG. 1;
fig. 3 is a schematic diagram of an internal structure of a highway toll calibration device according to an embodiment of the present invention;
fig. 4 is a block diagram of a highway toll calibration procedure in the highway toll calibration device according to an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, an embodiment of the present invention provides a method for calibrating highway toll, including:
step S10: acquiring original data; the original data comprises an original traffic transaction flow uploaded on a highway section; the original passing flow comprises an entrance station passing flow, an ETC portal charging transaction flow, an exit ETC passing flow, an exit other transaction flow, a toll station plate flow identifying water and an ETC portal plate flow identifying water;
step S20: data cleaning, namely performing data cleaning on the original data to obtain cleaned basic data;
step S30: data processing, namely grouping and aggregating the basic data according to the pass identification and the license plate number to construct a road network model;
step S40: path fitting reduction, namely inputting effective data into the road network model and performing fitting reduction on the road section and the travel of the vehicle;
step S50: theoretical real-time collection calculation, namely accumulating real-time collection amount of the charging units of the vehicle running path which is fit and restored to obtain road section theoretical real-time collection data;
step S60: checking and comparing theoretical real received data with split real received data, and performing data association comparison on transaction split real received data obtained by associating with the provincial networking center and the theoretical real received data to form a difference analysis result;
step S70: data difference analysis, namely comparing the presented difference details step by step according to the difference analysis result to obtain a check conclusion;
step S80: and generating an evidence chain report, and generating the evidence chain report according to the checking conclusion.
Referring to fig. 2, in detail, the data cleansing step of step S20 includes:
step S210: receiving the original data;
step S220: performing validity check on the key flow information in the original data, and filtering abnormal information and format error data; the key flow information comprises license plate numbers, entrance time, exit time and the like, the validity check firstly carries out preliminary screening on transaction flow in the original data, and the abnormal key information and the data with wrong format are firstly eliminated;
step S230: establishing a data cleaning rule, wherein the data cleaning rule is used for cleaning data of the data cleaning abnormal type; the data cleaning exception type comprises any one or more of repeated running water, waste running water, entry time exception, expired data, delayed data, non-format running water, repeated transaction, invalid license plate, invalid data, reverse interference, card reading failure and no gantry number; establishing a data cleaning rule, cleaning abnormal acquisition running water, and screening out repeated, invalid and reverse interference data;
step S240: performing data cleaning according to the data cleaning rule to obtain cleaned basic data; and the cleaned data is used as effective input data and is used as basic data for path restoration.
Data processing, namely grouping and aggregating the basic data according to the pass identification and the license plate number to construct a road network model; specifically, data processing groups and aggregates data according to a pass identifier and a license plate number, splits transactions generated by preorder fitting reduction, and splits the transactions to corresponding portals and charging units; constructing a complex road network model based on provincial path parameters; the provincial path parameters comprise road network node codes and adjacent node codes.
Path fitting reduction, namely inputting effective data into the road network model and performing fitting reduction on the road section and the travel of the vehicle; the vehicle running path which is subjected to fitting reduction comprises a running path of the road section entering the road section and leaving the road section, a running path of the road section entering the road section but not the road section, a running path of the road section but entering the road section and leaving the road section, and a running path of the road section; specifically, the route of the vehicle is that the vehicle enters the toll station at the entrance of other routes at a high speed, and the high-speed running track passes through 1 or more door frames of the route of the vehicle and leaves the toll station at the exit of other routes at a high speed. The fact that the road section is not called out means that the vehicle enters the high speed from the entrance toll station of the road section and leaves the high speed from the exit toll stations of other road sections; the non-exit of the road section is that the vehicle enters the high speed from the entrance toll station of other road sections and leaves the high speed from the exit toll station of the road section; the exit of the road section from the entrance toll station of the road section means that the vehicle enters the high speed from the entrance toll station of the road section and leaves the high speed from the exit toll station of the road section.
And theoretical actual collection calculation, namely accumulating the actual collection amount of the charging units of the vehicle running path which is fit and restored to obtain the road section theoretical actual collection data.
Checking and comparing theoretical real received data with split real received data, and performing data association comparison on transaction split real received data obtained by associating with the provincial networking center and the theoretical real received data to form a difference analysis result; the transaction split real data comprises correlation confirmation accounting data, non-correlation confirmation accounting data and dispute repudiation/bad account data; specifically, the checking calculation process is as follows:
setting:
a: fitting and reducing the real toll amount of the toll theory;
b: the provincial networking center splits the real toll collection amount;
c1: correlation confirmation accounting amount, namely running amount in the correlation of A and B according to the passID; wherein, the passID is the unique number of the vehicle passing through once;
c2: confirming the account amount without correlation, namely performing correlation according to the passID, wherein the running water exists in the step B, and the running water does not exist in the step A;
c3: the unassociated unconfirmed billing amount is associated according to the passId, the running water exists in the step A, and the running water does not exist in the step B;
d: checking the difference sum, namely performing association according to the passID, wherein the running water exists in the A and does not exist in the B;
then:
B＝C1+C2；
A＝C1+C3；
D＝C2+C3。
data difference analysis, namely comparing the presented difference details step by step according to the difference analysis result to obtain a check conclusion; and further, according to the difference analysis result, drilling down to detailed flow data according to the export transaction date, drilling down the flow data to a charging unit, comparing step by step to present difference details, and giving a check conclusion by assisting manual analysis.
Generating an evidence chain report, and generating the evidence chain report according to the checking conclusion; specifically, according to the check conclusion, a corresponding passage transaction detail evidence chain report is generated according to the corresponding template and submitted to the corresponding department, and the toll loss is recovered.
In addition, the invention also provides a device for calibrating the toll of the highway.
Referring to fig. 3, an internal structure of an expressway toll calibration apparatus according to an embodiment of the present invention is schematically shown, where the expressway toll calibration apparatus at least includes a memory 11, a processor 12, a communication bus 13, and a network interface 14.
The memory 11 includes at least one type of readable storage medium, which includes a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, and the like. The memory 11 may in some embodiments be an internal storage unit of the highway toll calibration device, for example a hard disk of the highway toll calibration device. The memory 11 may also be an external storage device of the highway toll calibration apparatus in other embodiments, such as a plug-in hard disk provided on the highway toll calibration apparatus, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. Further, the memory 11 may also include both an internal storage unit of the highway toll calibration apparatus and an external storage device. The memory 11 may be used not only to store application software installed in the highway toll calibration apparatus and various types of data, such as codes of highway toll calibration programs, etc., but also to temporarily store data that has been output or is to be output.
The processor 12 may be, in some embodiments, a Central Processing Unit (CPU), controller, microcontroller, microprocessor or other data Processing chip for executing program codes stored in the memory 11 or Processing data, such as executing a highway toll calibration program.
The communication bus 13 is used to realize connection communication between these components.
The network interface 14 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), and is typically used to establish a communication link between the highway toll calibration apparatus and other electronic devices.
Optionally, the highway toll calibration device may further comprise a user interface, the user interface may comprise a Display (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface may further comprise a standard wired interface and a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable for displaying information processed in the highway toll calibration device and for displaying a visual user interface.
While fig. 3 shows only the highway toll calibration device with the components 11-14 and the highway toll calibration procedure, it will be understood by those skilled in the art that the configuration shown in fig. 3 does not constitute a limitation of the highway toll calibration device, and may include fewer or more components than shown, or some components in combination, or a different arrangement of components.
In the embodiment of the highway toll calibration device shown in fig. 3, a highway toll calibration program is stored in the memory 11; the processor 12, when executing the highway toll calibration program stored in the memory 11, implements the following steps:
step S10: acquiring original data; the original data comprises an original traffic transaction flow uploaded on a highway section;
step S20: data cleaning, namely performing data cleaning on the original data to obtain cleaned basic data;
step S30: data processing, namely grouping and aggregating the basic data according to the pass identification and the license plate number to construct a road network model;
step S40: path fitting reduction, namely inputting effective data into the road network model and performing fitting reduction on the road section and the travel of the vehicle;
step S50: theoretical real-time collection calculation, namely accumulating real-time collection amount of the charging units of the vehicle running path which is fit and restored to obtain road section theoretical real-time collection data;
step S60: checking and comparing theoretical real received data with split real received data, and performing data association comparison on transaction split real received data obtained by associating with the provincial networking center and the theoretical real received data to form a difference analysis result;
step S70: data difference analysis, namely comparing the presented difference details step by step according to the difference analysis result to obtain a check conclusion;
step S80: and generating an evidence chain report, and generating the evidence chain report according to the checking conclusion.
Referring to fig. 4, a schematic diagram of program modules of a highway toll calibration procedure in an embodiment of the highway toll calibration apparatus according to the present invention is shown, in this embodiment, the highway toll calibration procedure can be divided into an acquisition module 10, a data cleaning module 20, a data processing module 30, a check and comparison module 40, and an output module 50, and exemplarily:
an obtaining module 10, configured to obtain original data;
a data cleaning module 20, configured to perform data cleaning on the original data to obtain cleaned basic data;
the data processing module 30 is used for grouping and aggregating the basic data according to the pass identification and the license plate number to construct a road network model;
the checking and comparing module 40 is used for checking and comparing the theoretical actual received data and the split actual received data to form a difference analysis result;
an output module 50 outputs the variance analysis and evidence chain report.
The functions or operation steps implemented when the program modules such as the acquiring module 10, the data cleaning module 20, the data processing module 30, the checking and comparing module 40, and the output module 50 are executed are substantially the same as those of the above embodiments, and are not described herein again.
Furthermore, an embodiment of the present invention further provides a storage medium, where the storage medium is a computer-readable storage medium, and the storage medium stores thereon an expressway toll calibration program, where the expressway toll calibration program is executable by one or more processors to implement the following operations:
step S10: acquiring original data; the original data comprises an original traffic transaction flow uploaded on a highway section;
step S20: data cleaning, namely performing data cleaning on the original data to obtain cleaned basic data;
step S30: data processing, namely grouping and aggregating the basic data according to the pass identification and the license plate number to construct a road network model;
step S40: path fitting reduction, namely inputting effective data into the road network model and performing fitting reduction on the road section and the travel of the vehicle;
step S50: theoretical real-time collection calculation, namely accumulating real-time collection amount of the charging units of the vehicle running path which is fit and restored to obtain road section theoretical real-time collection data;
step S60: checking and comparing theoretical real received data with split real received data, and performing data association comparison on transaction split real received data obtained by associating with the provincial networking center and the theoretical real received data to form a difference analysis result;
step S70: data difference analysis, namely comparing the presented difference details step by step according to the difference analysis result to obtain a check conclusion;
step S80: and generating an evidence chain report, and generating the evidence chain report according to the checking conclusion.
The embodiment of the storage medium of the present invention is substantially the same as the embodiments of the method and the apparatus for calibrating highway toll, and will not be described herein again.
Compared with the prior art, the invention provides a method, a device and a storage medium for calibrating the toll of an expressway, wherein the method, the device and the storage medium are used for carrying out data cleaning and data processing on a traffic transaction flow, reducing and calculating theoretical real collection based on path fitting of a road network model, and completing the toll calibration of the expressway by checking and comparing theoretical real collection data and split real collection data, and the gains of the method comprise:
the first income helps each operating unit of the highway to integrally master the traffic transaction flow condition of the road section after online charging, thereby better mastering the income condition of the road section and providing data support for further management;
the method has the advantages that the second income is that reliable evidence is provided for unreasonable, unfair and unfair dispute streamline treatment which may exist by accurately estimating the traffic flow and toll data of the road section;
income III, the theoretical real-time data is calculated automatically through the system, and the abnormal splitting condition is rapidly found through the difference between the splitting result of the system and the splitting result of the settlement center, so that the toll loss of the road section is avoided;
the profit is four, the calculation process is simple and convenient, too much manual intervention is not needed, the system can automatically realize difference analysis and comparison, a large amount of manual work is saved to remove the workload of comparing one by one, and the working efficiency is improved.
It should be noted that the above-mentioned numbers of the embodiments of the present invention are merely for description, and do not represent the merits of the embodiments. And the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, apparatus, article, or method that comprises the element.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above, and includes instructions for enabling a terminal device (e.g., a drone, a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A highway toll calibration method is characterized by comprising the following steps:
acquiring original data; the original data comprises an original traffic transaction flow uploaded on a highway section;
data cleaning, namely performing data cleaning on the original data to obtain cleaned basic data;
data processing, namely grouping and aggregating the basic data according to the pass identification and the license plate number to construct a road network model;
path fitting reduction, namely inputting effective data into the road network model and performing fitting reduction on the road section and the travel of the vehicle;
theoretical real-time collection calculation, namely accumulating real-time collection amount of the charging units of the vehicle running path which is fit and restored to obtain road section theoretical real-time collection data;
and checking and comparing the theoretical real received data with the split real received data, and performing data association comparison on the transaction split real received data obtained by associating with the provincial networking center and the theoretical real received data to form a difference analysis result.
2. The highway toll calibration method according to claim 1, further comprising:
data difference analysis, namely comparing the presented difference details step by step according to the difference analysis result to obtain a check conclusion;
and generating an evidence chain report, and generating the evidence chain report according to the checking conclusion.
3. The method according to claim 1, wherein the raw passage traffic includes an entrance station traffic, an ETC portal billing traffic, an exit ETC traffic, an exit other traffic, a toll station sign recognition traffic, and an ETC portal sign recognition traffic.
4. The highway toll calibration method of claim 1, wherein the data washing step comprises:
receiving the original data;
performing validity check on the key flow information in the original data, and filtering abnormal information and format error data;
establishing a data cleaning rule, wherein the data cleaning rule is used for cleaning data of the data cleaning abnormal type;
and cleaning the data according to the data cleaning rule to obtain cleaned basic data.
5. The method of claim 4, wherein the data cleansing exception type comprises any one or more of repeat run, waste run, entry time exception, expired data, delayed data, plain run, repeat transaction, invalid license plate, invalid data, reverse interference, card-reading failure, and no gantry number.
6. The method of claim 1, wherein the road network model is constructed based on provincial path parameters, the provincial path parameters comprising road network node codes and neighboring node codes.
7. The method of claim 1, wherein the fit-reduced vehicle travel paths include a local segment entry local segment exit travel path, a local segment entry non-local segment exit travel path, a non-local segment entry local segment exit travel path, and a route local segment travel path.
8. The method of claim 1, wherein the transaction split real charge data comprises associated confirmation billing data and non-associated confirmation billing data.
9. An expressway toll calibration apparatus comprising a memory and a processor, wherein the memory stores an expressway toll calibration program operable on the processor, and the expressway toll calibration program when executed by the processor implements the steps of the expressway toll calibration method according to any one of claims 1 to 8.
10. A storage medium, wherein the storage medium is a computer-readable storage medium having a highway toll calibration program stored thereon, the highway toll calibration program being executable by one or more processors to implement the steps of the highway toll calibration method according to any one of claims 1 to 8.
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| CN113554770A (en) * | 2021-07-07 | 2021-10-26 | 中国银行股份有限公司 | Method, device and equipment for acquiring wrong account information and readable storage medium |
| CN114036146A (en) * | 2021-11-23 | 2022-02-11 | 哈尔滨智路科技开发有限公司 | ETL processing method and device in high-speed audit service data warehouse |
| CN114360083A (en) * | 2022-01-13 | 2022-04-15 | 北京中交国通智能交通***技术有限公司 | Highway toll settlement system |
| CN114360084A (en) * | 2022-01-13 | 2022-04-15 | 北京中交国通智能交通***技术有限公司 | Highway toll settlement method and device |
| CN115273258A (en) * | 2022-07-06 | 2022-11-01 | 太极计算机股份有限公司 | High-speed fee calculation method, device and system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20090077114A (en) * | 2008-01-10 | 2009-07-15 | 한국도로공사 | System for checking an unpaid car of the toll road and controlling method for the same |
| CN105184875A (en) * | 2015-08-25 | 2015-12-23 | 广州新软计算机技术有限公司 | Rate calculating and splitting system and method at complex path |
| US20160055466A1 (en) * | 2014-08-19 | 2016-02-25 | iDiggApp Inc. | Gps-based toll collection system and method |
| CN110956812A (en) * | 2019-11-05 | 2020-04-03 | 南京感动科技有限公司 | Highway inspection data cloud rapid analysis processing method |
| CN111063042A (en) * | 2019-12-23 | 2020-04-24 | 湖北省交通科学研究所 | Highway free flow toll collection path fitting system based on big data |
-
2020
- 2020-09-18 CN CN202010987921.7A patent/CN112419526A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20090077114A (en) * | 2008-01-10 | 2009-07-15 | 한국도로공사 | System for checking an unpaid car of the toll road and controlling method for the same |
| US20160055466A1 (en) * | 2014-08-19 | 2016-02-25 | iDiggApp Inc. | Gps-based toll collection system and method |
| CN105184875A (en) * | 2015-08-25 | 2015-12-23 | 广州新软计算机技术有限公司 | Rate calculating and splitting system and method at complex path |
| CN110956812A (en) * | 2019-11-05 | 2020-04-03 | 南京感动科技有限公司 | Highway inspection data cloud rapid analysis processing method |
| CN111063042A (en) * | 2019-12-23 | 2020-04-24 | 湖北省交通科学研究所 | Highway free flow toll collection path fitting system based on big data |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113554770A (en) * | 2021-07-07 | 2021-10-26 | 中国银行股份有限公司 | Method, device and equipment for acquiring wrong account information and readable storage medium |
| CN114036146A (en) * | 2021-11-23 | 2022-02-11 | 哈尔滨智路科技开发有限公司 | ETL processing method and device in high-speed audit service data warehouse |
| CN114360083A (en) * | 2022-01-13 | 2022-04-15 | 北京中交国通智能交通***技术有限公司 | Highway toll settlement system |
| CN114360084A (en) * | 2022-01-13 | 2022-04-15 | 北京中交国通智能交通***技术有限公司 | Highway toll settlement method and device |
| CN114360084B (en) * | 2022-01-13 | 2024-03-12 | 北京中交国通智能交通***技术有限公司 | Highway toll settlement method and device |
| CN114360083B (en) * | 2022-01-13 | 2024-03-29 | 北京中交国通智能交通***技术有限公司 | Highway toll settlement system |
| CN115273258A (en) * | 2022-07-06 | 2022-11-01 | 太极计算机股份有限公司 | High-speed fee calculation method, device and system |
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