CN116895103A - A payment method, system and electronic device based on high-speed composite pass card - Google Patents

Abstract

The invention relates to the technical field of highways, in particular to a payment method, a payment system and electronic equipment based on a high-speed composite pass card. The method comprises the following steps: the method comprises the steps of obtaining traffic flow data in a preset distance range of a toll station outlet, carrying out congestion prediction according to the traffic flow data and preset congestion factors to obtain congestion outlet information, obtaining historical traffic data and inlet information of an in-transit user, carrying out outlet prediction according to the historical traffic data and the inlet information to obtain first toll station outlet information and a first toll bill of the in-transit user, matching the first toll station outlet information with the congestion outlet information, pushing the first toll bill to a user terminal of the in-transit user when matching is successful, generating payment information according to payment information when receiving payment information of the first toll bill, solving the problem that the toll station is easy to congestion in the conventional CPC traffic mode, and improving traffic efficiency of vehicles holding CPC cards.

Description

A payment method, system and electronic device based on high-speed composite pass card

Technical Field

The present invention relates to the technical field of expressways, and in particular to a payment method, system and electronic equipment based on an expressway composite pass card.

Background Art

With the rapid development of science and technology, the toll collection model of expressways is also keeping pace with the times. At present, the toll collection structure of my country's expressways mainly includes manual semi-automatic toll collection (MTC, Manual Toll Collection) and electronic toll collection (ETC, Electronic Toll Collection).

With the cancellation of provincial toll stations, the traffic volume on provincial highways has increased rapidly. However, some toll plazas with large traffic volume are difficult to expand due to various restrictions. The speed of vehicles has decreased, resulting in congestion in the toll plazas. Although ETC can improve the traffic efficiency of vehicles by deducting fees without stopping, it is limited to vehicles equipped with dedicated OBU equipment and needs to enter dedicated ETC lanes. In addition, the ETC application process is cumbersome, and the quality of after-sales service varies. As a result, a large number of car owners still choose to use CPC cards to pass. CPC cards, that is, composite toll cards for highways, are used in manual semi-automatic toll collection MTC toll collection systems. CPC cards can identify vehicle entry and exit information of toll stations, accurately record the actual driving path of vehicles, and provide important basis for inter-provincial toll billing and settlement.

When using the CPC card passage method, it is necessary to collect a CPC card at the toll station entrance, and pay the highway toll in sequence and leave by queuing at the toll station exit of the MTC lane. Therefore, the existing CPC card passage method requires queuing to pay, which easily causes congestion at toll stations and is difficult to meet the needs of unimpeded traffic at toll stations. Moreover, especially for the above-mentioned toll stations with large traffic volume, the use of the existing CPC card passage method will aggravate the congestion of MTC lanes and mixed lanes.

Therefore, how to maximize the traffic efficiency of vehicles holding CPC cards and alleviate congestion at toll stations within the existing lane scale without affecting the current toll structure has become an urgent problem that needs to be solved.

Summary of the invention

The present invention provides a payment method, system and electronic equipment based on a high-speed composite pass card, which are used to improve the passing efficiency of vehicles holding CPC cards.

In one aspect, the present invention provides a payment method based on a high-speed composite pass card, the method comprising:

Obtain traffic data within a preset distance range of the toll station exit;

Perform congestion prediction based on the traffic flow data and a preset congestion factor to obtain congestion exit information;

Obtain historical travel data and entry information of users in transit;

Performing an exit prediction based on the historical traffic data and the entrance information to obtain the first toll station exit information and the first toll bill of the en-route user;

matching the first toll station exit information with the congested exit information, and when the match is successful, pushing the first toll bill to the user terminal of the en-route user;

When the payment information of the first toll bill is received, payment information is generated according to the payment information.

Optionally, performing congestion prediction according to the traffic flow data and a preset congestion factor to obtain congestion exit information includes:

Calculate the predicted number of vehicles at the toll station during the predicted period at the toll station exit according to the traffic flow data;

Calculating the congestion parameter of the toll station exit according to the predicted number of vehicles and the preset congestion factor;

When the congestion parameter is not less than a preset threshold, the toll station exit is marked as a congested exit, and the predicted time period is marked as a congested time period; and the congested exit and the congested time period are used as the congested exit information.

Optionally, the traffic flow data includes: a gantry identification, a number of gantry vehicles, and a collection period; and the calculation of the predicted number of vehicles in the prediction period based on the traffic flow data includes:

According to the gantry identifier and a preset first association relationship, a historical diversion ratio associated with the gantry identifier is determined; the first association relationship is an association relationship between the gantry identifier and the historical diversion ratio;

According to the collection period and the preset second association relationship, determining the historical period diversion ratio corresponding to the collection period from the historical classification ratio;

The predicted number of vehicles in the prediction period is calculated based on the diversion ratio in the historical period and the number of vehicles on the gantry.

Optionally, the predicted number of vehicles includes: the number of trucks and the number of buses; the preset congestion factor includes the outer dimensions of trucks and the outer dimensions of buses; the preset threshold includes the capacity threshold of the toll plaza;

The congestion parameter of the toll station exit is calculated based on the predicted number of vehicles and the preset congestion factor, including:

The truck capacity is obtained by multiplying the number of trucks by the outer dimensions of the trucks, and the bus capacity is obtained by multiplying the number of buses by the outer dimensions of the buses. The truck capacity and the bus capacity are summed to obtain the congestion parameter of the toll station exit.

Optionally, the method further comprises:

When the payment confirmation result of the first toll bill is not received within a first preset time, obtaining the real-time en-route data of the en-route user;

updating the first toll station exit information and the first toll bill according to the real-time in-transit data and the entrance information, and obtaining the second toll station exit information and the second toll bill;

The step of matching the first toll station exit information with the congested exit information and, when the matching is successful, pushing the first toll bill to the user terminal of the on-the-way user comprises:

The second toll station exit information and the congested exit information are matched, and when the match is successful, the second toll bill is pushed to the user terminal of the en route user.

Optionally, the method further comprises:

When the payment confirmation result of the second toll bill is not received within the second preset time, and the estimated fee information sent by the preset target gantry is received, a third toll bill is generated according to the estimated fee information;

When it is determined that the in-transit user is a password-free payment user, a password-free payment request is initiated to the third-party payment platform according to the estimated payment information, and upon receiving the password-free payment callback information from the third-party payment platform, password-free payment information is generated according to the password-free payment callback information.

Optionally, the method further comprises:

When it is determined that the in-transit user is not a password-free payment user, the third toll bill is pushed to the user terminal of the in-transit user, and upon receiving the payment confirmation instruction of the in-transit user, a payment request is initiated to a third-party payment platform, and upon receiving payment callback information from the third-party payment platform, payment information is generated according to the payment callback information.

Optionally, the method further comprises:

When a temporary correction instruction is received, the temporary correction instruction is parsed to obtain correction period and correction object information, and the historical period diversion ratio is corrected according to the correction period and correction object information.

Another aspect of the present invention provides a payment system based on a high-speed composite pass card, the system comprising:

A vehicle flow data acquisition module is used to acquire vehicle flow data within a preset distance range of a toll station exit;

A congestion prediction module, used to perform congestion prediction based on the traffic flow data and a preset congestion factor to obtain congestion exit information;

The en-route user data acquisition module is used to obtain the historical travel data and entry information of the en-route user;

An exit prediction module, used to perform exit prediction based on the historical traffic data and the entrance information, and obtain the first toll station exit information and the first toll bill of the en-route user;

a matching module, configured to match the first toll station exit information with the congested exit information, and when a match is successful, push the first toll bill to a user terminal of the on-the-way user;

The information generating module is used to generate payment information according to the payment information of the first toll bill when the payment information of the first toll bill is received.

Another aspect of the present invention provides an electronic device, the device comprising a processor and a memory:

The memory is used to store program code and transmit the program code to the processor;

The processor is used to execute the method as described above according to the instructions in the program code.

It can be seen from the above technical solutions that the present invention has the following advantages:

The present invention acquires traffic flow data within a preset distance range of a toll station exit, and performs congestion prediction based on the traffic flow data and a preset congestion factor to obtain congestion exit information, thereby updating and predicting the congestion status of the toll station exit. The present invention acquires historical traffic data and entrance information of an on-the-go user, performs exit prediction based on the historical traffic data and the entrance information, obtains the first toll station exit information and the first toll bill of the on-the-go user, thereby predicting the destination toll station exit of the on-the-go user, and matches the first toll station exit information with the congestion exit information. When the matching information is When successful, there is congestion at the toll station exit of the user in transit, and the first toll bill is pushed to the user terminal of the user in transit, so as to remind the user in transit to pay the toll before driving to the toll station booth. When the payment information of the first toll bill is received, the payment information is generated according to the payment information, so that after the user in transit arrives at the toll station booth, he only needs to return the CPC pass card to be released, which solves the existing CPC card passage method, which requires queuing at the toll station exit booth to pay, which easily causes congestion at the toll station, and improves the passage efficiency of vehicles holding CPC cards.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

FIG1 is a flow chart of a payment method based on a high-speed composite pass card provided in Embodiment 1 of the present invention;

FIG2 is a schematic diagram of the installation of a toll station exit gantry according to the first embodiment of the present invention;

FIG3 is a flow chart of a payment method based on a high-speed composite pass card provided in Embodiment 2 of the present invention;

FIG4 is a flow chart of a payment method based on a high-speed composite pass card provided in Embodiment 3 of the present invention;

FIG5 is a schematic diagram of the structure of a payment system based on a high-speed composite pass card provided in Embodiment 7 of the present invention;

FIG6 is a system architecture diagram 1 provided by the present invention;

FIG. 7 is a second diagram of the system architecture provided by the present invention.

DETAILED DESCRIPTION

The embodiment of the present invention provides a payment method, system and electronic equipment based on a high-speed composite pass card, which are used to improve the passing efficiency of vehicles holding CPC cards.

In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

Embodiment 1:

Referring to FIG. 1 , a first embodiment of the present invention provides a payment method based on a high-speed composite pass card, the steps of which include:

101. Obtain traffic flow data within a preset distance range of a toll station exit.

It should be noted that this embodiment takes the toll station exit as the benchmark, and a number of gantries are set on the highway within a preset distance range before and after the toll station. Each gantry has a unique identification, and the traffic data collected by different gantries can be distinguished according to the identification. RSU antennas, license plate capture devices and other hardware devices are deployed on each gantry, where the RSU antenna is used to interact with the CPC card and collect the estimated fee information such as the highway entrance information, toll amount, vehicle model, license plate type, etc. in the CPC card, and synchronize the estimated fee information to the system database. Therefore, the traffic data passing through the gantry can be determined by using the interactive information between the gantry and the CPC card. Since the instantaneous traffic volume of the gantry is very small, in order to improve the accuracy of the prediction, the gantry counts the number of vehicles within a preset time length, and updates the number of vehicles according to the preset data update cycle.

Among them, the preset distance range can be determined according to the actual situation of the toll station, and the data update cycle is determined according to the distance between the gantry and the toll station. In this embodiment, in order to make effective early warnings for traffic at the toll station exit and allow the toll station administrator to make efficient scheduling work, priority is given to obtaining all traffic data within 30km before and after the toll station exit. It is understandable that the number of toll station exits can be multiple. For example, all toll stations in the expressway network can be preferred. This embodiment takes the data acquisition of a toll station exit as an example, and specifically takes the range of 30km before and after the toll station exit as an example to illustrate as follows:

Under normal circumstances, vehicles will reach the toll station from two directions, one is the main lane and the other is the branch lane. As shown in Figure 2, the main lane is equipped with gantry 1, gantry 2, and gantry 3 in the direction of the toll station, which are approximately 30km, 20km, and 10km away from the toll station respectively. The branch lane has gantry 4, gantry 5, and gantry 6, which are approximately 30km, 20km, and 10km away from the ramp respectively. This embodiment obtains the number of vehicles counted by gantry 1-gantry 6.

102. Congestion prediction is performed based on traffic flow data and preset congestion factors to obtain congestion exit information.

It should be noted that the distance between the gantry and the toll station exit can be determined based on the gantry identification, and the driving time required for the vehicle to reach the toll station from the gantry can be determined based on the distance and the vehicle's driving speed. Therefore, the traffic data of the toll station in different time periods can be predicted in advance by combining the driving time and the gantry's traffic data.

Congestion prediction refers to determining whether the predicted traffic flow data of a toll station exceeds the tolerance of the toll station. If so, the toll station is determined to be in a congested state, and the toll station exit is marked as a congested exit. The predicted time period is also marked as a congested period. The tolerance of the toll station is mainly considered from the number of vehicles allowed to pass through the toll station and/or the capacity of the toll plaza. The congestion factor is used to assist in calculating the number and/or volume of passing vehicles corresponding to the traffic flow data. Congestion exit information includes congestion period and congestion exit.

It should be noted that the number of toll station exits may be one or more. In the case of multiple toll station exits, congestion prediction is performed on each toll station exit using the traffic data of each toll station and a preset congestion factor.

103. Obtain the historical travel data and entry information of users in transit.

It should be noted that in-transit users refer to registered users who have entered the toll station entrance and received and activated CPC cards. Registered users refer to users who have completed authorization registration in the system, submitted corresponding user information (such as driving license information, vehicle information, etc.), and completed information binding and review.

It is understandable that before the first use, the car owner accesses the system and submits the driving license information and user information on the system for binding the frequently used vehicle. After receiving the information submitted by the car owner, the system reviews the information and completes the registration after the review is passed. Among them, the registration channel selected by the car owner can be one or more of the mini-programs, public accounts, web links, APP terminals or registration platforms provided by the system front end, etc. The specific registration channel can be selected according to the actual situation, and this embodiment does not make specific limitations here.

When a vehicle passes through the entrance of a toll station, the toll station personnel write the vehicle information, toll station entrance information and entry time into the CPC card, and synchronize the vehicle information, entrance information, entry time and other information to the system. The system forms an order for the received information, and after filtering the order (screening out orders for holidays, special vehicles, etc.), the system compares the vehicle information in the order with the vehicle information of the pre-stored registered user to determine whether it is a registered user. If so, the user's historical traffic data and entrance information and other data are obtained from the system database. It can be understood that the system database stores the historical traffic data of all vehicles in the highway network and the CPC card data read in real time by the gantry and other road network data.

104. Predict the toll station exit based on historical traffic data and entrance information to obtain the first toll station exit information and the first toll bill.

It should be noted that historical traffic data includes license plate information, gantry information, historical exits, historical entrances, historical routes, historical travel time, historical traffic bills and other historical data. Among them, there is a correlation between historical entrances and historical exits, historical routes, historical travel time, and historical traffic bills. Among them, gantry information includes gantry identification, historical reading time and other information.

The toll station exit prediction specifically includes: matching the entrance information with the historical entrances in the historical traffic data, determining the first target historical entrance that matches the entrance information, and determining the first target historical exit, the first target historical passage path, the first target historical driving time and the first target historical passage bill corresponding to the first target historical entrance according to the first target historical entrance and the association relationship; when there are multiple first target historical exits, calculating the passage frequency of each first target historical exit, and taking the first target historical exit with a passage frequency greater than a preset frequency threshold as the first predicted exit for this prediction, and taking the first target historical passage path corresponding to the first predicted exit as the first target passage path for this prediction, and determining the predicted arrival time period for the on-the-way user to arrive at the predicted exit according to the first target passage path and the driving speed of the on-the-way user, and taking the first target historical passage bill corresponding to the predicted exit as the first toll bill for this prediction, or calculating the first toll bill in combination with the entrance information, the predicted exit, and the historical driving path between the entrance information and the predicted exit, wherein the first toll station exit information includes the first predicted exit and the first predicted arrival time period.

In this embodiment, when the on-the-go user just exits the toll station entrance, the on-the-go user's historical travel data and entrance information are obtained to predict the on-the-go user's destination toll station exit in advance, and a fee bill is generated in advance for the on-the-go user to confirm and pay, so that the on-the-go user can prepay the toll in advance, thereby helping to alleviate congestion in mixed lanes and MTC lanes.

It should be noted that there is no order relationship between steps 101 - 102 and steps 103 - 104 , for example, steps 103 - 104 may be before steps 101 - 102 .

105. Match the first toll station exit information with the congested exit information, and when the match is successful, push the first toll bill to the user terminal of the on-the-way user.

It should be noted that the first predicted exit and the first predicted arrival time in the first toll station exit information are matched with the congested exit and the congested time in the congested exit information. When the congested exit is consistent with the predicted exit and the predicted arrival time is consistent with the congested time, the match is successful, indicating that when the on-the-way user arrives at the toll station exit, the toll station will be in a congested state. When the match is successful, the first toll bill corresponding to the predicted exit is pushed to the on-the-way user to remind the user to pay the toll in advance.

It is understandable that when there are multiple predicted exits that are matched successfully, the first toll bills corresponding to the multiple predicted exits will be sent to the on-the-way user, who can select and confirm according to his or her own needs and pay the toll in advance. The specific push method can be determined according to the actual situation, such as push through mini-programs or a combination of SMS and H5 links.

106. When the payment information of the first toll bill is received, payment information is generated according to the payment information.

It should be noted that after receiving the first toll bill, the on-the-way user can confirm the predicted exit in advance on the way or in front of the toll plaza or toll station exit booth, and pay the first toll bill corresponding to the predicted exit. Therefore, when the payment information of the first toll bill fed back by the on-the-way user is received, the payment information is generated according to the payment information, and the payment information is synchronized to the existing mixed lane toll collection system. Among them, the payment information includes entrance information, exit information, driving path, payment amount, license plate, vehicle model, vehicle type and other information. Therefore, when the on-the-way user returns the CPC card at the toll station booth, the staff at the toll station exit booth only needs to check the license plate and vehicle model in the payment information of the on-the-way user, and can quickly release it, which solves the existing CPC card passage method, which requires queuing at the toll station exit booth to wait for payment, which easily causes congestion at the toll station, and improves the passage efficiency of vehicles holding CPC cards.

This embodiment acquires traffic flow data within a preset distance range of the toll station exit, and performs congestion prediction based on the traffic flow data and a preset congestion factor to obtain congested exit information, thereby updating and predicting the congestion status of the toll station exit. In addition, by acquiring historical traffic data and entrance information of the on-the-go user, an exit prediction is performed based on the historical traffic data and entrance information to obtain the first toll station exit information and the first toll bill of the on-the-go user, thereby predicting the destination toll station exit of the on-the-go user. In addition, by matching the first toll station exit information with the congested exit information, when the match is successful, the destination toll station exit of the on-the-go user is congested, and the first toll bill is pushed to The user terminal of the user on the way is used to remind the user on the way to pay the toll before driving to the toll station booth. When the payment information of the first toll bill is received, the payment information is generated according to the payment information, so that after the user on the way arrives at the toll station booth, he only needs to return the CPC pass card to be released. This solves the problem of the existing CPC card passage method, which requires queuing at the toll station exit booth to wait for payment, which easily causes congestion at the toll station. It improves the passage efficiency of vehicles holding CPC cards, alleviates the congestion of MTC lanes and mixed lanes, and improves the passage efficiency of MTC lanes and mixed lanes, thereby achieving the goal of improving the overall passage capacity of the toll plaza and improving the convenience of toll payment.

Embodiment 2:

Please refer to FIG. 3 , a payment method based on a high-speed composite pass card is provided in Embodiment 2 of the present invention. Based on Embodiment 1, this embodiment further defines step 102, and the steps include:

201. Determine the predicted number of vehicles at the toll station exit during the predicted period based on the traffic flow data.

It should be noted that the traffic data includes: gantry identification, number of gantry vehicles, collection period and traffic statistics duration. Among them, the gantry identification can be the gantry number or identification code or other identification information that can be used to distinguish different gantries. The collection period is obtained by adding the traffic statistics duration to the timing start time when the gantry starts to count the traffic data. The prediction period is obtained based on the collection period and the advance prediction time interval. Among them, the advance prediction interval is obtained by the distance between the gantry and the toll station exit and the vehicle driving speed. The gantry identification is used to feedback the gantry position, and the distance between the gantry and the toll station exit can be determined based on the gantry identification.

The specific steps of step 201 are as follows:

S01: Determine a historical diversion ratio associated with the gantry identification according to the gantry identification and a preset first association relationship; the first association relationship is an association relationship between the gantry identification and the historical diversion ratio.

It should be noted that, since the distances between each gantry and the toll station exit are different, the traffic flow of the toll station can be predicted by using the traffic flow data of different gantries, and the traffic flow of the toll station after different prediction time intervals can be obtained. During the collection period, there is a situation of vehicle diversion between gantries and between gantries and toll station exits. In this embodiment, the vehicle diversion situation can be represented by a historical diversion ratio. The historical diversion rate in this embodiment includes the historical diversion ratio of the gantry and the diversion ratio of entering the toll station.

Among them, the first association relationship is pre-constructed in the database, and its construction steps include: determining the position of the gantry according to the gantry identification, determining all diversion nodes between the gantry and the toll station exit according to the gantry position, and establishing an association relationship between the gantry identification and the historical diversion ratio of all diversion nodes.

According to the branch lanes and main lanes, the gantries can be divided into branch gantries and main lane gantries. The historical diversion ratio of the gantry includes the historical diversion ratio of the branch gantries and the historical diversion ratio of the main lane gantries. The diversion ratio entering the toll station includes the diversion ratio of entering the toll station from the branch lane and the diversion ratio of entering the toll station from the main lane.

The following is an explanation of the case listed in Example 1:

As shown in Figure 2, assuming that the vehicle speed is 70 km/h, the average time for vehicles in the main lane to reach the toll station from gantry 1, gantry 2, and gantry 3 is about 26 minutes, 17 minutes, and 8 minutes, respectively. Similarly, the average time for vehicles in the branch lane to reach the ramp from gantry 4, gantry 5, and gantry 6 is also about 26 minutes, 17 minutes, and 8 minutes, respectively. See Tables 1 and 2.

Table 1 Basic information of mainline gantry

Table 2 Basic information of branch line gantry

Door frame Distance from gantry to ramp Average time for vehicles to travel from the gantry to the ramp (speed 70km/h) Door frame 4 About 30km About 26 minutes Door frame 5 About 20km About 17 minutes Door frame 6 About 10km About 8 minutes

Since the distance from the ramp to the toll station is negligible, the branch lane and the main lane are in the same situation, so the branch lane can be superimposed with reference to the down lane. In this embodiment, the traffic data statistics of the main lane are mainly used as an example for explanation.

Specifically, assuming that the vehicle's travel speed is 70 km/h, for the main lane, the data update cycles of gantry 1, gantry 2, and gantry 3 are 5 minutes, 5 minutes, and 3 minutes, respectively. When the first vehicle passes through gantry 1, gantry 1 starts timing and counts the number of vehicles passing through gantry 1 in 5 minutes. Some of these vehicles will arrive at the toll station around 21 minutes to 26 minutes. Therefore, based on the vehicle data of gantry 1, taking the timing starting point of gantry 1 as the reference point, the number of vehicles at the toll station around 21 minutes to 26 minutes in the future can be predicted in advance, and the prediction time interval is 21 minutes to 26 minutes. When the first vehicle passes through gantry 2, gantry 2 starts timing and counts the number of vehicles passing through gantry 2 in 5 minutes. Some of them will arrive at the toll station around 12 minutes to 17 minutes. Similarly, based on the number of vehicles at gantry 2 and the collection time point, the number of vehicles at the toll station 12 minutes to 17 minutes after the collection time point can be determined. When the first vehicle passes through gantry 3, gantry 3 starts timing and counts the number of vehicles passing through gantry 3 in 3 minutes. Some of these vehicles will arrive at the toll station in about 5 to 8 minutes. The above information is shown in Table 3.

Table 3 Gantry traffic statistics duration, data update cycle and advance prediction time interval

Door frame Traffic statistics duration Data update cycle Predict time interval in advance Door frame 1 0-5min 5min 21-26min Door frame 2 0-5min 5min 12-17min Door frame 3 0-3min 3min 5-8min

As shown in Figure 2, the diversion nodes between gantry 1 and the toll station exit are: the diversion node between gantry 1 and gantry 2, the diversion node between gantry 2 and gantry 3, and the diversion node between gantry 3 and the toll station. The historical diversion ratios associated with gantry 1 include: the historical diversion ratio P1 through gantry 2, the historical diversion ratio P2 through gantry 3, and the ratio P3 of the main lane entering the toll station. The historical diversion ratios associated with gantry 2 include: the historical diversion ratio P2 through gantry 3, and the ratio P3 of the main lane entering the toll station. The historical diversion ratios associated with gantry 3 include: the ratio P3 of the main lane entering the toll station.

Specifically, with regard to the historical diversion ratio, since the traffic volume on highways usually changes significantly with holidays and seasons, and the correlation with holidays is the greatest, followed by the correlation with seasons, in this embodiment, the historical diversion ratio is preferably the historical diversion ratio for each time period per day on holidays in the previous year on average, or the historical diversion ratio for each time period per day in a certain quarter of the previous year (including the first quarter from January to March, the second quarter from April to June, the third quarter from July to September, and the fourth quarter from October to December).

It is understood that the historical diversion ratio is calculated in advance based on the traffic data of the previous year and stored in the database. The calculation method is as follows:

The gantry vehicle diversion ratio is obtained by calculating the ratio of the number of vehicles in the front and rear gantries.

The historical diversion ratio of the branch lane entering the toll station is calculated by subtracting the number of vehicles in the main lane's gantry closest to the toll station from the number of vehicles in the next gantry ranked after the gantry, obtaining the difference in the number of vehicles, and dividing the obtained difference in the number of vehicles by the number of vehicles in the gantry closest to the toll station.

The historical diversion ratio of the branch lane entering the toll station is calculated from the traffic flow at the toll station, the traffic flow and diversion ratio of the last gantry of the branch lane, the traffic flow of the first gantry of the main lane, and the diversion ratio of all gantries other than the first gantry of the main lane.

The calculation method of the historical diversion ratio is further explained in combination with the above case as follows:

Divide 24 hours a day into 48 time periods, each of which lasts 30 minutes. Measure and count the traffic flow Sp of the toll station, the traffic flow S1, S2, S3 of the main line gantry 1, gantry 2, and gantry 3, and the traffic flow S6, S7 of the branch line gantry 6 and 7 in each time period.

Then the ratio of vehicles passing through gantry 2 is:

The rate of vehicles passing through gantry 3 is:

The ratio of vehicles entering the toll booth from the feeder lane is:

The ratio of vehicles entering the toll booth from the main lane is:

Finally, the historical diversion ratio of each time period corresponding to each gantry is recorded in the historical diversion ratio table, and the historical diversion ratio table is shown in Table 4. When it is necessary to obtain the historical diversion ratio, the historical diversion ratio corresponding to the gantry can be queried according to the gantry identifier and the first association relationship.

It can be understood that Table 4 is only an example of data format recording. In actual application, specific gantry vehicle data can be filled in the table.

Table 4 Historical diversion ratio

S02: According to the collection period and the preset second association relationship, determine the historical period diversion ratio corresponding to the collection period from the historical classification ratio.

As can be seen from the above Table 4, each time period corresponds to a historical diversion ratio, and the historical diversion ratio corresponding to each time period is the historical time period diversion ratio. In this embodiment, a second association relationship between the collection time period and the historical time period diversion ratio is pre-constructed and stored in the database.

According to the collection period and the second association, the historical period diversion ratio corresponding to the collection period is determined from the historical diversion ratio obtained in step S01. Among them, the collection period can be determined according to the timing starting point of the gantry, the traffic statistics duration, and the data update cycle. For example: the traffic statistics duration of gantry 1 is 0-5min, and the data update cycle is 5min. In the 0:30 period, the diversion ratio of gantry 2 is A, the diversion ratio of gantry 3 is B, and the diversion ratio of the main lane entering the toll station is C. Assuming that the timing starting point is 0:00, according to the timing starting point and the data update cycle, it can be determined that the first collection period is 0:00-0:05, and the collection period is within the 0:30 period. Therefore, the historical period diversion ratios associated with gantry 1 are A, B, and C.

S03: Calculate the predicted number of vehicles in the forecast period based on the diversion ratio in the historical period, the number of gantry vehicles and the traffic statistics duration.

It should be noted that the number of gantry vehicles includes: the number of mainline gantry vehicles and the number of branchline gantry vehicles. The traffic statistics duration includes the mainline gantry traffic statistics duration and the branchline gantry traffic statistics duration. The traffic statistics duration of the mainline gantry and the branchline gantry are compared, and according to the comparison results, the corresponding calculation formula is used to calculate the advance prediction time interval and the predicted number of vehicles in the advance prediction time interval, and the prediction period is calculated according to the collection period and the advance prediction time interval. The number of vehicles corresponding to the advance prediction time interval is the predicted number of vehicles in the prediction period.

The details are as follows:

(1) When the traffic statistics duration of the main line gantry is the same as that of the branch line gantry, that is, k = l, the formula for calculating the predicted number of vehicles is:

Among them, the advance prediction time interval is:

(2) When the traffic statistics time of the main line gantry is less than that of the branch line gantry, that is, k < l, the formula for calculating the predicted number of vehicles is:

Among them, the advance prediction time interval is:

(3) When the traffic statistics duration of the main line gantry is longer than that of the branch line gantry, that is, k>l, the formula for calculating the predicted number of vehicles is:

Among them, the advance prediction time interval is:

Among them, k is the duration of traffic statistics of the main line gantry, in min (minutes); l is the duration of traffic statistics of the branch line gantry, in min (minutes); i is the i-th minute of the duration of traffic statistics of the main line gantry; j is the j-th minute of the duration of traffic statistics of the branch line gantry; _sm is the cumulative traffic volume of the main line gantry per minute; _sb is the cumulative traffic volume of the branch line gantry per minute; _dm is the distance from the main line gantry to the toll station, in km (kilometers); _db is the distance from the branch line gantry to the toll station, in km (kilometers); v is the average speed of the road section, in km/h (kilometers/hour); The advance prediction time interval for the main lane, in minutes; is the advance prediction time interval of the branch lane, in minutes; m is the mth diversion node between the main line gantry and the toll station; b is the bth diversion node between the branch line gantry and the toll station, _Pm is the historical diversion ratio of the mth diversion node on the main lane, _Pb is the historical diversion ratio of the bth diversion node on the branch lane, x is the total number of diversion nodes on the main lane, and y is the total number of diversion nodes on the branch lane.

The above cases are further explained as follows:

According to Table 3 above, the advance prediction time interval of gantry 1 of the main lane is 21-26 minutes. The distance between gantry 4 and the ramp of the main lane is consistent with the distance between gantry 1 and the toll station. Since the distance between the ramp and the toll station can be ignored, the advance prediction time interval between gantry 4 and gantry 1 is also 21-26 minutes. Based on this, the number of vehicles predicted at the toll station within 21-26 minutes can be determined as:

Similarly, the calculation formulas for the predicted number of vehicles corresponding to other advance prediction time intervals in the above cases are shown in Table 5.

Table 5: Advance prediction time interval and corresponding predicted vehicle number

202. According to the predicted number of vehicles and the preset congestion factor, the congestion parameter of the toll station exit is calculated.

It should be noted that when judging the congestion of a toll station based on the capacity of the toll plaza, the congestion factors include: the external dimensions of trucks and the external dimensions of buses.

It is understandable that when a vehicle holding a CPC card passes through the gantry, the gantry can read the vehicle information (such as license plate, vehicle model, vehicle type, etc.) stored in the CPC card, and count the number of different types of vehicles passing by according to the vehicle information. Therefore, the number of vehicles counted by the gantry includes the number of passenger vehicles and the number of truck vehicles. In this embodiment, the predicted number of vehicles obtained includes the predicted number of passenger vehicles and the predicted number of truck vehicles.

The truck capacity is obtained by multiplying the number of trucks by the truck's external dimensions, and the bus capacity is obtained by multiplying the number of buses by the bus's external dimensions; the truck capacity and the bus capacity are summed to obtain the congestion parameter at the toll station exit.

When judging the congestion of a toll station based on the vehicle traffic capacity of the toll station, the congestion factor is a constant, and in this embodiment, it is preferably 1. At this time, the congestion parameter is equal to the predicted number of vehicles.

203. When the congestion parameter is not less than a preset threshold, the toll station exit is marked as a congested exit; and the congested exit and congested time period are used as congested exit information.

When judging the congestion of a toll station based on the capacity of the toll plaza, the preset threshold is the capacity threshold of the toll station plaza. When the congestion parameter is not less than the capacity threshold of the toll station plaza, it means that the toll plaza of the toll station has reached saturation or limit within the prediction period. Therefore, the toll station exit corresponding to the prediction period is marked as a congested exit, and the prediction period is marked as a congested period, and the congested exit information is generated.

When judging the congestion of a toll station based on the vehicle traffic capacity of the toll station, the preset threshold is the threshold of the number of vehicles passing through. When the congestion parameter is not less than the threshold of the number of vehicles passing through, it means that the predicted number of vehicles exceeds the vehicle release capacity of the toll station during the forecast period, and the toll station is in a congested state during the forecast period. The toll station exit corresponding to the forecast period is marked as a congested exit, and the forecast period is marked as a congested period, and congested exit information is generated. The congested exit information includes: congested exit and congested period.

This embodiment calculates the predicted number of vehicles in the predicted time period based on the traffic data, and calculates the congestion parameter of the toll station exit based on the predicted number of vehicles and the preset congestion factor; and when the congestion parameter is not less than the preset threshold, the toll station exit is marked as a congested exit, and the predicted time period is marked as a congested period; and the congested exit and the congested period are used as congested exit information, thereby realizing the prediction of the congested exit of the toll station.

In another preferred embodiment, the congestion level of the vehicle toll station can also be divided according to the above judgment results, as follows:

When the congestion parameter is not less than the threshold of the number of passing vehicles, the congestion level of the toll station is set to the first level; when the congestion parameter is approximately equal to the capacity threshold of the toll station square, the congestion level of the toll station is set to the second level; when the congestion parameter is not less than the capacity threshold of the toll station square, the congestion level of the toll station is set to the third level. Among them, the congestion conditions of the first level, the second level, and the third level increase step by step. By setting the congestion level, this embodiment facilitates the toll station to dispatch personnel according to the congestion level, so as to further improve the traffic efficiency of the toll station.

In another preferred embodiment, it also includes:

When a temporary correction instruction is received, the temporary correction instruction is parsed to obtain correction period and correction object information, and the historical diversion ratio is corrected according to the correction period and correction object information.

It should be noted that when a temporary correction instruction is received, it indicates that a sudden temporary state may have occurred within the preset distance range of the toll station, such as a toll station or ramp construction closure, a sudden high-speed accident (such as a car accident), and other temporary events. If the previous historical diversion ratio is continued to be used to calculate the predicted number of vehicles, the accuracy of the prediction will be reduced. Therefore, it is necessary to correct the historical diversion ratio according to the correction period and correction object in the temporary correction instruction, so as to calculate the predicted number of vehicles using a new diversion ratio that is more in line with the actual environment of the temporary event. For example, the ramp between gantry 1 and gantry 2 is temporarily closed from 16:00 to 17:00. At this time, S1=S2, P1=1, and the corrected diversion ratio table is generated, as shown in Table 6.

In this embodiment, when a temporary correction instruction is received, the temporary correction instruction is parsed to obtain the correction time period and correction object information, and the historical diversion ratio is corrected based on the correction time period and correction object information to make the historical diversion ratio fit the special situation occurring at the moment, thereby improving the accuracy of toll station congestion prediction.

In another preferred embodiment, when a restoration instruction is received, the restoration instruction is parsed to obtain restoration period information and a restoration object, and a restoration operation is performed on the historical diversion ratio according to the restoration period information and the restoration object.

It should be noted that when a restoration command is received, indicating that the temporary event is over, the corrected historical diversion ratio needs to be restored to the initial data. For example, if the ramp between gantry 1 and gantry 2 is reopened at 16:00-17:00, and the traffic data of gantry 2 is restored from S1 to S2, the ratio passing through gantry 2 will be restored from 1 to S2/S1, and P2 will be restored from S3/S1 to S3/S2.

Table 6 Historical diversion ratio correction

Embodiment three:

Please refer to FIG. 4 . Embodiment 3 provides a payment method based on a high-speed composite toll card. Based on Embodiment 1 or Embodiment 2, after step 105, when the payment confirmation result of the first toll bill is not received within the first preset time, the method further includes:

301. Obtain real-time en-route data of en-route users.

It should be noted that, when the payment confirmation result of the first toll bill is not received within the first preset time, it means that the toll station exit predicted above may not be the actual destination exit of the user on the way.

Real-time in-transit data refers to the gantry data of the gantry nodes that the in-transit user has passed through up to the current moment, which includes: gantry identification, CPC card data, and reading time. CPC card data refers to the data stored in the card when the gantry interacts with the CPC card.

It can be understood that every time a vehicle holding a CPC card passes through a gantry, the CPC card will interact with the gantry for data. The gantry reads the data stored in the CPC card (such as license plate information, station passing information, billing amount, entrance information, etc.) and uploads it to the system via multicast.

302. Update the first toll station exit information and the first toll bill according to the real-time in-transit data, historical traffic data and entrance information, obtain the second toll station exit information and the second toll bill, and match the second toll station exit information with the congested exit information. When the match is successful, push the second toll bill to the user terminal of the in-transit user.

It should be noted that the first toll station exit information and the first toll bill are updated according to the real-time in-transit data and the entrance information to obtain the second toll station exit information and the second toll bill, and the updating steps include:

S11: Determine the actual driving path of the user on the way based on the entrance information and the real-time on-way data.

It should be noted that the gantry nodes that the user on the way passes through are determined according to the gantry identification and reading time, and the path is restored and drawn in combination with the entrance information, so as to obtain the actual driving path of the user on the way.

S12: Match the actual driving path with the historical traffic data to obtain the total number of historical traffic flows corresponding to the actual traffic path, the second target historical traffic path, the number of traffic of the second target historical traffic path, and the second target historical exit corresponding to the second target historical traffic path.

It should be noted that the actual driving path is matched with the historical path in the historical travel data of the on-the-way user to determine whether there is a matching historical path. If so, the historical path corresponding to the actual driving path, the historical exit corresponding to the historical path, the number of flows at the historical exit, and the total number of flows are counted and output.

S13: Calculate the traffic ratio of the historical traffic path based on the number of traffic flows and the total number of traffic flows of the historical traffic path; update the second target historical traffic path with the highest traffic ratio to the second target traffic path, and update the second target historical exit corresponding to the second target historical traffic path with the highest traffic ratio to the second predicted exit; and calculate the second predicted arrival time period for the on-the-way user to arrive at the predicted exit based on the driving speed of the on-the-way user and the target traffic path.

It should be noted that the pass rate of a historical pass path is the ratio of the pass flow times of the historical pass path to the total pass flow times of the historical pass path. If there is only one record of the historical pass path obtained, the second target historical pass path with the highest pass rate is itself.

For example, assuming that the entrance information of the en-route user is Gate A, and the gantry billing nodes currently passed are Gate 1 and Gate 2, the actual driving path of the en-route user is restored to be: Gate A-Gate 1-Gate 2. Matching Gate A-Gate 1-Gate 2 with the historical traffic data of the en-route user, the matching results are as follows:

(Ⅰ) Exit A - gantry 1 - gantry 2 - gantry 3 - gantry 5 - exit b, the number of passes is 5;

(II) Exit A - gantry 1 - gantry 2 - gantry 3 - gantry 6 - exit c, the number of passes is 3;

(III) Exit A - gantry 1 - gantry 2 - gantry 4 - gantry 7 - exit d, the number of passes is 2;

As above, the total number of traffic flows that meet the conditions of port A and gantry 1-gantry 2 is 10 times, and the corresponding historical traffic paths are paths (Ⅰ), (II), and (Ⅲ). The historical exits corresponding to the historical paths are b, c, and d, and the corresponding times are 5, 3, and 2, respectively. The calculated ratios of the historical traffic paths are 50%, 30%, and 20%, respectively. Then the historical traffic path (Ⅰ) is the second target traffic path, and exit b is the second predicted exit.

It can be understood that the above case is only used as an example and is not a limitation of the implementation of this embodiment. If there are more times or other matching results, such as there are multiple different travel paths between entrance A and exit B, you can also refer to the above calculation method to obtain the travel ratio of different paths to the same exit, and then determine the target travel path and the second predicted arrival time based on the travel ratio.

S14: updating the first toll bill according to the entrance information, the second predicted exit and the second target travel path to obtain a second toll bill;

It should be noted that the toll is recalculated based on the second target travel path, the second predicted exit, and the entrance information to obtain a second toll bill.

S15: Match the second toll station exit information with the congested exit information, and when the match is successful, push the second toll bill to the user terminal of the on-the-way user.

As can be seen from the above, the second toll station exit information includes the second predicted arrival time period and the second predicted exit. The matching principle can be referred to step 105, which will not be described here.

In this embodiment, when the payment confirmation result is not received within the first preset time, the second toll station exit information and the second toll bill are obtained by obtaining real-time in-transit data, and updating the first toll station exit information and the first toll bill according to the real-time in-transit data and the entrance information, thereby realizing the correction of the destination toll station exit of the in-transit user. By matching the second toll station exit information and the second toll bill, when the match is successful, the second toll bill is pushed to the user terminal of the in-transit user, thereby providing the in-transit user with an exit prediction that better meets the user's needs, thereby facilitating the in-transit user to prepay the tolls in advance.

In another preferred embodiment, step S5 further includes:

S16: When receiving the real-time en route data of the next node of the en route user, execute steps S11-S15.

It should be noted that every time the vehicle of the on-the-go user passes a gantry, the gantry will upload the real-time on-the-go data of the on-the-go user. When the real-time on-the-go data of the new gantry node is received, the actual driving path is updated according to the latest real-time on-the-go data, and then the second exit toll station information is updated, thereby providing the on-the-go user with an exit and toll bill that better meets the user's needs, so that the on-the-go user can prepay the fees in advance.

303. When the payment confirmation result of the second toll bill is not received within the second preset time, and the estimated toll information sent by the preset target gantry is received, a third toll bill is generated according to the estimated toll information; when it is determined that the on-the-way user is a password-free payment user, a password-free payment request is initiated to the third-party payment platform according to the estimated toll information; and when the password-free payment callback information is received from the third-party payment platform, the password-free payment information is generated according to the password-free payment callback information.

It should be noted that the preset target gantry refers to the gantry set up on the exit ramp of the toll station. When the estimated fee information sent by the preset target gantry is received, it means that the vehicle has been driving on the exit ramp and is about to arrive at the toll plaza. The position of the preset target gantry can be determined according to the actual ramp conditions. In the system database, the association between the preset target gantry information and the toll station exit information represented by the preset target gantry is pre-stored. When the payment confirmation result is not received within the second preset time, it means that the user in transit has not prepaid the toll in advance. It is possible that the predicted exit is not the destination of the user in transit, or it is inconvenient for the user in transit to confirm the payment. If the estimated fee information sent by the preset target gantry is received at this time, it means that the user in transit is driving on the exit ramp of the destination toll station exit and is about to arrive at the destination toll station from the ramp.

Specifically, when a vehicle holding a CPC card passes through a preset target gantry, the preset target gantry reads the estimated fee information such as the expressway entrance information, license plate, toll amount, vehicle model, and vehicle type stored in the CPC card. According to the estimated fee information sent by the preset target gantry and the name of the toll station exit represented by the preset target gantry stored in the database, the third toll bill can be calculated. It is understandable that the calculation of the toll can refer to the relevant existing expressway toll regulations, which will not be described in detail in this embodiment. The third toll bill includes entrance information, exit information, license plate, vehicle model, vehicle type, station passing information, total toll amount, and the like.

During the user registration phase, when the user information is reviewed and approved, the user in transit can choose whether to sign a contract with the third-party payment platform for password-free payment. The user in transit who has signed a contract for password-free payment and whose password-free mode is activated normally is a password-free payment user. Therefore, when the third toll bill is generated, it is determined whether the user in transit is a password-free payment user. If so, it means that the user in transit supports password-free payment and initiates a password-free payment request to the third-party payment platform authorized by the user in transit. After receiving the password-free payment request, the third-party payment platform pays the corresponding fee according to the password-free payment request and returns the corresponding password-free payment callback information, and generates payment information according to the payment callback information.

In this embodiment, when the payment confirmation result of the second toll bill is not received within the second preset time, and the estimated fee information sent by the preset target gantry is received, a third toll bill is generated based on the estimated fee information, and when it is determined that the on-the-go user is a password-free payment user, a password-free payment request is initiated to the third-party payment platform based on the estimated fee information, and when the password-free payment callback information is received from the third-party payment platform, password-free payment information is generated based on the password-free payment callback information, thereby further improving the convenience of on-the-go users in paying tolls and further improving the vehicle traffic efficiency of the MTC lanes and mixed traffic lanes at the toll station exit.

304. When it is determined that the user in transit is not a password-free payment user, the third toll bill is pushed to the user terminal of the user in transit, and upon receiving the payment confirmation instruction from the user in transit, a payment request is initiated to the third-party payment platform, and upon receiving the payment callback information from the third-party payment platform, payment information is generated according to the payment callback information.

It should be noted that when it is determined that the user in transit is not a password-free user, it means that the user in transit does not support password-free payment or the activation status of the password-free mode is abnormal, and the fees cannot be directly deducted according to the password-free payment mode. Therefore, the generated third toll bill is sent to the user terminal of the user in transit, and when the payment confirmation instruction of the user in transit is received, a payment request is initiated to the third-party payment platform, and after receiving the payment callback information from the third-party payment platform, the payment information is generated according to the payment callback information.

Embodiment 4:

On the basis of Embodiment 1, Embodiment 2 or Embodiment 3, the payment method provided in Embodiment 4 also includes: when receiving a first bill query instruction from an in-transit user or a non-in-transit user, parsing the first bill query instruction to obtain first access information, obtaining a corresponding fourth toll bill based on the first access information, and pushing the fourth toll bill to the in-transit user or the non-in-transit user, upon receiving a payment confirmation instruction from the in-transit user or the non-in-transit user, initiating a payment request to a third-party payment platform, and upon receiving payment callback information from the third-party payment platform, generating payment information based on the payment callback information.

It should be noted that non-on-the-go users who have not turned on message notifications or password waivers, or non-on-the-go users who have not bound vehicle information, can scan the code or follow the official account to input the corresponding traffic information (such as toll station exit, license plate, license plate color, CPC card number, etc.) into the system, and actively initiate bill inquiries. For non-first-time users, they can click on the historical license plate query to automatically generate the first bill inquiry instruction containing the license plate information. When the user receives the toll bill, the user sends a confirmation payment instruction to the system through the user terminal to complete the toll payment. It is understandable that on-the-go users can inquire about and prepay bills at the toll plaza, service area on the way, or other occasions. The specific occasions and inquiry channels can be selected according to actual conditions, and this embodiment is not specifically limited here.

In this embodiment, when a query instruction is received, the query instruction is parsed to obtain the traffic information, and the corresponding toll bill is retrieved from the system database based on the traffic information, and the retrieved toll bill is sent to the corresponding user terminal. When a confirmation payment instruction is received from an in-transit user or a non-in-transit user, a payment request is initiated to a third-party payment platform, and when the payment callback information from the third-party payment platform is received, payment information is generated based on the payment callback information, so that both non-in-transit users and in-transit users who are not bound to vehicle information can pay tolls in advance. This embodiment further improves the vehicle traffic efficiency at the toll station exit.

In another preferred embodiment, it also includes:

When a second bill query instruction is received, the second bill query instruction is parsed to obtain the second access information, the fifth toll bill corresponding to the second access information is queried and output according to the second access information, and when a confirmation instruction of the fifth toll bill is received, it is determined whether the user corresponding to the fifth toll bill is a password-free payment user. If so, a payment request is initiated to the third-party payment platform, and after receiving the payment callback information from the third-party payment platform, the payment information is generated according to the payment callback information; if not, a confirmation payment request is initiated to the user terminal of the user, and after receiving the confirmation payment instruction returned by the user terminal, a payment request is initiated to the third-party payment platform, and after receiving the payment callback information from the third-party payment platform, the payment information is generated according to the payment callback information.

It should be noted that the second bill query instruction can be a query instruction formed by the CPC card number input by the toll collector, or it can be triggered by the system generating the second bill query instruction after the toll collector swipes the CPC card with a radio frequency device. In this embodiment, if the on-the-way user has not paid the fee in advance and has driven to the booth to return the CPC card, the toll collector swipes the card by using a radio frequency device, or swipes the card to retrieve the corresponding toll bill, and enters the confirmation instruction after verifying the toll bill. After receiving the confirmation instruction, the system determines whether the user of the toll bill is a password-free payment user. If so, the password-free payment process is carried out. Otherwise, a request for confirmation of payment is initiated to the user terminal corresponding to the toll bill, and after the user confirms the payment, a payment request is initiated to the third-party payment platform to realize the fee payment, which reduces the time for users to scan the code to pay and further improves the traffic efficiency.

Embodiment five:

On the basis of Embodiment 1, Embodiment 2, Embodiment 3, or Embodiment 4, the payment method provided in Embodiment 5 also includes:

When a refund instruction is received, the refund instruction is parsed to obtain the refund user information, and a refund request is issued to the third-party payment platform based on the refund user information. When a refund callback information is received from the third-party payment platform, a refund result is generated based on the refund callback information.

It should be noted that the refund information includes the refund user account, refund path and refund amount. When a refund instruction is received, a refund request is initiated to the third-party payment platform based on the refund user account, refund path and refund amount. The third-party payment platform responds to the refund request and returns the refund amount to the user account.

It can be understood that in this embodiment, when the on-the-way user has paid the toll in advance and returned the CPC card at the toll station exit booth, the toll station exit personnel swipe the card or enter the CPC card number into the lane toll collection system. The lane toll collection system at the toll station exit retrieves the corresponding payment information based on the received CPC card information and verifies the payment information. If there are abnormal situations such as inconsistent license plates or vehicle models, incorrect tolls, etc., a lane refund will be automatically initiated (the paid toll will be returned to the user's account along the original route), and the user will re-pay the toll according to the existing conventional process. For example, users who have signed a contract for password-free payment can directly pay without password when re-paying the toll. In addition, if the user's payment is incorrect due to special circumstances, the section customer service can operate a refund in the system background, and the system will initiate a refund application to the third-party payment platform, so that the third-party platform will return the refund amount to the user.

Embodiment six:

On the basis of Embodiment 1 or Embodiment 2 or Embodiment 3 or Embodiment 4 or Embodiment 5, the payment method provided in this Embodiment 6 also includes: when receiving real-time entry information of an in-transit user, judging whether the in-transit user has signed a password-free payment contract based on the user information of the in-transit user; if so, activating the password-free payment mode, and judging in real time whether the status of the password-free payment mode is normal; if so, determining that the in-transit user is a password-free payment user.

It should be noted that the status of the password-free payment mode can be determined by calling the in-transit user status query API. Based on the query results, it can be determined whether the in-transit user has activated, authorized, owed fees, or is on the blacklist.

In a specific embodiment, it also includes: after the payment information of the password-free payment user is generated, the password-free payment mode is closed.

This embodiment improves the smoothness and security of payment by monitoring the password-free payment mode of users on the way in real time and shuts it down when they are not on the way, thereby further improving the vehicle traffic efficiency at the toll station exit.

Embodiment seven:

Referring to FIG. 5 , the seventh embodiment of the present invention provides a payment system based on a high-speed composite pass card, which specifically includes:

The vehicle flow data acquisition module 401 is used to acquire the vehicle flow data within a preset distance range of the toll station exit;

The congestion prediction module 402 is used to perform congestion prediction based on the traffic flow data and the preset congestion factor to obtain congestion exit information;

The en-route user data acquisition module 403 is used to acquire the historical travel data and entrance information of the en-route user;

An exit prediction module 404 is used to perform exit prediction based on historical traffic data and entrance information, and obtain the first toll station exit information and the first toll bill of the on-the-way user;

A matching module 405 is used to match the first toll station exit information with the congested exit information, and when the match is successful, push the first toll bill to the user terminal of the on-the-way user;

The information generating module 406 is used to generate payment information according to the payment information when receiving the payment information of the first toll bill.

In a specific embodiment, the congestion prediction module 402 specifically includes:

The first calculation unit is used to calculate the predicted number of vehicles at the toll station in the predicted period at the toll station exit according to the traffic flow data;

The second calculation unit is used to calculate the congestion parameter of the toll station exit according to the predicted number of vehicles and the preset congestion factor;

The marking unit is used to mark the toll station exit as a congested exit and the predicted period as a congested period when the congestion parameter is not less than a preset threshold; and use the congested exit and the congested period as congested exit information.

In a specific embodiment, the first computing unit includes:

A first determining subunit is used to determine a historical diversion ratio associated with the gantry according to the gantry identifier and a preset first association relationship; the first association relationship is an association relationship between the gantry identifier and the historical diversion ratio;

A second determining subunit is used to determine the historical time period diversion ratio corresponding to the collection period from the historical classification ratio according to the collection period and the preset second association relationship;

The third determination subunit is used to calculate the predicted number of vehicles in the prediction period according to the diversion ratio and the number of gantry vehicles in the historical period.

In a specific embodiment, the second calculation unit is specifically used to multiply the number of trucks by the external dimensions of the trucks to obtain the truck capacity, and multiply the number of buses by the external dimensions of the buses to obtain the bus capacity; sum the truck capacity and the bus capacity to obtain the congestion parameter of the toll station exit.

In a preferred embodiment, the system further comprises:

A real-time in-transit data acquisition module, used to acquire the real-time in-transit data of the in-transit user when the payment confirmation result of the first toll bill is not received within a first preset time;

The updating module is used to update the exit information of the first toll station and the first toll bill according to the real-time in-transit data and the entrance information, and obtain the exit information of the second toll station and the second toll bill.

The matching module is updated to match the second toll station exit information and the congested exit information, and when the match is successful, the second toll bill is pushed to the user terminal of the user on the way.

In a specific embodiment, the system further comprises:

A toll prepayment bill generating module, configured to generate a third toll bill according to the estimated fee information when the payment confirmation result of the second toll bill is not received within the second preset time and the estimated fee information sent by the preset target gantry is received;

The password-free payment information generation module is used to initiate a password-free payment request to the third-party payment platform based on the estimated payment information when the in-transit user is determined to be a password-free payment user, and to generate the password-free payment information based on the password-free payment callback information received from the third-party payment platform.

In a preferred embodiment, the system further comprises:

The correction module is used to parse the temporary correction instruction when it is received, obtain the correction period and correction object information, and correct the historical period diversion ratio according to the correction period and correction object information.

In a specific application example, when constructing this system in the actual process, it can be constructed with reference to the system architecture shown in Figure 6. It can be understood that the system architecture can be divided into: Internet area, security front area, and road section charging area according to the flow direction of data interaction. Among them, the interconnection area includes a third-party payment platform and a mobile terminal. A firewall is set between the Internet area and the security front area. The security front area includes a prepayment interface service, an unknown threat detection system, a network access system, a front interaction machine, a security management module, and the security management module includes log auditing, database auditing, vulnerability scanning, and a bastion machine; a network gate is set between the security front area and the road section charging right. The road section charging area includes: a core switch, a prepayment applet background, and a road section charging system, wherein the road section charging system includes a charging support system and a transmission system. The prepayment applet background includes a prepayment applet and a prepayment background. The prepayment background is used to interact with the prepayment applet background and the charging support system of the front end to provide users with prepayment bill query, payment, refund and other functions. The charging support system is used to receive the billing flow data of the gantry and generate prepayment bills, which are sent to the prepayment background through the transmission system.

In another specific application example, as shown in FIG7 , the system architecture provided in this embodiment can be divided into user terminals, front-end systems, back-end applications and technical support according to the application level, wherein the user terminal is provided with a prepayment applet, a fee prepayment push module and a congestion exit notification module, and the front-end system includes a CPC prepayment system, a mixed lane charging system, a pre-transaction multicast system, a congestion prediction module and a path prediction module; the back-end application includes a charging support platform, a mobile payment back-end, an invoice platform and a prepayment system management platform; the bottom-level technical support includes a microservice architecture, a queue segmentation technology, a ramp prepayment technology and a data visualization technology. It is understandable that the above-mentioned application-level architecture can be constructed according to actual conditions.

In another preferred embodiment, the present invention provides an electronic device, the device comprising a processor and a memory:

The memory is used to store program code and transmit the program code to the processor;

The processor is used to execute the above method embodiment according to the instructions in the program code.

In the several embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each functional unit may be physically separate, or two or more functional units may be integrated into one processing unit. The above integrated unit may be implemented in the form of hardware or in the form of software functional units.

If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein, for example. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (10)

1. A payment method based on a high-speed composite pass card, the method comprising:

acquiring traffic flow data in a preset distance range of a toll station outlet;

carrying out congestion prediction according to the traffic flow data and a preset congestion factor to obtain congestion exit information;

acquiring historical traffic data and entry information of an in-transit user;

carrying out exit prediction according to the historical traffic data and the entrance information to obtain first toll station exit information and a first toll bill of the on-road user;

matching the first toll station outlet information with the congestion outlet information, and pushing the first toll bill to a user terminal of the in-transit user when the matching is successful;

And when the payment information of the first toll bill is received, generating payment information according to the payment information.

2. The method of claim 1, wherein the performing congestion prediction according to the traffic flow data and a preset congestion factor, and obtaining congestion exit information includes:

calculating to obtain the predicted vehicle number of the predicted period of the toll station outlet according to the traffic flow data;

calculating to obtain the congestion parameters of the toll station outlet according to the predicted number of vehicles and a preset congestion factor;

when the congestion parameter is not smaller than a preset threshold value, marking the exit of the toll station as a congestion exit, and marking the predicted period as a congestion period; and taking the congestion exit and the congestion period as the congestion exit information.

3. The method of claim 2, wherein the traffic data comprises: portal identification, portal vehicle number, acquisition period and traffic flow statistics duration; the calculating, according to the traffic flow data, the predicted number of vehicles in the predicted period of the toll station exit includes:

according to the portal identification and a preset first association relation, determining a historical shunt ratio associated with the portal identification; the first association relationship is the association relationship between the portal identification and the historical shunt ratio;

According to the acquisition time period and a preset second association relation, determining a history time period shunt ratio corresponding to the acquisition time period from the history classification ratio;

and calculating the predicted vehicle number of the predicted period according to the historical period split ratio, the portal vehicle number and the vehicle flow statistical duration.

4. The method of claim 3, wherein predicting the number of vehicles comprises: the number of trucks and buses; the preset congestion factors comprise truck outline dimensions and passenger car outline dimensions; the preset threshold value comprises a capacity threshold value of a toll station square;

the step of calculating the congestion parameters of the toll station outlet according to the predicted number of vehicles and the preset congestion factor comprises the following steps:

multiplying the number of trucks by the overall size of the truck to obtain truck capacity, and multiplying the number of buses by the overall size of the bus to obtain bus capacity; and summing the freight car capacity and the passenger car capacity to obtain the congestion parameter of the toll station outlet.

5. A method according to claim 3, wherein when a payment confirmation result of the first toll bill is not received within a first preset time, the method further comprises:

Acquiring real-time in-transit data of the in-transit user;

updating the first toll station outlet information and the first toll bill according to the real-time in-transit data, the historical traffic data and the entrance information to obtain second toll station outlet information and a second toll bill;

the step of matching the first toll station outlet information and the congestion outlet information, when the matching is successful, pushing the first toll bill to the user terminal of the in-transit user comprises the following steps:

and matching the second toll station outlet information with the congestion outlet information, and pushing the second toll bill to the user terminal of the in-transit user when the matching is successful.

6. The method of claim 5, wherein the method further comprises:

when a payment confirmation result of the second toll bill is not received within a second preset time, and pre-charging information sent by a preset target portal is received, generating a third toll bill according to the pre-charging information;

when the in-transit user is judged to be the secret payment-free user, a secret payment-free request is initiated to a third party payment platform according to the pre-payment information, secret payment-free callback information of the third party payment platform is received, and secret payment-free information is generated according to the secret payment-free callback information.

7. The method of claim 6, wherein the method further comprises:

when the on-road user is judged to be a non-secret payment-free user, pushing the third toll bill to a user terminal of the on-road user, when a payment confirmation instruction of the on-road user is received, initiating a payment request to a third party payment platform, and when payment callback information of the third party payment platform is received, generating payment information according to the payment callback information.

8. A method according to claim 3, characterized in that the method further comprises:

when a temporary correction instruction is received, the temporary correction instruction is analyzed to obtain a correction period and correction object information, and the historical period split ratio is corrected according to the correction period and the correction object information.

9. A payment system based on a high-speed composite pass card, the system comprising:

the traffic flow data acquisition module is used for acquiring traffic flow data in a preset distance range of the toll station outlet;

the congestion prediction module is used for carrying out congestion prediction according to the traffic flow data and a preset congestion factor to obtain congestion outlet information;

The on-road user data acquisition module is used for acquiring historical traffic data and entry information of the on-road user;

the exit prediction module is used for carrying out exit prediction according to the historical traffic data and the entrance information to obtain first toll station exit information and a first toll bill of the on-road user;

the matching module is used for matching the first toll station outlet information with the congestion outlet information, and pushing the first toll bill to the user terminal of the in-transit user when the matching is successful;

and the information generation module is used for generating payment information according to the payment information when receiving the payment information of the first toll bill.

10. An electronic device, the device comprising a processor and a memory:

the memory is used for storing program codes and transmitting the program codes to the processor;

the processor is configured to perform the method of any of claims 1-8 according to instructions in the program code.