Highway Free-Flow Tolling System Based on Cloud Native Technology

Abstract

The present invention discloses a free-flow toll collection system for expressways based on cloud-native technology, which relates to the technical field of free-flow toll collection for expressways and aims to solve the problems of unclear toll items and inconvenient toll collection. Through the visual interface, the on-duty personnel can intuitively see the load conditions of each ETC lane, avoiding the situation where some lanes are overloaded while others are idle. Through cloud-native technology, the toll station control center can remotely monitor the operation of each ETC lane. The free-flow toll collection system for expressways based on cloud-native technology needs continuous technological innovation and upgrading to adapt to the changing traffic demands and technological environment. The matching trajectory is fitted using a spline curve, making the fitted trajectory smoother, more continuous, and better able to reflect the actual driving path of the vehicle. After the fitting is completed, the driving path of the vehicle on the expressway can be automatically marked as vehicle guidance toll collection data.

Description

Technical Field

[0001] The present invention relates to the technical field of free-flow toll collection on highways, and in particular to a free-flow toll collection system on highways based on cloud native technology. Background Art

[0002] Free-flow toll collection on highways is a toll collection method based on electronic toll collection technology. It allows vehicles to travel freely on highways at the designed speed without slowing down or stopping to complete the toll collection process.

[0003] The Chinese patent with publication number CN111063042A discloses a free-flow toll path fitting system for highways based on big data. It mainly analyzes various states such as whether the highway is passable, the toll of the highway, the comfort of the highway and the distance of the highway, and can timely plan and fit an optimal highway route that meets its own needs. It solves the problem that traditional highways charge passing vehicles freely during operation without processing and analyzing the relevant data of the charges, which leads to the problem that many vehicles cannot plan and fit an optimal highway route that meets their own needs when they need to travel on the highway. Although the above patent solves the problem of path fitting, there are still the following problems in actual operation:

[0004] 1. The vehicle information is not entered and received more completely, resulting in inaccurate verification results when the vehicle is verified.

[0005] 2. The toll station did not fit the vehicle's driving trajectory more accurately, resulting in the inability to audit the vehicle's trajectory.

[0006] 3. Before vehicles enter the ETC channel of the toll station, there is no targeted entry guidance based on the usage of the ETC channel on site, resulting in inconvenient traffic on site. Summary of the invention

[0007] The purpose of the present invention is to provide a highway free-flow toll collection system based on cloud native technology. Through the visual interface, the on-duty personnel can intuitively see the load conditions of each ETC channel to avoid the situation where some channels are overloaded while other channels are idle. Through cloud native technology, the toll station control center can remotely monitor the operation of each ETC channel. The highway free-flow toll collection system based on cloud native technology requires continuous technological innovation and upgrading to adapt to the ever-changing traffic needs and technical environment. The matching trajectory is fitted using a spline curve, so that the fitted trajectory is smoother and continuous, and can better reflect the actual driving path of the vehicle. After the fitting is completed, the vehicle's driving path on the highway can be automatically marked as vehicle-guided toll data, which can solve the problems in the prior art.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] A free-flow toll collection system for expressways based on cloud native technology, comprising:

[0010] A vehicle information acquisition unit, configured to:

[0011] Confirm the real-time information and basic information of the vehicle, and obtain standard vehicle information data after the confirmation is completed;

[0012] A toll station information processing unit, configured to:

[0013] When the vehicle travels to the expressway toll station, the toll station control center verifies the information of the traveling vehicle according to the standard vehicle information data, and obtains target toll vehicle data after the information verification is qualified;

[0014] A cloud native platform data receiving and processing unit, configured to:

[0015] The toll station control center transmits the target toll vehicle data to the cloud native platform, and the cloud native platform performs trajectory fitting on the received target toll vehicle data, and obtains vehicle guidance toll data after the fitting is completed;

[0016] A vehicle toll and guidance processing unit, configured to:

[0017] Guide the vehicle to the corresponding ETC lane according to the vehicle guidance toll data, and send the deduction information to the online payment system for automatic deduction. After the automatic deduction, the deduction bill is sent to the vehicle owner through the online bank.

[0018] Preferably, the vehicle information acquisition unit is further configured to:

[0019] An in-vehicle positioning device is provided in the vehicle, and the in-vehicle positioning device is used to obtain the position data of the vehicle in real time and generate driving trajectory data;

[0020] The real-time information of the vehicle includes vehicle position data, driving trajectory data, license plate number, vehicle speed, timestamp and ETC device status. Among them, for trucks, the number of vehicle axles and vehicle weight are also included;

[0021] The basic information of the vehicle includes vehicle owner information, vehicle registration information, vehicle type, vehicle size, ETC account information, payment information and black / white list status;

[0022] Standard vehicle information data is obtained after both the real-time information and the basic information of the vehicle are confirmed.

[0023] Preferably, the toll station information processing unit is further configured to:

[0024] The highway toll station is equipped with a signal acquisition device, a camera device, and a weighbridge. When a vehicle arrives at the highway toll station, the signal acquisition device receives the standard vehicle information data;

[0025] The camera device uses image recognition technology to extract the license plate number, vehicle type, and vehicle size, and compares the extracted license plate number, vehicle type, and vehicle size with the license plate number, vehicle type, and vehicle size in the standard vehicle information data, and judges whether the license plate number, vehicle type, and vehicle size are qualified according to the comparison result;

[0026] Then, the ETC device status is checked, and it is judged whether the ETC device status is the activated state according to the check result;

[0027] Compare the driving track data in the standard vehicle information data with the data obtained at each toll station site, and judge whether the vehicle driving track is legal according to the comparison result.

[0028] Preferably, the toll station information processing unit is further used for:

[0029] When the vehicle is a truck, the weighbridge at the highway toll station collects the vehicle axle number and vehicle weight of the truck in real time, and compares and judges the real-time collected data with the vehicle axle number and vehicle weight in the standard vehicle information data;

[0030] Verify the rationality of the timestamp in the standard vehicle information data;

[0031] Judge whether the vehicle is a blacklist vehicle according to the standard vehicle information data, and mark the blacklist vehicle as abnormal;

[0032] After all verifications are completed and qualified, it is marked as the target toll vehicle data;

[0033] Prompt and manually guide the vehicles with abnormal verification.

[0034] Preferably, the cloud-native platform data receiving and processing unit includes:

[0035] A data transmission module, which is used for:

[0036] The toll station control center transmits the target toll vehicle data to the cloud-native platform after confirmation;

[0037] When transmitting the target toll vehicle data, first confirm the data transmission volume of the target toll vehicle data;

[0038] Among them, the data transmission volume is to divide the target toll vehicle data into several data segments with the same length, and confirm the data transmission volume of the target toll vehicle data according to the number of data segments;

[0039] Then, confirm the transmission channel between the toll station control center and the cloud native platform, where the transmission channel data is not less than 9 pieces;

[0040] Confirm the remaining capacity of each transmission channel, and select the transmission channel for the target toll vehicle data according to the remaining capacity of the channel, where the remaining capacity of the channel is greater than the transmission volume of the target toll vehicle data;

[0041] When there are more than two transmission channels with the remaining capacity of the channel greater than the transmission volume of the target toll vehicle data, select the one with the strongest signal strength among the multiple transmission channels as the transmission channel for the target toll vehicle data.

[0042] Preferably, the data transmission module further includes:

[0043] A transmission rate real-time monitoring module for real-time monitoring of the data transmission rate of each transmission channel;

[0044] A data transmission index factor acquisition module for obtaining the data transmission index factor corresponding to each transmission channel according to the data transmission rate of each transmission channel;

[0045] Among them, the data transmission index factor corresponding to each transmission channel is obtained through the following formula:

[0046] ;

[0047] Among them, R represents the data transmission index factor corresponding to each transmission channel; n represents the number of elapsed unit times corresponding to the operation of each transmission channel, and the unit time is 1s; B i represents the data transmission rate corresponding to the i-th unit time of the transmission channel; B i represents the data transmission rate corresponding to the i-th unit time of the transmission channel; B bi represents the standard deviation of the data transmission rate corresponding to the i-th unit time of the transmission channel; B bi-1 represents the standard deviation of the data transmission rate corresponding to the (i - 1)-th unit time of the transmission channel; B bmax represents the maximum value of the standard deviation of the data transmission rate among the n - 1 standard deviations of the data transmission rate generated when the transmission channel runs for n unit times; B n represents the data transmission rate at the current moment of the transmission channel;

[0048] A comprehensive channel factor acquisition module for obtaining a comprehensive channel factor by combining the data transmission index factor corresponding to each transmission channel with the data transmission rate of each transmission channel at the current moment;

[0049] A target length acquisition module, configured to obtain a target length by using the comprehensive channel factor in combination with the data volume corresponding to the current target toll vehicle data; wherein, the target length is the length corresponding to the data segment when the target toll vehicle data is divided.

[0050] Preferably, the comprehensive channel factor acquisition module includes:

[0051] A data transmission index factor extraction module, configured to extract the data transmission index factor corresponding to each transmission channel;

[0052] A data transmission rate acquisition module, configured to extract the data transmission rate of each transmission channel at the current moment;

[0053] A value extraction module, configured to screen out the maximum data transmission rate and the minimum data transmission rate corresponding to the transmission channel from the data transmission rates of each transmission channel at the current moment;

[0054] An adjustment coefficient acquisition module, configured to obtain the adjustment coefficient corresponding to each transmission channel by using the maximum data transmission rate and the minimum data transmission rate;

[0055] Wherein, the adjustment coefficient corresponding to each transmission channel is obtained through the following formula:

[0056] ;

[0057] Wherein, f represents the adjustment coefficient corresponding to each transmission channel; B max and B min respectively represent the maximum data transmission rate and the minimum data transmission rate; R represents the data transmission index factor corresponding to each transmission channel; B m01 represents the standard deviation of the data transmission rate corresponding to the moment of the maximum data transmission rate; B m02 represents the standard deviation of the data transmission rate corresponding to the moment of the minimum data transmission rate;

[0058] A comprehensive channel factor acquisition execution module, configured to obtain a comprehensive channel factor by using the adjustment coefficient corresponding to each transmission channel in combination with the data transmission index factor corresponding to each transmission channel;

[0059] Wherein, the comprehensive channel factor is obtained through the following formula:

[0060] ;

[0061] Wherein, S represents the comprehensive channel factor; m represents the total number of transmission channels; f i represents the adjustment coefficient corresponding to the i-th transmission channel; R i represents the data transmission index factor corresponding to the i-th transmission channel; Rb It represents the standard deviation of the data transmission index factors corresponding to m transmission channels.

[0062] Preferably, the target length acquisition module includes:

[0063] An integrated channel factor extraction module for extracting the integrated channel factor;

[0064] A data volume extraction module for extracting the data volume corresponding to the current target toll vehicle data;

[0065] A historical data extraction module for extracting the data volume corresponding to each target toll vehicle data in the historical transmission record of the data transmission module and the length of the corresponding data segment during its transmission;

[0066] A target length acquisition execution module for obtaining the target length corresponding to the current target toll vehicle data for data transmission by using the integrated channel factor and the data volume corresponding to the current target toll vehicle data, in combination with the data volume corresponding to each target toll vehicle data in the historical transmission record of the data transmission module and the length of the corresponding data segment during its transmission;

[0067] Among them, the target length corresponding to the current target toll vehicle data for data transmission is obtained through the following formula:

[0068] ;

[0069] Among them, K represents the target length corresponding to the current target toll vehicle data for data transmission; K0 represents the preset initial data segment length; S represents the integrated channel factor; k represents the number of data transmissions of the target toll vehicle data; C i represents the data volume corresponding to the i-th data transmission of the target toll vehicle data; C x represents the preset data volume reference value; K i represents the data segment length corresponding to the i-th data transmission of the target toll vehicle data; C0 represents the data volume corresponding to the current target toll vehicle data.

[0070] Preferably, the cloud-native platform data receiving and processing unit further includes:

[0071] A driving trajectory fitting module for:

[0072] After the cloud-native platform receives the target toll vehicle data, it performs trajectory fitting;

[0073] First, match the driving trajectory data in the target toll vehicle data with the highway road network, and match the GPS points of the vehicle with the closest road segment by using the map matching algorithm;

[0074] The trajectory after matching is smoothed using Kalman filtering, and the physical laws of the smoothed trajectory are judged;

[0075] Finally, a spline curve is used to fit the matched trajectory. After the fitting is completed, the driving path of the vehicle on the highway is obtained and marked as vehicle guidance toll data.

[0076] Preferably, the vehicle toll collection and guidance processing unit includes:

[0077] A vehicle guidance module for:

[0078] Pre-check the capacity of the ETC lanes at the highway toll station;

[0079] Among them, the toll station control center monitors the real-time vehicle data of the number of waiting vehicles in each ETC lane at the toll station;

[0080] And display the monitored real-time vehicle data on the display screen above each ETC lane to show the number of waiting vehicles;

[0081] Before the driving vehicle enters the ETC lane of the toll station, it makes an optimal choice according to the number of waiting vehicles displayed on the display screen above each ETC lane;

[0082] After the selection is completed, the vehicle queues up and enters the ETC lane, and the number of waiting vehicles displayed on the display screen above each ETC lane and the picture of the toll station site are transmitted to the display screen of the duty personnel in a visual interface;

[0083] An ETC deduction module for:

[0084] When the driving vehicle reaches the ETC lane of the toll station, calculate the vehicle travel mileage according to the vehicle driving trajectory in the vehicle guidance toll data, and calculate the travel cost according to the vehicle travel mileage;

[0085] When the vehicle passes through the ETC lane of the toll station, the ETC lane exchanges information with the ETC account information. The ETC account information sends the deduction information of the ETC lane to the online payment system, and the online payment system automatically deducts the fee through the ETC account information;

[0086] After the ETC account information automatically deducts the fee, the deduction bill is sent to the vehicle owner through the online bank.

[0087] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0088] 1. The free-flow toll collection system for expressways based on cloud-native technology provided by the present invention can provide intelligent scheduling and route planning suggestions for traffic management departments, relieve traffic congestion, and improve road traffic efficiency. It can monitor the driving status of vehicles in real time, give timely warnings and handle behaviors such as speeding and illegal driving. With the support of cloud-native technology, real-time transmission, storage, and processing of data can be achieved, avoiding data loss or delay and ensuring data integrity. Through the remote monitoring and management platform, operators can monitor the system operation status in real time.

[0089] 2. The free-flow toll collection system for expressways based on cloud-native technology provided by the present invention uses spline curves to fit the matched trajectories, making the fitted trajectories smoother and more continuous, and better reflecting the actual driving paths of vehicles. After the fitting is completed, it can automatically label the driving paths of vehicles on the expressway as vehicle guidance toll collection data, reducing the workload of manual labeling. By accurately dividing data segments and selecting appropriate channels, data loss or damage during transmission can be minimized to the greatest extent. By confirming the remaining capacity of the channel and selecting the optimal channel, it helps to optimize resource utilization.

[0090] 3. The free-flow toll collection system for expressways based on cloud-native technology enables duty officers to intuitively see the load conditions of each ETC lane through the visualization interface, and take timely measures for load balancing to avoid situations where some lanes are overloaded while others are idle. Through cloud-native technology, the toll station control center can remotely monitor the operation of each ETC lane, discover and solve problems in a timely manner. The free-flow toll collection system for expressways based on cloud-native technology requires continuous technological innovation and upgrading to adapt to the changing traffic demands and technological environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0091] Figure 1 It is a schematic diagram of the free-flow toll collection unit of the present invention;

[0092] Figure 2 It is a schematic diagram of the free-flow toll collection process of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0093] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0094] In order to solve the problem in the prior art that the information of the vehicle is not more completely entered and received, resulting in inaccurate verification results when verifying the vehicle, please refer to Figure 1 and Figure 2 , the following technical solutions are provided in this embodiment:

[0095] A free-flow toll collection system for expressways based on cloud-native technology, including:

[0096] A vehicle information acquisition unit, for:

[0097] Confirm the real-time information and basic information of the vehicle, and obtain the standard vehicle information data after the confirmation is completed;

[0098] A toll station information processing unit, for:

[0099] When the vehicle drives to the expressway toll station, the toll station control center verifies the information of the driving vehicle according to the standard vehicle information data, and obtains the target toll vehicle data after the information verification is qualified;

[0100] A cloud-native platform data receiving and processing unit, for:

[0101] The toll station control center transmits the target toll vehicle data to the cloud-native platform, and the cloud-native platform performs trajectory fitting on the received target toll vehicle data, and obtains the vehicle guidance toll data after the fitting is completed;

[0102] A vehicle toll and guidance processing unit, for:

[0103] Guide the vehicle to the corresponding ETC lane according to the vehicle guidance toll data, and send the deduction information to the online payment system for automatic deduction. After the automatic deduction, send the deduction bill to the vehicle owner through the online bank.

[0104] Specifically, the vehicle information acquisition unit can provide intelligent dispatching and route planning suggestions for the traffic management department, relieve traffic congestion, and improve road traffic efficiency. Through the toll station information processing unit, real-time transmission, storage and processing of data can be realized, avoiding data loss or delay, and ensuring the integrity of data. Through the cloud-native platform data receiving and processing unit, it is ensured that the trajectory conforms to the actual driving situation, and the spline curve is used to fit the matched trajectory, making the fitted trajectory smoother and more continuous. The toll station control center can remotely monitor the operation of each ETC lane, and discover and solve problems in time.

[0105] The vehicle information acquisition unit is also used for:

[0106] An in-vehicle positioning device is set in the vehicle, and the in-vehicle positioning device is used to obtain the position data of the vehicle in real time and generate the driving trajectory data;

[0107] The real-time information of the vehicle includes vehicle location data, driving trajectory data, license plate number, vehicle speed, timestamp and ETC device status. For trucks, it also includes the number of vehicle axles and vehicle weight.

[0108] The basic information of the vehicle includes the owner information, vehicle registration information, vehicle type, vehicle size, ETC account information, payment information and blacklist and whitelist status;

[0109] After the real-time information and basic information of the vehicle are confirmed, standard vehicle information data is obtained.

[0110] Specifically, the on-board positioning device can obtain the vehicle's location data and driving trajectory in real time, which helps the system to accurately calculate the receivables and avoid missed or wrong charges. Through basic information such as license plate number and vehicle type, the system can accurately identify the vehicle to ensure that the toll collection is correct. Real-time acquisition of ETC equipment status helps the system to promptly discover and resolve equipment failures and ensure the normal implementation of ETC charging. Based on the vehicle's real-time location and driving trajectory, the system can provide intelligent scheduling and route planning suggestions to traffic management departments, alleviate traffic congestion, and improve road traffic efficiency. It can monitor the vehicle's driving status in real time, and promptly warn and handle speeding, illegal driving and other behaviors, thereby improving the level of intelligent traffic management. By providing accurate vehicle location and driving trajectory information, the system can provide car owners with more accurate navigation and travel services and enhance travel experience. Based on in-depth mining and analysis of vehicle data, highway management departments can explore new business models and service methods.

[0111] The toll booth information processing unit is also used for:

[0112] The highway toll station is equipped with a signal collection device, a camera device and a weighing scale. When a vehicle drives to the highway toll station, the signal collection device receives standard vehicle information data;

[0113] The camera device uses image recognition technology to extract the license plate number, vehicle type and vehicle size, and compares the extracted license plate number, vehicle type and vehicle size with the license plate number, vehicle type and vehicle size in the standard vehicle information data, and determines whether the license plate number, vehicle type and vehicle size are qualified according to the comparison result;

[0114] Then check the ETC device status and determine whether the ETC device status is activated based on the check result;

[0115] The driving trajectory data in the standard vehicle information data is compared with the data obtained at each toll station, and the legality of the vehicle's driving trajectory is determined based on the comparison results.

[0116] When the vehicle is a truck, the weighbridge at the highway toll station collects real-time data on the number of vehicle axles and the vehicle weight of the truck, and compares and judges the real-time collected data with the number of vehicle axles and the vehicle weight in the standard vehicle information data;

[0117] Verify the rationality of the timestamp in the standard vehicle information data;

[0118] Judge whether the vehicle is a blacklist vehicle according to the standard vehicle information data, and mark the blacklist vehicle as abnormal;

[0119] After all verifications are completed and qualified, it is marked as target toll vehicle data;

[0120] Prompt and manually guide the vehicles with abnormal verification.

[0121] Specifically, through automated means such as license plate recognition, vehicle type and size judgment, the vehicle can quickly pass through the toll station without decelerating, significantly reducing the queuing time and the risk of traffic congestion. Automatically collecting and processing data reduces manual intervention, thus improving the efficiency and safety of the entire toll collection process. Using high-precision devices such as image recognition technology and weighbridges, vehicle information such as license plate number, vehicle type, vehicle size, number of vehicle axles and vehicle weight can be collected in real time and accurately, ensuring the accuracy of the data. With the support of cloud-native technology, real-time transmission, storage and processing of data can be achieved, avoiding data loss or delay and ensuring the integrity of the data. Through the remote monitoring and management platform, system operators can monitor the system operation status in real time, discover and solve potential problems in a timely manner, and improve the reliability and stability of the system.

[0122] To solve the problem in the prior art that the toll station does not perform more accurate travel fitting on the driving trajectory of the vehicle, resulting in the inability to inspect the trajectory of the vehicle, please refer to Figure 1 and Figure 2 In this embodiment, the following technical solutions are provided:

[0123] The cloud-native platform data receiving and processing unit includes:

[0124] The data transmission module is used for:

[0125] The toll station control center transmits the target toll vehicle data to the cloud-native platform after confirmation;

[0126] When transmitting the target toll vehicle data, first confirm the data transmission volume of the target toll vehicle data;

[0127] Among them, the data transmission volume is to divide the target toll vehicle data into several data segments with the same length, and confirm the data transmission volume of the target toll vehicle data according to the number of data segments;

[0128] Then, confirm the transmission channel between the toll station control center and the cloud-native platform, where the transmission channel data is not less than 9 pieces;

[0129] Confirm the remaining capacity of each transmission channel, and select the transmission channel for the target toll vehicle data according to the remaining capacity of the channel, where the remaining capacity of the channel is greater than the transmission volume of the target toll vehicle data;

[0130] When there are more than two transmission channels with the remaining capacity of the channel greater than the transmission volume of the target toll vehicle data, select the one with the strongest signal strength among the multiple transmission channels as the transmission channel for the target toll vehicle data.

[0131] Specifically, by confirming the data transmission volume of the target toll vehicle data and selecting the transmission channel accordingly, the efficiency of data transmission is ensured. Dividing the data into several data segments of the same length helps to more accurately estimate the transmission requirements, so as to select the most suitable transmission channel. The transmission channel data is not less than 9 pieces, providing multiple choices for data transmission. Among multiple channels, selecting the optimal channel according to the remaining capacity and signal strength of the channel helps to ensure the stability and reliability of data transmission. Transmitting data through multiple channels can reduce the risk of transmission failure of a single channel, thus improving the security of data transmission. In addition, this solution also implicitly guarantees the integrity and accuracy of data transmission, because by accurately dividing the data segments and selecting the appropriate channels, the loss or damage of data during transmission can be minimized. By confirming the remaining capacity of the channel and selecting the optimal channel, it helps to optimize resource utilization. It avoids the transmission bottleneck caused by insufficient channel capacity and also reduces the waste of resources caused by channel idleness.

[0132] Specifically, the data transmission module further includes:

[0133] A transmission rate real-time monitoring module for real-time monitoring of the data transmission rate of each transmission channel;

[0134] A data transmission index factor acquisition module for acquiring the data transmission index factor corresponding to each transmission channel according to the data transmission rate of each transmission channel;

[0135] Among them, the data transmission index factor corresponding to each transmission channel is obtained through the following formula:

[0136] ;

[0137] Among them, R represents the data transmission index factor corresponding to each transmission channel; n represents the number of elapsed unit times corresponding to the operation of each transmission channel, and the unit time is 1s; B iIndicates the data transmission rate corresponding to the i-th unit time of the transmission channel; B i Indicates the data transmission rate corresponding to the i-th unit time of the transmission channel; B bi Indicates the standard deviation of the data transmission rate corresponding to the i-th unit time of the transmission channel; B bi-1 Indicates the standard deviation of the data transmission rate corresponding to the (i - 1)-th unit time of the transmission channel; B bmax Indicates the maximum value of the data transmission rate standard deviation among the n - 1 data transmission rate standard deviations generated when the transmission channel operates for n unit times; B n Indicates the data transmission rate at the current moment of the transmission channel;

[0138] The comprehensive channel factor acquisition module is used to obtain the comprehensive channel factor by combining the data transmission index factors corresponding to each transmission channel with the data transmission rate of each transmission channel at the current moment;

[0139] The target length acquisition module is used to obtain the target length by combining the comprehensive channel factor with the data volume corresponding to the current target toll vehicle data; wherein, the target length is the length of the data segment when dividing the target toll vehicle data.

[0140] The technical effects of the above technical solution are as follows: Through the transmission rate real-time monitoring module, the data transmission rate of each transmission channel can be captured in real time, which is crucial for dynamic network environments and network load changes at different time periods. Real-time monitoring can ensure that the system can quickly respond to changes in the network state, thereby optimizing data transmission efficiency. The data transmission index factor acquisition module uses the above mathematical formula to comprehensively evaluate the performance of each transmission channel. This formula takes into account multiple factors, including the data transmission rate per unit time, the standard deviation and its change of the data transmission rate, and the data transmission rate at the current moment. This comprehensive evaluation method can more accurately reflect the stability and efficiency of the channel, helping to make more informed transmission decisions. The comprehensive channel factor acquisition module calculates the comprehensive channel factor using the data transmission index factor corresponding to each transmission channel and the current data transmission rate. This factor reflects the overall performance and current state of the channel and can be used to determine the optimal transmission channel or adjust the transmission strategy. The target length acquisition module determines the target length of data partitioning based on the comprehensive channel factor and the data volume of the target toll vehicles. This flexible data partitioning strategy can ensure the balanced transmission of data across different channels, avoid network congestion and data loss, and improve the efficiency and security of data transmission. Overall, through means such as real-time monitoring, precise evaluation, optimized transmission strategy, and flexible data partitioning, this technical solution significantly improves the efficiency and security of data transmission. This is a very important technical improvement for a toll vehicle data processing system that requires efficient and reliable data transmission. Each module and formula design in this technical solution has a certain degree of flexibility and adaptability and can be adjusted and optimized according to different network environments, data volumes, and transmission requirements. This enables this technical solution to be widely applied to various scenarios that require efficient data transmission.

[0141] In summary, through means such as real-time monitoring, precise evaluation, optimized transmission strategy, and flexible data partitioning, this technical solution has achieved a significant improvement in data transmission efficiency and security, providing strong technical support for the toll vehicle data processing system.

[0142] Specifically, the comprehensive channel factor acquisition module includes:

[0143] The data transmission index factor extraction module is used to extract the data transmission index factor corresponding to each transmission channel;

[0144] The data transmission rate acquisition module is used to extract the data transmission rate of each transmission channel at the current moment;

[0145] The numerical value extraction module is used to screen out the maximum data transmission rate and the minimum data transmission rate corresponding to the transmission channel from the data transmission rates of each transmission channel at the current moment;

[0146] An adjustment coefficient acquisition module, configured to obtain an adjustment coefficient corresponding to each transmission channel by using the maximum data transmission rate and the minimum data transmission rate;

[0147] Wherein, the adjustment coefficient corresponding to each transmission channel is obtained by the following formula:

[0148] ;

[0149] Wherein, f represents the adjustment coefficient corresponding to each transmission channel; B max and B min respectively represent the maximum data transmission rate and the minimum data transmission rate; R represents the data transmission index factor corresponding to each transmission channel; B m01 represents the standard deviation of the data transmission rate corresponding to the moment of the maximum data transmission rate; B m02 represents the standard deviation of the data transmission rate corresponding to the moment of the minimum data transmission rate;

[0150] A comprehensive channel factor acquisition execution module, configured to obtain a comprehensive channel factor by using the adjustment coefficient corresponding to each transmission channel in combination with the data transmission index factor corresponding to each transmission channel;

[0151] Wherein, the comprehensive channel factor is obtained by the following formula:

[0152] ;

[0153] Wherein, S represents the comprehensive channel factor; m represents the total number of transmission channels; f i represents the adjustment coefficient corresponding to the i-th transmission channel; R i represents the data transmission index factor corresponding to the i-th transmission channel; R b represents the standard deviation of the data transmission index factors corresponding to m transmission channels.

[0154] The technical effects of the above technical solution are as follows: Through the data transmission index factor extraction module, the data transmission index factor corresponding to each transmission channel can be accurately obtained. This factor combines the historical performance and current state of the channel, providing an important basis for subsequent channel selection. The data transmission rate acquisition module can capture the data transmission rate of each transmission channel at the current moment in real time, which is crucial for dynamically adjusting the transmission strategy and optimizing resource allocation. The adjustment coefficient acquisition module calculates the adjustment coefficient for each transmission channel by considering the maximum and minimum values of the data transmission rate, as well as the standard deviation of the data transmission rates corresponding to these two moments. This design not only considers the rate performance of the channel but also the stability and fluctuation of the rate, enabling a more comprehensive evaluation of the actual performance of the channel. The comprehensive channel factor acquisition execution module combines the adjustment coefficient and the data transmission index factor to calculate the comprehensive channel factor through the above mathematical formula. This factor can reflect the overall performance and current state of each channel, providing strong support for the formulation of the data transmission strategy. By comparing the comprehensive channel factors of different channels, the channel with the optimal performance can be selected for data transmission, thereby maximizing the transmission efficiency and reliability. At the same time, according to the change of the channel factor, the transmission strategy can be dynamically adjusted to adapt to the change of the network environment. Each module and formula design in this technical solution has a certain degree of flexibility and adaptability, and can be adjusted and optimized according to different network environments, data volumes, and transmission requirements. This enables this technical solution to be widely applied to various scenarios requiring efficient data transmission and adapt to the changes of different network environments. By comprehensively considering the rate performance, stability, and fluctuation of the channel, this technical solution can select the channel with the optimal performance for data transmission, thereby reducing the risk of data loss and transmission errors and enhancing the security and stability of data transmission.

[0155] In summary, through means such as refined channel performance evaluation, real-time data rate monitoring, dynamic adjustment coefficient calculation, and comprehensive channel factor calculation, this technical solution realizes the optimization of the data transmission strategy and the improvement of system adaptability. These technical effects are of great significance for systems requiring efficient and reliable data transmission.

[0156] Specifically, the target length acquisition module includes:

[0157] The comprehensive channel factor extraction module is used to extract the comprehensive channel factor;

[0158] The data volume extraction module is used to extract the data volume corresponding to the current target toll vehicle data;

[0159] The historical data extraction module is used to extract the data volume corresponding to each target toll vehicle data in the historical transmission records of the data transmission module and the length of the corresponding data segment during the transmission process;

[0160] A target length acquisition execution module, configured to use the comprehensive channel factor and the data volume corresponding to the current target toll vehicle data, and combine the data volume corresponding to each target toll vehicle data in the historical transmission record of the data transmission module and the length of the corresponding data segment during its transmission to obtain the target length corresponding to the current target toll vehicle data when performing data transmission;

[0161] Among them, the target length corresponding to the current target toll vehicle data when performing data transmission is obtained through the following formula:

[0162] ;

[0163] Among them, K represents the target length corresponding to the current target toll vehicle data when performing data transmission; K0 represents the preset initial data segment length; S represents the comprehensive channel factor; k represents the number of data transmissions of the target toll vehicle data; C i represents the data volume corresponding to the i-th data transmission of the target toll vehicle data; C x represents the preset data volume reference value; K i represents the data segment length corresponding to the i-th data transmission of the target toll vehicle data; C0 represents the data volume corresponding to the current target toll vehicle data.

[0164] The technical effects of the above technical solution are as follows: The target length acquisition execution module accurately calculates the target length by using the above mathematical formula by comprehensively considering the channel factor, the data volume of the current target toll vehicle data, and relevant information in the historical transmission record. This calculation method takes into account the current state, historical performance of the channel, and the actual size of the data, so as to more accurately determine the optimal length of the data segment and improve the efficiency and reliability of data transmission. This technical solution can dynamically adjust the length of the data segment according to the change of the comprehensive channel factor to adapt to different channel conditions and data volume sizes. This adaptive data transmission strategy helps to optimize resource allocation, reduce waste and bottlenecks in the data transmission process, and improve the overall transmission efficiency. The historical data extraction module can extract the historical transmission records of the data transmission module, including the data volume corresponding to each target toll vehicle data and the length of the corresponding data segment during the transmission process. These historical data provide valuable reference information for the calculation of the current target length, which helps to more accurately predict and evaluate the transmission performance under different data volumes and channel conditions. Each module and formula design in this technical solution has a certain degree of flexibility and scalability. For example, parameters such as the preset initial data segment length and data volume reference value can be adjusted and optimized according to the actual situation. At the same time, this technical solution is also applicable to different scales and types of data transmission scenarios, with strong generality and adaptability. By accurately calculating the target length and optimizing the data transmission strategy, this technical solution can reduce errors and losses during data transmission and improve the stability and reliability of data transmission. This is of great significance for a toll vehicle data processing system that requires efficient and reliable data transmission. Through the adaptive data transmission strategy and accurate target length calculation, this technical solution can more effectively utilize network resources and reduce unnecessary waste and redundancy. This helps to reduce the cost of data transmission and improve the economic benefits of the system.

[0165] In summary, through means such as accurately calculating the target length, adopting an adaptive data transmission strategy, effectively using historical data, designing with flexibility and scalability, and improving the stability and reliability of data transmission, this technical solution realizes the optimization of data transmission efficiency and the maximization of resource utilization. These technical effects have very important practical application value for a toll vehicle data processing system that requires efficient and reliable data transmission.

[0166] The driving trajectory fitting module is used for:

[0167] The cloud native platform performs trajectory fitting after receiving the target toll vehicle data;

[0168] First, match the driving trajectory data in the target toll vehicle data with the highway road network, and match the vehicle's GPS points with the closest road segment by using the map matching algorithm;

[0169] The trajectory after matching is smoothed using Kalman filtering, and the physical laws of the smoothed trajectory are judged;

[0170] Finally, a spline curve is used to fit the matched trajectory. After the fitting is completed, the driving path of the vehicle on the highway is obtained and marked as vehicle guidance toll data.

[0171] Specifically, the cloud-native platform has powerful real-time data processing capabilities, can quickly receive and process a large amount of vehicle data, ensure the timeliness of trajectory fitting, and can be elastically expanded according to business needs to cope with the data processing pressure during peak periods, ensuring the stability and reliability of the system. Using a high-precision map matching algorithm, the GPS points of the vehicle are matched with the closest road segment, improving the accuracy of the trajectory. The matched trajectory is smoothed using Kalman filtering, effectively reducing noise and errors, and further improving the accuracy of the trajectory. The physical laws of the smoothed trajectory are judged, such as checking the rationality of parameters such as speed and acceleration, to ensure that the trajectory conforms to the actual driving situation. A spline curve is used to fit the matched trajectory, making the fitted trajectory smoother and more continuous, and better reflecting the actual driving path of the vehicle. After the fitting is completed, the driving path of the vehicle on the highway can be automatically marked as vehicle guidance toll data, reducing the workload of manual marking.

[0172] To solve the problem in the prior art that before a vehicle enters the ETC lane of a toll station, there is no targeted driving guidance according to the usage situation of the on-site ETC lane, resulting in inconvenient on-site traffic, please refer to Figure 1 and Figure 2 , this embodiment provides the following technical solutions:

[0173] The vehicle toll and guidance processing unit includes:

[0174] The vehicle guidance module is used for:

[0175] Pre-check the capacity of the ETC lanes of the highway toll station;

[0176] Among them, the toll station control center monitors the real-time vehicle data of the number of waiting vehicles in each ETC lane of the toll station;

[0177] And displays the monitored real-time vehicle data as the number of waiting vehicles on the display screen above each ETC lane;

[0178] Before the driving vehicle enters the ETC lane of the toll station, it makes an optimal choice according to the number of waiting vehicles displayed on the display screen above each ETC lane;

[0179] After the selection is completed, the vehicle queues up and enters through the ETC lane, and the number of waiting vehicles displayed on the display screen above each ETC lane and the scene at the toll station are transmitted to the display screen of the duty officer through a visual interface.

[0180] Specifically, the toll station control center monitors the number of waiting vehicles in each ETC lane in real time and displays the data on the display screen above each ETC lane in real time. Before entering the toll station, vehicles can make an optimal choice based on the number of waiting vehicles on the display screen, avoiding blind queuing and congestion. Vehicle owners can flexibly choose the ETC lane with fewer waiting vehicles according to the information on the display screen, thus speeding up the passing speed and reducing the overall waiting time. The toll station control center can accurately grasp the real-time vehicle data of each ETC lane, which helps to manage and allocate the toll station resources more precisely. Through the visual interface, the duty officer can intuitively see the load situation of each ETC lane and take timely measures for load balancing to avoid the situation where some lanes are overloaded while others are idle. Through cloud-native technology, the toll station control center can remotely monitor the operation of each ETC lane and discover and solve problems in a timely manner.

[0181] The ETC deduction module is used for:

[0182] When the vehicle travels to the ETC lane of the toll station, calculate the vehicle travel mileage according to the vehicle travel trajectory in the vehicle guidance toll data, and calculate the travel expenses according to the vehicle travel mileage;

[0183] When the vehicle passes through the ETC lane of the toll station, the ETC lane exchanges information on the deduction information with the ETC account information. The ETC account information sends the deduction information of the ETC lane to the online payment system, and the online payment system automatically deducts the fee through the ETC account information;

[0184] After the automatic deduction through the ETC account information, the deduction bill is sent to the vehicle owner through the online bank.

[0185] Specifically, when the vehicle passes through the ETC lane, the system can quickly identify the vehicle and complete the deduction without the vehicle decelerating or stopping, significantly improving the passing efficiency. Since the deduction process is fast and automated, it reduces the queuing waiting phenomenon caused by manual toll collection, thereby reducing the risk of traffic congestion. The entire deduction process is automatically completed by the system without manual intervention, reducing the management cost. Vehicle owners only need to pre-set the payment method in the ETC account to achieve automatic deduction without having to carry cash or perform additional payment operations. The deduction bill is sent to the vehicle owner through the online bank, enabling the vehicle owner to clearly understand the cost of each passage. The free-flow toll system for expressways based on cloud-native technology needs continuous technological innovation and upgrading to adapt to the changing traffic demands and technological environment.

[0186] It should be noted that, in this document, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device.

[0187] Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention.

Claims

1. A free-flow toll collection system for expressways based on cloud-native technology, characterized in that, Including: A vehicle information acquisition unit, which is used for: Confirming the real-time information and basic information of the vehicle, and obtaining standard vehicle information data after the confirmation is completed; A toll station information processing unit, which is used for: When the vehicle drives to the highway toll station, the toll station control center verifies the information of the driving vehicle according to the standard vehicle information data, and obtains target toll vehicle data after the information verification is qualified; A cloud-native platform data receiving and processing unit, which is used for: The toll station control center transmits the target toll vehicle data to the cloud-native platform, and the cloud-native platform performs trajectory fitting on the received target toll vehicle data, and obtains vehicle guidance toll data after the fitting is completed; A vehicle toll and guidance processing unit, which is used for: Guiding the vehicle to the corresponding ETC lane according to the vehicle guidance toll data, sending the deduction information to the online payment system for automatic deduction, and sending the deduction bill to the vehicle owner through the online bank after the automatic deduction; The cloud-native platform data receiving and processing unit includes: A data transmission module, which is used for: The toll station control center transmits the target toll vehicle data to the cloud-native platform after confirmation; The data transmission module further includes: A transmission rate real-time monitoring module, which is used for real-time monitoring the data transmission rate of each transmission channel; A data transmission index factor acquisition module, which is used for obtaining the data transmission index factor corresponding to each transmission channel according to the data transmission rate of each transmission channel; Wherein, the data transmission index factor corresponding to each transmission channel is obtained through the following formula: ； Wherein, R represents the data transmission index factor corresponding to each transmission channel; n represents the number of elapsed unit times during the operation corresponding to each transmission channel, and the unit time is 1 s; B i represents the data transmission rate corresponding to the i-th unit time of the transmission channel; B bi represents the standard deviation of the data transmission rate corresponding to the i-th unit time of the transmission channel; B bi-1 represents the standard deviation of the data transmission rate corresponding to the (i - 1)-th unit time of the transmission channel; B bmax represents the maximum value of the standard deviations of the data transmission rates among the n - 1 standard deviations of the data transmission rates generated when the transmission channel operates for n unit times; B n represents the data transmission rate at the current moment of the transmission channel.

2. The free-flow toll collection system for expressways based on cloud-native technology according to claim 1, characterized in that The vehicle information acquisition unit is further used for: An in-vehicle positioning device is set in the vehicle, and the in-vehicle positioning device is used for real-time acquiring the position data of the vehicle and generating driving trajectory data; The real-time information of the vehicle includes vehicle position data, driving trajectory data, license plate number, vehicle speed, timestamp and ETC device status. Among them, for trucks, it also includes the number of vehicle axles and vehicle weight; The basic information of the vehicle includes vehicle owner information, vehicle registration information, vehicle type, vehicle size, ETC account information, payment information and black / white list status; Standard vehicle information data is obtained after the confirmation of both the real-time information and basic information of the vehicle is completed.

3. The free-flow toll collection system for expressways based on cloud native technology according to claim 2, wherein, The toll station information processing unit is further used for: A signal acquisition device, a camera device and a weighbridge are set at the highway toll station. When the vehicle drives to the highway toll station, the signal acquisition device receives the standard vehicle information data; The camera device uses image recognition technology to extract the license plate number, vehicle type and vehicle size, and compares the extracted license plate number, vehicle type and vehicle size with the license plate number, vehicle type and vehicle size in the standard vehicle information data, and judges whether the license plate number, vehicle type and vehicle size are qualified according to the comparison result; Then, the ETC device status is checked, and it is judged whether the ETC device status is the activated state according to the check result; The driving trajectory data in the standard vehicle information data is compared with the data obtained at each toll station site, and it is judged whether the vehicle driving trajectory is legal according to the comparison result.

4. The free-flow toll collection system for expressways based on cloud native technology according to claim 3, characterized in that The toll station information processing unit is further used for: When the vehicle is a truck, the weighbridge at the highway toll station collects real-time data on the number of vehicle axles and the vehicle weight of the truck, and compares and judges the real-time collected data with the number of vehicle axles and the vehicle weight in the standard vehicle information data; Verify the rationality of the timestamp in the standard vehicle information data; Judge whether the vehicle is a blacklist vehicle according to the standard vehicle information data, and mark the blacklist vehicle as abnormal; After all verifications are completed and qualified, it is marked as target toll vehicle data; Prompt and manually guide the vehicles with abnormal verification.

5. The free-flow toll collection system for expressways based on cloud-native technology according to claim 4, characterized in that The data transmission module is also used for: When transmitting the target toll vehicle data, first confirm the data transmission volume of the target toll vehicle data; Among them, the data transmission volume is to divide the target toll vehicle data into several data segments with the same length, and confirm the data transmission volume of the target toll vehicle data according to the number of data segments; Then confirm the transmission channel between the toll station control center and the cloud native platform, where the transmission channel data is not less than 9; Confirm the remaining capacity of each transmission channel, and select the transmission channel of the target toll vehicle data according to the remaining capacity of the channel, where the remaining capacity of the channel is greater than the data transmission volume of the target toll vehicle data; When there are more than two transmission channels with the remaining capacity of the channel greater than the data transmission volume of the target toll vehicle data, select the one with the strongest signal strength among the multiple transmission channels as the transmission channel of the target toll vehicle data.

6. The free-flow toll collection system for expressways based on cloud native technology according to claim 5, wherein, The data transmission module also includes: The comprehensive channel factor acquisition module is used to obtain the comprehensive channel factor by combining the data transmission index factors corresponding to each transmission channel with the data transmission rate of each transmission channel at the current moment; The target length acquisition module is used to obtain the target length by combining the comprehensive channel factor with the data volume corresponding to the current target toll vehicle data; among them, the target length is the length corresponding to the data segment when dividing the target toll vehicle data.

7. The free-flow toll collection system for expressways based on cloud-native technology according to claim 6, wherein The comprehensive channel factor acquisition module includes: The data transmission index factor extraction module is used to extract the data transmission index factors corresponding to each transmission channel; The data transmission rate acquisition module is used to extract the data transmission rate of each transmission channel at the current moment; The value extraction module is used to screen out the maximum data transmission rate and the minimum data transmission rate corresponding to the transmission channel from the data transmission rates of each transmission channel at the current moment; The adjustment coefficient acquisition module is used to obtain the adjustment coefficient corresponding to each transmission channel by using the maximum data transmission rate and the minimum data transmission rate; Among them, the adjustment coefficient corresponding to each transmission channel is obtained through the following formula: ； Among them, f represents the adjustment coefficient corresponding to each transmission channel; B max and B min respectively represent the maximum data transmission rate and the minimum data transmission rate; R represents the data transmission index factor corresponding to each transmission channel; B m01 represents the standard deviation of the data transmission rate corresponding to the moment of the maximum data transmission rate; B m02 represents the standard deviation of the data transmission rate corresponding to the moment of the minimum data transmission rate; The comprehensive channel factor acquisition execution module is used to obtain the comprehensive channel factor by combining the adjustment coefficient corresponding to each transmission channel with the data transmission index factor corresponding to each transmission channel; Among them, the comprehensive channel factor is obtained through the following formula: ； Among them, S represents the comprehensive channel factor; m represents the total number of transmission channels; f i represents the adjustment coefficient corresponding to the i-th transmission channel; R i represents the data transmission index factor corresponding to the i-th transmission channel; R b represents the standard deviation of the data transmission index factors corresponding to the m transmission channels.

8. The free-flow toll collection system for expressways based on cloud-native technology according to claim 7, characterized in that The target length acquisition module includes: The comprehensive channel factor extraction module is used to extract the comprehensive channel factor; The data volume extraction module is used to extract the data volume corresponding to the current target toll vehicle data; A historical data extraction module, which is used to extract the data volume corresponding to each target toll vehicle data in the historical transmission records of the data transmission module and the length of the corresponding data segment during its transmission process; A target length acquisition execution module, which is used to utilize the comprehensive channel factor and the data volume corresponding to the current target toll vehicle data, and combine the data volume corresponding to each target toll vehicle data in the historical transmission records of the data transmission module and the length of the corresponding data segment during its transmission process to obtain the target length corresponding to the current target toll vehicle data when performing data transmission; Among them, the target length corresponding to the current target toll vehicle data when performing data transmission is obtained through the following formula: ； Among them, K represents the target length corresponding to the data transmission of the current target toll vehicle data; K0 represents the preset initial data segment length; S represents the comprehensive channel factor; k represents the number of data transmissions of the target toll vehicle data; C i represents the data volume corresponding to the data transmission of the target toll vehicle data for the i-th time; C x represents the preset data volume reference value; K i represents the data segment length corresponding to the data transmission of the target toll vehicle data for the i-th time; C0 represents the data volume corresponding to the current target toll vehicle data.

9. The free-flow toll collection system for expressways based on cloud native technology according to claim 8, wherein The cloud native platform data receiving and processing unit further includes: A driving trajectory fitting module, which is used for: The cloud native platform performs trajectory fitting after receiving the target toll vehicle data; First, match the driving trajectory data in the target toll vehicle data with the highway road network, and match the vehicle's GPS points with the closest road segments using the map matching algorithm; Perform smoothing processing on the matched trajectory using Kalman filtering, and perform physical law judgment on the smoothed trajectory; Finally, use a spline curve to fit the matched trajectory. After the fitting is completed, the driving path of the vehicle on the highway is obtained and marked as vehicle guidance toll data.

10. The free-flow toll collection system for expressways based on cloud native technology according to claim 9, characterized in that, The vehicle toll and guidance processing unit includes: A vehicle guidance module, which is used for: Perform capacity pre-inspection on the ETC lanes of the highway toll station; Among them, the toll station control center monitors the real-time vehicle data of the number of waiting vehicles in each ETC lane of the toll station; And display the monitored real-time vehicle data on the display screen above each ETC lane; Before the driving vehicle enters the ETC lane of the toll station, make an optimal selection according to the number of waiting vehicles displayed on the display screen above each ETC lane; After the selection is completed, the vehicle queues up and enters the ETC lane, and the number of waiting vehicles displayed on the display screen above each ETC lane and the scene of the toll station on-site are transmitted to the display screen of the duty personnel in a visual interface; An ETC deduction module, which is used for: When the driving vehicle reaches the ETC lane of the toll station, calculate the vehicle travel mileage according to the vehicle driving trajectory in the vehicle guidance toll data, and calculate the travel cost according to the vehicle travel mileage; When the vehicle passes through the ETC lane of the toll station, the ETC lane exchanges the deduction information with the ETC account information, and the ETC account information sends the deduction information of the ETC lane to the online payment system, and the online payment system performs automatic deduction through the ETC account information; After the ETC account information performs automatic deduction, the deduction bill is sent to the vehicle owner through the online bank.

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