Vehicle free flow tolling system and vehicle free flow tolling method
By receiving traffic management data from multiple sources, analyzing vehicle type, travel time, and trajectory, the system automatically calculates and deducts the amount due, solving the problem of low traffic efficiency caused by physical toll stations and achieving contactless payment and accurate billing.
Patent Information
- Application Number
- CN202611325011.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-08-28
- Publication Date
- 2026-11-06
AI Technical Summary
In existing technologies, physical toll booths result in extremely low road traffic efficiency, which is especially noticeable during periods of poor network conditions or peak travel times such as holidays.
The system receives multi-source traffic management data through a sensing module, analyzes the vehicle type, travel time, and travel trajectory, processes the data to be paid, and automatically deducts the fee, achieving contactless payment and avoiding physical toll booths.
It has improved road traffic efficiency, enabled contactless payment, reduced the possibility of vehicles evading tolls through improper means such as using fake license plates, and improved the fairness and rationality of toll collection.
Smart Images
Figure CN123052840A_ABST
Abstract
Description
Technical Field
[0001] This application belongs to the field of intelligent transportation technology, and in particular relates to a vehicle free-flow tolling system and a vehicle free-flow tolling method. Background Technology
[0002] To implement toll management on highways, national roads, and provincial roads, physical toll stations are usually added at road junctions. By identifying information from the vehicle's on-board unit (such as OBU), the vehicle's mileage is obtained, the vehicle's travel cost is calculated, and then the travel cost is collected through an interactive process.
[0003] However, due to objective factors such as network conditions and peak travel periods during holidays, setting up physical toll booths to collect vehicle fees can easily lead to queuing and congestion, resulting in extremely low traffic efficiency. Summary of the Invention
[0004] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application proposes a vehicle free-flow toll collection system and method to solve the problem of extremely low road traffic efficiency caused by physical toll stations.
[0005] Firstly, this application provides a vehicle free-flow toll collection system, including: The sensing module is used to receive multi-source traffic management data collected from various traffic control points; The analysis module is used to perform analysis operations on multi-source traffic management data to obtain the target vehicle's type, travel time, and travel trajectory between different traffic control points; The processing module is used to obtain the amount payable by the target vehicle based on the vehicle type, the time period of passage, and the passage trajectory. The deduction module is used to perform deduction operations on the target account linked to the target vehicle based on the amount due.
[0006] According to the free-flow toll collection method for vehicles in this application, the analysis module performs analysis operations on the multi-source traffic management data collected at each traffic control point to obtain the vehicle type, travel time, and travel trajectory between different traffic control points. The processing module then obtains the amount payable for the vehicle based on the vehicle type, travel time, and travel trajectory. Finally, the deduction module automatically deducts the fee from the target account linked to the vehicle. This eliminates the need for physical toll stations, automatically calculates the toll for the vehicle based on the vehicle type, travel time, and travel trajectory, and automatically pays the fee using only the target account linked to the vehicle, achieving seamless payment for vehicle passage and improving traffic efficiency.
[0007] According to one embodiment of this application, the multi-source traffic management data includes at least video stream data, radar data, positioning data, and image data; the analysis module includes: The data parsing unit is used to obtain the vehicle's license plate information and appearance features based on image data, and to obtain the vehicle's model based on radar data, for the current traffic control point; the current traffic control point can be any one of the traffic control points. The comparison unit is used to determine whether a vehicle is the target vehicle based on license plate information, appearance features, and vehicle model; the target vehicle is the vehicle that was detected at the previous intersection adjustment point. The generation unit is used to obtain the travel trajectory of the target vehicle based on the positioning data of the current traffic control point and the previous traffic control point when the vehicle is the target vehicle, and to obtain the travel time period based on the time information of the target vehicle passing through the previous traffic control point and the time information of passing through the current traffic control point.
[0008] According to one embodiment of this application, the processing module includes: The processing unit is used to obtain the travel mileage based on the travel trajectory, obtain the vehicle type coefficient based on the vehicle type, and obtain the time period coefficient based on the travel time period; The determination unit is used to determine the amount payable by the target vehicle by multiplying the toll mileage, the basic cost per kilometer, the vehicle type coefficient, and the time period coefficient.
[0009] According to one embodiment of this application, the system further includes: The acquisition module is used to obtain the travel path of the target vehicle based on the travel trajectory of the target vehicle between different traffic control points; The audit module is used to detect the driving path and trigger the audit process when the detection results indicate that the target vehicle has detoured.
[0010] According to one embodiment of this application, the system further includes: The interaction module is used to obtain the driver's personal information, vehicle information, and account information for each driver. The registration module is used to perform the binding operation between drivers, vehicles, and accounts based on personal information, vehicle information, and account information.
[0011] Secondly, this application provides a method for toll collection for free-flowing vehicles, including: Receive multi-source traffic management data collected from various traffic control points; Perform analysis on multi-source traffic management data to obtain the vehicle type, travel time, and travel trajectory between different traffic control points of the target vehicle; Based on vehicle type, time of day, and travel route, obtain the amount payable for the target vehicle; Based on the amount due, deduct the fee from the target account linked to the target vehicle.
[0012] According to the free-flow toll collection method for vehicles in this application, by analyzing multi-source traffic management data collected from various traffic control points, the vehicle type, travel time, and travel trajectory between different traffic control points of the target vehicle are obtained. Based on the vehicle type, travel time, and travel trajectory, the amount payable for the target vehicle is obtained, and the toll is automatically deducted from the target account bound to the target vehicle. There is no need to set up physical toll stations. The toll collection for the target vehicle is completed automatically based on the vehicle type, travel time, and travel trajectory, and the payment is made automatically solely based on the target account bound to the target vehicle, realizing contactless payment for the target vehicle's passage and improving traffic efficiency.
[0013] According to one embodiment of this application, multi-source traffic management data includes at least video stream data, radar data, positioning data, and image data; performing analysis operations on the multi-source traffic management data to obtain the target vehicle's vehicle type, travel time period, and travel trajectory between different traffic control points includes: For the current traffic adjustment point, the vehicle's license plate information and appearance features are obtained based on image data, and the vehicle model is obtained based on radar data; the current traffic adjustment point can be any one of the traffic adjustment points. Based on license plate information, appearance features, and vehicle model, determine whether the vehicle is the target vehicle; the target vehicle is the vehicle that was detected at the previous traffic control point. When the vehicle is the target vehicle, the travel trajectory of the target vehicle is obtained based on the positioning data of the current traffic control point and the previous traffic control point, and the travel time period is obtained based on the time information of the target vehicle passing through the previous traffic control point and the time information of passing through the current traffic control point.
[0014] According to one embodiment of this application, the amount payable by the target vehicle is obtained based on vehicle type, time period, and travel route, including: The mileage is obtained based on the travel trajectory, the vehicle type coefficient is obtained based on the vehicle type, and the time period coefficient is obtained based on the travel time period; The product of the toll mileage, the basic cost per kilometer, the vehicle type coefficient, and the time period coefficient is used to determine the amount payable for the target vehicle.
[0015] According to one embodiment of this application, after performing analysis operations on multi-source traffic management data to obtain the target vehicle's vehicle type, travel time period, and travel trajectory between different traffic control points, the method further includes: Based on the travel trajectory of the target vehicle between different traffic control points, the driving path of the target vehicle is obtained; The driving path is detected, and the audit process is triggered if the detection results indicate that the target vehicle is taking a detour.
[0016] According to one embodiment of this application, before performing analysis operations on multi-source traffic management data to obtain the vehicle type, travel time period, and travel trajectory between different traffic control points of the target vehicle, the method includes: For each driver, obtain the driver's personal information, vehicle information, and account information; Based on personal information, vehicle information, and account information, perform the binding operation between the driver, vehicle, and account.
[0017] Thirdly, this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the vehicle free-flow tolling method described in the second aspect.
[0018] Fourthly, this application provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the vehicle free-flow tolling method described in the second aspect.
[0019] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the vehicle free-flow tolling method described in the second aspect.
[0020] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description
[0021] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a schematic diagram of the structure of the vehicle free-flow toll collection system provided in the embodiments of this application; Figure 2 This is a schematic flowchart of the vehicle free-flow toll collection method provided in the embodiments of this application; Figure 3 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation
[0022] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.
[0023] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.
[0024] The following description, in conjunction with the accompanying drawings, details the vehicle free-flow toll collection system, vehicle free-flow toll collection method, electronic equipment, and storage medium provided in this application through specific embodiments and application scenarios.
[0025] Among them, the vehicle free-flow toll collection method can be applied to the terminal, which can be executed by the hardware or software in the terminal.
[0026] The terminal includes, but is not limited to, portable communication devices such as mobile phones or tablets with touch-sensitive surfaces (e.g., touchscreen displays and / or touchpads). It should also be understood that, in some embodiments, the terminal may not be a portable communication device, but rather a desktop computer with touch-sensitive surfaces (e.g., touchscreen displays and / or touchpads).
[0027] The following embodiments describe a terminal including a display and a touch-sensitive surface. However, it should be understood that the terminal may include one or more other physical user interface devices such as a physical keyboard, mouse, and joystick.
[0028] This application provides a vehicle free-flow toll collection system, which can be deployed on edge devices in highways, national roads, provincial roads, or any theoretically feasible road scenarios.
[0029] In some embodiments, such as Figure 1 As shown, the vehicle free-flow toll collection system 100 includes: The sensing module 110 is used to receive multi-source traffic management data collected from each traffic control point; The analysis module 120 is used to perform analysis operations on multi-source traffic management data to obtain the vehicle type, travel time, and travel trajectory between different traffic control points of the target vehicle. Processing module 130 is used to obtain the amount payable by the target vehicle based on vehicle type, time period of passage, and passage trajectory; The deduction module 140 is used to perform deduction operations on the target account bound to the target vehicle based on the amount payable.
[0030] In some embodiments, the sensing module can be communicatively connected to each of the various traffic control points. Each traffic control point can be equipped with video surveillance equipment, radar, image acquisition equipment (e.g., cameras), and positioning equipment (e.g., BeiDou high-precision positioning equipment). The sensing module can be used to receive video stream data collected by the video surveillance equipment at each traffic control point. The video stream data includes the entire passage process and panoramic images of each vehicle among several vehicles passing through the traffic control point. The sensing module can also be used to receive radar data for each vehicle collected by the radar at each traffic control point, and image data for each vehicle collected by the image acquisition equipment. The image data includes license plate information and appearance information.
[0031] In some embodiments, after receiving multi-source traffic management data collected from various traffic control points, the sensing module can perform at least one of the following operations on the multi-source traffic management data: quality verification, time synchronization, and standardization. Quality verification includes deduplication, error correction, and data completion. Time synchronization is used to unify the timestamp reference between different traffic control points and between different acquisition devices at the same traffic control point.
[0032] In some embodiments, for each type of multi-source traffic management data, the analysis module can perform analysis operations on the video stream data in the multi-source traffic management data to obtain the passage video data of each vehicle; based on deep learning algorithms, it can identify the image data in the multi-source traffic management data to obtain the license plate information and appearance features of each vehicle; and it can perform analysis operations on the radar data in the multi-source traffic management data to obtain the vehicle type of each vehicle, such as small passenger cars, medium-sized trucks, large trucks, and special vehicles. Based on the passage video data, license plate information, vehicle type, and appearance features of vehicles obtained from different traffic control points, it can determine whether vehicles passing through different traffic control points are the same vehicle. If vehicles passing through different traffic control points are the same vehicle, the vehicle is identified as the target vehicle to prevent vehicles from evading tolls through methods such as using cloned license plates or modifications.
[0033] In some embodiments, for a target vehicle, the analysis module can be used to obtain the vehicle's model, travel time, and travel trajectory between different traffic control points based on video stream data, radar data, positioning data, and image data collected from different traffic control points.
[0034] In some embodiments, the analysis module can be used to form a chain of payment evidence for the target vehicle based on the vehicle's travel trajectory between different traffic control points, thereby enhancing the road toll management capability.
[0035] In some embodiments, for a target vehicle, the driver's target vehicle and target account can be bound based on the target vehicle's license plate information and the driver's account information. A target vehicle can be bound to at least one target account.
[0036] In some embodiments, the target account may be a mobile payment platform account registered and held by the driver of the target vehicle, such as WeChat, Alipay, UnionPay QuickPass, or any theoretically feasible account. This application does not specifically limit this.
[0037] In some embodiments, the deduction module can be used to obtain the credit score of the driver corresponding to the target vehicle, and determine the deduction method for performing the deduction operation based on the credit score.
[0038] In some embodiments, the deduction module can be used to directly deduct fees from the target account linked to the target vehicle based on the amount due, when the credit score of the driver corresponding to the target vehicle is greater than or equal to the credit threshold, without requiring manual confirmation from the vehicle owner, thus achieving "payment upon passage, seamless passage". Alternatively, if the credit score of the driver corresponding to the target vehicle is less than the credit threshold, the deduction module can obtain an estimated payment amount based on historical deduction records and deduct fees from the target account linked to the target vehicle based on the estimated payment amount. After obtaining the amount due, if the amount due is greater than the estimated payment amount, the module will deduct fees from the target account again based on the difference between the amount due and the estimated payment amount. If the amount due is less than the estimated payment amount, a refund will be issued to the target account based on the difference between the estimated payment amount and the amount due.
[0039] According to the vehicle free-flow toll collection system of this application, the analysis module performs analysis operations on the multi-source traffic management data collected from various traffic control points to obtain the vehicle type, travel time, and travel trajectory between different traffic control points. The processing module obtains the amount payable by the target vehicle based on the vehicle type, travel time, and travel trajectory. Then, the deduction module automatically performs the deduction operation on the target account bound to the target vehicle. Without setting up physical toll stations, the system automatically completes the toll calculation for the target vehicle based on the vehicle type, travel time, and travel trajectory, and automatically pays the toll based solely on the target account bound to the target vehicle, realizing seamless payment for the target vehicle's passage and improving traffic efficiency.
[0040] In some embodiments, multi-source traffic management data includes at least video stream data, radar data, positioning data, and image data; the analysis module includes: The data parsing unit is used to obtain the vehicle's license plate information and appearance features based on image data, and to obtain the vehicle's model based on radar data, for the current traffic control point; the current traffic control point can be any one of the traffic control points. The comparison unit is used to determine whether a vehicle is the target vehicle based on license plate information, appearance features, vehicle model, and driver facial features; the target vehicle is the vehicle that was detected at the previous intersection control point. The generation unit is used to obtain the travel trajectory of the target vehicle based on the positioning data of the current traffic control point and the previous traffic control point when the vehicle is the target vehicle, and to obtain the travel time period based on the time information of the target vehicle passing through the previous traffic control point and the time information of passing through the current traffic control point.
[0041] In some embodiments, the data parsing unit can be used to identify the image data of the current intersection point based on a deep learning algorithm, and obtain the vehicle's license plate information and appearance features to avoid the effects of strong light suppression, rain and fog penetration, and low illumination at night.
[0042] In practice, license plate information includes the license plate number and the color of the vehicle. Exterior features include at least the vehicle color and the number of axles.
[0043] In some embodiments, the data parsing unit can be used to acquire the outer contour of a vehicle based on radar data, and to determine the vehicle type based on the outer contour and the number of axles, such as a small passenger car, a medium-sized truck, a large truck, or a special vehicle (e.g., an ambulance, a police car).
[0044] In some embodiments, for any vehicle passing through the current traffic control point, the comparison unit can be used to match and compare the vehicle's license plate information, appearance features, and vehicle model with the license plate information, appearance features, vehicle model, and driver facial features of the target vehicle detected at the previous traffic control point, respectively, to determine whether the vehicle is the target vehicle.
[0045] In some embodiments, for any vehicle passing through the current traffic control point, the comparison unit can be used to determine whether the vehicle is the target vehicle if at least two of the vehicle's license plate information, appearance features, and vehicle model are the same as the target vehicle detected at the previous traffic control point.
[0046] In some embodiments, for any vehicle passing through the current traffic control point, the comparison unit can be used to determine that the vehicle is not the target vehicle if the vehicle's license plate information, appearance features, and model are all different from the target vehicle detected at the previous traffic control point.
[0047] In some embodiments, the generating unit may be used to determine the passage period of the target vehicle based on the timestamp of the target vehicle detected in the video stream data of the current intersection point and the timestamp of the target vehicle detected in the video stream data of the previous intersection point.
[0048] According to the vehicle free-flow toll collection system of this application embodiment, for the current traffic control point, the system obtains the vehicle's license plate information and appearance features based on image data, and obtains the vehicle's model based on radar data; the current traffic control point can be any of the traffic control points; based on the license plate information, appearance features, and model, it determines whether the vehicle is the target vehicle; the target vehicle is the vehicle detected at the previous traffic control point; if the vehicle is the target vehicle, based on the positioning data of the current traffic control point and the previous traffic control point, the system obtains the target vehicle's travel trajectory, and based on the time information of the target vehicle passing through the previous traffic control point and the time information of passing through the current traffic control point, it obtains the travel time period, and based on the model, travel time period, and travel trajectory, it obtains the amount payable by the target vehicle. By comprehensively considering the license plate information, appearance features, and model, the system matches and determines the vehicle, reducing the possibility of vehicles maliciously evading tolls through single improper means such as using cloned license plates.
[0049] In some embodiments, the processing module includes: The processing unit is used to obtain the travel mileage based on the travel trajectory, obtain the vehicle type coefficient based on the vehicle type, and obtain the time period coefficient based on the travel time period; The determination unit is used to determine the amount payable by the target vehicle by multiplying the toll mileage, the basic cost per kilometer, the vehicle type coefficient, and the time period coefficient.
[0050] In some embodiments, the processing unit can be used to pre-store the vehicle model coefficient corresponding to each vehicle type, for example, the vehicle model coefficient for a small passenger car is 1.0, the vehicle model coefficient for a medium-sized truck is 1.5, the vehicle model coefficient for a large truck is 2.0, and the vehicle model coefficient for a special vehicle is 0. The processing unit can be used to obtain the vehicle model coefficient corresponding to the target vehicle based on the vehicle type of the target vehicle.
[0051] In some embodiments, the processing unit can be used to pre-store time period coefficients corresponding to different time periods, for example, the time period coefficient for 22:00-6:00 at night is 0.8, and the time period coefficient for 0:00 on October 1st to 23:59 on October 7th is 0.7. The processing unit can be used to obtain the time period coefficient based on the passage time of the target vehicle.
[0052] In some embodiments, the determining unit may be used to determine the amount payable by the target vehicle between adjacent traffic control points by multiplying the toll mileage, the basic cost per kilometer, the vehicle type coefficient, and the time period coefficient, and to determine the total amount payable by the target vehicle by summing the amounts payable at all traffic control points traversed by the target vehicle.
[0053] According to the vehicle free-flow toll system of this application embodiment, by performing analysis operations on multi-source traffic management data collected from various traffic control points, the system obtains the vehicle type, travel time, and travel trajectory between different traffic control points of the target vehicle. Based on the travel trajectory, the system obtains the travel mileage, the vehicle type coefficient, and the travel time coefficient. The product of the travel mileage, the basic fee per kilometer, the vehicle type coefficient, and the travel time coefficient is determined as the amount payable for the target vehicle. The system automatically performs a deduction operation on the target account bound to the target vehicle. By dynamically generating the amount payable based on the vehicle type, travel time, and travel trajectory, the system achieves a leap from a "one-size-fits-all" fixed toll to precise metered toll, improving the fairness and rationality of toll collection.
[0054] In some embodiments, the vehicle free-flow toll system may further include: The acquisition module is used to obtain the travel path of the target vehicle based on the travel trajectory of the target vehicle between different traffic control points; The audit module is used to detect the driving path and trigger the audit process when the detection results indicate that the target vehicle has detoured.
[0055] In some embodiments, the acquisition module can be used to stitch together the travel trajectory of the target vehicle between different traffic control points based on the BIM model to obtain the driving path of the target vehicle.
[0056] In some embodiments, the audit module can be used to mark the target vehicle as abnormal when the detection results of the target vehicle's driving path indicate that the target vehicle has detour behavior, deduct the credit score of the driver corresponding to the target vehicle, generate abnormal alarm information based on the target vehicle's license plate information and driving path, and broadcast the abnormal alarm information to the management platform for fee recovery.
[0057] According to the vehicle free-flow toll collection system of this application embodiment, by performing analysis operations on multi-source traffic management data collected from various traffic control points, the system obtains the vehicle type, travel time period, and travel trajectory between different traffic control points of the target vehicle. Based on the travel trajectory between different traffic control points of the target vehicle, the system obtains the driving path of the target vehicle. The system detects the driving path and, if the detection result indicates that the target vehicle has detoured, triggers the audit process, thereby effectively solving the audit problem of detour toll evasion and achieving full collection of tolls due.
[0058] In some embodiments, the vehicle free-flow toll system may further include: The interaction module is used to obtain the driver's personal information, vehicle information, and account information for each driver. The registration module is used to perform the binding operation between drivers, vehicles, and accounts based on personal information, vehicle information, and account information.
[0059] In some embodiments, the interaction module can be used to query whether a target vehicle has a corresponding target account based on the target vehicle's license plate information. If no target account exists, the driver can be guided to complete the binding process via SMS, mini-program push notifications, information board prompts, or other means.
[0060] In some embodiments, personal information may include an identity card number, a mobile device's communication number, and facial features.
[0061] According to the vehicle free-flow toll collection system of this application embodiment, for each driver, the system obtains the driver's personal information, vehicle information, and account information; based on the personal information, vehicle information, and account information, it performs a binding operation between the driver, vehicle, and account. By performing analysis operations on multi-source traffic management data collected from various traffic control points, the system obtains the target vehicle's vehicle type, travel time, and travel trajectory between different traffic control points. Based on the vehicle type, travel time, and travel trajectory, the system obtains the amount payable for the target vehicle and automatically performs a deduction operation on the target account bound to the target vehicle. Without setting up physical toll stations, the system automatically completes the toll calculation for the target vehicle based on the vehicle type, travel time, and travel trajectory, and automatically pays the toll using only the target account bound to the target vehicle, achieving seamless payment for the target vehicle's passage and improving traffic efficiency.
[0062] The vehicle free-flow tolling method provided in this application embodiment can be executed by an electronic device or a functional module or entity in an electronic device that can implement the vehicle free-flow tolling method. The electronic devices mentioned in this application embodiment include, but are not limited to, mobile phones, tablets, computers, cameras, and wearable devices. The vehicle free-flow tolling method provided in this application embodiment will be described below using an electronic device as the execution subject as an example.
[0063] In some embodiments, the vehicle free-flow tolling method in this application can be executed by an edge device, which can be deployed on highways, national roads, provincial roads or any theoretically feasible road scenario, which includes several traffic control points.
[0064] like Figure 2 As shown, the free-flow toll collection method for vehicles includes steps 210, 220, 230, and 240.
[0065] Step 210: Receive multi-source traffic management data collected from each traffic control point.
[0066] In some embodiments, multi-source traffic management data collected by each traffic control point can be received in real time. The multi-source traffic management data includes at least video stream data, radar data, positioning data, and image data.
[0067] In some embodiments, each interchange can be equipped with video surveillance equipment, radar, image acquisition equipment (e.g., cameras), and positioning equipment (e.g., BeiDou high-precision positioning equipment). The system can receive video stream data acquired by the video surveillance equipment at each interchange, including the entire passage process and panoramic images of each vehicle among several vehicles passing through that interchange. It can also receive radar data for each vehicle acquired by the radar at each interchange, and image data for each vehicle acquired by the image acquisition equipment, including license plate information and appearance information.
[0068] In some embodiments, after receiving multi-source traffic management data collected from various traffic control points, at least one of the following operations can be performed on the multi-source traffic management data: quality verification, time synchronization, and standardization. Quality verification includes deduplication, error correction, and data completion. Time synchronization is used to unify the timestamp reference between different traffic control points and between different acquisition devices at the same traffic control point.
[0069] Step 220: Perform analysis on the multi-source traffic management data to obtain the target vehicle's vehicle type, travel time, and travel trajectory between different traffic control points.
[0070] In some embodiments, for each multi-source traffic management data set, analysis operations can be performed on the video stream data to obtain the passage video data of each vehicle; based on deep learning algorithms, image data in the multi-source traffic management data can be identified to obtain the license plate information and appearance features of each vehicle; analysis operations can be performed on the radar data in the multi-source traffic management data to obtain the vehicle type, such as small passenger cars, medium-sized trucks, large trucks, and special vehicles. Based on the passage video data, license plate information, vehicle type, and appearance features of vehicles obtained from different traffic control points, it can be determined whether vehicles passing through different traffic control points are the same vehicle. If the vehicles passing through different traffic control points are the same vehicle, that vehicle is identified as the target vehicle to prevent vehicles from evading tolls through methods such as using cloned license plates or modifications.
[0071] In some embodiments, for a target vehicle, based on video stream data, radar data, positioning data, and image data of the target vehicle collected at different traffic control points, the vehicle type, travel time period, and travel trajectory between different traffic control points are obtained.
[0072] In some embodiments, a chain of payment evidence for the target vehicle can be formed based on the vehicle's travel trajectory between different traffic control points, thereby enhancing the road toll management capability.
[0073] Step 230: Based on vehicle type, time period, and travel route, obtain the amount payable for the target vehicle.
[0074] In some embodiments, the amount payable by the target vehicle can be dynamically obtained based on the vehicle type, time of day, and route, so as to implement charging strategies such as overweight surcharges and discounts for nighttime or holiday use.
[0075] Step 240: Based on the amount payable, perform a deduction operation on the target account linked to the target vehicle.
[0076] In some embodiments, for a target vehicle, the driver's target vehicle and target account can be bound based on the target vehicle's license plate information and the driver's account information. A target vehicle can be bound to at least one target account.
[0077] In some embodiments, the target account may be a mobile payment platform account registered and held by the driver of the target vehicle, such as WeChat, Alipay, UnionPay QuickPass, or any theoretically feasible account. This application does not specifically limit this.
[0078] In some embodiments, the credit score of the driver corresponding to the target vehicle can be obtained, and the deduction method for performing the deduction operation can be determined based on the credit score.
[0079] In some embodiments, if the credit score of the driver corresponding to the target vehicle is greater than or equal to the credit threshold, the toll is deducted directly from the target account linked to the target vehicle based on the amount due, without requiring manual confirmation from the vehicle owner, achieving "payment upon passage, seamless passage". If the credit score of the driver corresponding to the target vehicle is less than the credit threshold, an estimated payment amount is obtained based on historical deduction records, and a deduction is made from the target account linked to the target vehicle based on the estimated payment amount. After obtaining the amount due, if the amount due is greater than the estimated payment amount, a deduction is made again from the target account based on the difference between the amount due and the estimated payment amount. If the amount due is less than the estimated payment amount, a refund is made to the target account based on the difference between the estimated payment amount and the amount due.
[0080] In some embodiments, after performing a deduction operation on the target account bound to the target vehicle, a deduction detail can be generated based on the target vehicle's model, travel time, travel route, amount due, and electronic invoice link, and sent based on the target interaction method. The target interaction method can be a mini-program push, SMS, WeChat service notification, email, or any theoretically feasible interaction method.
[0081] In some embodiments, the deduction details can be stored based on blockchain evidence storage technology. Upon receiving a complaint request from a driver, the deduction details corresponding to the complaint request are queried, and a review operation is performed on the deduction details. If the review result indicates that the deduction is incorrect, a refund or supplementary payment operation can be performed.
[0082] In some embodiments, abnormal traffic events (such as pedestrian intrusion, vehicle accidents, illegal lane changes, and overloading) can be monitored on the video stream data for each intersection adjustment point. When an abnormal traffic event is detected, the corresponding vehicle is marked as an abnormal vehicle and a linkage alarm is triggered to form an electronic fence and improve the level of road safety management.
[0083] According to the vehicle free-flow tolling method of this application embodiment, by performing analysis operations on multi-source traffic management data collected from various traffic control points, the vehicle type, travel time, and travel trajectory between different traffic control points of the target vehicle are obtained. Based on the vehicle type, travel time, and travel trajectory, the amount payable by the target vehicle is obtained, and the toll is automatically deducted from the target account bound to the target vehicle. Without setting up physical toll stations, the method automatically calculates the toll for the target vehicle based on the vehicle type, travel time, and travel trajectory, and automatically pays the toll based solely on the target account bound to the target vehicle, realizing contactless payment for the target vehicle's passage and improving traffic efficiency.
[0084] In some embodiments, multi-source traffic management data includes at least video stream data, radar data, positioning data, and image data; for the current traffic control point, the vehicle's license plate information and appearance features are obtained based on the image data, and the vehicle's model is obtained based on the radar data; the current traffic control point can be any one of the traffic control points; based on the license plate information, appearance features, and vehicle model, it is determined whether the vehicle is the target vehicle; the target vehicle is a vehicle that was detected at the previous traffic control point; if the vehicle is the target vehicle, the target vehicle's travel trajectory is obtained based on the positioning data of the current traffic control point and the previous traffic control point, and the travel time period is obtained based on the time information of the target vehicle passing through the previous traffic control point and the time information of passing through the current traffic control point.
[0085] In some embodiments, deep learning algorithms can be used to identify the image data of the current intersection point to obtain the vehicle's license plate information and appearance features, thereby avoiding the effects of strong light suppression, rain and fog penetration, and low nighttime illumination.
[0086] In practice, license plate information includes the license plate number and the color of the vehicle. Exterior features include at least the vehicle color and the number of axles.
[0087] In some embodiments, the vehicle's outer contour can be obtained based on radar data, and the vehicle type can be determined based on the outer contour and the number of axles, such as a small passenger car, a medium-sized truck, a large truck, or a special vehicle (e.g., an ambulance, a police car).
[0088] In some embodiments, for any vehicle passing through the current traffic control point, the license plate information, appearance features, and vehicle model of that vehicle can be matched and compared with the license plate information, appearance features, and vehicle model of the target vehicle detected at the previous traffic control point to determine whether the vehicle is the target vehicle.
[0089] In some embodiments, for any vehicle passing through the current traffic control point, it can be determined whether the vehicle is the target vehicle if at least two of its license plate information, appearance features, and vehicle model are the same as the target vehicle detected at the previous traffic control point.
[0090] In some embodiments, for any vehicle passing through the current traffic control point, if the vehicle's license plate information, appearance features, and model are different from the target vehicle detected at the previous traffic control point, it can be determined that the vehicle is not the target vehicle.
[0091] In some embodiments, for any vehicle passing through the current traffic control point, if it is determined that the vehicle is not the target vehicle, the license plate information, appearance features and vehicle model of the vehicle can be compared with the license plate information, appearance features and vehicle model of the target vehicle detected at the previous traffic control point, based on manual comparison, to confirm whether the vehicle is the target vehicle again.
[0092] In some embodiments, the passage time of a target vehicle can be determined based on the timestamp of the target vehicle detected in the video stream data of the current traffic control point and the timestamp of the target vehicle detected in the video stream data of the previous traffic control point.
[0093] According to the vehicle free-flow toll collection method of this application embodiment, for the current traffic control point, the vehicle's license plate information and appearance features are obtained based on image data, and the vehicle model is obtained based on radar data; the current traffic control point can be any of the traffic control points; based on the license plate information, appearance features, and vehicle model, it is determined whether the vehicle is the target vehicle; the target vehicle is the vehicle detected at the previous traffic control point; if the vehicle is the target vehicle, the target vehicle's travel trajectory is obtained based on the positioning data of the current traffic control point and the previous traffic control point, and the travel time period is obtained based on the time information of the target vehicle passing through the previous traffic control point and the time information of passing through the current traffic control point, and the toll amount of the target vehicle is obtained based on the vehicle model, travel time period, and travel trajectory, and the vehicle is matched and determined by comprehensively considering the license plate information, appearance features, and vehicle model, to prevent vehicles from maliciously escaping toll collection by improper means such as using cloned license plates during driving.
[0094] In some embodiments, the mileage is obtained based on the travel trajectory, the vehicle type coefficient is obtained based on the vehicle type, and the time period coefficient is obtained based on the travel time period; the product of the mileage, the basic cost per kilometer, the vehicle type coefficient, and the time period coefficient is determined as the amount payable by the target vehicle.
[0095] In some embodiments, vehicle model coefficients for each type of vehicle can be pre-stored. For example, the vehicle model coefficient for a small passenger car is 1.0, for a medium-sized truck it is 1.5, for a large truck it is 2.0, and for a special vehicle it is 0. The vehicle model coefficient corresponding to the target vehicle is obtained based on the target vehicle's vehicle model.
[0096] In some embodiments, time period coefficients corresponding to different time periods can be pre-stored. For example, the time period coefficient for 22:00-6:00 at night is 0.8, and the time period coefficient for 0:00 on October 1st to 23:59 on October 7th is 0.7. The time period coefficient is obtained based on the travel time of the target vehicle.
[0097] In some embodiments, the product of the toll mileage, the basic cost per kilometer, the vehicle type coefficient, and the time period coefficient is determined as the amount payable by the target vehicle between adjacent traffic control points, and the sum of the amounts payable by the target vehicle at all traffic control points it passes through is determined as the total amount payable by the target vehicle.
[0098] According to the vehicle free-flow tolling method in this application, by performing analysis operations on multi-source traffic management data collected from various traffic control points, the vehicle type, travel time, and travel trajectory between different traffic control points of the target vehicle are obtained. The travel mileage is obtained based on the travel trajectory, the vehicle type coefficient is obtained based on the vehicle type, and the time period coefficient is obtained based on the travel time. The product of the travel mileage, the basic cost per kilometer, the vehicle type coefficient, and the time period coefficient is determined as the amount payable for the target vehicle. The toll is automatically deducted from the target account bound to the target vehicle. The amount payable is dynamically generated by comprehensively considering the vehicle type, travel time, and travel trajectory of the target vehicle, realizing a leap from a "one-size-fits-all" fixed toll to precise metered toll, and improving the fairness and rationality of toll collection.
[0099] In some embodiments, after performing analysis on multi-source traffic management data to obtain the target vehicle's vehicle type, travel time, and travel trajectory between different traffic control points, the target vehicle's driving path is obtained based on its travel trajectory between different traffic control points; the driving path is detected, and if the detection result indicates that the target vehicle has detour behavior, an audit process is triggered.
[0100] In some embodiments, the travel trajectory of the target vehicle between different traffic control points can be stitched together based on the BIM model to obtain the driving path of the target vehicle.
[0101] In some embodiments, if the detection results of the target vehicle's driving path indicate that the target vehicle has detoured, the target vehicle is marked as abnormal, the credit score of the driver corresponding to the target vehicle is deducted, and an abnormal alarm message is generated based on the target vehicle's license plate information and driving path. The abnormal alarm message is broadcast to the management platform for fee recovery.
[0102] According to the vehicle free-flow toll collection method of this application embodiment, by performing analysis operations on multi-source traffic management data collected at each traffic control point, the vehicle type, travel time period, and travel trajectory between different traffic control points of the target vehicle are obtained. Based on the trajectory of the target vehicle between different traffic control points, the driving path of the target vehicle is obtained. The driving path is detected, and if the detection result indicates that the target vehicle has detour behavior, the audit process is triggered, so as to effectively solve the audit problem of detour toll evasion and achieve full collection of tolls due.
[0103] In some embodiments, before performing analysis on multi-source traffic management data to obtain the target vehicle's model, travel time, and travel trajectory between different traffic control points, personal information, vehicle information, and account information of each driver are obtained; and based on the personal information, vehicle information, and account information, a binding operation between the driver, vehicle, and account is performed.
[0104] In some embodiments, the system can query whether a target vehicle has a corresponding target account based on the vehicle's license plate information. If no target account exists, the system can guide the driver to complete the binding process via SMS, mini-program push notifications, information board prompts, or other means.
[0105] In some embodiments, personal information may include an identity card number and facial features.
[0106] According to the vehicle free-flow toll collection method of this application, for each driver, the driver's personal information, vehicle information, and account information are obtained; based on the personal information, vehicle information, and account information, a binding operation is performed between the driver, vehicle, and account. By performing analysis operations on multi-source traffic management data collected from various traffic control points, the vehicle type, travel time, and travel trajectory between different traffic control points of the target vehicle are obtained. Based on the vehicle type, travel time, and travel trajectory, the amount payable for the target vehicle is obtained, and the toll is automatically deducted from the target account bound to the target vehicle. Without setting up physical toll stations, the toll collection for the target vehicle is automatically completed based on the vehicle type, travel time, and travel trajectory, and the payment is automatically made solely based on the target account bound to the target vehicle, realizing seamless payment for the target vehicle's passage and improving traffic efficiency.
[0107] The vehicle free-flow toll collection method in this application embodiment can be executed by an electronic device or by a component within the electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices besides a terminal. For example, the electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, mobile internet device (MID), augmented reality (AR) / virtual reality (VR) device, robot, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc. It can also be a server, network attached storage (NAS), personal computer (PC), television (TV), ATM, or self-service machine, etc. This application embodiment does not specifically limit the scope of the electronic device.
[0108] The vehicle free-flow toll collection system in this application embodiment can be a device with an operating system. This operating system can be a Microsoft (Windows) operating system, an Android operating system, an iOS operating system, or other possible operating systems; this application embodiment does not specifically limit it.
[0109] In some embodiments, such as Figure 3 As shown, this application embodiment also provides an electronic device 300, including a processor 301, a memory 302, and a computer program stored in the memory 302 and executable on the processor 301. When the program is executed by the processor 301, it implements the various processes of the above-described vehicle free-flow tolling method embodiment and can achieve the same technical effect. To avoid repetition, it will not be described again here.
[0110] It should be noted that the computer equipment in this application embodiment includes the mobile electronic equipment and non-mobile electronic equipment described above.
[0111] This application also provides a non-transitory computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the various processes of the above-described vehicle free-flow toll collection method embodiments and achieves the same technical effect. To avoid repetition, it will not be described again here.
[0112] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.
[0113] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described vehicle free-flow toll collection method.
[0114] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.
[0115] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above-described vehicle free-flow tolling method embodiments and can achieve the same technical effect. To avoid repetition, it will not be described again here.
[0116] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.
[0117] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.
[0118] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.
[0119] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.
[0120] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.
[0121] Although embodiments of this application have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the claims and their equivalents.
Claims
1. A vehicle free-flow toll collection system, characterized in that, include: The sensing module is used to receive multi-source traffic management data collected from various traffic control points; The analysis module is used to perform analysis operations on the multi-source traffic management data to obtain the target vehicle's vehicle type, travel time period, and travel trajectory between different traffic control points; The processing module is used to obtain the amount payable by the target vehicle based on the vehicle type, the time period of passage, and the passage trajectory; The deduction module is used to perform a deduction operation on the target account bound to the target vehicle based on the amount payable.
2. The vehicle free-flow toll collection system according to claim 1, characterized in that, The multi-source traffic management data includes at least video stream data, radar data, positioning data, and image data; the analysis module includes: The data parsing unit is used to obtain the vehicle's license plate information and appearance features based on image data, and to obtain the vehicle's model based on radar data, for the current traffic convergence point; the current traffic convergence point can be any one of the traffic convergence points. The comparison unit is used to determine whether the vehicle is the target vehicle based on the license plate information, the appearance features, and the vehicle model; the target vehicle is the vehicle that was detected at the previous intersection adjustment point. The generation unit is configured to, when the vehicle is the target vehicle, obtain the travel trajectory of the target vehicle based on the positioning data of the current traffic control point and the previous traffic control point, and obtain the travel time period based on the time information of the target vehicle passing through the previous traffic control point and the time information of passing through the current traffic control point.
3. The vehicle free-flow toll collection system according to claim 1, characterized in that, The processing module includes: The processing unit is used to obtain the travel mileage based on the travel trajectory, obtain the vehicle type coefficient based on the vehicle type, and obtain the time period coefficient based on the travel time period; The determining unit is used to determine the amount payable by the target vehicle by multiplying the toll mileage, the basic cost per kilometer, the vehicle type coefficient, and the time period coefficient.
4. The vehicle free-flow toll collection system according to claim 1, characterized in that, The system also includes: The acquisition module is used to acquire the travel path of the target vehicle based on the travel trajectory of the target vehicle between different traffic adjustment points; The audit module is used to detect the driving path and trigger the audit process when the detection result indicates that the target vehicle has detoured.
5. The vehicle free-flow toll collection system according to any one of claims 1-4, characterized in that, The system also includes: The interaction module is used to obtain the driver's personal information, vehicle information, and account information for each driver. The registration module is used to perform the binding operation between the driver, vehicle and account based on the personal information, vehicle information and account information.
6. A method for toll collection in free-flowing traffic, characterized in that, include: Receive multi-source traffic management data collected from various traffic control points; The multi-source traffic management data is analyzed to obtain the vehicle type, travel time, and travel trajectory between different traffic control points of the target vehicle. Based on the vehicle type, the time period of passage, and the passage trajectory, the amount payable by the target vehicle is obtained; Based on the amount payable, a deduction operation is performed on the target account linked to the target vehicle.
7. The vehicle free-flow toll collection method according to claim 6, characterized in that, The multi-source traffic management data includes at least video stream data, radar data, positioning data, and image data; the step of performing analysis operations on the multi-source traffic management data to obtain the target vehicle's vehicle type, travel time period, and travel trajectory between different traffic control points includes: For the current traffic adjustment point, the vehicle's license plate information and appearance features are obtained based on image data, and the vehicle model is obtained based on radar data; the current traffic adjustment point can be any one of the traffic adjustment points. Based on the license plate information, the appearance features, and the vehicle model, it is determined whether the vehicle is the target vehicle; the target vehicle is the vehicle that was detected at the previous traffic control point. If the vehicle is the target vehicle, the travel trajectory of the target vehicle is obtained based on the positioning data of the current traffic control point and the previous traffic control point, and the travel time period is obtained based on the time information of the target vehicle passing through the previous traffic control point and the time information of passing through the current traffic control point.
8. The vehicle free-flow toll collection method according to claim 6, characterized in that, The process of obtaining the amount payable for the target vehicle based on the vehicle type, the travel time period, and the travel trajectory includes: The travel mileage is obtained based on the travel trajectory, the vehicle type coefficient is obtained based on the vehicle type, and the time period coefficient is obtained based on the travel time period; The product of the travel mileage, the basic cost per kilometer, the vehicle type coefficient, and the time period coefficient is determined as the amount payable by the target vehicle.
9. The vehicle free-flow toll collection method according to claim 6, characterized in that, After performing analysis on the multi-source traffic management data to obtain the target vehicle's vehicle type, travel time period, and travel trajectory between different traffic control points, the method further includes: Based on the travel trajectory of the target vehicle between different traffic control points, the travel path of the target vehicle is obtained; The driving path is detected, and if the detection result indicates that the target vehicle is taking a detour, the audit process is triggered.
10. The vehicle free-flow toll collection method according to any one of claims 6-9, characterized in that, Before performing analysis on the multi-source traffic management data to obtain the target vehicle's vehicle type, travel time period, and travel trajectory between different traffic control points, the method includes: For each driver, obtain the driver's personal information, vehicle information, and account information; Based on the personal information, vehicle information, and account information, a binding operation is performed between the driver, vehicle, and account.