Toll fee estimation method and software, map data service cloud platform and client

Abstract

The disclosure discloses a toll estimation method and software, a map data service cloud platform and a client, and belongs to the technical field of intelligent transportation. The method comprises the following steps: obtaining toll path information corresponding to a planned path and charging parameter information; obtaining charging key point coordinates in the toll path information, and calling a pre-created charging model and a rate data model according to the charging key point coordinates and the charging parameter information to calculate a charging unit associated with the toll path; and calculating a toll corresponding to the toll path according to the charging unit and outputting the toll. Therefore, by implementing the technical solution of the disclosure, the storage amount of data can be reduced, the operation amount of data can be reduced, the operation speed can be accelerated, and the user experience can be significantly improved.

Description

Technical Field

[0001] The present disclosure relates to the field of smart transportation technology, and in particular to a toll estimation method and software, a map data service cloud platform, and a client. Background Art

[0002] Highway toll collection uses toll stations as nodes, dividing the highway network into several minimum charging units. In the data, the minimum unit is defined as a Subgroup. Toll metadata is generated based on the Subgroup and the minimum unit fee amount FEE (Subgroup) is calculated. Generally speaking, the toll collection system needs to identify the entry and exit of the toll station on the route, then automatically connect the highway network between the entry and exit stations, match the Subgroup of the route, and finally accumulate the FEE (Subgroup) to complete the fee calculation.

[0003] Currently, the toll station relationship model data can only calculate tolls for the shortest path between toll stations, and cannot be used to calculate tolls based on the actual travel path. The existing toll calculation model requires storing over 5 million toll station relationship models, resulting in large amounts of data, complex user interactions, low efficiency, and a poor user experience. Summary of the Invention

[0004] The present invention discloses a toll estimation method and software, a map data service cloud platform and a client to solve at least one of the problems in the existing technology, namely, the large amount of data required for billing, slow calculation speed, inaccurate billing, and difficulty in nationwide one-stop billing after the provincial border toll stations are deleted.

[0005] Therefore, according to a first aspect of the present disclosure, a toll fee estimation method is disclosed, the method comprising:

[0006] Obtain the travel path information and billing parameter information corresponding to the planned path;

[0007] Obtain the coordinates of the key charging points in the passage path information, and based on the coordinates of the key charging points and the charging parameter information, call the pre-created charging model and rate data model to calculate the charging unit associated with the passage path;

[0008] Calculate the toll generated by the travel path according to the billing unit and output it;

[0009] Among them, the travel path information includes the travel path and its starting point, end point and / or optional waypoint information; the billing parameter information includes time, vehicle type, license plate, load and / or road type information including bridges, tunnels and / or general roads.

[0010] As an optional implementation, the above method of calling a pre-created billing model based on the billing key point coordinates and billing parameter information to calculate the billing unit further includes:

[0011] Determine the segmented road corresponding to the travel path based on the coordinates of the charging key point, wherein the nth charging unit corresponds to the nth segmented road, where n is an integer greater than or equal to 1;

[0012] According to the vehicle type information in the n-th segmented road and the billing parameter information, the rate data model corresponding to the n-th segmented road is called, and the n-th road rate and the n-th bridge and tunnel rate are obtained according to the rate data model and the billing parameter information;

[0013] According to the road line length of the nth divided road, the nth road rate and the nth bridge and tunnel rate, the billing model calculates the corresponding nth road billing unit and the nth bridge and tunnel billing unit, takes the sum of the nth road billing unit and the nth bridge and tunnel billing unit to obtain the nth billing unit, and accumulates all the obtained nth billing units to obtain the billing unit.

[0014] As an optional implementation, the above-mentioned toll fee estimation method may further include:

[0015] Regularly update the rate data model, and update the billing model accordingly based on the rate data model; and, or,

[0016] Obtain billing discount information based on the travel time and path planning information in the billing parameter information; calculate the toll generated corresponding to the travel path based on the billing discount information and the billing unit; wherein the billing discount information includes at least one of a billing discount rate for a specific road section, a billing discount rate for a specific time period, a billing discount rate for a specific vehicle model, and a billing discount rate for a specific license plate location.

[0017] As an optional implementation, the above-mentioned calculation of the toll corresponding to the prime number passage path according to the charging unit further includes:

[0018] For offline services, the fees for different types of vehicles corresponding to each billing unit stored in the offline database are matched with the travel path information and / or billing parameter information to calculate the toll and output it.

[0019] As an optional implementation method, for the above online service, based on the input travel path information and / or billing parameter information, the billing unit stored in the online database on the network cloud is called through the data interface to calculate the toll in real time and feed it back to the user.

[0020] As an optional implementation method, in the above-mentioned billing data model, according to each billing unit, in the process of offline calculation of tolls, the charging standards in the static database are called to generate tolls in segments, and during the output process, the third-party data in the multi-source database is called to correct the tolls.

[0021] As an optional implementation, the aforementioned billing data model uses the charging standards in the static database to generate segmented tolls during online toll calculation for each billing unit. Third-party data from the multi-source database is used to correct the tolls during output, and the tolls are displayed overlaid with other information from the dynamic database. The static database stores pre-collected and program-processed charging standards for different road sections and vehicle types; the dynamic database stores preferential information, including discounts on road tolls and / or free travel; and the multi-source database stores third-party data, including actual toll receipts for various vehicles passing through various road sections, which is used to verify and correct tolls calculated in offline billing scenarios.

[0022] According to a second aspect of the present disclosure, a toll fee intelligent estimation software is disclosed, the estimation software comprising:

[0023] An input module is used to obtain travel path information and charging parameter information corresponding to the planned route; wherein the travel path information includes the travel path and its starting point, end point, and / or optional waypoint information; the charging parameter information includes time, vehicle type, license plate, load, and / or road type information including bridge and tunnel roads and / or general roads;

[0024] The estimation module is used to obtain the coordinates of the key charging points according to the passage path information, and call the pre-created charging model and rate data model based on the coordinates of the key charging points and the charging parameter information to calculate the charging unit associated with the passage path;

[0025] A billing module is used to calculate the toll generated by the passage path according to the billing unit;

[0026] The output module is used to output the toll according to the travel path information and billing parameter information.

[0027] According to a third aspect of the present disclosure, a component-based lightweight map data service cloud platform is disclosed. The service platform includes:

[0028] User interaction components are used to provide access to the platform through Web, API, or SDK;

[0029] Unified authentication component for identity authentication, functional permission management, access control and / or dynamic configuration;

[0030] A database component for storing electronic map data, coordinates of key charging points, various high-speed line units pre-divided according to the coordinates of the key charging points, and tolls corresponding to the high-speed line units;

[0031] Product editing components, configured with an independent data editing space, are used to generate customized data products based on editing, transforming, fusing, checking, differencing, batch processing data in database components and / or combining with imported reference data;

[0032] Product release components, used for data and business version management, permission management, incremental data release, real-time push, service launch, traffic control, and service shutdown;

[0033] A business customization component is used to customize map data products and services according to needs, including matching travel paths with expressway units, extracting and outputting the billing units corresponding to each expressway unit corresponding to the travel path;

[0034] Statistical analysis component, used for usage statistics, hot data analysis, operation and maintenance monitoring, and early warning.

[0035] As an optional implementation, in the above-mentioned component-based lightweight map data service cloud platform, the unified authentication component further includes:

[0036] Load balancer, which monitors network ports and dynamically configures network resources;

[0037] API gateway module, used for API routing and access control;

[0038] The authentication module is used to authenticate users and manage their functional permissions.

[0039] As an optional implementation, in the above-mentioned component-based lightweight map data business cloud platform, the database component further includes:

[0040] Static database, used to store pre-collected and program-processed charging standards for different road sections and different vehicle types;

[0041] A dynamic database for storing preferential information, including discount information on road tolls and / or free road travel information;

[0042] A multi-source database is used to store third-party data, including toll receipt data of various vehicles actually passing through various road sections, which is used to verify and correct the tolls calculated in offline billing scenarios.

[0043] According to a fourth aspect of the present disclosure, a smart travel client is disclosed, the client comprising:

[0044] The user interaction module is used to obtain user information and billing parameter information; the billing parameter information includes time, vehicle type, license plate, load and / or road type information including bridge and tunnel roads and / or general roads;

[0045] A route planning module, configured to generate at least one travel route based on the starting point, end point, and / or optional waypoint information of the trip;

[0046] A billing module, configured to calculate a toll corresponding to a travel path based on a billing unit obtained from the service platform according to claim 7 or 8;

[0047] The output module is used to output the toll according to the travel path and billing parameter information.

[0048] According to a fifth aspect of the present disclosure, a computer device is disclosed, which includes a processor and a memory, wherein the memory stores computer instructions, and the processor operates the computer instructions to execute the toll fee estimation method of any one of the aforementioned embodiments.

[0049] Compared with the prior art, the technical solution disclosed in the embodiments of the present disclosure has the following beneficial effects:

[0050] Through the technical solution disclosed in this disclosure, by obtaining the travel path information and billing parameter information of the vehicle's travel path, the coordinates of the key billing points including the gantry are obtained, and the billing unit of the vehicle's travel is obtained through the pre-built billing model. The toll of the vehicle's formal path is calculated through the billing unit, thereby reducing the amount of data storage, reducing the amount of data calculation, speeding up the calculation speed, improving the experience, and conforming to the charging method of highways under the new national standard. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 An embodiment of the toll fee estimation method disclosed in the present invention is shown;

[0052] Figure 2 An optional embodiment of the toll fee estimation method disclosed in the present invention is shown;

[0053] Figure 3 An example of high-speed line segmentation in the toll fee estimation method disclosed in the present invention is shown;

[0054] Figure 4 An optional embodiment of the charging data model in the toll fee estimation method disclosed in the present invention is shown;

[0055] Figure 5 An example of the process flow of the billing data model disclosed in the present invention in offline services and online services is shown;

[0056] Figure 6An example of the toll fee estimation method disclosed in the present invention is shown;

[0057] Figure 7 One embodiment of the navigation system of the present disclosure is shown;

[0058] Figure 8 An example of the navigation system of the present disclosure is shown;

[0059] Figure 9 An example of using the navigation system of the present disclosure is shown;

[0060] Figure 10 The present invention shows the composition of the toll fee intelligent estimation software embodiment disclosed in the present invention;

[0061] Figure 11 The composition of the map data service cloud platform and client embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0062] To make the objectives, technical solutions, and advantages of the embodiments of the present disclosure more clear, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present disclosure without making any creative efforts shall fall within the scope of protection of the present disclosure.

[0063] The terms "first," "second," "third," "fourth," and the like (if any) in the specification and claims of the present disclosure and in the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a particular order or sequential sequence. It should be understood that the numbers used in this way are interchangeable where appropriate so that the embodiments of the present disclosure described herein can be implemented in orders other than those illustrated or described herein. In addition, the terms "including" and "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or that are inherent to these processes, methods, products, or apparatus.

[0064] The existing toll station relationship model only calculates tolls for the shortest path between toll stations and cannot calculate tolls based on the actual travel path. Furthermore, the existing toll calculation model requires storing over 5 million toll station relationships, resulting in a large amount of data and making toll calculation complex and time-consuming. Furthermore, the existing billing model also suffers from complex interactions with users, making communication inefficient and leading to a poor user experience.

[0065] To address the above technical issues, the present disclosure discloses a toll estimation method and software, a map data service cloud platform, and a client. These methods reduce data storage and computational complexity, accelerate computation, and enhance the user experience, aligning with the new national highway toll collection system. The toll estimation method comprises obtaining route information and charging parameter information corresponding to a travel route. The route information includes the planned starting and ending points, as well as optional waypoints, for a vehicle during travel. The charging parameter information includes planned route information, including distance and type. Route types include general roads and bridge-tunnel roads; the vehicle model; and the estimated travel time along the route. The method then obtains the coordinates of key charging points from the route information and, based on the coordinates and parameter information, invokes a pre-established charging model to calculate the charging units associated with the route. The key charging points are selected as road gantry points. The corresponding key charging points are obtained by integrating the pre-collected road gantry information with the map. Using a pre-created billing model, the billing unit corresponding to the vehicle's route is calculated. Finally, the toll associated with the route is calculated and output based on the billing unit. This toll calculation takes into account the differences in tolls for non-traveled bridges and tunnels and general roads, as well as discounts for road travel during specific time periods. Ultimately, the accurate toll for the current time period is calculated.

[0066] Application scenarios: The method disclosed herein can be applied to various types of vehicles, including trucks, buses, etc., to calculate the tolls on a planned route, thereby obtaining an estimated toll for the vehicle on a certain route and at a certain time, and providing a quotation service.

[0067] The following specific embodiments describe in detail the technical solutions of the present disclosure and how they solve the above-mentioned technical problems. The following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some instances. The following embodiments of the present disclosure are described in conjunction with the accompanying drawings.

[0068] Method Example:

[0069] Reference Figure 1 , which shows an embodiment of the toll fee estimation method disclosed in the present invention. The toll fee estimation method disclosed in this embodiment includes the following processing steps:

[0070] S101, obtaining the travel path information and charging parameter information corresponding to the planned path;

[0071] S102, obtaining the coordinates of the key charging points in the passage path information, and calling the pre-created charging model and rate data model based on the coordinates of the key charging points and the charging parameter information to calculate the charging unit associated with the passage path;

[0072] S103: Calculate the toll generated by the toll path according to the charging unit and output it.

[0073] In this embodiment, the travel path information includes the travel path and its starting point, end point, and / or optional waypoint information. The charging parameter information includes the intended travel time, vehicle type, license plate, load, and / or road type information including bridges, tunnels, and / or general roads.

[0074] In this embodiment, when calculating the toll for a vehicle's planned route, the toll information and charging parameter information corresponding to the vehicle's planned route are first obtained. The vehicle's planned route can be determined based on the user's driving needs. The toll information includes the vehicle's starting point, end point, and optional waypoints. The charging parameter information includes the intended travel time, vehicle type, license plate, load, and / or road type information including bridges, tunnels, and / or general roads. Road type information includes general roads and bridges and tunnels. For example, for a passenger car, the following vehicle type definitions can be used: Vehicle Type 1: 0-9 seats; Vehicle Type 2: 10-19 seats; Vehicle Type 3: 20-39 seats; Vehicle Type 4: Greater than 40 seats.

[0075] Next, the coordinates of the key charging points in the route information are obtained. The route is segmented based on the key point coordinates, and the corresponding charging units are obtained based on the charging parameter information. Each charging unit represents the road toll for the corresponding segment, including general road tolls and bridge and tunnel tolls within the segment. The key charging points can be determined based on the location of the gantry on the route.

[0076] Finally, the fees of each billing unit are accumulated to obtain the toll corresponding to the toll path. For example: toll amount fee = sum of A values ​​calculated for general road links + sum of B values ​​calculated for bridge / tunnel strings.

[0077] This embodiment divides toll roads into different expressway toll units for calculating tolls. Each toll unit uses different toll rates based on the highway it is on to calculate the toll corresponding to the route. If the route includes a bridge or tunnel, the toll rates for that bridge or tunnel are also used to calculate the toll for that toll unit. The output process uses third-party data from a multi-source database for correction. Therefore, this embodiment can calculate tolls based on different planned routes, reducing data storage and computing workload, speeding up calculations, and improving the user experience, in line with the new national highway toll collection method.

[0078] As an optional implementation, in the above embodiment, the billing model may be configured based on the following structure:

[0079] Tablename Field_code Field_Type FIELD_LENGTH Field_name SC_TOLL_SUBGROUP_INFO SUB_GROUP_ID NUMBER 20 GROUP subgroup number SC_TOLL_SUBGROUP_INFO GROUP_S_ID NUMBER 20 Starting point of GROUP subgroup SC_TOLL_SUBGROUP_INFO GROUP_E_ID NUMBER 20 GROUP subgroup endpoint SC_TOLL_SUBGROUP_INFO GROUP_ID NUMBER 20 ParentGROUP SC_TOLL_SUBGROUP_INFO RD_NAME VARCHAR2 500 road name SC_TOLL_SUBGROUP_INFO NAME_GROUPID NUMBER 10 Road name group number SC_TOLL_SUBGROUP_INFO SYSTEM_ID NUMBER 10 Area Code SC_TOLL_SUBGROUP_INFO SUMLEN NUMBER 15 Total LINK length SC_TOLL_SUBGROUP_INFO NOTE VARCHAR2 20 Remark SC_TOLL_SUBGROUP_INFO fee NUMBER 10 Subgroup corresponding fee

[0080] As an optional implementation, in the above embodiment, the rate data model may be configured based on the following structure:

[0081]

[0082]

[0083] In step S101 of the above-described toll fee estimation method embodiment, the vehicle-mounted application optionally obtains at least one possible planned route by inputting a starting point, an end point, and / or waypoints. Each of the at least one planned route can be used as a toll-charging route. Toll fee calculation is triggered based on route information corresponding to the selected toll fee route, including the starting point, end point, and optional waypoints, as well as toll parameter information. In this embodiment, the toll parameter information input by the user can be obtained through the estimation software user interface.

[0084] In an alternative embodiment, if Figure 2 As shown, the above process of calculating the billing unit by calling the pre-created billing model and rate data model based on the billing key point coordinates and billing parameter information may further include steps S201-S203, which are described as follows:

[0085] S201: Determine the segmented road corresponding to the billing unit according to the coordinates of the billing key point; wherein the nth billing unit corresponds to the nth segmented road, and n is an integer greater than or equal to 1.

[0086] In this embodiment, the billing key points on the expressway are determined based on the positions of the gantry on the expressway, wherein the billing key points correspond one-to-one to the gantries; the expressway is divided with the billing key points as dividing points to obtain divided roads corresponding to the billing units, wherein the nth billing unit corresponds to the nth divided road, and n is an integer greater than or equal to 1.

[0087] This embodiment uses gantries in high-speed lines to divide the high-speed line, obtaining high-speed line units as basic billing units, reducing the amount of data stored in the billing units and improving the accuracy of the billing unit data. As infrastructure construction, the gantries will remain stable and unchanged for many years. Therefore, the new high-speed toll collection method built based on the gantries is also highly stable. In addition, using gantries as the division nodes of the high-speed line billing units, because the number of gantries is small, not only reduces the amount of data stored, but also reduces costs during actual verification. The smaller amount of data storage also speeds up the calculation speed of the billing system, making the interaction with the user simpler and more efficient, and improving the practical experience.

[0088] In an optional embodiment, the process of determining the key nodes on the high-speed main line based on the position of the gantry on the high-speed main line includes: calibrating the position of the gantry on the high-speed main line; and fitting the high-speed main line nodes corresponding to the gantry with the gantry to obtain billing key points.

[0089] In this optional embodiment, when determining charging key points on a highway main line based on the gantry position on the highway main line, the gantry position on the highway main line is first determined. After the gantry position is determined, the coordinates and other information corresponding to the gantry are fitted with the highway main line node corresponding to the gantry in the highway main line database, thereby determining the corresponding gantry position in the highway main line data. Subsequently, the gantry pair and highway main line are divided.

[0090] In an alternative embodiment, the stake numbers and coordinates of gantries on toll highways nationwide are obtained through field data collection and / or intelligence gathering. Then, through coordinate matching and fitting, the gantries' locations are annotated in a map database that includes the highway's main lines. Key nodes corresponding to the gantries are generated, with a one-to-one correspondence between the gantries and key charging points.

[0091] The gantry's location is obtained and matched with the map database containing the expressway's main route. The gantry's location is then calibrated in the map database and used as the key point for charging demarcation along the expressway. There is a one-to-one correspondence between the gantry and the key point. Using the gantry as the key point for charging demarcation along the expressway offers greater stability, as fewer gantries are needed, reducing data storage requirements while increasing data storage speed.

[0092] In an optional embodiment, the process of dividing the expressway main line with the billing key points as the dividing points includes: dividing the expressway main line according to the driving direction of the expressway and in the order of the billing key points, wherein the ending billing key point of the current expressway main line unit is the starting billing key point of the next expressway main line unit.

[0093] In this optional embodiment, to avoid missing certain charging key points, the expressway is segmented according to the direction of travel on the expressway and the order of the key nodes in that direction. During segmentation, the continuity between expressway units is maintained, and the ending key node of the current expressway unit becomes the starting key node of the next expressway unit.

[0094] Figure 3 An example of high-speed line segmentation in the toll fee estimation method disclosed in the present invention is shown. Figure 3 In the example shown, the expressway has key charging nodes K-N1, K-N2, and K-N3, determined by the gantry. The segmentation is performed according to the direction of travel of the expressway and the order of the key nodes. The section between key nodes K-N1 and K-N2 is expressway unit M-U1, and the section between key nodes K-N2 and K-N3 is expressway unit M-U2. Key node K-N2 is both the ending key node of M-U1 and the starting key node of M-U2, ensuring continuity between all expressway units.

[0095] By dividing the high-speed line according to the billing key points corresponding to the gantry, the corresponding high-speed line units are obtained to ensure the continuity and accuracy between each high-speed line unit.

[0096] S202: Based on the vehicle type information in the nth segmented road and the billing parameter information, call the rate data model corresponding to the nth segmented road, and obtain the nth road rate and the nth bridge and tunnel rate based on the rate data model and the billing parameter information.

[0097] In this embodiment, after determining each segmented road, the rate data model corresponding to each segmented road is called according to the vehicle type information in the billing parameter information, and the road rate and bridge and tunnel rate corresponding to each segmented road are determined through the vehicle travel time, date and other information in the billing parameter information.

[0098] In one example of the present disclosure, different vehicle types correspond to different toll rates when traveling on a highway. Therefore, when calculating tolls, different tolls will be applied based on the vehicle type. For example, for buses, vehicles with 0-9 seats are defined as vehicle type 1, corresponding to the first toll rate; buses with 10-19 seats are defined as vehicle type 2, corresponding to the second toll rate; buses with 20-39 seats are defined as vehicle type 3, corresponding to the third toll rate; and buses with more than 40 seats are defined as vehicle type 4, corresponding to the fourth toll rate. By assigning different vehicle rates to different vehicle types, the calculation of vehicle tolls is more accurate.

[0099] It should be noted that when determining vehicle types, appropriate classifications can be made based on vehicle load and relevant high-speed toll collection rules for different vehicles, so that the calculated tolls are consistent with actual vehicle toll collection conditions. This disclosure does not specifically limit the specific classification of vehicle types and their correspondence to toll rates.

[0100] S203: According to the road line length of the nth divided road, the nth road rate and the nth bridge and tunnel rate, the corresponding nth road billing unit and the nth bridge and tunnel billing unit are calculated, and the sum of the nth road billing unit and the nth bridge and tunnel billing unit is taken to obtain the nth billing unit.

[0101] In this embodiment, the expressway is divided into sections using the gantry as the key charging point. The length of each section, as well as the corresponding general roads and bridge-tunnel roads, varies. Therefore, after determining each section, the corresponding road and bridge-tunnel charging units are determined based on the length of the general roads and bridge-tunnel roads within each section, as well as the corresponding road and bridge-tunnel charging rates. The road and bridge-tunnel charging units are then superimposed to obtain the charging units corresponding to each section.

[0102] In one example of the present disclosure, for example, a certain divided road includes a section of general road and a section of bridge-tunnel road, then the corresponding road billing unit and bridge-tunnel billing unit are calculated according to the length of the general road and the bridge-tunnel road and the corresponding road tolls and bridge-tunnel rates, respectively, and the road billing unit and the bridge-tunnel billing unit are added together to obtain the billing unit corresponding to the divided road; for example, a certain divided road only includes general roads, then the corresponding road billing unit is calculated according to the length of the general road and the bridge-tunnel road and the corresponding road tolls, and the road billing unit is directly used as the billing unit corresponding to the divided road.

[0103] exist Figure 1 In the illustrated embodiment, the toll fee estimation method disclosed herein includes: S103 , calculating the toll fee corresponding to the toll path according to the charging unit, and outputting the calculated toll fee.

[0104] In this embodiment, after obtaining the billing units corresponding to each section of the divided road, the toll corresponding to each section of the divided road can be calculated based on the billing units, and then the toll corresponding to each section of the divided road is accumulated to obtain the toll generated by the vehicle passing through the passage.

[0105] In one example of the present disclosure, a vehicle's route includes three sections of road. The toll for the first section is 10 yuan, calculated based on the charging unit for the first section; 15 yuan, calculated based on the charging unit for the second section; and 12 yuan, calculated based on the charging unit for the third section. The toll for the vehicle on this route is 10 + 15 + 12 = 37 yuan.

[0106] In an optional embodiment, the method disclosed herein also includes: obtaining billing discount information based on the travel time and path planning information in the billing parameter information; calculating the toll generated corresponding to the travel path based on the billing discount information and the billing unit; wherein the billing discount information includes at least one of a billing discount rate for a specific road section, a billing discount rate for a specific time period, a billing discount rate for a specific vehicle model, and a billing discount rate for a specific license plate location.

[0107] In this embodiment, when a vehicle is traveling on a highway, certain discounts may be applied to tolls during different time periods and on different road sections, based on national and highway toll preferential policies. For example, there are discounts on highway tolls during holidays. Therefore, when calculating vehicle tolls, based on the vehicle's travel time and the road section of the vehicle's planned route, discount information for that time period and road section is obtained. The toll corresponding to the travel route is then calculated based on the discount information and the determined billing unit. The discount information includes at least one of a specific road section discount rate, a specific time period discount rate, a specific vehicle model discount rate, and a specific license plate location discount rate.

[0108] In one example of the present disclosure, a vehicle's travel path includes three sections of road. The toll for the first section is 10 yuan, according to the toll unit for the first section; 15 yuan, according to the toll unit for the second section; and 12 yuan, according to the toll unit for the third section. Based on the obtained toll discount information, the vehicle enjoys a 50% discount on the toll for the first section during the travel time; a 80% discount on the toll for the second section due to the specific vehicle type. No relevant discount information is available for the third section. Therefore, the toll for the vehicle through this route is 10*0.5+15*0.2+12=20 yuan.

[0109] It should be noted that the vehicle toll discount information is determined based on the high-speed driving preferential information released by the state and is updated in real time to ensure that the calculated toll is consistent with the actual traffic conditions.

[0110] In an optional embodiment, calculating the toll generated corresponding to the travel path according to the charging unit further includes:

[0111] For offline service scenarios, based on the billing model and rate data model stored in the offline database, corresponding fee units for different vehicle types are matched with backend data through an interface based on the user's travel path information and billing parameters, and then output. For example, the offline fee generation process for each billing unit will call on the charging standards in the static database to generate the fee segment, and the output process can call on third-party data from multiple source databases for correction.

[0112] For online service scenarios, based on the user's travel path information and billing parameters, the billing units stored in the online database on the network cloud are called through a data interface to calculate tolls in real time and provide feedback to the user. For example, the online fee generation process for each billing unit will call on the charging standards in the static database to generate the fee in sections. The output process can also call on third-party data from multiple source databases for correction, and simultaneously overlay discount information from the dynamic database for calculation and display output to the user.

[0113] In this embodiment, toll calculation is divided into offline and online services. In the offline service, the fees for different vehicle types corresponding to each billing unit are pre-stored in an offline database. When calculating the fees, the billing unit corresponding to the travel path is matched based on the input driving parameters. The toll is then calculated using the above-mentioned fee calculation method and fed back to the user. Driving parameters include vehicle type, starting and ending points, waypoints, and / or date. In the online service, the billing unit stored in the online database on the network cloud is called through the corresponding data interface based on the input driving parameters. The toll is calculated in real time according to the above-mentioned fee calculation method and fed back to the user.

[0114] This embodiment stores the billing unit by setting up an offline database and an online database, and can obtain accurate path toll data in different offline and online scenarios, thereby improving user experience.

[0115] In an optional embodiment, the above method may further include: regularly updating billing parameter information, and correspondingly updating the billing unit according to the billing parameter information.

[0116] In this embodiment, in order to ensure the accuracy of toll calculations, it is necessary to update the billing standard data. The rate update process can be based on the news released on the official website or the latest rate standards of each highway collected on the spot, and updated to the static database. When calculating the toll, the program will call the rate in the static database. For example, the billing key points based on the gantry are updated, and the corresponding billing key points are added or deleted, and the billing units are added or deleted accordingly. In addition, according to the national document on the rate setting of highway tolls, the latest road toll rates are updated in a timely manner, and then each billing unit is updated. When calculating vehicle tolls, it conforms to the actual road charging situation and improves the user experience.

[0117] Figure 4 FIG. 1 shows an optional embodiment of the billing database in the toll fee estimation method disclosed in the present invention. Figure 4 As shown, the databases used for billing in this embodiment include a static database 401, a multi-source database 402, and a dynamic database 403, wherein:

[0118] The static database 401 mainly stores the charging standards corresponding to different road sections and different vehicle models that have been collected and processed in advance; the multi-source database 402 mainly stores third-party data, which includes data on the actual verification of various vehicles passing through various road sections; the dynamic database 403 mainly stores fee information, which includes discount information on road charges and / or free road driving information.

[0119] In this embodiment, the static database stores pre-collected and program-processed toll rates for different road sections and vehicle types. For example, this includes the locations of gantry cranes on the expressway, the key charging points corresponding to the gantry crane coordinates, the road segments that divide the expressway based on the key charging points, the road type information corresponding to each segment, and the toll rate information for each segment and vehicle type.

[0120] The multi-source database primarily stores third-party data, including data verified by various vehicles actually passing through various road sections. For example, the actual travel time or actual tolls reported by vehicles passing through a certain road section in third-party data are verified against the estimated tolls for that road section using the disclosed method. If the difference between the two exceeds a preset threshold, the corresponding road section's billing information, discount information, etc., needs to be updated and checked to ensure that the estimated tolls for vehicles obtained using the disclosed method are consistent with the actual road tolls.

[0121] The dynamic database stores fee information, including discounts on road tolls and free road travel. For example, the dynamic database mainly stores information such as free travel during holidays, free travel during epidemics, and ETC discounts issued by various transportation departments or government departments.

[0122] In this embodiment, the basic data for toll calculation, the discount information for toll calculation and the related verification information are stored in the corresponding storage unit, so that the billing unit obtained through the billing data model is more in line with the actual driving conditions of the vehicle model, and the final calculated toll is in line with the actual charging conditions, thereby improving the user experience.

[0123] In an optional embodiment, during the offline calculation of tolls based on various billing units, the charging standards in the static database are called to generate tolls in segments, and during the output process, third-party data in the multi-source database is called to correct the tolls.

[0124] In this embodiment, when calculating tolls using an offline service, the toll system first generates tolls by segment based on the toll standards in the static database. The toll standards include the road type and toll rate for each road segment. After the tolls are calculated, third-party data from a multi-source database is used to correct them during the toll output process. This third-party data includes actual tolls reported by drivers who have already traveled the corresponding road segments. This ensures that the final toll output is consistent with actual toll costs, improving the user experience.

[0125] In an optional embodiment, in the process of online calculation of tolls based on each billing unit, the charging standard segments in the static database are called to generate tolls, and in the output process, third-party data in the multi-source database are called to correct the tolls, and the tolls are displayed superimposed on other information in the dynamic database.

[0126] In this embodiment, toll calculations using online services first generate tolls by sourcing the toll standards in a static database. These standards include the road type and toll rate for each road segment. After the tolls are calculated, third-party data from a multi-source database is used to correct them during the toll output process. This third-party data includes actual tolls reported by users who have traveled the corresponding road segments. Discount information is then retrieved from the dynamic database in real time via the network to further update the calculated tolls. The final discounted tolls, along with relevant discount information, are then presented to the user.

[0127] Reference Figure 5, which shows a flow chart of the disclosed billing data model in offline services and downstream services. In this example, the static database stores pre-collected and program-processed charging standards for different road sections and different vehicle models, including data collected in the field, data collected by crowdsourcing, and intelligence collection data; the multi-source database stores third-party data such as feedback or UGC data; and the dynamic database stores road travel discount data. The static database is mainly used for the calculation of road tolls, the multi-source database mainly integrates and corrects the tolls calculated by the static database, and the dynamic database adds the relevant discount data to the calculated tolls. Finally, the corresponding tolls are presented to the user through offline services or online services.

[0128] Reference Figure 6 , which shows an example of the toll fee estimation method disclosed in the present invention. Figure 6 In the example shown, when the planned path on the application side is to enter the highway at toll station 1 and leave the highway at toll station 2, the corresponding key nodes are K-N1 and K-N2, thereby determining that the corresponding highway main line unit is M-U1. Therefore, the cost of the planned path is the cost corresponding to the highway main line unit M-U1. When the planned path on the application side is to enter the highway at toll station 1 and leave the highway at toll station 3, the corresponding key nodes are K-N1, K-N2, K-N3, and K-N4, thereby determining that the corresponding highway main line units are M-U1, M-U2, and M-U3. Therefore, the cost of the planned path is the cumulative sum of the corresponding costs of the highway main line units M-U1, M-U2, and M-U3.

[0129] By using gantries as key nodes for demarcating expressway main lines, the number of expressway main line units used in the demarcation process is reduced, reducing the amount of data stored. This also reduces the amount of data calculated when subsequently calculating fees based on expressway main lines and modified planned routes, speeding up operations and ensuring convenient and fast user interaction, enhancing the user experience. At the same time, road gantries, as infrastructure equipment, are highly stable. Because the number of gantries is significantly smaller than the number of toll stations used in previous fee calculations, they reduce the amount of data collected and calculated, while also reducing the cost of data collection and, to a certain extent, improving the accuracy of data statistics. In subsequent actual fee calculations, the reduction in data speeds up fee calculations, making the user interaction process simpler and faster, and improving the practical experience. This addresses the difficulty of achieving one-stop fee calculations nationwide after the removal of provincial boundary toll stations.

[0130] In addition, the toll estimation method disclosed in the present invention uses the actual distance traveled by the vehicle as the basis for fee calculation. Compared with the existing intelligent calculation of tolls based on the shortest path between toll stations, it is more in line with the principle of charging according to the actual driving path and is in line with the toll collection method of highways under the new national standard, thereby improving the accuracy and fairness of toll collection.

[0131] Product Example:

[0132] Reference Figure 7 , which shows an embodiment of the navigation system of the present disclosure. Figure 7 In the illustrated embodiment, the navigation system of the present disclosure includes: a module 701 for obtaining the passage path information and billing parameter information corresponding to the passage path; a module 702 for obtaining the coordinates of the billing key points in the passage path information, and calling a pre-created billing model based on the billing key point coordinates and the billing parameter information to calculate the billing unit associated with the passage path; and a module 703 for calculating the toll generated corresponding to the passage path based on the billing unit, and outputting the passage path information including the starting point, end point, and optional waypoint information.

[0133] In this embodiment, the navigation application inputs the start and end point information, which is then transmitted to the map provider server. The map provider server then performs route planning based on the start and end point information and transmits the results to the data service center. The data service center calculates the toll associated with the planned route based on the planned route and stored data on the various high-speed line units divided by gantry nodes, as well as the tolls associated with each unit. The data service center then feeds this toll back to the map provider server, which then feeds it back to the navigation application, presenting the toll information for the planned route to the user.

[0134] In an optional embodiment, the key nodes on the expressway are determined based on the position of the gantry on the expressway, and the expressway is divided with the key nodes as the dividing points to obtain multiple continuous expressway units which are stored in the data service center; and the toll corresponding to each expressway unit is determined according to the billing principle and stored in the data service center.

[0135] In this optional embodiment, the data service center obtains in advance the data on the various high-speed line units obtained by dividing the high-speed line with the gantry as the key node, as well as the tolls corresponding to each high-speed line unit. The gantry information on the high-speed line is obtained through field collection and intelligence gathering, and the gantry information is matched with the map data to obtain the key nodes for dividing the high-speed line. The high-speed line is then divided to obtain the corresponding high-speed line units. The fees corresponding to each high-speed line unit are calculated according to the billing principle. Then, based on the planned path, the high-speed line units corresponding to the planned path are obtained. When calculating the fees, the fees corresponding to each high-speed line unit are accumulated to obtain the fee corresponding to the planned path.

[0136] Reference Figure 8 , which shows an example of the navigation system of the present disclosure. Figure 8 In the illustrated example, the navigation system includes an application, a map service, a toll service gateway, and a data service center. When inquiring about road tolls, the application enters the starting and ending point information. The application then transmits this information to the map service via a network protocol. The map service plans a route based on this starting and ending point information, while the toll service gateway performs relevant verifications, including validating the legitimacy of relevant parameters, implementing traffic control monitoring, and managing traffic. Finally, the planned route obtained by the map service is transmitted to the data service center. The data service center extracts the key nodes and high-speed route elements corresponding to the planned route from a database, then accumulates the costs of each high-speed route element to determine the corresponding route fare. Finally, the data service center feeds the corresponding route fare back to the map service, which then transmits this fare back to the application for presentation to the user.

[0137] Reference Figure 9 , which shows an example of using the navigation system of the present disclosure. Figure 9 As shown, first the user applies to open an account. After receiving the user's application, the corresponding interface is opened according to the user's application; the interface is called to load the planned route, and the toll corresponding to the planned route is calculated through the cloud database, and finally the toll is returned to the user.

[0138] By using the gantry as the key node for dividing the expressway main line, the number of expressway main line units in the division is reduced, and the amount of data stored is reduced; and in the subsequent cost calculation based on the expressway main line and the modification of the planned path, the amount of data calculation is reduced, the speed of calculation is improved, and the interaction with the user is ensured to be convenient and fast, thereby improving the experience.

[0139] To implement the above method embodiment, this embodiment discloses a toll fee intelligent estimation software, such as Figure 10 As shown, the toll fee intelligent estimation software includes the following components:

[0140] An input module is used to obtain travel path information and charging parameter information corresponding to the planned route; wherein the travel path information includes the travel path and its starting point, end point, and / or optional waypoint information; the charging parameter information includes time, vehicle type, license plate, load, and / or road type information including bridge and tunnel roads and / or general roads;

[0141] The estimation module is used to obtain the coordinates of the key charging points according to the passage path information, and call the pre-created charging model and rate data model based on the coordinates of the key charging points and the charging parameter information to calculate the charging unit associated with the passage path;

[0142] A billing module is used to calculate the toll generated by the passage path according to the billing unit;

[0143] The output module is used to output the toll according to the travel path information and billing parameter information.

[0144] Accordingly, this embodiment discloses a component-based lightweight map data service cloud platform, such as Figure 11 As shown, the map data business cloud platform includes the following components:

[0145] User interaction components are used to provide access to the platform through Web, API, or SDK;

[0146] Unified authentication component for identity authentication, functional permission management, access control and / or dynamic configuration;

[0147] A database component for storing electronic map data, coordinates of key charging points, various high-speed line units pre-divided according to the coordinates of the key charging points, and tolls corresponding to the high-speed line units;

[0148] Product editing components, configured with an independent data editing space, are used to generate customized data products based on editing, transforming, fusing, checking, differencing, batch processing data in database components and / or combining with imported reference data;

[0149] Product release components, used for data and business version management, permission management, incremental data release, real-time push, service launch, traffic control, and service shutdown;

[0150] A business customization component is used to customize map data products and services according to needs, including matching travel paths with expressway units, extracting and outputting the billing units corresponding to each expressway unit corresponding to the travel path;

[0151] Statistical analysis component, used for usage statistics, hot data analysis, operation and maintenance monitoring, and early warning.

[0152] As an optional implementation, in the above-mentioned component-based lightweight map data service cloud platform, the unified authentication component further includes:

[0153] Load balancer, which monitors network ports and dynamically configures network resources;

[0154] API gateway module, used for API routing and access control;

[0155] Authentication module, used for user identity authentication and function permission management;

[0156] As an optional implementation, in the above-mentioned component-based lightweight map data business cloud platform, the database component further includes:

[0157] Static database, used to store pre-collected and program-processed charging standards for different road sections and different vehicle types;

[0158] A dynamic database for storing preferential information, including discount information on road tolls and / or free road travel information;

[0159] A multi-source database is used to store third-party data, including toll receipt data of various vehicles actually passing through various road sections, which is used to verify and correct the tolls calculated in offline billing scenarios.

[0160] Accordingly, this embodiment discloses a smart travel client, such as Figure 11 As shown, the smart travel client includes the following components:

[0161] The user interaction module is used to obtain user information and billing parameter information; the billing parameter information includes time, vehicle type, license plate, load and / or road type information including bridge and tunnel roads and / or general roads;

[0162] A route planning module, configured to generate at least one travel route based on the starting point, end point, and / or optional waypoint information of the trip;

[0163] A billing module, configured to calculate the toll corresponding to the travel path based on the billing unit obtained from any of the aforementioned map data service cloud platforms;

[0164] The output module is used to output the toll according to the travel path and billing parameter information.

[0165] In one embodiment of the present disclosure, a computer-readable storage medium is disclosed, which stores computer instructions, wherein the computer instructions are operated to execute the toll fee estimation method disclosed in any of the above embodiments. The storage medium may be directly in hardware, in a software module executed by a processor, or in a combination of the two.

[0166] It should be emphasized that the method embodiments and product embodiments disclosed herein have the same inventive concept, and the beneficial effects produced by the aforementioned method embodiments can also be produced by the product embodiments. They will not be repeated here, and reference may be made to the aforementioned method embodiments.

[0167] The software modules may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such that the processor can read information from and write information to the storage medium.

[0168] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic, discrete hardware components, or any combination thereof. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors combined with a DSP core, or any other such configuration. In the alternative, the storage medium may be integral to the processor. The processor and storage medium may reside in an ASIC. The ASIC may reside in a terminal. In the alternative, the processor and storage medium may reside in the terminal as discrete components.

[0169] In one embodiment of the present disclosure, a smart travel fare estimation software is provided, wherein a computer program is run in the fare estimation software, wherein the computer program is run to execute the toll estimation method described in any embodiment.

[0170] In the embodiments provided in the present disclosure, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or through-connection shown or discussed can be through some interfaces, indirect coupling or through-connection of devices or units, which can be electrical, mechanical or other forms.

[0171] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0172] The above are merely embodiments of the present disclosure and are not intended to limit the patent scope of the present disclosure. Any equivalent structural transformations made using the contents of the present disclosure and the drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present disclosure.

Claims

1. A toll fee estimation method, characterized in that: include: Obtain the travel path information and billing parameter information corresponding to the planned path; Obtaining the coordinates of the key charging points in the passage path information, and calling a pre-created charging model and rate data model based on the key charging point coordinates and the charging parameter information to calculate the charging unit associated with the passage path; Calculating the toll generated by the passage path according to the charging unit and outputting the toll; The travel path information includes the travel path and its starting point, end point, and / or optional waypoint information; the charging parameter information includes time, vehicle type, license plate, load, and / or road type information including bridge, tunnel, and / or general road; In the billing model, during the offline calculation of tolls according to each billing unit, charging standards in a static database are called to generate tolls in segments, and third-party data in a multi-source database is called to correct the tolls during the output process; and / or, In the billing model, according to each billing unit, during the process of online toll calculation, the charging standards in the static database are called to generate tolls in sections, and during the output process, the third-party data in the multi-source database is called to correct the tolls, and the tolls are displayed superimposed on other information in the dynamic database; Among them, the static database stores the charging standards corresponding to different road sections and different vehicle models that have been collected and processed in advance; the dynamic database stores preferential information, which includes discount information on road charges and / or free road driving information; the multi-source database stores third-party data, which includes charging voucher data of various vehicles actually passing through various road sections, which is used to verify and correct the toll calculated in the offline billing scenario.

2. The toll fee estimation method according to claim 1, characterized in that: The method further includes: calling a pre-created billing model according to the billing key point coordinates and the billing parameter information to calculate the billing unit; Determine, based on the coordinates of the charging key point, a segmented road corresponding to the travel path, wherein the nth charging unit corresponds to the nth segmented road, where n is an integer greater than or equal to 1; Based on the nth segmented road and the vehicle type information in the charging parameter information, calling a rate data model corresponding to the nth segmented road, and obtaining an nth road rate and an nth bridge and tunnel rate based on the rate data model and the charging parameter information; According to the road line length of the nth divided road, the nth road rate and the nth bridge and tunnel rate, the billing model calculates the corresponding nth road billing unit and the nth bridge and tunnel billing unit, takes the sum of the nth road billing unit and the nth bridge and tunnel billing unit to obtain the nth billing unit, and accumulates all the obtained nth billing units to obtain the billing unit.

3. The toll fee estimation method according to claim 2, characterized in that: The method further includes: regularly updating the rate data model, and correspondingly updating the billing model according to the rate data model; and / or, Obtaining billing discount information based on the travel time and path planning information in the billing parameter information; The toll generated corresponding to the passage path is calculated based on the billing discount information and the billing unit; wherein the billing discount information includes at least one of a billing discount rate for a specific road section, a billing discount rate for a specific time period, a billing discount rate for a specific vehicle model, and a billing discount rate for a specific license plate location.

4. The toll fee estimation method according to claim 3, characterized in that: The calculating, according to the charging unit, the toll generated corresponding to the passage path, further includes: For offline services, the toll is calculated and outputted by matching the tolls of different vehicle types corresponding to the billing units stored in the offline database with the travel path information and / or the billing parameter information; and / or For online services, based on the input travel path information and / or the billing parameter information, the billing unit stored in the online database on the network cloud is called through the data interface to calculate the toll in real time and feed it back to the user.

5. A toll fee intelligent estimation software, characterized by: include: An input module is configured to obtain route information and charging parameter information corresponding to the planned route; wherein the route information includes the route and its starting point, end point, and / or optional waypoint information; and the charging parameter information includes time, vehicle type, license plate, load, and / or road type information including bridge, tunnel, and / or general road. an estimation module, configured to obtain the coordinates of the corresponding charging key points according to the passing path information, and to call a pre-created charging model and rate data model based on the charging key point coordinates and the charging parameter information to calculate the charging unit associated with the passing path; A charging module, configured to calculate a toll corresponding to the passage path according to the charging unit; An output module, configured to output the toll fee according to the toll path information and the charging parameter information; In the billing model, during the offline calculation of tolls according to each billing unit, charging standards in a static database are called to generate tolls in segments, and third-party data in a multi-source database is called to correct the tolls during the output process; and / or, In the billing model, according to each billing unit, during the process of online toll calculation, the charging standards in the static database are called to generate tolls in sections, and during the output process, the third-party data in the multi-source database is called to correct the tolls, and the tolls are displayed superimposed on other information in the dynamic database; Among them, the static database stores the charging standards corresponding to different road sections and different vehicle models that have been collected and processed in advance; the dynamic database stores preferential information, which includes discount information on road charges and / or free road driving information; the multi-source database stores third-party data, which includes charging voucher data of various vehicles actually passing through various road sections, which is used to verify and correct the toll calculated in the offline billing scenario.

6. A component-based map data business cloud platform, characterized by: include: User interaction components are used to provide access to the platform through Web, API, or SDK; Unified authentication component for identity authentication, functional permission management, access control and / or dynamic configuration; A database component for storing electronic map data, coordinates of key charging points, various high-speed line units pre-divided according to the coordinates of the key charging points, and tolls corresponding to the high-speed line units; A product editing component, configured with an independent data editing space, for generating customized data products based on editing, converting, fusing, checking, differencing, batch processing of data in the database component and / or combining with imported reference data; Product release components, used for data and business version management, permission management, incremental data release, real-time push, service launch, traffic control, and service shutdown; A service customization component, used to customize map data products and services according to needs, including matching the travel path with the expressway main line unit, extracting the billing unit corresponding to each expressway main line unit corresponding to the travel path, and outputting it; Statistical analysis component, used for usage statistics, hot data analysis, operation and maintenance monitoring, and early warning; Wherein, the component-based map data service cloud platform includes the toll intelligent estimation software as described in claim 5.

7. The component-based map data service cloud platform according to claim 6, characterized in that: The unified authentication component further includes: Load balancer, which monitors network ports and dynamically configures network resources; API gateway module, used for API routing and access control; An authentication module, used to authenticate users and manage their functional permissions; and / or The database component further includes: Static database, used to store pre-collected and program-processed charging standards for different road sections and different vehicle types; A dynamic database for storing preferential information, wherein the preferential information includes discount information on road charges and / or free road travel information; A multi-source database is used to store third-party data, including toll voucher data of various vehicles actually passing through various road sections, which is used to verify and correct the tolls calculated in the offline billing scenario.

8. A smart travel client, characterized in that: include: A user interaction module is used to obtain user information and billing parameter information; the billing parameter information includes time, vehicle type, license plate, load, and / or road type information including bridge and tunnel roads and / or general roads; A route planning module, configured to generate at least one travel route based on the starting point, end point, and / or optional waypoint information of the trip; a billing module, configured to calculate a toll corresponding to the travel path according to a billing unit obtained from the map data service cloud platform according to claim 6 or 7; An output module is used to output the toll according to the toll path and the charging parameter information.

9. A computer device, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer instructions, and the processor operates the computer instructions to execute the toll fee estimation method according to any one of claims 1 to 4.

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