A method and system for highway diversion based on multi-source data

Abstract

This invention provides a method and system for highway traffic diversion based on multi-source data. The method includes: selecting a target highway segment for traffic diversion based on acquired highway transaction data; determining non-competitive highway segments surrounding the selected target highway segment based on electronic map data; calculating the number of pedestrians on the non-competitive highway segments and the target highway segment based on terminal signaling data, thereby calculating the traffic flow of the non-competitive highway segments using the traffic flow data of the target highway segment; selecting a non-competitive highway segment with a traffic flow greater than that of the target highway segment as the diverted segment, and controlling the base station through a mobile communication operator's server to send traffic diversion instruction information to at least some users on the diverted segment. This invention, based on multi-source data analysis, not only balances traffic flow across different types of roads, improving user experience, but also enhances the flexibility of road network traffic adjustment.

Description

Technical Field

[0001] This invention relates to the field of highway traffic technology, and in particular to a highway traffic diversion method and system based on multi-source data. Background Technology

[0002] With the continuous construction of transportation infrastructure, passengers have a much wider range of travel options. Current major highways mainly include expressways, national highways, and provincial highways. As toll-free roads continue to improve, the environmental quality of national and provincial toll-free roads is also rising, making more users willing to choose to travel on toll-free roads. However, this also increases the likelihood of traffic congestion and even a higher rate of traffic accidents on toll-free roads due to heavy traffic volume.

[0003] Compared to toll-free national and provincial highways, expressways have higher road standards, allow higher speeds, are typically wider, and lack traffic lights and cross traffic flow. Therefore, expressways generally offer advantages such as better road conditions, faster travel times, and higher safety. How to scientifically and rationally formulate traffic diversion strategies to effectively alleviate traffic pressure and balance traffic flow across the road network is a pressing problem that needs to be solved.

[0004] Furthermore, highways are toll roads, and tolls are charged except during specific holidays, which to some extent limits highway traffic flow. How to fully consider the differences between toll-free and free roads to implement differentiated tolling, balancing traffic flow across the road network while helping the logistics industry reduce costs and increase efficiency, is also a problem that needs to be solved. Summary of the Invention

[0005] In view of this, embodiments of the present invention provide a high-speed traffic diversion method and system based on multi-source data to efficiently balance the differences in traffic flow on different roads, improve the traveler experience, and enhance the flexibility of road network traffic adjustment.

[0006] One aspect of the present invention provides a highway traffic diversion method based on multi-source data, the method comprising the following steps:

[0007] Acquire highway transaction data within a predetermined area, determine traffic flow and direction data of toll stations based on the acquired transaction data, select target toll stations for diversion based on traffic flow size, and select target highway sections and directions for diversion based on highway route data associated with the target toll stations.

[0008] Based on electronic map data, identify the non-highway competing road sections around the selected target highway section for traffic diversion;

[0009] The system obtains terminal signaling data from base stations covering non-high-speed competitive road sections and base stations covering the target high-speed road sections from the mobile communication operator's server. It calculates the number of pedestrians on the non-high-speed competitive road sections based on the terminal signaling data from the base stations covering the target high-speed road sections, and calculates the number of pedestrians on the target high-speed road sections based on the terminal signaling data from the base stations covering the target high-speed road sections.

[0010] Based on the pedestrian and vehicle traffic data on the target highway sections, the correspondence between pedestrian and vehicle traffic is obtained, and based on the determined correspondence, the traffic flow of non-highway competitive sections corresponding to pedestrian traffic is calculated.

[0011] Select non-highway competing road sections with traffic flow greater than the target high-speed road section as the road sections to be diverted, and control the base station through the mobile communication operator's server to send diversion instruction information to at least some users on the road sections to be diverted.

[0012] In some embodiments of the present invention, the method further includes: calculating differentiated charging parameters based on the cost quantification indicators and corresponding weights of multiple differentiated factors obtained from the target highway section and the section to be diverted, and charging vehicles on the target highway section based on the calculated differentiated charging parameters.

[0013] In some embodiments of the present invention, the multiple differentiation factors obtained based on the target highway segment and the segment to be diverted include multiple of the following factors: the difference in toll fees between the target highway segment and the segment to be diverted, the difference in travel time between the target highway segment and the segment to be diverted, and the difference in driving safety between the target highway segment and the segment to be diverted.

[0014] The cost quantification indicators corresponding to multiple differentiating factors are multiple discount values ​​for standard charges corresponding to multiple differentiating factors, and the differentiated charging parameters are the differentiated charging discount ratios for standard charges; or, the cost quantification indicators corresponding to multiple differentiating factors are multiple charging amount reference values ​​corresponding to multiple differentiating factors, and the differentiated charging parameters are differentiated charging amount indicators calculated based on multiple charging amount reference values ​​and corresponding weights corresponding to multiple differentiating factors.

[0015] In some embodiments of the present invention, differentiated toll parameters are calculated based on cost quantification indicators and corresponding weights corresponding to multiple differentiating factors obtained from the target highway segment and the segment to be diverted, including:

[0016] Based on multiple differentiated factors obtained from the target highway sections and the sections to be diverted, multiple discount values ​​and corresponding weights are assigned to the standard toll, and a differentiated toll discount ratio is calculated based on pre-calculated user discount level indicators; or

[0017] Based on multiple differentiated factors obtained from the target highway section and the section to be diverted, there are multiple reference values ​​and corresponding weights for the toll amount, as well as differentiated toll amount indicators calculated based on pre-calculated user discount level indicators.

[0018] The user discount level indicator is calculated based on one or more of the following indicators: the user's historical mileage on highways, the user's frequency of driving on highways, and the user's credit rating.

[0019] In some embodiments of the present invention, the target highway segment and traffic direction for traffic diversion are selected based on the highway route data associated with the target toll station, including:

[0020] Based on the traffic volume corresponding to different traffic flow directions in the highway route data associated with the target toll station, highway sections with specific traffic flow directions that meet the traffic volume requirements are selected as the target highway sections for traffic diversion, and the specific traffic flow direction is the selected travel direction.

[0021] In some embodiments of the present invention, the base stations covering the target highway section include base stations located within the set range of highway positioning points. The highway positioning points include the starting point and ending point of the target highway section, toll stations on the target highway section, and key highway transit points. Furthermore, the base stations covering the target highway section are divided into a highway entrance subgroup, a highway transit point subgroup, and a highway exit subgroup.

[0022] Among them, the key high-speed transit points are the location points that belong only to the target high-speed section of the diversion; the base stations whose communication range covers the toll stations and key high-speed transit points on the target high-speed section of the diversion belong to the transit point subgroup; the base stations whose communication range covers the starting point of the target high-speed section of the diversion belong to the high-speed entrance subgroup; and the base stations whose communication range covers the ending point of the target high-speed section of the diversion belong to the high-speed exit subgroup.

[0023] The base station group covering the competing road segment includes base stations located within the range of the competing location points. The competing location points include the starting and ending points of the non-high-speed competing road segment and the key competitive path points. The base stations covering the non-high-speed competing road segment include the competing entry subgroup, the competing exit subgroup, and the competing path point subgroup.

[0024] Among them, the key competitive path points are the location points that belong only to non-high-speed competitive road sections; base stations whose communication range covers the key competitive path points belong to the competitive path point subgroup, base stations whose communication range covers the starting point of the non-high-speed competitive road section belong to the competitive entry subgroup, and base stations whose communication range covers the ending point of the non-high-speed competitive road section belong to the competitive exit subgroup.

[0025] Among them, at least one of the high-speed entrance subgroup, high-speed transit point subgroup, and high-speed exit subgroup has a communication range that only covers the target high-speed section of the diverted traffic, or at least one of the competing entrance subgroup, competing exit subgroup, and competing transit point subgroup has a communication range that only covers non-high-speed competing sections.

[0026] In some embodiments of the present invention, after acquiring terminal signaling data of base stations covering non-high-speed competitive road sections and terminal signaling data of base stations covering target high-speed road sections, the method further includes: performing data preprocessing on the terminal signaling data of base stations covering non-high-speed competitive road sections, and performing data preprocessing on the terminal signaling data of base stations covering target high-speed road sections.

[0027] Data preprocessing is performed on terminal signaling data for base stations covering non-high-speed, non-competitive road sections, including:

[0028] The terminal signaling data of users whose travel time on non-high-speed competitive road segments falls within the travel time range of those non-high-speed competitive road segments are filtered out; whereby the travel time range of non-high-speed competitive road segments is set based on the average travel time of those non-high-speed competitive road segments;

[0029] Filter all terminal signaling data during the fixed train travel period; and

[0030] Filter terminal signaling data corresponding to users who appear only in one or two of the competition entry subgroup, competition exit subgroup, and competition path point subgroup;

[0031] Data preprocessing is performed on the terminal signaling data of base stations covering the target highway sections for traffic diversion, including:

[0032] Filter terminal signaling data corresponding to users whose travel time on the target highway segment exceeds the average travel time on that target highway segment;

[0033] Filter all terminal signaling data during the fixed train travel period; and

[0034] Filter terminal signaling data corresponding to users that appear only in one or two of the highway entrance subgroup, highway transit point subgroup, and highway exit subgroup;

[0035] The average travel time of non-high-speed competitive road sections is the ratio of the travel mileage of non-high-speed competitive road sections to the average travel speed of non-high-speed competitive road sections. The average travel time of the target high-speed road sections is obtained based on highway transaction data.

[0036] In some embodiments of the present invention, at least some users include free users and users who use heavy vehicles;

[0037] Among them, free users are those who pass through the highway at a set frequency during the free period; heavy vehicle users are those whose number of passes is lower than the average number of passes and whose vehicle weight is higher than the average weight; the frequency and number of passes are determined based on highway transaction data.

[0038] Another aspect of the present invention provides a highway traffic diversion system based on multi-source data, including a processor, a memory, and a computer program / instructions stored in the memory. The processor is used to execute the computer program / instructions, and when the computer program / instructions are executed, the system implements the steps of the method described in any of the above embodiments.

[0039] Another aspect of the present invention provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the method described in any of the above embodiments.

[0040] This invention proposes a method and system for diverting traffic on highways based on multi-source data. By comparing and analyzing the actual traffic conditions of highways and surrounding competing road sections, it makes full use of multi-source data such as highway transaction data, map path data, and terminal signaling data to accurately locate and divert users. This not only improves the user experience but also enhances the flexibility of road network traffic adjustment.

[0041] Additional advantages, objects, and features of the invention will be set forth in part in the description which follows, and will also become apparent in part to those skilled in the art upon studying the description, or may be learned by practice of the invention. The objects and other advantages of the invention can be realized and obtained by means of the structures specifically pointed out in the description and drawings.

[0042] Those skilled in the art will understand that the objectives and advantages achievable with the present invention are not limited to those specifically described above, and that the above and other objectives achievable with the present invention will become clearer from the following detailed description. Attached Figure Description

[0043] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, are not intended to limit the scope of the invention. In the drawings:

[0044] Figure 1This is a flowchart illustrating a highway traffic diversion method based on multi-source data in one embodiment of the present invention.

[0045] Figure 2 This is a schematic diagram illustrating the process of determining the target highway section and traffic direction in one embodiment of the present invention.

[0046] Figure 3 This is a schematic diagram illustrating the process of determining the traffic diversion section in one embodiment of the present invention.

[0047] Figure 4 This is a schematic diagram illustrating the main idea of ​​a highway traffic diversion method based on multi-source data in one embodiment of the present invention. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the embodiments and accompanying drawings. Here, the illustrative embodiments and descriptions of this invention are used to explain the invention, but are not intended to limit the invention.

[0049] It should also be noted that, in order to avoid obscuring the invention with unnecessary details, only the structures and / or processing steps closely related to the solution according to the invention are shown in the accompanying drawings, while other details that are not closely related to the invention are omitted.

[0050] It should be emphasized that the term "including / comprises" as used herein refers to the presence of a feature, element, step, or component, but does not exclude the presence or addition of one or more other features, elements, steps, or components.

[0051] In the following description, embodiments of the invention will be illustrated with reference to the accompanying drawings. In the drawings, the same reference numerals represent the same or similar parts, or the same or similar steps.

[0052] To address the current imbalance between traffic flow on toll and free roads, this application proposes a highway traffic diversion method based on multi-source data. By utilizing multi-source data to accurately locate users requiring traffic diversion and providing them with targeted guidance, traffic congestion can be alleviated and traffic efficiency improved. Furthermore, this invention can also determine differentiated toll strategies based on factors that users are sensitive to regarding the differences between toll and free roads, such as differences in current toll standards, travel time, and driving safety, in order to improve traffic diversion effectiveness and further enhance the user experience.

[0053] As an example, this invention integrates data from different sources and dimensions, such as highway transaction data, road network map data, and terminal signaling data from mobile communication operators, to form more comprehensive, accurate, and effective basic information. This allows for precise user location and the delivery of referral information, thereby achieving effective customer referral. Furthermore, this invention comprehensively considers differentiating factors such as current toll standard differences, travel time differences, and driving safety differences to assist in generating differentiated tolling decisions. Moreover, it can confirm user discount level indicators based on user driving history information, and further use user discount level indicators as differentiated tolling decision factors to determine differentiated tolling parameters, thereby significantly improving the efficiency of referral and user experience.

[0054] Figure 1 This is a flowchart illustrating a highway traffic diversion method based on multi-source data in one embodiment of the present invention. Figure 1 As shown, the method includes steps S110-S150.

[0055] Step S110: Obtain highway transaction data within the predetermined area, determine the traffic flow and direction data of the toll station based on the obtained transaction data, select the target toll station for diversion based on the traffic flow size, and select the target highway section and direction of traffic for diversion based on the highway route data associated with the target toll station.

[0056] More specifically, highway transaction data can be obtained through identification communication between highway toll stations and vehicles. This data includes toll station entrance and exit numbers, license plate numbers, vehicle types, travel routes, and transaction amounts. Highway transaction data can be obtained directly from toll stations within a predetermined area, or from the ETC (Electronic Toll Collection) system. Based on the toll station entrance and exit numbers in the highway transaction data, traffic flow direction can be determined. The toll station's traffic flow direction data includes all traffic directions determined by the highway transaction data. Furthermore, the cross-sectional traffic flow volume for each traffic flow direction at the toll station within a specific time period can be calculated using the highway transaction data; that is, the toll station's traffic flow volume data.

[0057] Furthermore, to ensure the most efficient possible alleviation of traffic congestion, predetermined areas can be designated based on geographical locations where traffic congestion frequently occurs. This method of designating predetermined areas is merely an example; the present invention does not impose specific limitations on the location and size of the predetermined areas, and adjustments can be made according to actual application needs.

[0058] As an example, the toll station with the largest total traffic flow in all traffic directions within a predetermined area can be selected as the target toll station for traffic diversion, or the toll station with the smallest total traffic flow in all traffic directions within the predetermined area can be selected as the target toll station for traffic diversion; the toll station with the largest traffic flow in a certain traffic direction within the predetermined area can be selected as the target toll station for traffic diversion, or the toll station with the smallest traffic flow in a certain traffic direction within the predetermined area can be selected as the target toll station for traffic diversion; only one toll station can be selected as the target toll station for traffic diversion, or multiple toll stations can be selected as the target toll stations for traffic diversion. The method of selecting the target toll station for traffic diversion in this invention is not limited to these.

[0059] In some embodiments of the present invention, the target highway segment and traffic direction for traffic diversion are selected based on the highway route data associated with the target toll station, including:

[0060] Based on the traffic volume corresponding to different traffic flow directions in the highway route data associated with the target toll station, highway sections with specific traffic flow directions that meet the traffic volume requirements are selected as the target highway sections for traffic diversion, and the specific traffic flow direction is the selected travel direction.

[0061] More specifically, highway toll stations are typically associated with multiple highways, meaning different highways may pass through the same toll station. Therefore, based on the highway route data associated with the target toll station (or using highway network map data), multiple highway segments associated with the target toll station can be obtained. A highway segment can be selected from these multiple highway segments associated with the target toll station using a custom selection strategy. However, considering that the purpose of this application is traffic diversion, this application selects highway segments with specific traffic flow directions that meet the requirements based on traffic flow volume in different traffic flow directions. These highway segments are then used as the target highway segments for traffic diversion, and the traffic flow direction of the selected target highway segments can be a specific direction of travel.

[0062] As an example, to better achieve the goal of traffic diversion from highways, the highway segment with the highest traffic volume can be selected as the target highway segment for traffic diversion (the higher the traffic volume of a highway segment, the higher the likelihood that it will be chosen by passing users). The highway segments associated with the target toll stations are obtained from the highway route data associated with the target toll stations. Based on the traffic flow direction and volume data of the target toll stations, the total traffic volume of the highway segments associated with the target toll stations having the same traffic flow direction is calculated. The traffic flow direction with the highest total traffic volume is obtained, and the highway segment associated with the target toll station corresponding to the traffic flow direction with the highest total traffic volume is selected from the highway segments associated with the target toll station with the highest total traffic volume. This determines the target highway segment and traffic direction for traffic diversion. That is, based on the traffic flow direction data and traffic volume data of the target toll stations, the traffic volume of the highway segment associated with the target toll station in a certain traffic flow direction can be calculated. Therefore, the traffic volume of the highway segment associated with the target toll station in the same traffic flow direction can be calculated, and the traffic flow direction with the largest traffic volume is determined as the direction of travel. Based on the traffic volume data, the highway segment associated with the target toll station with the largest traffic volume is selected from the highway segments associated with the target toll station in the direction of travel, and the target highway segment for traffic diversion can be determined.

[0063] As an example, consider a highway segment associated with the target toll station A, which includes segments B, C, and D. Based on the traffic flow direction and volume data of the target toll station, the traffic flow directions of segments B, C, and D at the target toll station A are a to b, b to c, and a to b, respectively. The traffic volumes of segments B, C, and D are 5, 8, and 7, respectively. Therefore, the traffic volume for the a to b direction is 5 + 7 = 12, and the traffic volume for the b to c direction is 8. Thus, a to b is the traffic flow direction with the largest traffic volume. The traffic volumes of segments B and D with the traffic flow direction a to b at the target toll station A are 5 and 7, respectively. Therefore, segment D is selected as the target highway segment for traffic diversion.

[0064] As an example, when selecting target toll stations and target highway sections for traffic diversion, in addition to considering traffic flow and direction data, the impact of transaction volume (determined based on transaction amount) on the selection of target toll stations and target highway sections can also be considered.

[0065] For example, firstly, based on highway transaction data within a predetermined area, the total traffic flow in all directions at each toll station is calculated, and toll stations with total traffic flow exceeding a set traffic flow are identified as key toll stations. Secondly, based on highway transaction data, the transaction volume of each key toll station is calculated, and toll stations with transaction volumes exceeding a first set transaction volume are selected as target toll stations for traffic diversion. Then, using the highway route data associated with the target toll stations, the associated highway segments can be determined. Based on highway transaction data, segments with route transaction volumes exceeding a second set transaction volume are selected from the highway segments associated with the target toll stations, and the route transaction volumes for the same traffic flow direction (which can be determined based on the start and end points of the segment) are calculated. The traffic flow direction with the largest route transaction volume is then determined, thereby identifying the highway start and end points, i.e., the direction of travel. Finally, from the highway segments associated with the target toll stations whose traffic flow direction is the direction of travel, the segment with the largest route transaction volume is selected as the target highway segment for traffic diversion. Among them, the toll station transaction volume is the transaction volume of a certain highway toll station, and the route transaction volume represents the sum of the transaction volumes of all highway toll stations on a certain road segment; the second set transaction volume is greater than or equal to the first set transaction volume.

[0066] As an example, such as Figure 2 As shown, key toll stations can be identified based on highway transaction data. Then, the highway toll station with the highest transaction volume can be selected from the key toll stations and used as the target toll station for traffic diversion. Based on the highway route data associated with the target toll station, all routes containing the highway toll station with the highest transaction volume can be determined. Based on the highway transaction data, the top 10 routes with the highest transaction volume can be selected from all the determined routes. The transaction volume in the same traffic flow direction on the selected routes can be calculated. Based on the transaction volume, the highway start and end points and the target highway sections for traffic diversion can be determined.

[0067] For example, the maximum traffic flow direction is determined as follows: Path 1 includes two traffic flow directions, a to b and b to a, with transaction volumes of 10 and 8 respectively; Path 2 includes three traffic flow directions, c to d, d to c, and a to b, with transaction volumes of 7, 9, and 5 respectively; Path 3 includes two traffic flow directions, c to d and d to c, with transaction volumes of 14 and 5 respectively. Therefore, the transaction volume for traffic flow direction a to b is 10 + 5 = 15, the transaction volume for traffic flow direction b to a is 8, the transaction volume for traffic flow direction c to d is 7 + 14 = 21, and the transaction volume for traffic flow direction d to c is 9 + 5 = 14. It can be seen that the traffic flow direction with the largest transaction volume is c to d. Based on the traffic flow direction with the largest transaction volume, the starting point (point c) and the ending point (point d) of the expressway can be determined, i.e., the traffic direction is c to d. Path 2 has a transaction volume of 7 in the c to d traffic flow direction, and Path 3 has a transaction volume of 14 in the c to d traffic flow direction. Therefore, Path 3 is selected as the target expressway segment for traffic diversion.

[0068] The method of determining the traffic direction and the target highway section based on the maximum traffic flow mentioned in this invention is only an example. This invention is not limited to this. A section with a certain traffic flow direction can be selected from the highway sections associated with the target toll station according to a custom selection strategy.

[0069] For example, a customized selection strategy could be to select a highway segment with a relatively long mileage as the target highway segment for traffic diversion. Considering that the longer the mileage of a highway segment means that it is more likely to be selected by high-value users, the longest highway segment can be selected as the target highway segment for traffic diversion based on the highway route data associated with the target toll station (the direction of travel can be any direction of the target highway segment).

[0070] Step S120: Based on electronic map data, determine the non-highway competing road sections around the selected target high-speed road section.

[0071] More specifically, the target highway segment may include multiple highway entrances and exits. Vehicles traveling on other road segments can enter or exit the target highway segment through any of its entrances or exits. Therefore, the start and end points of the target highway segment can be obtained first based on the target highway segment and travel direction determined in step S110. Then, multiple other non-highway segments with the same start and end points can be obtained using electronic map data. Some or all of the other non-highway segments that are connected to the highway entrances and exits included in the target highway segment are designated as non-highway competing segments (i.e., travelers can enter the target highway segment from a non-highway competing segment and exit from the target highway segment to a non-highway competing segment).

[0072] For example, other non-highway sections between adjacent highway entrances and exits within the target highway segment can be considered as non-highway competing sections. Another example is a toll-free section parallel to the highway.

[0073] As an example, electronic maps can be obtained from traffic maps, third-party navigation software, or through on-site surveys.

[0074] This invention does not specifically limit the distance between other non-highway sections or non-highway competing sections and the target highway section for diversion; the distance can be adjusted according to the diversion requirements.

[0075] Step S130: Obtain terminal signaling data of base stations covering non-high-speed competitive road sections and terminal signaling data of base stations covering the target high-speed road sections from the mobile communication operator's server; calculate the number of pedestrians on the non-high-speed competitive road sections based on the terminal signaling data of base stations covering the target high-speed road sections; and calculate the number of pedestrians on the target high-speed road sections based on the terminal signaling data of base stations covering the target high-speed road sections.

[0076] More specifically, considering that real-time statistics on vehicles passing through non-highway competition sections cannot be obtained, this application introduces terminal signaling data generated when mobile communication operator base stations communicate with mobile terminal users. This data is then used to infer the number of vehicles passing through the non-highway competition section based on the vehicle traffic situation (primarily the number of vehicles in this application) of the target highway section. In other words, this application considers base stations around the non-highway competition section and the target highway section as "virtual gantries." Terminal signaling data for corresponding mobile terminal users is obtained through communication between vehicles passing through the non-highway competition section and the virtual gantries. Similarly, terminal signaling data assisting in highway transaction data is obtained through communication between vehicles passing through the target highway section and the virtual gantries. The terminal signaling data is obtained through communication between the mobile terminal and base stations near the section. The base stations can upload the obtained terminal signaling data to the mobile communication operator's server. The terminal signaling data includes at least one of the following: communication user information (e.g., user number), communication base station information (e.g., base station location or base station number, and the mobile communication operator to which the base station belongs), and communication time. Therefore, when a base station covers a non-high-speed competitive road segment or a high-speed road segment that is being diverted, the base station can communicate with the mobile terminals held by users traveling on the corresponding road segment to generate terminal signaling data for the base station covering the non-high-speed competitive road segment or the base station covering the high-speed road segment being diverted.

[0077] In some embodiments of the present invention, the base station covering the target highway section includes a base station located within the set range of the highway positioning point, and the base station covering the non-highway competing section includes a base station located within the set range of the competing positioning point.

[0078] More specifically, based on the handover relationships between mobile terminals (such as mobile phones) held by users traveling on a road segment and relevant location base stations within a reasonable time period, terminal signaling data can be obtained. Based on the existing physical base station locations of mobile communication operators, base stations covering the target highway segment and base stations covering non-highway competing segments can be determined according to highway positioning points and competing positioning points. For example, all base stations within a 3-kilometer radius of the highway positioning point can be selected as base stations covering the target highway segment.

[0079] As an example, the range of high-speed positioning points and the range of competing positioning points can be adjusted according to the density of base station distribution. The aforementioned 3-kilometer radius is only an example. This invention does not specifically limit the range values ​​of the high-speed positioning point setting range and the competing positioning point setting range. Furthermore, the high-speed positioning point setting range and the competing positioning point setting range can be the same or different. That is, this invention does not limit the size between the high-speed positioning point setting range and the competing positioning point setting range.

[0080] Furthermore, the high-speed positioning points include the locations of the starting and ending points of the target high-speed section, the locations of toll stations on the target high-speed section, and the locations of key highway transit points. Considering the actual origin of vehicles and potential errors caused by base stations not communicating with all users on the road segment, the base stations covering the target high-speed section can be divided into three groups: a high-speed entrance subgroup, a high-speed transit point subgroup, and a high-speed exit subgroup. Specifically, base stations whose communication range covers the locations of toll stations and key highway transit points on the target high-speed section belong to the transit point subgroup; base stations whose communication range covers the location of the starting point of the target high-speed section belong to the high-speed entrance subgroup; and base stations whose communication range covers the location of the ending point of the target high-speed section belong to the high-speed exit subgroup.

[0081] The competitive positioning points include the starting and ending points of non-high-speed competitive road segments, as well as the locations of key competitive path points. Considering the actual origin of vehicles and potential errors caused by base stations not communicating with all users on the road segment, base stations covering non-high-speed competitive road segments can be divided into three groups: a competitive entry subgroup, a competitive exit subgroup, and a competitive path point subgroup. Specifically, base stations whose communication range covers the locations of key competitive path points belong to the competitive path point subgroup; base stations whose communication range covers the starting point of the non-high-speed competitive road segment belong to the competitive entry subgroup; and base stations whose communication range covers the ending point of the non-high-speed competitive road segment belong to the competitive exit subgroup.

[0082] In some embodiments of the present invention, a critical waypoint is a location belonging only to a non-highway competitive road segment, and a critical waypoint for high-speed traffic is a location belonging only to the target high-speed road segment. That is, a critical waypoint is a location point belonging to a single path, not an intersection of one path and another. For example, if waypoint A is the intersection of path a and path b, then waypoint A cannot be a critical waypoint for both paths a and b; if waypoint B is a point belonging only to path c, then waypoint B can be a critical waypoint for path c. The location or distance of the critical waypoint can be determined according to specific circumstances, and the present invention does not impose specific limitations on it.

[0083] As an example, when grouping base stations, if the same base station does not belong to any multiple groups among the three groups of entrance group, exit group, and transit point group (for example, base station A cannot belong to both the entrance group and the transit point group at the same time; it must belong to either the entrance group or the transit point group), this can be achieved by adjusting the range of the location point settings.

[0084] In addition, to distinguish between terminal signaling data generated by base stations covering non-high-speed competitive road sections and terminal signaling data generated by base stations covering the target high-speed road sections for diversion, at least one of the high-speed entrance subgroup, high-speed transit point subgroup, and high-speed exit subgroup has a communication range that only covers the target high-speed road sections for diversion, or at least one of the competitive entrance subgroup, competitive exit subgroup, and competitive transit point subgroup has a communication range that only covers non-high-speed competitive road sections.

[0085] In some embodiments of the present invention, when the acquired raw terminal signaling data is applied to the transportation sector, inaccurate data may occur. Therefore, the raw terminal signaling data obtained by mobile communication operators can be cleaned to remove noise data in order to accurately reconstruct the target customer referral data. Data cleaning includes filtering out non-driving people (such as people living or active around the road segment), filtering out pedestrians on nearby roads (considering that users who appeared in all three subgroups on the same day must be pedestrians on that road segment, terminal signaling data of users who did not appear in all three subgroups can be filtered out), and if there are other public transportation modes such as railways or ships near the base station at fixed times, it is necessary to filter out people taking other public transportation. Therefore, after acquiring the terminal signaling data of base stations covering non-high-speed competitive road segments and the terminal signaling data of base stations covering the target high-speed road segments, the present invention also needs to perform data preprocessing on the terminal signaling data of base stations covering non-high-speed competitive road segments and base stations covering the target high-speed road segments.

[0086] Data preprocessing is performed on terminal signaling data for base stations covering non-high-speed, non-competitive road sections, including:

[0087] The system filters terminal signaling data corresponding to users whose travel time on non-high-speed competitive sections falls within the travel time range of the competitive entrance and exit subgroups. It also filters all terminal signaling data within fixed train travel periods (considering the high probability that train routes, such as those of high-speed rail, appear on non-high-speed competitive sections, filtering out all data within fixed train travel periods from the acquired terminal signaling data can be considered as filtering out people using other public transportation). Furthermore, it filters terminal signaling data corresponding to users who appear only in one or two of the competitive entrance, exit, and transit point subgroups. The travel time range for non-high-speed competitive sections is set based on the average travel time of those sections.

[0088] Data preprocessing is performed on the terminal signaling data of base stations covering the target highway sections for traffic diversion, including:

[0089] The system filters terminal signaling data for users whose travel time on the target highway segment (which can be determined based on the communication time of the highway entrance subgroup and the highway exit subgroup) is greater than the average travel time on the target highway segment; filters all terminal signaling data within the fixed train travel period; and filters terminal signaling data for users who have only appeared in one or two of the highway entrance subgroup, highway transit point subgroup, and highway exit subgroup.

[0090] The average travel time for non-highway competitive road sections is the ratio of the travel mileage of non-highway competitive road sections to the average travel speed of non-highway competitive road sections (which can be obtained through user surveys or on-site surveys). The average travel time for the target high-speed road sections can be obtained based on high-speed road transaction data, or it can be obtained by the ratio of the total travel distance (e.g., the total length between the start and end points of the high-speed road) to the average travel speed of the high-speed road (which can be obtained through user surveys or high-speed road transaction data).

[0091] Furthermore, terminal signaling data can be used to determine whether a user traverses a target highway segment or a non-highway competitive segment within a certain time period, thereby obtaining the number of passengers passing through the corresponding segment. Moreover, since the same communication user on the target highway segment appears in the terminal signaling data of the highway entrance subgroup, highway transit point subgroup, and highway exit subgroup, and the same communication user on the non-highway competitive segment appears in the competitive entrance subgroup, competitive exit subgroup, and competitive transit point subgroup, the number of passengers passing through the non-highway competitive segment can be calculated based on the terminal signaling data of any subgroup of base stations covering the non-highway competitive segment, and the number of passengers passing through the target highway segment can also be calculated based on the terminal signaling data of any subgroup of base stations covering the target highway segment.

[0092] As an example, in the absence of other public transportation options operating at fixed times (i.e., the terminal signaling data does not need to filter out all terminal signaling data within the train's fixed travel time), the number of passengers on the target highway section can be determined as follows: From the terminal signaling data obtained from the base stations covering the target highway section, obtain all users appearing in the highway entrance subgroup, highway transit point subgroup, and highway exit subgroup within a set time period (e.g., calculated on a daily basis). This involves excluding mobile phone users who only appear in one or two subgroups (meaning mobile terminal users who have not appeared in all three subgroups). Then, sort the excluded terminal signaling data according to time sequence (communication time between the mobile terminal and the base station), and exclude mobile phone users whose start and end times on the target highway section exceed the average travel time of that target highway section. This will give the number of passengers on the target highway section for that day.

[0093] In the absence of other public transportation options operating at fixed times in the vicinity (i.e., terminal signaling data does not need to filter out all terminal signaling data within the fixed train travel time), the number of passengers passing through non-high-speed competitive sections can be determined as follows: Based on the competitive entrance subgroup, competitive exit subgroup, and competitive transit point subgroup, obtain all users who have appeared in these three subgroups within a set time period (e.g., calculated on a daily basis), and filter out users who have appeared in all three subgroups (i.e., appeared at least once in each subgroup); sort the filtered users according to their communication time, and perform a second filtering to obtain all mobile terminal users whose travel time on the non-high-speed competitive section falls within the travel time range of that non-high-speed competitive section, thus obtaining the number of passengers passing through the non-high-speed competitive section.

[0094] As an example, the travel time range for non-highway competitive road sections can be obtained through the following calculation method:

[0095] The average travel time of a non-high-speed competitive road segment is obtained by calculating the ratio of its travel mileage to the average travel speed of vehicles on that segment. Based on this average travel time, a 20% fluctuation in travel time caused by other factors (i.e., average travel time ± 20%) is considered to determine the range of travel times for that segment. For example, if the average travel time of a non-high-speed competitive road segment is 1 hour, then the range of travel times for that segment is 0.8 hours to 1.2 hours.

[0096] The 20% fluctuation in travel time mentioned in this application is only an example and may be other values ​​(such as 30%). This invention does not impose specific limitations on it and can be obtained based on historical experience or historical travel data.

[0097] As an example, after the data cleaning process, if the same mobile phone user appears multiple times in the remaining data, they will not be removed; they can be considered as multiple trips. For instance, suppose user A travels on a highway twice on a certain day; they can be considered two different users and will not be removed from the terminal signaling data.

[0098] Step S140: Based on the pedestrian and vehicle traffic data on the target highway section, obtain the correspondence between pedestrian and vehicle traffic, and calculate the traffic flow of the non-highway competitive section corresponding to the pedestrian traffic on the non-highway competitive section based on the determined correspondence.

[0099] More specifically, based on high-speed transaction data, the number of vehicles (i.e., traffic flow) on the target high-speed section within the first set time period can be determined, and based on terminal signaling data of base stations covering the target high-speed section, the number of pedestrians passing through the target high-speed section within the first set time period can be determined, thereby determining the correspondence between the number of pedestrians and the number of vehicles.

[0100] Based on the correspondence between pedestrian and vehicle traffic, and using the pedestrian traffic data obtained from the terminal signaling data of the base station covering the non-high-speed competitive road section within the second set time period, the traffic flow of the non-high-speed competitive road section within the second set time period can be calculated, and thus the traffic flow can be diverted.

[0101] The correspondence between pedestrian traffic and vehicle traffic is the ratio of pedestrian traffic to vehicle traffic volume on the target expressway section within the first set time period. By calculating the ratio of pedestrian traffic to vehicle traffic on the non-expressway competition section within the second set time period, the potential traffic volume of the non-expressway competition section within the second set time period can be obtained.

[0102] The potential traffic volume is an estimate, obtained by estimating the traffic flow of non-high-speed competitive road sections over a certain period of time in the future using the methods described above.

[0103] As an example, the number of vehicles passing through the target highway segment can also be considered as the traffic flow obtained from the highway transaction data of a portion of the target highway segment (in this case, the number of passengers passing through the target highway segment is the number of passengers corresponding to that portion of the segment). However, to more comprehensively consider the changes in traffic conditions of the entire target highway segment, the number of vehicles and passengers passing through the target highway segment can be obtained from the highway transaction data of the start and end points of the target highway segment (i.e., the entire target highway segment), and the number of vehicles passing through the non-highway competition segment can be calculated.

[0104] The number of vehicles and pedestrians passing through the target highway section can also be the average of multiple time periods, but they must correspond to the number of vehicles and pedestrians passing through the same road section and the same time period.

[0105] Step S150: Select a non-highway competing road segment with a traffic flow greater than that of the target high-speed road segment as the road segment to be diverted, and control the base station through the mobile communication operator's server to send diversion instruction information to at least some users on the road segment to be diverted.

[0106] More specifically, such as Figure 3 As shown, considering that the purpose of this application is to balance the traffic flow distribution of the road network, the road segment to be diverted needs to meet two conditions: the road segment to be diverted is a non-high-speed competitive road segment, and the traffic flow on the road segment to be diverted needs to be greater than the traffic flow on the target high-speed road segment. Therefore, non-high-speed competitive road segments can be determined in step S130. After calculating the traffic flow of the non-high-speed competitive road segments in step S140, non-high-speed competitive road segments with traffic flow greater than the traffic flow of the target high-speed road segment can be selected and used as the road segments to be diverted.

[0107] As an example, if the first set time period and the second set time period are the same time period, then step S140 is not required; simply select a non-highway competitive road segment with a higher number of passengers than the target high-speed road segment as the road segment to be diverted. Alternatively, a non-highway competitive road segment with a higher number of passengers than the target high-speed road segment and a passenger difference greater than a set passenger threshold can be selected as the road segment to be diverted.

[0108] As an example, in step S140, path transaction volume can be used to replace the number of passing vehicles, and the road segment to be diverted can be selected based on the transaction volume. The specific process is as follows: Based on the number of passing vehicles and path transaction volume on the target highway segment, the correspondence between the number of passing vehicles and the transaction volume is obtained, and based on the determined correspondence, the path transaction volume of the non-highway competitive road segment corresponding to the number of passing vehicles on the non-highway competitive road segment is calculated, thereby selecting the non-highway competitive road segment with a transaction volume greater than the path transaction volume of the target highway segment as the road segment to be diverted.

[0109] As an example, one could first select non-highway competitive road segments whose transaction volume exceeds that of the target highway segment. Then, from these selected non-highway competitive road segments, a second selection could be made of road segments where the traffic flow of at least some vehicle types exceeds that of the corresponding vehicle types on the target highway segment (based on the ratio of pedestrians to vehicles on the target highway segment, the traffic flow of at least some vehicle types on the non-highway competitive road segments is determined by the number of pedestrians on the non-highway competitive road segments). These would then be the road segments to be diverted. The vehicle types on the non-highway competitive road segments can be obtained using traffic management data (i.e., road network traffic data) that includes user information such as user numbers and the corresponding vehicle types. The vehicle types on the target highway segment can be obtained using highway transaction data.

[0110] Furthermore, since mobile communication operators' base stations can cover the surrounding road network, they can further fit vehicle traffic conditions by acquiring terminal signaling data, enabling a more accurate evaluation of traffic conditions on the sections to be diverted, and precise location and reach of target customers. Introducing mobile communication operator data into the highway traffic diversion process has the following advantages: First, it integrates highway transaction and terminal signaling data, thereby improving the data source for calculating differentiated tolls; second, it verifies existing traffic management data (by comparing traffic management data with base station terminal signaling data, user traffic conditions can be further verified; traffic management data includes the correspondence between license plates and user numbers); third, at the execution level, mobile communication operators can reach users, making the selection of diverted users more targeted, i.e., the mobile communication operator's server controls the base station to send diversion instruction information to at least some users on the sections to be diverted.

[0111] During the process of diverting traffic on highways, diversion instruction information can be sent to some or all users on the section to be diverted. Diversion instruction information can also be sent to users of a specified level according to the pre-set user priority. For example, free users and heavy vehicle users can be set as the first priority. Mobile communication operators can control base stations to send diversion instruction information to free users and heavy vehicle users on the section to be diverted (free users and heavy vehicle users on the section to be diverted can be identified by combining the terminal signaling data and traffic management data of mobile communication operators).

[0112] In some embodiments of the present invention, at least some users include free users and heavy vehicle users; wherein, free users are users whose frequency of passage during the free period of the highway reaches a set frequency; heavy vehicle users are users whose number of passages is lower than the average number of passages and whose vehicle weight is higher than the average weight; wherein, the passage frequency and number of passages are determined based on highway transaction data.

[0113] As an example, after determining the road segment to be diverted, the mobile communication operator can send diversion instruction information to free users and heavy vehicle users on the base station covering the road segment to be diverted. The diversion instruction information may include: the nearest highway entrance, the route to the nearest highway entrance, and highway discount information (i.e., highway discount notification), etc.

[0114] For example, two key target customers can be identified: those who "use highways during free periods but not when tolls are charged" and those who "use highways with full loads but not empty ones," and these can be considered as "fluctuating users." The free period for highways refers to the time during holidays when highway tolls are waived; at other times, normal tolls are charged. Based on highway transaction data, users who travel on highways more frequently during free periods than a set frequency (e.g., 6 times / year) can be identified as the "use highways during free periods but not when tolls are charged" vehicle group. By comparing truck data (obtained from highway transaction data) from the same period this year and last year, the average weight and average number of trips per vehicle can be compared. Users with fewer trips per vehicle than the average number of trips but higher vehicle weight can be identified as the "use highways with full loads but not empty ones" vehicle group.

[0115] The users mentioned in this invention, including free users and heavy vehicle users, are merely examples and may also include other types of vehicle users; this invention is not limited thereto. To more accurately reach customers, the user travel needs obtained through signaling data can be further filtered, and users traveling the entire length of the diverted road segment can be considered as diversion targets, to whom instruction information can be sent.

[0116] In order to further enhance the traffic-driving effect of expressways, in addition to sending traffic-driving prompts to users by locating them, the possibility of users choosing expressway travel can also be increased by adjusting the expressway toll collection method. At present, expressway toll collection mainly implements a differentiated toll collection scheme. The toll collection standard of expressways can be formulated based on factors such as highway technical grade, total investment, price index and traffic volume, and the price lever can be used to deepen the differentiated toll collection strategy. However, subjective factors such as toll collection experience have a great influence on the formulation of the differentiated toll collection discount ratio of expressways. The formulation of differentiated toll collection strategy based on human experience has the following disadvantages: (1) Lack of scientific basis. The process of formulating differentiated toll collection strategy is usually based on the personal experience, intuition or prejudice of decision-makers or relevant stakeholders. Therefore, such toll collection strategy may not accurately reflect the true value of services or products, resulting in price distortion and resource misallocation. (2) Information asymmetry. The formulator of the toll collection strategy based on human experience may make wrong judgments on market demand and consumer behavior based on their own experience, thereby formulating unreasonable toll collection standards, increasing the transaction costs and market risks of expressway operation and management. (3) Lack of flexibility and adaptability: The artificial experience-based pricing strategy lacks the ability to predict and respond to future market changes. When market demand changes, the strategy may not be able to be adjusted in time, making it difficult to adapt to the changing market demand, resulting in resource waste and decreased market efficiency.

[0117] In some embodiments of the present invention, the method further includes differentiated charging for all users on the target highway segment: step S160, at least based on the cost quantification indicators and corresponding weights of multiple differentiated factors obtained from the target highway segment and the segment to be diverted, differentiated charging parameters are calculated, and vehicles on the target highway segment are charged based on the calculated differentiated charging parameters.

[0118] In some embodiments of the present invention, the multiple differentiation factors obtained based on the target highway segment and the segment to be diverted include multiple of the following factors: the difference in toll fees between the target highway segment and the segment to be diverted, the difference in travel time between the target highway segment and the segment to be diverted, and the difference in safety between the target highway segment and the segment to be diverted.

[0119] The cost quantification indicators corresponding to multiple differentiating factors are multiple discount values ​​for the original standard toll for highways corresponding to multiple differentiating factors, and the differentiated toll parameters are the differentiated toll discount ratios for the standard toll; or, the cost quantification indicators corresponding to multiple differentiating factors are multiple toll amount reference values ​​corresponding to multiple differentiating factors, and the differentiated toll parameters are differentiated toll amount indicators calculated based on the multiple toll amount reference values ​​and corresponding weights corresponding to multiple differentiating factors.

[0120] As an example, taking multiple cost quantification indicators corresponding to differentiating factors as multiple discount values, and the differentiated tolling parameter as the differentiated tolling discount ratio, the specific process of calculating the differentiated tolling discount ratio based on the differences in toll fees between the target highway segment and the segment to be diverted, the differences in travel time between the target highway segment and the segment to be diverted, and the differences in driving safety between the target highway segment and the segment to be diverted can be described as follows:

[0121] First, calculate the differences in toll fees, travel time, and road safety (measured by a road safety factor) between the expressway and the diverted road segment. The expressway toll fee is determined by the expressway toll standard, while the diverted road segment is a toll-free segment. The expressway travel time is the average travel time obtained based on expressway transaction data, and the diverted road segment travel time is the ratio of the diverted road segment's mileage to its average speed. The safety of both the expressway and the diverted road segment is measured by a road safety factor, which is based on the expressway accident rate and the diverted road segment's accident rate, respectively (a lower accident rate results in a higher road safety factor). The discount value is the percentage discount applied to a specific differential factor, within the range [0,1]. A lower discount value results in a greater reduction in cost compared to the original expressway toll, while a higher discount value results in a smaller reduction.

[0122] Secondly, the discount values ​​and weights corresponding to the differences in toll fees, travel time, and road safety coefficients are multiplied separately, and the sum of the products is used as the differentiated toll discount ratio. The discount values ​​can be obtained from a pre-stored discount value-differentiation factor correspondence table, and the discount values ​​in this table can be fixed values.

[0123] Differential pricing discount ratio Z Discount It can be represented as:

[0124] Z Discount =w1×Z cost(高速公路-被引流路段) +w2×Z time(高速公路-被引流路段) +w3×Z safety(高速公路-被引流路段) ;

[0125] Where w1, w2, and w3 represent the weights corresponding to the differences in toll fees, travel time, and driving safety, respectively; Cost(Highway - Diverted Section) represents the difference in toll fees between the target highway section and the diverted section; Z cost(高速公路-被引流路段) Z represents the discount value corresponding to the difference in toll fees between the target highway segment and the segment to be diverted. `time(highway - diverted segment)` represents the difference in travel time between the target highway segment and the segment to be diverted. time(高速公路-被引流路段) Z represents the discount value corresponding to the difference in travel time between the target highway segment and the segment to be diverted. safety(highway - diverted segment) represents the difference in driving safety coefficient between the target highway segment and the segment to be diverted. safety(高速公路-被引流路段) This represents the discount value corresponding to the difference in driving safety between the target highway section and the section to be diverted.

[0126] If only the differences in toll fees, travel time, and driving safety are considered as user-sensitive differentiating factors, then the sum of the weight values ​​corresponding to the differences in toll fees, travel time, and driving safety can be set to 1.

[0127] For example, a comparative analysis can be conducted on the target highway segment and the segment to be diverted. By considering users' sensitivity to three differentiating factors—differences in toll fees, travel time, and driving safety—weighted values ​​can be assigned. Then, the differentiated toll discount ratio can be calculated based on the discount values ​​corresponding to these differences and their assigned weights. Assuming the discount values ​​for the differences in toll fees, travel time, and driving safety between the target and diverted highway segments are 0.7, 0.3, and 0.5, respectively, and the corresponding weights are 0.5, 0.4, and 0.1, respectively, then the differentiated toll discount ratio is 0.7 × 0.5 + 0.3 × 0.4 + 0.5 × 0.1 = 0.52. Assuming the original highway toll is 100 yuan (i.e., the toll determined according to the highway toll standard is 100 yuan), the toll charged to this vehicle at the toll station on the target highway section is 52 yuan.

[0128] As an example, taking the cost quantification indicators corresponding to multiple differentiating factors as reference values ​​for multiple toll amounts corresponding to multiple differentiating factors, and the differentiated toll parameters as differentiated toll amount indicators, the specific process of calculating the differentiated toll discount ratio based on the differences in toll fees between the target highway segment and the segment to be diverted, the differences in travel time between the target highway segment and the segment to be diverted, and the differences in driving safety between the target highway segment and the segment to be diverted can be described as follows:

[0129] The reference values ​​for toll amounts corresponding to the differences in toll fees, travel time, and road safety coefficients are multiplied by their respective weights, and the sum of these products is used as the differentiated toll amount index. Here, the reference values ​​for toll amounts do not refer to the original highway toll standards, but rather toll standards determined based on each differentiating factor. The differentiated toll amount index refers to the fees that users on highways will be charged at toll stations after implementing the differentiated toll strategy proposed in this application.

[0130] Differentiated pricing index M Discount It can be represented as:

[0131] M Discount =w'1×M cost(高速公路-被引流路段) +w'2×M time(高速公路-被引流路段) +w'3×M safety(高速公路-被引流路段) ;

[0132] Where w'1, w'2, and w'3 represent the weights corresponding to differences in toll fees, differences in travel time, and differences in driving safety, respectively, M cost(高速公路-被引流路段) M represents a reference value for the toll amount corresponding to the difference between the toll fees of the target highway section and the section to be diverted. time(高速公路-被引流路段) M represents a reference value for the toll amount corresponding to the difference in travel time between the target highway segment and the segment to be diverted. safety(高速公路-被引流路段) This indicates the reference value for the toll amount corresponding to the difference in driving safety between the target highway section and the section to be diverted.

[0133] For example, a pre-set toll reference value-differentiation factor correspondence table can be used to obtain the corresponding toll reference value based on the differentiation factors between the target highway segment and the segment to be diverted. Assuming the toll reference values ​​for the differences in toll fees, travel time, and driving safety between the target highway segment and the segment to be diverted are 40 yuan, 10 yuan, and 20 yuan respectively, and the weights for these differences are 0.3, 0.5, and 0.2 respectively, then the differentiated toll amount index is 40 × 0.3 + 10 × 0.5 + 20 × 0.2 = 21. Therefore, the toll charged to the vehicle at the toll station on the target highway segment is 21 yuan.

[0134] As an example, the toll reference value in the toll reference value - differentiation factor correspondence table can be a fixed value (such as a randomly set value) or a variable value (for example, the toll reference value corresponding to each differentiation factor for each vehicle can be determined based on the different actual tolls obtained by different vehicles based on the original highway toll standard). For example, if the toll reference value is a variable value, the toll obtained by the vehicle based on the original highway toll standard can be multiplied by the set travel time discount value, and the product can be used as the toll reference value for the vehicle corresponding to the difference in travel time.

[0135] Furthermore, the discount values ​​and weights corresponding to the differentiating factors can be determined based on expert experience (or user surveys), or using data such as highway transaction data and road conditions and usage frequency of the highway and the diverted road segment; the toll reference value and corresponding weight can be determined based on expert experience (or user surveys), or using data such as the difference in toll fees between the highway and the diverted road segment, highway transaction data, and road conditions of the highway and the diverted road segment. This invention does not specifically limit the methods for determining the discount values ​​and weights, or the toll reference value and corresponding weight. Moreover, since w1, w2, and w3, and w'1, w'2, and w'3 are the weights corresponding to the discount values ​​and toll reference values ​​for multiple differentiating factors, w1 and w'1, w2 and w'2, and w3 and w'3 are not necessarily the same.

[0136] In some embodiments of the present invention, differentiated toll parameters are calculated based on cost quantification indicators and corresponding weights corresponding to multiple differentiating factors obtained from the target highway segment and the segment to be diverted, including:

[0137] Based on multiple differentiated factors obtained from the target highway sections and the sections to be diverted, multiple discount values ​​and corresponding weights are assigned to the standard toll, and a differentiated toll discount ratio is calculated based on pre-calculated user discount level indicators; or

[0138] Based on multiple differentiated factors obtained from the target highway section and the section to be diverted, there are multiple reference values ​​and corresponding weights for the toll amount, as well as differentiated toll amount indicators calculated based on pre-calculated user discount level indicators.

[0139] The user discount level indicator is calculated based on one or more of the following indicators: the user's historical mileage on highways, the user's frequency of driving on highways, and the user's credit rating.

[0140] More specifically, user discount levels can be calculated based on a user's historical highway mileage, frequency of highway travel, and credit rating to identify price elasticity and customer characteristics. For example, the highway mileage in the first three months can be considered; higher historical mileage results in lower discounts (i.e., higher discount levels), thus increasing cumulative rewards to boost highway traffic. Similarly, the frequency of travel in the first six months can be considered; higher frequency results in lower discounts. To strengthen highway management, users with a history of toll evasion in highway transaction data can be screened through a toll road vehicle credit list, with higher discounts or no differentiated tolling strategy (i.e., charging according to the original toll standard).

[0141] As an example, the user discount level indicator ranges from [0,1]. The user discount level indicator can be calculated by assigning values ​​to historical mileage, driving frequency, and user credit rating using a weighted method, or it can be obtained using other methods; this invention does not specifically limit this. Furthermore, this invention does not specifically limit the specific calculation method for obtaining the differentiated charging discount ratio by combining the discount values ​​of multiple differentiating factors with the user discount level indicator. Similarly, this invention does not specifically limit the specific calculation method for obtaining the differentiated charging amount indicator by combining the charging amount reference values ​​corresponding to multiple differentiating factors with the user discount level indicator.

[0142] Furthermore, differentiated pricing can also be implemented based on other differentiating factors such as entrances / exits, vehicle types, time periods, and directions of travel. For example, if a user enters the target highway segment through a designated entrance, exits through a designated exit, uses a designated vehicle type, travels during a designated low-traffic period, and travels in a designated direction, an appropriate discount or toll reference value and corresponding weight can be assigned to them, thereby calculating differentiated pricing parameters based on the aforementioned differentiating factors.

[0143] like Figure 4 As shown, the data analysis approach for highway traffic diversion in this application is as follows: First, analyze traffic demand to determine the general direction of traffic flow. By analyzing highway transaction data of highways to which differentiated tolling is to be implemented, the start and end points of the highways are determined. Second, locate the road sections to be diverted. Based on the start and end points of the highways and traffic flow, the road sections to be diverted can be determined. Then, accurately locate customers. Perform multi-dimensional analysis on data such as highway transaction information, user information, and vehicle information, and send instruction information to at least some users on the road sections to be diverted.

[0144] With the continuous improvement of the highway network, expressway operation faces increasing challenges. To assist expressway operators and management units in leveraging big data analysis and traffic diversion strategies, and through differentiated tolling supplemented by system construction, this invention proposes a multi-source data-based expressway traffic diversion method, which offers the following advantages:

[0145] 1. Accuracy: The analysis of multi-source data can more accurately reflect the actual situation of the highway, including traffic flow, congestion level and travel time of the diverted road sections, so as to accurately locate diverted users. Furthermore, the more realistic differentiated tolling strategy based on data analysis can more accurately adjust vehicle travel arrangements and route selection, thereby improving the efficiency of road network operation.

[0146] 2. Comprehensiveness: The comprehensive analysis of multi-dimensional data not only considers toll factors but also covers multiple analytical dimensions such as driving safety and travel time, enabling differentiated charging strategies to more comprehensively consider user needs and facilitating a fair charging mechanism. Furthermore, by introducing mobile communication operators during the traffic diversion process, this application can determine the road segments to be diverted based on the operators' terminal signaling data and the highway's own transaction data. In other words, the comprehensive analysis of multi-source data makes the traffic diversion method more scientific and reasonable.

[0147] 3. Flexibility: By sending instruction information to users on the diverted road sections through mobile communication operators, users can choose to enter or exit the highway according to their travel needs. This enhances the flexibility of traffic flow distribution on the road network by increasing users' autonomy in choosing their travel routes. Furthermore, the data-driven differentiated tolling strategy proposed in this application can be flexibly adjusted and optimized according to the real-time operation of the highway, allowing the differentiated tolling strategy to better adapt to changes in highway conditions. For example, when a diverted road section becomes congested, the highway toll can be reduced to guide vehicles to choose highway travel, thereby alleviating congestion on the diverted road section and increasing highway traffic volume.

[0148] Corresponding to the above method, the present invention also provides a highway traffic diversion system based on multi-source data. The system includes a computer device, which includes a processor and a memory. The memory stores computer programs / instructions, and the processor is used to execute the computer programs / instructions stored in the memory. When the computer programs / instructions are executed by the processor, the system implements the steps of the method described above.

[0149] This invention also provides a computer program product storing a computer program / instructions thereon, which, when executed by a processor, implements the steps of the aforementioned edge computing server deployment method. The computer program product can be a tangible product, such as random access memory (RAM), memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, floppy disks, hard disks, removable storage disks, CD-ROMs, or any other form of product known in the art.

[0150] Those skilled in the art will understand that the exemplary components, systems, and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software, or a combination of both. Whether implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention. When implemented in hardware, it can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this invention are programs or code segments used to perform the desired tasks. The programs or code segments can be stored in a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried in a carrier wave.

[0151] It should be clarified that the present invention is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of the present invention.

[0152] In this invention, features described and / or illustrated for one embodiment may be used in the same or similar manner in one or more other embodiments, and / or combined with or in place of features of other embodiments.

[0153] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, various modifications and variations of the embodiments of the present invention are possible. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A highway traffic diversion method based on multi-source data, characterized in that, The method includes the following steps: Acquire highway transaction data within a predetermined area, determine traffic flow and direction data of toll stations based on the acquired transaction data, select target toll stations for diversion based on traffic flow size, and select target highway sections and directions for diversion based on highway route data associated with the target toll stations. Based on electronic map data, identify the non-highway competing road sections around the selected target highway section for traffic diversion; The system obtains terminal signaling data from base stations covering non-high-speed competitive road sections and base stations covering the target high-speed road sections from the mobile communication operator's server. Based on the terminal signaling data from the base stations covering non-high-speed competitive road sections, it calculates the number of pedestrians on the non-high-speed competitive road sections and the number of pedestrians on the target high-speed road sections from the base stations covering the target high-speed road sections. Based on the pedestrian and vehicle traffic data on the target highway sections, the correspondence between pedestrian and vehicle traffic is obtained, and based on the determined correspondence, the traffic flow of non-highway competitive sections corresponding to pedestrian traffic is calculated. Select a non-highway competitive road segment with a traffic flow greater than that of the target high-speed road segment as the road segment to be diverted, and control the base station through the mobile communication operator's server to send diversion instruction information to at least some users on the road segment to be diverted. The selection of the target highway segment and traffic direction for traffic diversion based on the highway route data associated with the target toll station includes: Based on the traffic volume corresponding to different traffic flow directions in the highway route data associated with the target toll station, a highway segment with a specific flow direction that meets the traffic volume requirements is selected as the target highway segment for traffic diversion, and the specific flow direction is the selected travel direction. The method further includes: calculating differentiated toll parameters based on cost quantification indicators and corresponding weights corresponding to multiple differentiating factors obtained from the target highway segment and the road segment to be diverted, and charging vehicles on the target highway segment based on the calculated differentiated toll parameters; wherein, the multiple differentiating factors obtained from the target highway segment and the road segment to be diverted include multiple of the following factors: the difference in toll fees between the target highway segment and the road segment to be diverted, the difference in travel time between the target highway segment and the road segment to be diverted, and the difference in driving safety between the target highway segment and the road segment to be diverted.

2. The method according to claim 1, characterized in that, The cost quantification indicators corresponding to the multiple differentiation factors are multiple discount values ​​for the standard charges corresponding to the multiple differentiation factors, and the differentiated charging parameters are the differentiated charging discount ratios for the standard charges; or, the cost quantification indicators corresponding to the multiple differentiation factors are multiple charging amount reference values ​​corresponding to the multiple differentiation factors, and the differentiated charging parameters are differentiated charging amount indicators calculated based on the multiple charging amount reference values ​​and corresponding weights corresponding to the multiple differentiation factors.

3. The method according to claim 2, characterized in that, The differential tolling parameters are calculated based on the cost quantification indicators and corresponding weights corresponding to multiple differentiating factors obtained at least from the target highway segment and the road segment to be diverted, including: Based on multiple differentiated factors obtained from the target highway sections and the sections to be diverted, multiple discount values ​​and corresponding weights are assigned to the standard toll, and a differentiated toll discount ratio is calculated based on pre-calculated user discount level indicators; or Based on multiple differentiated factors obtained from the target highway section and the section to be diverted, there are multiple reference values ​​and corresponding weights for the toll amount, as well as differentiated toll amount indicators calculated based on pre-calculated user discount level indicators. The user discount level index is calculated based on one or more of the following indicators: the user's historical mileage on highways, the user's frequency of driving on highways, and the user's credit rating.

4. The method according to claim 1, characterized in that, The base stations covering the target highway section include base stations located within the set range of highway positioning points. The highway positioning points include the starting and ending points of the target highway section, toll stations on the target highway section, and key highway passage points. The base stations covering the target highway section are divided into a highway entrance subgroup, a highway passage point subgroup, and a highway exit subgroup. Among them, the key high-speed transit points are the location points that belong only to the target high-speed section of the diversion; the base stations whose communication range covers the toll stations and key high-speed transit points on the target high-speed section of the diversion belong to the transit point subgroup; the base stations whose communication range covers the starting point of the target high-speed section of the diversion belong to the high-speed entrance subgroup; and the base stations whose communication range covers the ending point of the target high-speed section of the diversion belong to the high-speed exit subgroup. The competing road segment base station group includes base stations located within the range of the competing location points. The competing location points include the start and end points of the non-high-speed competing road segment and the key competitive path points. The base stations covering the non-high-speed competing road segment include a competing entry subgroup, a competing exit subgroup, and a competing path point subgroup. Among them, the key competitive path points are the location points that belong only to the non-high-speed competitive road sections; the base stations whose communication range covers the key competitive path points belong to the competitive path point subgroup, the base stations whose communication range covers the starting point of the non-high-speed competitive road section belong to the competitive entry subgroup, and the base stations whose communication range covers the ending point of the non-high-speed competitive road section belong to the competitive exit subgroup. Among them, at least one of the high-speed entrance subgroup, high-speed transit point subgroup, and high-speed exit subgroup has a communication range that only covers the target high-speed section of the diverted traffic, or at least one of the competing entrance subgroup, competing exit subgroup, and competing transit point subgroup has a communication range that only covers non-high-speed competing sections.

5. The method according to claim 4, characterized in that, After acquiring the terminal signaling data of the base station covering the non-high-speed competition section and the terminal signaling data of the base station covering the target high-speed section, the method further includes: performing data preprocessing on the terminal signaling data of the base station covering the non-high-speed competition section and performing data preprocessing on the terminal signaling data of the base station covering the target high-speed section. Data preprocessing is performed on the terminal signaling data of the base stations covering non-high-speed, non-competitive road sections, including: The terminal signaling data of users whose travel time on non-high-speed competitive road sections falls within the travel time range of those non-high-speed competitive road sections are filtered out; wherein, the travel time range of the non-high-speed competitive road sections is set based on the average travel time of those non-high-speed competitive road sections; Filter all terminal signaling data during the fixed train travel period; and Filter terminal signaling data corresponding to users who appear only in one or two of the competition entry subgroup, competition exit subgroup, and competition path point subgroup; Data preprocessing is performed on the terminal signaling data of the base stations covering the target highway section, including: Filter terminal signaling data corresponding to users whose travel time on the target highway segment exceeds the average travel time on the target highway segment; Filter all terminal signaling data during the fixed train travel period; and Filter terminal signaling data corresponding to users that appear only in one or two of the highway entrance subgroup, highway transit point subgroup, and highway exit subgroup; The average travel time of the non-high-speed competitive road segment is the ratio of the travel mileage of the non-high-speed competitive road segment to the average travel speed of the non-high-speed competitive road segment, and the average travel time of the target high-speed road segment is obtained based on highway transaction data.

6. The method according to claim 1, characterized in that, The at least some of the users include free users and users with heavy vehicles; Among them, the free users are users whose frequency of passage during the free period of the highway reaches the set frequency; the heavy vehicle users are users whose number of passages is lower than the average number of passages and whose vehicle weight is higher than the average weight; wherein, the passage frequency, the number of passages and the vehicle weight are determined based on highway transaction data.

7. A highway traffic diversion system based on multi-source data, comprising a processor, a memory, and a computer program / instructions stored in the memory, characterized in that, The processor is used to execute the computer program / instructions, and when the computer program / instructions are executed, the system implements the steps of the method as described in any one of claims 1 to 6.

8. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method described in any one of claims 1 to 6.

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