A global SMS provider optimization and switching system and method for vehicle-to-everything (V2X) communication

Abstract

This invention belongs to the field of vehicle-to-everything (V2X) SMS switching technology. It discloses a system and method for optimizing the switching of global SMS providers in the V2X network. The method includes: acquiring navigation route information of a driving vehicle; acquiring location data of the driving vehicle per unit time based on the navigation route information; performing feature processing on the location data to obtain feature-processed data, which includes region name, location characteristics, and time interval data; setting the provider serial number corresponding to the global SMS provider; acquiring SMS data from the global SMS provider, which includes SMS sending success rate, average latency time, and SMS cost; and establishing a digital model based on the feature-processed data, provider serial number, and SMS data. This invention can further improve the user experience.

Description

Technical Field

[0001] This invention relates to the field of vehicle-to-everything (V2X) SMS switching technology, and more specifically, to a global SMS provider optimization switching system and method for V2X. Background Technology

[0002] Chinese Patent CN104394188B discloses a method and system for data transmission in a vehicle-to-everything (V2X) network. By configuring a wireless access point (AP) on the vehicle's main unit, the AP receives first data information from a V2X backend server. The main unit then acquires this first data information and performs corresponding operations based on it. This first data information can be in various forms, overcoming the limitation that V2X data transmission must be multimedia data, and it does not rely on cloud backup or remote control technologies, thus facilitating data transmission within the V2X network.

[0003] The existing technology still has the following problems:

[0004] When vehicles travel long distances across regions, signal strength varies significantly across different geographical locations. Furthermore, different SMS providers exhibit varying response times and SMS costs when sending messages to the vehicle-to-everything (V2X) system. However, current technologies typically do not allow for pre-emptive switching of SMS providers based on actual conditions to achieve optimal V2X SMS delivery, resulting in a need for improved user experience.

[0005] In view of this, the present invention proposes a global SMS provider optimization and switching system and method for vehicle networking to solve the above problems. Summary of the Invention

[0006] To overcome the aforementioned deficiencies of the prior art and to achieve the above objectives, the present invention provides the following technical solution: a method for optimizing and switching global SMS providers for vehicle-to-everything (V2X) communication, comprising:

[0007] Obtain navigation route information for the vehicle in motion;

[0008] Based on navigation route information, obtain the location data of vehicles traveling per unit time;

[0009] The location data is subjected to feature processing to obtain feature-processed data, which includes region name, location features and time interval data;

[0010] Set the supplier serial number corresponding to the global SMS provider;

[0011] Obtain SMS data from global SMS providers, including SMS delivery success rate, average latency, and SMS cost;

[0012] A digital model is established based on feature processing data, supplier serial numbers, and SMS data;

[0013] The target conditions are set based on a digital model, including the shortest total latency, the lowest total SMS cost, and the highest reliability.

[0014] Randomly generated Pre-supply plan;

[0015] Based on the target conditions, an adaptive allocation algorithm is used to optimize the pre-supply plan, and the optimized pre-supply plan is output.

[0016] Furthermore, the method for optimizing the pre-supply scheme using the adaptive allocation algorithm includes:

[0017] Step N1: Initialize the particle swarm. Each particle swarm represents a pre-supply plan. The pre-supply plan includes the supplier number selected when the vehicle is in different regions, with different location characteristics and corresponding time interval data.

[0018] Step N2: Obtain the total delay time, total SMS cost, and reliability for each pre-supply plan;

[0019] Step N3: Calculate based on total latency, total SMS cost, and reliability. Overall adaptability of pre-supply programs ;

[0020] Step N4: Update the particle's velocity and position, that is, update the supplier sequence number selected by the vehicle when it is in different regions, with different location characteristics and corresponding time interval data, and generate a new pre-supply plan.

[0021] Step N5, if the position is updated after the first... If the reliability of a single particle is greater than the reliability corresponding to the historical best position, then let If the position is updated after the first... If the reliability of a single particle is greater than the reliability corresponding to the global optimal position, then let ; For the first The particle in the first The position at the next iteration; For the first The best historical position that each particle finds in the corresponding pre-supply scheme is the one with the highest reliability. The globally optimal position found among all particles;

[0022] Step N6: Repeat steps N2 to N5 until the preset number of repetitions is reached. Then, select the pre-supply plan with the highest overall adaptability. The pre-supply plan with the highest overall adaptability is the output optimized pre-supply plan, which meets the set target conditions.

[0023] Furthermore, the method for obtaining the reliability includes:

[0024] ;

[0025] In the formula, For reliability; This represents the total delay time. For the first SMS sending success rate corresponding to group feature processing data; and These are the corresponding preset weights; This represents the total number of feature processing data sets corresponding to the current navigation route information. .

[0026] Furthermore, the method for obtaining the SMS sending success rate includes:

[0027] Step S1: Obtain historical transmission status data, which includes the SMS sending status, sending time, and delivery time; divide the historical transmission status data into different regions, corresponding location features, and different time intervals. Group data transmission; statistics The sending status of all SMS messages corresponding to the group transmission data, including success and failure; It is a positive integer greater than 1;

[0028] Step S2: For each group of transmitted data, divide the SMS messages with a successful sending status by the total number of SMS messages to calculate the corresponding SMS sending success rate.

[0029] Furthermore, the method for obtaining the average delay time includes:

[0030] Step M1, Statistics The sending and delivery times of all SMS messages corresponding to the group transmission data;

[0031] Step M2: Subtract the sending time from the delivery time of each SMS message to calculate the delay time for each SMS message.

[0032] Step M3: Calculate the average delay time of all SMS messages in each group of transmitted data.

[0033] Furthermore, the method for obtaining the total delay time includes:

[0034] Step Q1: For all feature processing data on the current navigation route of the vehicle, obtain the average delay time corresponding to each set of feature processing data;

[0035] Step Q2: Sum all the average delay times to calculate the total delay time;

[0036] The method for obtaining the total delay time is used to obtain the total SMS cost.

[0037] Furthermore, the overall fitness The calculation methods include:

[0038] ;

[0039] In the formula, , and Preset weighting coefficients; For the total SMS cost, For reliability, This represents the total delay time.

[0040] Furthermore, methods for updating particle velocity include:

[0041] ;

[0042] In the formula, For the first The particle in the first Speed ​​during the next iteration; For the first The particle in the first Speed ​​during the next iteration; For the first The particle in the first The position at the next iteration; Inertial weights control the continuity of particle velocity; For individual learning factors; For group learning factors; and All are random numbers in the range [0,1].

[0043] Particle position update methods include:

[0044] .

[0045] Furthermore, the location data includes the vehicle location and the corresponding timestamp data; the location features include urban areas, highway areas, mountainous areas, and rural areas; the region name is the name of the city area to which the vehicle location belongs; and the time interval data is the hourly time period corresponding to the current specific time.

[0046] A global SMS provider optimization and switching system for connected vehicles, comprising the method for optimizing and switching global SMS providers for connected vehicles, including:

[0047] The first acquisition module is used to acquire navigation route information of the driving vehicle;

[0048] The second acquisition module acquires the location data of vehicles traveling per unit time based on navigation route information;

[0049] The feature processing module is used to perform feature processing on location data and obtain feature-processed data, which includes region name, location features and time interval data.

[0050] The serial number setting module is used to set the supplier serial number corresponding to the global SMS provider;

[0051] The third acquisition module is used to acquire SMS data from global SMS providers, including SMS sending success rate, average latency time and SMS cost.

[0052] The digital modeling module builds a digital model based on feature processing data, supplier serial numbers, and SMS data.

[0053] The target setting module sets target conditions based on a digital model. These target conditions include the shortest total delay time, the lowest total SMS cost, and the highest reliability.

[0054] The scheme generation module is used to randomly generate schemes. Pre-supply plan;

[0055] The scheme analysis module optimizes the pre-supply scheme using an adaptive allocation algorithm based on the target conditions and outputs the optimized pre-supply scheme.

[0056] The technical effects and advantages of the present invention, a global SMS provider optimization and switching system and method for vehicle networking, are as follows:

[0057] When a vehicle is traveling long distances across regions, this invention obtains the navigation route of the vehicle and the corresponding regional names, location characteristics, and time interval data of the vehicle at different locations. With the shortest total delay time, the lowest total SMS cost, and the highest reliability as objective conditions, it pre-selects the optimal pre-supply scheme corresponding to the current navigation route through an adaptive allocation algorithm. This reduces SMS sending costs and system response time, while also improving the SMS sending efficiency of the SMS provider, thereby further enhancing the user experience.

[0058] By acquiring data on SMS delivery success rate, average latency, and SMS cost, the system can assess the reliability of various SMS providers at different geographical locations and times. Selecting providers with high success rates, short latency, and good stability can significantly improve the reliability of information transmission, ensuring that critical notifications, traffic warnings, and emergency communications are delivered accurately and promptly.

[0059] The vehicle-to-everything (V2X) system uses navigation to pre-determine the vehicle's route (e.g., urban areas, highways, mountainous regions) and corresponding time periods, dynamically selecting a suitable SMS provider. For example, when a vehicle enters a mountainous area, it may choose a provider with strong signal penetration and low latency; while in urban areas or on highways, it will choose a provider with high success rates and good coverage, improving the overall flexibility and reliability of the system. Attached Figure Description

[0060] Figure 1 This is a schematic diagram of a vehicle-to-everything (V2X) global SMS provider optimization and switching system according to Embodiment 1 of the present invention;

[0061] Figure 2 This is a flowchart of a global SMS provider optimization and switching method for vehicle networking according to Embodiment 2 of the present invention;

[0062] Figure 3 This is a simplified schematic diagram of a navigation route for a vehicle in Embodiment 1 of the present invention;

[0063] Figure 4 This is a flowchart of the adaptive allocation algorithm of Embodiment 1 of the present invention. Detailed Implementation

[0064] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0065] Example 1

[0066] Please see Figure 1 As shown in this embodiment, a global SMS provider optimization and switching system for vehicle networking includes: a first acquisition module, a second acquisition module, a feature processing module, a sequence number setting module, a third acquisition module, a digital modeling module, a target setting module, a scheme generation module, and a scheme analysis module. The modules are connected to each other via wired and / or wireless means.

[0067] The first acquisition module is used to acquire navigation route information of the vehicle, including the current location, destination location, areas traversed, and total travel time; the areas traversed include mountainous areas, urban areas, and highway areas, etc. Figure 3 The image shows a simplified diagram illustrating the navigation route for a vehicle.

[0068] By obtaining navigation route information of the vehicle, the geographical location and route of the vehicle during its journey can be determined, and the total travel time can be obtained. This helps to obtain the vehicle's location data based on the navigation route, thereby selecting the optimal pre-supply plan from the SMS provider.

[0069] The navigation route information is obtained through third-party navigation platforms (such as Baidu Maps and Gaode Maps).

[0070] The second acquisition module acquires the location data of the vehicles traveling per unit time based on the navigation route information. The location data includes the vehicle location and the corresponding timestamp data. The length of the unit time is less than the total time spent.

[0071] The feature processing module is used to perform feature processing on location data and obtain feature-processed data. The feature-processed data includes region name, location features, and time interval data. The location features include urban areas, highway areas, mountainous areas, and rural areas. The region name is the name of the city area to which the vehicle location belongs. The time interval data is the hourly time period corresponding to the current specific time.

[0072] For example, in the location data, the vehicle's current location is longitude 117.0000 and latitude 39.0000, represented as [117.0000, 39.0000]; the timestamp data corresponding to the vehicle location is December 1, 2024, 10:30:00, represented as [2024, 12, 01, 103000]; in the corresponding feature processing data, the region name is Tianjin City; the location feature is highway area; the time interval data is between 10:00 and 11:00, represented as [10, 11].

[0073] The serial number setting module is used to set the supplier serial number corresponding to the global SMS provider.

[0074] For example, the global SMS providers include Tencent Cloud, MTC, MTN and AWS; the supplier number corresponding to Tencent Cloud is a1, the supplier number corresponding to MTC is a2, the supplier number corresponding to MTN is a3, and the supplier number corresponding to AWS is a4.

[0075] The supplier serial number is automatically set through the corresponding API interface of the supplier.

[0076] The third acquisition module is used to acquire SMS data from global SMS providers, including SMS delivery success rate, average latency time, and SMS cost.

[0077] SMS delivery success rate represents the percentage of SMS messages successfully delivered by a particular global SMS provider over a given period, directly reflecting the provider's reliability. A high success rate means the SMS messages effectively reach their destination, while a low success rate indicates that some messages are lost or not delivered, which is extremely dangerous for the transmission of important notifications and information in connected vehicle applications. By obtaining the SMS delivery success rates of global SMS providers in different geographical regions and time periods, we can improve the rationality of calculating the highest reliability in subsequent adaptive allocation algorithms, thereby aiding in the selection of the optimal solution for subsequent pre-supply schemes.

[0078] Average latency time represents the average time from the sending to the delivery of multiple text messages sent through a global SMS provider over a period of time. In connected vehicle applications, SMS sending delays can affect the efficiency of certain real-time decisions. For example, vehicles need to receive timely road condition updates, speed limit warnings, and emergency communications. Long delays can lead to information lag, which in turn affects the decision-making of drivers or autonomous driving systems. By obtaining the average latency time of global SMS providers in different geographical regions and time periods, it is helpful for subsequent adaptive allocation algorithms to calculate the total latency time in the target conditions, thereby aiding in the selection of the optimal solution for subsequent pre-supply schemes.

[0079] SMS cost represents the cost of each SMS message, directly impacting the economic efficiency of the system, especially in connected vehicle applications where a large number of SMS messages are sent. Optimizing costs helps reduce unnecessary expenses and ensures the system continues to operate within budget. Obtaining SMS costs from global providers in different geographical regions and time periods helps in selecting the optimal solution for subsequent pre-supply plans.

[0080] The method for obtaining the SMS sending success rate includes:

[0081] Step S1: Obtain historical transmission status data, which includes the SMS sending status, sending time, and delivery time; divide the historical transmission status data into different regions, corresponding location features, and different time intervals. Group data transmission; statistics The sending status of all SMS messages corresponding to the group transmission data, including success and failure; It is a positive integer greater than 1; the historical transmission status data is obtained through the supplier's API interface.

[0082] Step S2: For each group of transmitted data, divide the SMS messages with a successful sending status by the total number of SMS messages to calculate the corresponding SMS sending success rate.

[0083] The method for obtaining the average delay time includes:

[0084] Step M1, Statistics The sending and delivery times of all SMS messages corresponding to the group transmission data.

[0085] Step M2: Subtract the sending time from the delivery time of each SMS message to calculate the delay time for each SMS message.

[0086] Step M3: Calculate the average delay time of all SMS messages in each group of transmitted data.

[0087] The SMS cost was obtained from the pricing information on the supplier's official website.

[0088] The digital modeling module builds a digital model based on feature processing data, supplier serial numbers, and SMS data.

[0089] The target setting module sets target conditions based on a digital model. These target conditions include the shortest total delay time, the lowest total SMS cost, and the highest reliability.

[0090] The reliability refers to the applicability of the pre-supply plan corresponding to the current navigation route information.

[0091] The scheme generation module is used to randomly generate schemes. A pre-supply plan.

[0092] The scheme analysis module optimizes the pre-supply scheme using an adaptive allocation algorithm based on the target conditions, and outputs the optimized pre-supply scheme to meet the set target conditions.

[0093] Please see Figure 4 The adaptive allocation algorithm optimizes the pre-supply plan by including:

[0094] Step N1: Initialize the particle swarm. Each particle swarm represents a pre-supply plan. The pre-supply plan includes the supplier number selected by the vehicle when it is in different regions, with different location characteristics and corresponding time interval data.

[0095] For example, if the domain name of the current vehicle's location is Tianjin City; the location characteristic is a highway area; and the time interval data is between 10:00 and 11:00, then the corresponding supplier number a1 of Tencent Cloud is selected.

[0096] Step N2: Obtain the total delay time, total SMS cost, and reliability for each pre-supply plan.

[0097] The method for obtaining the total delay time includes:

[0098] Step Q1: For all feature processing data on the current navigation route of the vehicle, obtain the average delay time corresponding to each set of feature processing data.

[0099] Step Q2: Sum all the average delay times to calculate the total delay time.

[0100] The method for obtaining the total delay time is used to obtain the total SMS cost; the method for obtaining the total SMS cost includes:

[0101] Step V1: For all feature processing data on the current navigation route of the vehicle, obtain the SMS cost corresponding to each set of feature processing data.

[0102] Step V2: Sum all SMS costs to calculate the total SMS cost.

[0103] The method for obtaining the reliability includes:

[0104] .

[0105] In the formula, For reliability; This represents the total delay time. For the first SMS sending success rate corresponding to group feature processing data; and These are the corresponding preset weights; This represents the total number of feature processing data sets corresponding to the current navigation route information. .

[0106] Step N3: Calculate based on total latency, total SMS cost, and reliability. Overall adaptability of pre-supply programs The overall fitness The calculation methods include:

[0107] .

[0108] In the formula, , and Preset weighting coefficients; This represents the total cost of SMS messages.

[0109] Step N4: Update the particle velocity and position, i.e., update the supplier sequence number selected by the vehicle when considering different region names, location characteristics, and corresponding time interval data, and generate a new pre-supply plan; the method for updating particle velocity includes:

[0110] .

[0111] In the formula, For the first The particle in the first Speed ​​during the next iteration; For the first The particle in the first Speed ​​during the next iteration; For the first The particle in the first The position at the next iteration; For the first The best historical position that each particle finds in the corresponding pre-supply scheme is the one with the highest reliability. The optimal position found globally (i.e., among all pre-supply schemes) for all particles; Inertial weights control the continuity of particle velocity; For individual learning factors, The larger the value, the more the particle will rely on its own historical experience; As a group learning factor, The larger the value, the more likely the particle will rely on the collective experience of the group; and All numbers are random numbers in the range [0,1], increasing the randomness of the search.

[0112] For example, the first The parameters of each particle are as follows: ; ; ; ; ; ; ; ; .

[0113] Inertia term calculation:

[0114] .

[0115] Individual cognitive item calculation:

[0116] .

[0117] Group cognition item calculation:

[0118] .

[0119] Update speed calculation:

[0120] .

[0121] Particle position update methods include:

[0122] .

[0123] For example, the first The updated positions of the particles are:

[0124] .

[0125] Step N5, if the position is updated after the first... If the reliability of a single particle is greater than the reliability corresponding to the historical best position, then let If the position is updated after the first... If the reliability of a single particle is greater than the reliability corresponding to the global optimal position, then let .

[0126] Step N6: Repeat steps N2 to N5 until the preset number of repetitions is reached. Then, select the pre-supply plan with the highest overall adaptability. The pre-supply plan with the highest overall adaptability is the output optimized pre-supply plan, which meets the set target conditions.

[0127] Example 2

[0128] Please see Figure 2 As shown, this embodiment provides a method for optimizing and switching global SMS providers for connected vehicles, including:

[0129] Obtain navigation route information for the vehicle in motion;

[0130] Based on navigation route information, obtain the location data of vehicles traveling per unit time;

[0131] The location data is subjected to feature processing to obtain feature-processed data, which includes region name, location features and time interval data;

[0132] Set the supplier serial number corresponding to the global SMS provider;

[0133] Obtain SMS data from global SMS providers, including SMS delivery success rate, average latency, and SMS cost;

[0134] A digital model is established based on feature processing data, supplier serial numbers, and SMS data;

[0135] The target conditions are set based on a digital model, including the shortest total latency, the lowest total SMS cost, and the highest reliability.

[0136] Randomly generated Pre-supply plan;

[0137] Based on the target conditions, an adaptive allocation algorithm is used to optimize the pre-supply plan, and the optimized pre-supply plan is output.

[0138] Example 3

[0139] The electronic device in this embodiment includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps in an embodiment of a method for optimizing and switching global SMS providers for connected vehicles. Figure 2 The steps shown. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 1 The functions of the module shown.

[0140] For example, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal device.

[0141] Those skilled in the art will understand that this is merely an example of an electronic device and does not constitute a limitation on the electronic device. It may include more or fewer components than illustrated, or combine certain components, or different components. For example, the electronic device may also include input / output devices, network access devices, buses, etc.

[0142] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0143] The memory can be an internal storage unit of the terminal device, such as a hard drive or RAM. Alternatively, it can be an external storage device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or FlashCard. Furthermore, the memory can include both internal and external storage units. The memory is used to store the computer program and other programs and data required by the terminal device. It can also be used to temporarily store data that has been output or will be output.

[0144] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are 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 application.

[0145] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0146] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0147] If integrated modules / units are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the above method embodiments. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0148] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for optimizing and switching global SMS providers for connected vehicles, characterized in that, include: Obtain navigation route information for the vehicle in motion; Based on navigation route information, obtain the location data of vehicles traveling per unit time; The location data is subjected to feature processing to obtain feature-processed data, which includes region name, location features and time interval data; Set the supplier serial number corresponding to the global SMS provider; Obtain SMS data from global SMS providers, including SMS delivery success rate, average latency, and SMS cost; A digital model is established based on feature processing data, supplier serial numbers, and SMS data; The target conditions are set based on a digital model, including the shortest total latency, the lowest total SMS cost, and the highest reliability. The method for obtaining the total delay time includes: Step Q1: For all feature processing data on the current navigation route of the vehicle, obtain the average delay time corresponding to each set of feature processing data; Step Q2: Sum all the average delay times to calculate the total delay time; The method for obtaining the total SMS cost includes: Step V1: For all feature processing data on the current navigation route of the vehicle, obtain the SMS cost corresponding to each set of feature processing data; Step V2: Sum all SMS costs to calculate the total SMS cost; Randomly generated Pre-supply plan; Based on the target conditions, an adaptive allocation algorithm is used to optimize the pre-supply plan, and the optimized pre-supply plan is output.

2. The method for optimizing and switching global SMS providers for vehicle-to-everything (V2X) communication according to claim 1, characterized in that, The adaptive allocation algorithm optimizes the pre-supply scheme by including the following methods: Step N1: Initialize the particle swarm. Each particle swarm represents a pre-supply plan. The pre-supply plan includes the supplier number selected when the vehicle is in different regions, with different location characteristics and corresponding time interval data. Step N2: Obtain the total delay time, total SMS cost, and reliability for each pre-supply plan; Step N3: Calculate based on total latency, total SMS cost, and reliability. Overall adaptability of pre-supply programs ; Step N4: Update the particle's velocity and position, that is, update the supplier sequence number selected by the vehicle when it is in different regions, with different location characteristics and corresponding time interval data, and generate a new pre-supply plan. Step N5, if the position is updated after the first... If the reliability of a single particle is greater than the reliability corresponding to the historical best position, then let If the position is updated after the first... If the reliability of a single particle is greater than the reliability corresponding to the global optimal position, then let ; For the first The particle in the first The position at the next iteration; For the first The best historical position that each particle finds in the corresponding pre-supply scheme is the one with the highest reliability. The globally optimal position found among all particles; Step N6: Repeat steps N2 to N5 until the preset number of repetitions is reached. Then, select the pre-supply plan with the highest overall adaptability. The pre-supply plan with the highest overall adaptability is the output optimized pre-supply plan, which meets the set target conditions.

3. The method for optimizing and switching global SMS providers for vehicle-to-everything (V2X) communication according to claim 2, characterized in that, The method for obtaining the reliability includes: ； In the formula, For reliability; This represents the total delay time. For the first SMS sending success rate corresponding to group feature processing data; and These are the corresponding preset weights; This represents the total number of feature processing data sets corresponding to the current navigation route information. .

4. The method for optimizing and switching global SMS providers for vehicle-to-everything (V2X) communication according to claim 1, characterized in that, The method for obtaining the SMS sending success rate includes: Step S1: Obtain historical transmission status data, which includes the SMS sending status, sending time, and delivery time; divide the historical transmission status data into different regions, corresponding location features, and different time intervals. Group data transmission; statistics The sending status of all SMS messages corresponding to the group transmission data, including success and failure; It is a positive integer greater than 1; Step S2: For each group of transmitted data, divide the SMS messages with a successful sending status by the total number of SMS messages to calculate the corresponding SMS sending success rate.

5. The method for optimizing and switching global SMS providers for vehicle-to-everything (V2X) communication according to claim 1, characterized in that, The method for obtaining the average delay time includes: Step M1, Statistics The sending and delivery times of all SMS messages corresponding to the group transmission data; Step M2: Subtract the sending time from the delivery time of each SMS message to calculate the delay time for each SMS message. Step M3: Calculate the average delay time of all SMS messages in each group of transmitted data.

6. The method for optimizing and switching global SMS providers for vehicle-to-everything (V2X) communication according to claim 2, characterized in that, The overall fitness The calculation methods include: ； In the formula, , and Preset weighting coefficients; For the total SMS cost, For reliability, This represents the total delay time.

7. The method for optimizing and switching global SMS providers for vehicle-to-everything (V2X) communication according to claim 2, characterized in that, Methods for updating particle velocity include: ； In the formula, For the first The particle in the first Speed ​​during the next iteration; For the first The particle in the first Speed ​​during the next iteration; For the first The particle in the first The position at the next iteration; Inertial weights control the continuity of particle velocity; For individual learning factors; For group learning factors; and All are random numbers in the range [0,1]. Particle position update methods include: 。 8. The method for optimizing and switching global SMS providers for vehicle networking according to claim 1, characterized in that... The location data includes the vehicle location and the corresponding timestamp data; the location features include urban areas, highway areas, mountainous areas, and rural areas; the region name is the name of the city area to which the vehicle location belongs; and the time interval data is the hourly time period corresponding to the current specific time.

9. A global SMS provider optimization and switching system for connected vehicles, implementing the global SMS provider optimization and switching method for connected vehicles as described in any one of claims 1-8, characterized in that, include: The first acquisition module is used to acquire navigation route information of the driving vehicle; The second acquisition module acquires the location data of vehicles traveling per unit time based on navigation route information; The feature processing module is used to perform feature processing on location data and obtain feature-processed data, which includes region name, location features and time interval data. The serial number setting module is used to set the supplier serial number corresponding to the global SMS provider; The third acquisition module is used to acquire SMS data from global SMS providers, including SMS sending success rate, average latency time and SMS cost. The digital modeling module builds a digital model based on feature processing data, supplier serial numbers, and SMS data. The target setting module sets target conditions based on a digital model. These target conditions include the shortest total delay time, the lowest total SMS cost, and the highest reliability. The scheme generation module is used to randomly generate schemes. Pre-supply plan; The scheme analysis module optimizes the pre-supply scheme using an adaptive allocation algorithm based on the target conditions and outputs the optimized pre-supply scheme.

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