Network optimization method, vehicle, storage medium and computer program product

Abstract

The invention discloses a network optimization method, a vehicle, a storage medium and a computer program product, and relates to the technical field of vehicles, the network optimization method is applied to the vehicle, the vehicle comprises a vehicle-mounted communication module and a vehicle-mounted calculation module, and the method specifically comprises the steps that the module state of the vehicle-mounted calculation module is detected, the module state is a use state or an idle state; when it is detected that the module state is the use state, an interaction log of the vehicle-mounted calculation module is read; and executing network optimization operation according to a target network optimization strategy which is a first network optimization strategy or a second network optimization strategy under the condition that the vehicle-mounted computing module is determined to have a network lagging phenomenon according to the interaction log. According to the invention, the technical effect of improving the network optimization operation efficiency is achieved.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a network optimization method, a vehicle, a storage medium, and a computer program product. Background Art

[0002] With the continuous development of the automotive industry, vehicles have increasingly higher demands for the real-time and stability of network connections, especially for on-board communication modules and on-board computing modules that are highly dependent on a reliable network environment with low latency.

[0003] In related technologies, vehicles periodically upload network status parameters to the base station, which then screens all switchable base stations based on the network status parameters to determine the target base station / target cell that best matches the vehicle's network status parameters, and then sends a switching instruction to the target base station / target cell to complete the vehicle's network optimization operation.

[0004] However, base stations usually need to process massive amounts of network status data uploaded by vehicles, which results in a large delay in the process from collecting network status parameters to specifying switching strategies, which greatly reduces the efficiency of network optimization operations. Summary of the invention

[0005] The main purpose of this application is to provide a network optimization method, vehicle, storage medium and computer program product, aiming to solve the technical problem of low efficiency of network optimization operation in related technologies.

[0006] To achieve the above object, the present application proposes a network optimization method, which is applied to a vehicle, wherein the vehicle includes an on-board communication module and an on-board computing module, and the network optimization method includes: Detecting a module state of the vehicle-mounted computing module, wherein the module state is a use state or an idle state; When it is detected that the module state is the use state, reading the interaction log of the vehicle-mounted computing module; When it is determined according to the interaction log that the on-board computing module has a network lag phenomenon, a network optimization operation is performed according to a target network optimization strategy, wherein the target network optimization strategy is a first network optimization strategy or a second network optimization strategy.

[0007] In one embodiment, after the step of reading the interaction log of the vehicle-mounted computing module, the method further includes: Determine the number of screen clicks and the screen click time contained in the interaction log, and determine the user operation frequency according to the number of screen clicks and the screen click time; When it is detected that the user operation frequency reaches a preset click frequency threshold, it is determined that the vehicle-mounted computing module has a network jam phenomenon, and the step of performing the network optimization operation according to the target network optimization strategy is executed.

[0008] In one embodiment, the vehicle is in communication with a cloud server, and after the step of detecting the module status of the vehicle-mounted computing module, the method further includes: When it is detected that the module state is the use state, determining a plurality of first network state parameters corresponding to the vehicle-mounted computing module; Sending the plurality of the first network status parameters to the cloud server, and receiving a network environment detection result issued by the cloud server, wherein the network environment detection result is generated by a lightweight timing prediction model deployed in the cloud server based on the plurality of the first network status parameters; A target network optimization strategy is determined according to the network environment detection result, and a network optimization operation is performed according to the target network optimization strategy.

[0009] In one embodiment, the step of determining a target network optimization strategy according to the network environment detection result includes: When it is detected that the network environment detection result is that the vehicle-mounted computing module is in a weak network environment, a preset first network optimization strategy is determined as a target network optimization strategy, wherein the first network optimization strategy is a network optimization strategy for switching a communication cell corresponding to the vehicle; When it is detected that the network environment detection result is that the on-board computing module is in a network change environment, the preset second network optimization strategy is determined as the target network optimization strategy, wherein the second network optimization strategy is a network optimization strategy for switching the network connection mode corresponding to the vehicle.

[0010] In one embodiment, the vehicle is in communication connection with the target mobile terminal, and the step of performing the network optimization operation according to the target network optimization strategy includes: When detecting that the target network optimization strategy is the first network optimization strategy, receiving a cell feature database sent by the target mobile terminal; The cell feature database is queried based on a plurality of first network status parameters to determine a target cell, and the vehicle is connected to the target cell through the vehicle communication module.

[0011] In one embodiment, the step of performing the network optimization operation according to the target network optimization strategy further includes: In the case where it is detected that the target network optimization strategy is the second network optimization strategy, determining a preset target network connection standard; The current network connection mode corresponding to the vehicle is switched to the target network connection mode through the vehicle-mounted communication module.

[0012] In one embodiment, after the step of detecting the module status of the vehicle-mounted computing module, the method further includes: When detecting that the module state is the idle state, determining a plurality of second network state parameters corresponding to the vehicle-mounted communication module; Determine a preset global network environment judgment rule, and determine a state parameter threshold corresponding to each of a plurality of second network state parameters included in the global network environment judgment rule; Comparing the plurality of second network status parameters with the respective corresponding status parameter thresholds to obtain a plurality of first comparison results, and determining a target network status parameter based on the plurality of first comparison results, wherein the target network status parameter is a second network status parameter that reaches the status parameter threshold; When it is detected that the number of the target network status parameters reaches a first number threshold, determining that the network environment corresponding to the vehicle-mounted communication module is a weak network environment; The first network optimization strategy is determined as a target network optimization strategy, and a network optimization operation is performed according to the target network optimization strategy.

[0013] In one embodiment, after the step of determining the target network state parameter based on the plurality of first comparison results, the method further includes: In the case where it is detected that the number of the target network state parameters reaches a second number threshold, determining that the network environment corresponding to the vehicle-mounted communication module is a network change environment, wherein the second number threshold is greater than the first number threshold; The second network optimization strategy is determined as the target network optimization strategy, and the network optimization operation is performed according to the target network optimization strategy.

[0014] In addition, to achieve the above-mentioned purpose, the present application also proposes a vehicle, which includes: an on-board communication module, an on-board computing module, a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the computer program is configured to implement the steps of the network optimization method described above.

[0015] In addition, to achieve the above objectives, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the network optimization method described above are implemented.

[0016] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, wherein the computer program product includes a computer program, and when the computer program is executed by a processor, the steps of the network optimization method described above are implemented.

[0017] The network optimization method provided in the embodiment of the present application is applied to a vehicle, wherein the vehicle includes an on-board communication module and an on-board computing module, and the module state of the on-board computing module is detected, wherein the module state is a use state or an idle state; when it is detected that the module state is the use state, the interaction log of the on-board computing module is read; when it is determined according to the interaction log that the on-board computing module has a network lag phenomenon, a network optimization operation is performed according to a target network optimization strategy, wherein the target network optimization strategy is a first network optimization strategy or a second network optimization strategy.

[0018] In this embodiment, while the vehicle is driving, it first detects the on-board computing module configured with itself to determine whether the module state of the on-board computing module is in use or idle state. After that, when the vehicle detects that the module state of the on-board computing module is in use, the vehicle further reads the interaction log contained in the on-board computing module. Finally, the vehicle identifies whether the on-board computing module has a network lag phenomenon based on the interaction log, and when it is determined that the on-board computing module has a network lag phenomenon, the vehicle determines the preset first network optimization strategy or the second network optimization strategy as the target network execution strategy, and actively performs network optimization operations based on the target network execution strategy to change the connected base station or network connection standard.

[0019] In this way, the present application solves the technical problem of low efficiency of network optimization operations in related technologies. That is, the present application determines whether the on-board computing module has network lag based on the interaction log of the on-board computing module when it detects that the on-board computing module is in use, and actively performs network optimization operations according to the target network optimization strategy when it detects that the on-board computing module has network lag. This enables the vehicle end to actively initiate a network optimization request to the base station, so that the base station does not need to further screen the appropriate target base station / target cell after collecting the network status parameters, thereby reducing the delay in the network optimization operation process and greatly improving the efficiency of the network optimization operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0021] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 A schematic diagram of an existing network optimization operation scenario involved in an embodiment of the network optimization method of the present application; Figure 2 A flowchart of the first embodiment of the network optimization method of the present application is provided; Figure 3 This is a schematic diagram of a multi-terminal interaction scenario involved in an embodiment of the network optimization method of the present application; Figure 4 This is a schematic diagram of the module structure of the network optimization device according to an embodiment of the present application; Figure 5 A schematic diagram of the device structure of the hardware operating environment involved in the network optimization method in the embodiment of the present application.

[0023] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0024] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0025] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0026] In this embodiment, for ease of description, the following description is based on a vehicle equipped with an on-board computing module and an on-board communication module, or a mobile terminal, a data storage control terminal, a PC and other terminals connected to an electronic control unit of the vehicle as the execution subject.

[0027] It should be noted that the vehicle-mounted computing module is a device with strong computing power configured in the vehicle, which can be specifically hardware devices such as smart cockpit controller and intelligent driving controller. In addition, the vehicle-mounted communication device is a communication device with weak computing power configured in the vehicle, which can switch network connection standards and base stations.

[0028] Based on the above-mentioned vehicle, the overall concept of the network optimization method of the present application is proposed here.

[0029] With the continuous development of the automotive industry, vehicles have higher and higher requirements for the real-time and stability of network connections, especially for vehicle communication modules and vehicle computing modules, which are highly dependent on a reliable network environment with low latency. Figure 1 , Figure 1 Schematic diagram of an existing network optimization operation scenario involved in an embodiment of the network optimization method of the present application, such as Figure 1 As shown, the vehicle periodically uploads network status parameters to the base station, and the base station screens all switchable base stations based on the network status parameters to determine the target base station / target cell that best matches the vehicle's network status parameters, and then sends a switching instruction to the target base station / target cell to complete the vehicle's network optimization operation. However, the base station usually needs to process a large amount of network status data uploaded by the vehicle, which results in a large delay in the process from collecting network status parameters to specifying switching strategies, which greatly reduces the efficiency of network optimization operations.

[0030] In response to the above phenomenon, the present application provides a network optimization method, which is applied to a vehicle, wherein the vehicle includes an on-board communication module and an on-board computing module, and the network optimization method includes: detecting a module state of the on-board computing module, wherein the module state is a use state or an idle state; when it is detected that the module state is the use state, reading an interaction log of the on-board computing module; when it is determined according to the interaction log that the on-board computing module has a network lag phenomenon, performing a network optimization operation according to a target network optimization strategy, wherein the target network optimization strategy is a first network optimization strategy or a second network optimization strategy.

[0031] In this way, the present application solves the technical problem of low efficiency of network optimization operations in related technologies. That is, the present application determines whether the on-board computing module has network lag based on the interaction log of the on-board computing module when it detects that the on-board computing module is in use, and actively performs network optimization operations according to the target network optimization strategy when it detects that the on-board computing module has network lag. This enables the vehicle end to actively initiate a network optimization request to the base station, so that the base station does not need to further screen the appropriate target base station / target cell after collecting the network status parameters, thereby reducing the delay in the network optimization operation process and greatly improving the efficiency of the network optimization operation.

[0032] Based on the overall concept of the network optimization method of the present application, the embodiment of the present application provides a network optimization method, referring to Figure 2 , Figure 2 This is a flow chart of the first embodiment of the network optimization method of the present application. In this embodiment, the network optimization method is applied to a vehicle, the vehicle includes an on-board communication module and an on-board computing module, and the network optimization method includes steps S10 to S30: Step S10: Detecting the module state of the vehicle-mounted computing module, wherein the module state is a use state or an idle state; It should be noted that the module status is the network resource occupancy status of the on-board computing module, including: usage status or idle status. When the on-board computing module is in the usage status, it indicates that the user has started network-related applications (such as music APP, navigation APP, etc.) through the on-board computing module, and the network-related applications are occupying network resources. Similarly, when the on-board computing module is in the idle state, it indicates that all network-related applications are not running, or the running network-related applications are not actively occupying network resources (such as an APP that is performing local updates in the background).

[0033] In this embodiment, when the vehicle is driving, the on-board control system integrated in the vehicle first accesses the system process management interface of the on-board computing module configured by the vehicle, so as to obtain the application running list of the on-board computing module through the system process management interface, and determine the network occupancy parameters corresponding to each of the running network-related applications according to the application running list. The on-board management system then determines that the module state of the on-board computing module is in use state based on the obtained application running list and each network occupancy parameter, when it detects that the network occupancy parameter of at least one network-related application reaches a preset occupancy parameter threshold. Similarly, the on-board management system determines that the module state is idle state when it detects that all network-related applications are in a closed state / the network occupancy parameters of all network-related applications have not reached the occupancy parameter threshold.

[0034] Exemplary, for example, while the vehicle is driving, if the user starts a music APP through the smart cockpit controller configured in the smart cockpit, and controls the music APP to play online music in real time, at this time, the on-board control system integrated in the vehicle accesses the system process management interface in the smart cockpit controller to obtain the startup APP list through the system process management interface, and determines that the on-board APP being started is a music APP based on the startup APP list. At the same time, the on-board management system determines the network occupancy parameters corresponding to the music APP based on the startup APP list, and when it detects that the network occupancy parameters reach the preset occupancy parameter threshold, it determines that the music APP is in an active state. At this time, the on-board management system determines that the module state of the smart cockpit controller is in use state.

[0035] Similarly, in this embodiment and another embodiment, if the vehicle control system reads the startup APP list and determines that all system APPs are not running, it directly determines that the module status of the cockpit controller is idle; or, if the vehicle control system reads the startup APP list and determines that the music APP is running, but the network occupancy parameter of the music APP does not reach the above-mentioned occupancy parameter threshold, the vehicle control system determines that the music APP is in an inactive state, and determines that the module status of the cockpit controller is idle.

[0036] Step S20: when it is detected that the module state is in use, reading the interaction log of the vehicle-mounted computing module; It should be noted that the interaction log contains various operation behaviors generated when the user controls the on-board computing module through the human-computer interaction interface. It can be understood that the operation behavior includes direct interaction behaviors such as touch clicks, voice commands, gesture operations, and indirect interaction behaviors such as sound quality adjustment, playback ratio switching, and application window scaling.

[0037] In this embodiment, when the vehicle-mounted control system detects that the module state of the vehicle-mounted computing module is in use, it further accesses the vehicle-mounted computing module to obtain the interaction log, and reads the direct interaction behaviors and / or indirect interaction behaviors contained in the interaction log, thereby judging whether there is network lag during use of the vehicle-mounted computing module based on the direct interaction behaviors and / or indirect interaction behaviors.

[0038] Exemplarily, for example, if the vehicle management system determines that the module state of the smart cockpit controller is in use, it further accesses the smart cockpit controller to obtain the interaction log stored in the smart cockpit controller, and the vehicle management system reads the touch click event contained in the interaction log, and determines the number of clicks and click time generated when the user performs interactive operations through the HMI (Human-Machine Interface) according to the touch click event, and then recognizes that the user continues to click pause in the music APP according to the number of clicks and click time, and determines that the smart cockpit controller has a network freeze phenomenon; Similarly, in this embodiment and another embodiment, after obtaining the interaction log, the vehicle management system can also read the sound quality adjustment event contained in the interaction log, and directly determine that the smart cockpit controller has a network freeze phenomenon when determining that the user performs a sound quality degradation operation in the music APP according to the sound quality adjustment event; Similarly, in this embodiment and another embodiment, after obtaining the interaction log, if the vehicle management system determines based on the interaction log that the user has not continuously clicked pause or performed sound quality degradation operations in the music APP, then it can be determined that there is no network lag in the smart cockpit controller.

[0039] In this way, the vehicle can identify the interactive behavior triggered by the user in the on-board computing module, and identify whether there is network lag in the on-board computing module based on the interactive behavior.

[0040] In a feasible implementation manner, after the above step S20, the network optimization method of the present application may further include steps S201-S202: Step S201: determining the number of screen clicks and the screen click time contained in the interaction log, and determining the user operation frequency according to the number of screen clicks and the screen click time; Step S202: When it is detected that the user operation frequency reaches a preset click frequency threshold, it is determined that the vehicle-mounted computing module has a network jam phenomenon, and the step of performing the network optimization operation according to the target network optimization strategy is executed.

[0041] In this embodiment, after obtaining the interaction log, the vehicle-mounted control system reads the number of screen clicks and the screen click time contained in the interaction log, and determines the user operation frequency of the user on the vehicle-mounted computing module within a certain time period based on the number of screen clicks and the screen click time. After that, the vehicle-mounted control system obtains a preset click frequency threshold, and compares the user operation frequency with the click frequency threshold. When the vehicle-mounted control system detects that the user operation frequency reaches the click frequency threshold, it determines that there is a network lag in the vehicle-mounted computing module.

[0042] Exemplarily, for example, after obtaining the interaction log, the vehicle control system reads the interaction log to determine the number of screen click operations on the HMI when the user controls the smart cockpit controller through the HMI, and determines the corresponding operation time each time the user clicks on the HMI based on the interaction log. The vehicle control system then calculates the user operation frequency of the user operating the HMI within a certain period of time based on the number of clicks and the click time. Thereafter, the vehicle control system obtains a preset click frequency threshold and compares the user operation frequency with the click frequency threshold. When the vehicle control system detects that the user operation frequency reaches the click frequency threshold, it determines that the smart cockpit controller is unable to respond to the user's click operation. At this time, the vehicle control system determines that the smart cockpit controller has a network lag phenomenon.

[0043] In addition, in this embodiment and another embodiment, after obtaining the interaction log, the vehicle management system can also read the sound quality adjustment events contained in the interaction log, and when it is determined based on the sound quality adjustment events that the user performs a sound quality degradation operation in the music APP, it can directly determine that there is a network lag in the smart cockpit controller.

[0044] In this way, the vehicle can identify the interactive behavior triggered by the user in the on-board computing module, and identify whether there is network lag in the on-board computing module based on the interactive behavior.

[0045] Step S30: when it is determined according to the interaction log that the vehicle-mounted computing module has a network freeze phenomenon, a network optimization operation is performed according to a target network optimization strategy, wherein the target network optimization strategy is a first network optimization strategy or a second network optimization strategy; It should be noted that the target network optimization strategy is a network adjustment plan dynamically selected according to the current network environment, including a first network optimization strategy or a second network optimization strategy, wherein the first network optimization strategy is a network optimization strategy for switching the communication cell corresponding to the vehicle, and the second network optimization strategy is a network optimization strategy for adjusting the network connection mode corresponding to the vehicle.

[0046] In this embodiment, when the vehicle management system determines that there is network lag in the vehicle computing module based on the interaction log, it determines the preset first network optimization strategy or the second network optimization strategy as the target network optimization strategy, and performs operations such as switching cells / adjusting network connection standards according to the target network optimization strategy to complete the network optimization operation.

[0047] Exemplarily, for example, when the vehicle management system determines, based on the above-mentioned interaction log, that the music APP running in the smart cockpit controller has network lag, it first determines that the target network optimization strategy for improving the network environment of the smart cockpit controller is the preset first network optimization strategy or the second network optimization strategy. The vehicle management system then controls the vehicle communication equipment according to the target network optimization strategy to enable the vehicle communication equipment to perform operations such as switching cells / switching the network connection mode from 5G mode to 4G mode, thereby optimizing the network environment of the smart cockpit controller.

[0048] In addition, in this embodiment and another embodiment, before the vehicle-mounted management system controls the vehicle-mounted communication equipment to execute operations such as switching cells / switching the network connection mode from 5G mode to 4G mode, the vehicle-mounted management system may first determine the application priority corresponding to each running APP, and determine the running non-critical APP according to each application priority, and then compress the bandwidth corresponding to each non-critical APP according to a preset compression ratio. After that, the vehicle-mounted management system re-detects whether there is a jamming phenomenon in the vehicle-mounted computing module, and if it is determined that the vehicle-mounted computing module still has a jamming phenomenon, it executes operations such as switching cells / switching the network connection mode from 5G mode to 4G mode according to the target network optimization strategy. It can be understood that in addition to compressing the bandwidth of non-critical APPs, the vehicle-mounted management system can also perform other parameter adjustment operations such as adjusting real-time traffic and optimizing TCP operations. This application does not limit the specific content of the parameter adjustment operation.

[0049] In this way, the vehicle can actively initiate a network optimization request to the base station, so that the base station does not need to further screen suitable target cells after collecting network status parameters, thereby reducing the delay in the network optimization operation process and greatly improving the efficiency of the network optimization operation.

[0050] In a feasible implementation manner, the vehicle is in communication connection with the target mobile terminal, and the step of "performing network optimization operation according to the target network optimization strategy" in the above step S30 may specifically include steps S301-S302: Step S301: receiving a cell feature database sent by the target mobile terminal when it is detected that the target network optimization strategy is the first network optimization strategy; Step S302: querying the cell feature database based on a plurality of first network status parameters to determine a target cell, and connecting the vehicle to the target cell through the vehicle communication module.

[0051] It should be noted that the cell feature database is a dynamic data set generated by unsupervised comparative learning of the target mobile terminal connected to the vehicle communication. The cell feature database contains multi-dimensional vector features of multiple cells contained in multiple base stations (such as signal strength, load rate, geographic location, historical performance), etc. It can be understood that the feature types and number of features contained in the cell feature database can be set by technical personnel according to actual needs, and this application does not impose any restrictions on this.

[0052] In this embodiment, when the vehicle-mounted control system determines that there is a network lag phenomenon in the vehicle-mounted computing module, if it is determined that the target network optimization strategy to be executed is the above-mentioned first network optimization strategy, it first receives the cell feature database sent by the target mobile terminal connected to itself for communication. Thereafter, the vehicle-mounted control system detects the vehicle-mounted computing module to obtain multiple first network status parameters corresponding to the vehicle-mounted computing module, and screens each preset cell contained in the cell feature database according to the multiple first network status parameters to determine the cells to be screened that meet the multiple first network status parameters, and determines the target cell that best matches the vehicle-mounted computing module according to the corresponding stability scores of each cell to be screened in the cell feature database. The vehicle-mounted control system sends the target cell to the vehicle-mounted communication module, and the vehicle-mounted communication module sends a switching request to the target cell to switch the cell currently connected to the vehicle to the target cell.

[0053] For example, see Figure 3 , Figure 3 Schematic diagram of a multi-terminal interaction scenario involved in an embodiment of the network optimization method of the present application, such as Figure 3As shown, when the vehicle control system determines that the smart cockpit controller has a network freeze phenomenon, if it determines that the target network optimization strategy to be executed is the above-mentioned first network optimization strategy, it first receives the cell feature database sent by the target mobile terminal connected to the vehicle communication, and then the vehicle control system detects the smart cockpit controller to determine the multiple first network status parameters such as RSSI (Received Signal Strength Indication) and delay contained in the smart cockpit controller. The vehicle control system then queries the cell feature database based on the multiple first network status parameters, and thus determines the cells to be screened in the cell feature database whose signal strength is greater than RSSI and whose load rate is less than a certain threshold based on the multiple first network status parameters. The vehicle control system then sorts the cells to be screened in order of priority according to the stability scores, geographical locations and other factors corresponding to each cell to be screened, so as to determine the target cell with the highest priority. Finally, the vehicle control system sends the target cell to the vehicle communication module Tx, and the vehicle communication module Tx sends a switching request carrying the vehicle-side identity information to the target cell to switch to the target cell.

[0054] In this way, the vehicle can actively initiate a network optimization request to the base station, so that the base station does not need to further screen suitable target cells after collecting network status parameters, thereby reducing the delay in the network optimization operation process and greatly improving the efficiency of the network optimization operation.

[0055] In a feasible implementation manner, the vehicle is in communication connection with the target mobile terminal, and the step of "performing network optimization operation according to the target network optimization strategy" in the above step S30 may further include steps S303-S304: Step S303: when it is detected that the target network optimization strategy is the second network optimization strategy, determining a preset target network connection standard; Step S304: Switching the current network connection standard corresponding to the vehicle to the target network connection standard through the vehicle-mounted communication module.

[0056] In this embodiment, when the vehicle-mounted control system determines that there is a network lag in the vehicle-mounted computing module, if it is determined that the target network optimization strategy to be executed is the above-mentioned second network optimization strategy, it first determines the target network connection standard to be switched, and then the vehicle-mounted control system sends the target network connection standard to the vehicle-mounted communication module, and the vehicle-mounted communication module switches the current network connection standard of the vehicle to the target network connection standard.

[0057] Exemplarily, for example, when the vehicle-mounted control system determines that there is a network lag in the smart cockpit controller, if it determines that the target network optimization strategy to be executed is the above-mentioned second network optimization strategy, it first determines the 4G low-frequency band standard as the target network connection standard based on the above-mentioned first network status parameters such as RSSI and latency. After that, the vehicle-mounted control system sends the target network connection standard to the vehicle-mounted communication module Tx, and the vehicle-mounted communication module Tx sends a standard switching request to the base station, thereby turning off the 5G RF module configured in the vehicle, activating the 4G module and connecting to the specified frequency band, so that the vehicle's connection standard is switched from 5G mode to 4G low-frequency band standard.

[0058] It is understandable that the specific process of the vehicle control system determining the target network connection mode based on the first network status parameter is prior art, so it will not be described in detail here.

[0059] In this embodiment, when the vehicle is driving, the vehicle control system integrated in the vehicle first accesses the system process management interface of the vehicle computing module configured by the vehicle, so as to obtain the application running list of the vehicle computing module through the system process management interface, and determine the network occupancy parameters corresponding to the running network-related application programs according to the application running list. The vehicle management system then determines that the module state of the vehicle computing module is in use state when it detects that the network occupancy parameter of at least one network-related application program reaches a preset occupancy parameter threshold value according to the obtained application running list and each network occupancy parameter. Similarly, the vehicle management system determines that the module state of the vehicle computing module is in use state when it detects that all network-related applications are in closed state / all network-related applications are in use state. If the network occupancy parameters of the program do not reach the occupancy parameter threshold, the module state is determined to be idle. After that, the vehicle control system accesses the vehicle computing module to obtain the interaction log, and reads the direct interaction behaviors and / or indirect interaction behaviors contained in the interaction log, so as to judge whether there is network lag phenomenon in the use of the vehicle computing module based on the direct interaction behaviors and / or indirect interaction behaviors. Finally, when the vehicle management system determines that there is network lag phenomenon in the vehicle computing module according to the interaction log, it determines the preset first network optimization strategy or the second network optimization strategy as the target network optimization strategy, and performs operations such as switching cells / adjusting network connection mode according to the target network optimization strategy to complete the network optimization operation.

[0060] In this way, the present application solves the technical problem of low efficiency of network optimization operations in related technologies. That is, the present application determines whether the on-board computing module has network lag based on the interaction log of the on-board computing module when it detects that the on-board computing module is in use, and actively performs network optimization operations according to the target network optimization strategy when it detects that the on-board computing module has network lag. This enables the vehicle end to actively initiate a network optimization request to the base station, so that the base station does not need to further screen the appropriate target base station / target cell after collecting the network status parameters, thereby reducing the delay in the network optimization operation process and greatly improving the efficiency of the network optimization operation.

[0061] Based on the first embodiment of the present application, a second embodiment of the present application is proposed. In the second embodiment of the present application, the same or similar contents as the above embodiments can be referred to the above description and will not be repeated later. On this basis, the vehicle and the cloud server are connected in communication. After the above step S10, the network optimization method of the present application can also include steps A10 to A30: Step A10: when it is detected that the module state is the use state, determining a plurality of first network state parameters corresponding to the vehicle-mounted computing module; Step A20: sending the plurality of the first network state parameters to the cloud server, and receiving a network environment detection result issued by the cloud server, wherein the network environment detection result is generated by a lightweight timing prediction model deployed in the cloud server based on the plurality of the first network state parameters; Step A30: Determine a target network optimization strategy according to the network environment detection result, and perform network optimization operations according to the target network optimization strategy.

[0062] In this embodiment, when the vehicle-mounted control system detects that the module state of the above-mentioned vehicle-mounted computing module is in use state, it further collects multiple first network state parameters generated by the vehicle-mounted computing module. After that, the vehicle-mounted control system uploads the collected multiple first network state parameters to a cloud server connected to the vehicle communication, and the cloud server generates input features based on the multiple first network state parameters, and inputs the input features into a lightweight timing prediction model configured in the cloud server. The lightweight timing prediction model generates a hidden state corresponding to the input features. The cloud server then determines the network environment of the smart cockpit controller according to the hidden state output by the lightweight timing prediction model, and generates a network environment detection result based on the network environment. The cloud server sends the network environment detection result to the vehicle-mounted management system. Finally, the vehicle-mounted control system reads the network environment detection result to determine that the target network optimization strategy is the above-mentioned first network optimization strategy or the second network optimization strategy according to the network environment detection result, and then controls the vehicle-mounted communication module according to the target network optimization strategy to perform network optimization operations.

[0063] For example, for example, Figure 3 As shown, when the vehicle-mounted control system detects that the module state of the above-mentioned vehicle-mounted computing module is in the use state, the intelligent cockpit controller is detected to obtain multiple first network state parameters such as RSSI, delay, packet loss rate, satellite signal strength, and throughput generated by the intelligent cockpit controller. After that, the vehicle-mounted control system accesses the cloud server connected to the vehicle communication and uploads the multiple first network state parameters to the cloud server. At this time, the cloud server generates an input feature containing multiple first network state parameters based on RSSI, delay, packet loss rate, satellite signal strength, and throughput. , the cloud server then inputs the features Input to the configured lightweight LSTM time series prediction model: ,in, is the input weight matrix used to map the input features to the latent space Down, (RSSI, throughput, latency, packet loss rate, satellite signal strength), The value is set according to the memory limit (typically 64 or 256), is a cyclic weight matrix used to model the temporal state transition relationship To prevent gradient explosion, is the hidden state output at the previous moment, which is used to retain the historical network feature memory to initialize the all-zero vector. is a bias term used to improve the model’s expressiveness. is an activation function, specifically a Hard Sigmoid function. It can be understood that the Hard Sigmoid function has the characteristic of lower computational complexity compared to the traditional Sigmoid function; The LSTM time series prediction model thus inputs the weight matrix For input features Processed to output the corresponding hidden state , the cloud server then reads the hidden state The network status timing characteristics contained in the network state are determined, and when the intelligent cockpit controller is determined to be in a weak network environment according to the timing characteristics of the network status, a corresponding network environment detection result is generated, and the cloud server then sends the network environment detection result to the vehicle control system. Finally, when the vehicle controller system determines that the intelligent cockpit controller is in a weak network environment according to the network environment detection result, the first network optimization strategy is determined as the target network optimization strategy, and the vehicle communication device Tx is controlled to perform the cell switching operation according to the first network optimization strategy; Similarly, if the cloud server determines that the smart cockpit controller is in a network change environment (for example, the normal network environment changes to the basement network environment, etc.) based on the timing characteristics of the network status, it generates a corresponding network environment detection result, and the cloud server then sends the network environment detection result to the vehicle control system. Finally, when the vehicle controller system determines that the smart cockpit controller is in a network change environment based on the network environment detection result, it determines the above-mentioned second network optimization strategy as the target network optimization strategy, and controls the vehicle communication device Tx to perform the connection mode switching operation according to the first network optimization strategy.

[0064] It should be noted that the lightweight LSTM time series prediction model combines the current input features (such as RSSI, delay) with historical hidden features through the cyclic weight matrix and the cyclic weight matrix to form a dynamic modeling of the network state, making the output hidden state It includes the mutation pattern of network parameters (such as a sudden drop in RSSI in the underground parking scenario) and periodic fluctuations (such as a periodic increase in packet loss rate in a weak network scenario), and then accurately identifies whether the network environment in which the vehicle is located is a weak network environment or a network change environment. It can be understood that there are many ways to train the lightweight LSTM time series prediction model, and this application does not limit this.

[0065] In this way, the vehicle can upload the collected network status data to the cloud server, and the cloud server will process the network status parameters through a lightweight time series prediction model to determine the network environment in which the vehicle is located. The vehicle can then select a network optimization strategy that matches the network environment, further improving the efficiency of network optimization operations.

[0066] In a feasible implementation manner, the step of "determining a target network optimization strategy according to the network environment detection result" in the above step A30 may specifically include steps A301-A302: Step A301: when it is detected that the network environment detection result is that the vehicle-mounted computing module is in a weak network environment, determining a preset first network optimization strategy as a target network optimization strategy, wherein the first network optimization strategy is a network optimization strategy for switching a communication cell corresponding to the vehicle; Step A302: When it is detected that the network environment detection result is that the on-board computing module is in a network change environment, a preset second network optimization strategy is determined as the target network optimization strategy, wherein the second network optimization strategy is a network optimization strategy for switching the network connection mode corresponding to the vehicle.

[0067] In this embodiment, after the vehicle-mounted control system receives the network environment detection result sent by the cloud server, if it is determined based on the network environment detection result that the vehicle-mounted computing module is in a weak network environment, the above-mentioned first network optimization strategy is determined as the target network optimization strategy to be executed. Similarly, if the vehicle-mounted control system determines based on the network environment detection result that the vehicle-mounted computing module is in a network changing environment, the above-mentioned second network optimization strategy for controlling the vehicle-mounted communication module to switch the network connection mode is determined as the target network optimization strategy.

[0068] Exemplarily, for example, when the cloud server determines that the smart cockpit controller is in a weak network environment, it generates a corresponding network environment detection result, and the cloud server then sends the network environment detection result to the vehicle control system. At this time, the vehicle control system receives the network environment detection result and reads the network environment included in the network environment detection result. The vehicle control system determines that the network environment is a weak network environment, and determines that the preset first network optimization strategy for controlling the vehicle communication device Tx to switch the communication cell is the target network optimization strategy; Similarly, when the cloud server determines that the smart cockpit controller is in a network change environment, it generates a corresponding network environment detection result, and the cloud server then sends the network environment detection result to the vehicle control system. At this time, the vehicle control system receives the network environment detection result and reads the network environment contained in the network environment detection result. The vehicle control system determines that the network environment is a network change environment, and then determines the preset second network optimization strategy for controlling the vehicle communication equipment Tx to switch the communication mode as the target network optimization strategy.

[0069] In this way, the vehicle can select the network optimization strategy that matches the network environment and further improve the efficiency of network optimization operations.

[0070] Based on the first embodiment and / or the second embodiment of the present application, the third embodiment of the present application is proposed here. In the third embodiment of the present application, the same or similar contents as the above embodiments can be referred to the above introduction, and will not be repeated later. On this basis, after the above step S10, the network optimization method of the present application can also include steps B10~B50: Step B10: when it is detected that the module state is the idle state, determining a plurality of second network state parameters corresponding to the vehicle-mounted communication module; Step B20: determining a preset global network environment judgment rule, and determining a state parameter threshold value corresponding to each of the plurality of second network state parameters included in the global network environment judgment rule; Step B30: comparing the plurality of second network status parameters with the respective corresponding status parameter thresholds to obtain a plurality of first comparison results, and determining a target network status parameter based on the plurality of first comparison results, wherein the target network status parameter is a second network status parameter that reaches the status parameter threshold; Step B40: when it is detected that the number of the target network status parameters reaches a first number threshold, determining that the network environment corresponding to the vehicle-mounted communication module is a weak network environment; Step B50: determine the first network optimization strategy as the target network optimization strategy, and perform network optimization operations according to the target network optimization strategy.

[0071] It should be noted that the global network judgment rule is a dynamic threshold setting rule generated by the cloud server based on massive data training, which is used to dynamically adjust the parameter judgment criteria according to different scenarios (such as cities, suburbs, and basements). In addition, the first quantity threshold is the minimum number of parameters that exceed the standard to trigger the weak network environment judgment (for example, if ≥3 parameters exceed the threshold, it is determined that the vehicle communication module is in a weak network environment), which is used to comprehensively evaluate the network environment.

[0072] In this embodiment, when the vehicle-mounted control system detects that the module state of the above-mentioned vehicle-mounted computing module is in an idle state, it further collects multiple second network state parameters generated by the vehicle-mounted communication module. After that, the vehicle-mounted control system obtains a preset global network judgment rule, and reads the state parameter thresholds corresponding to each of the multiple second network state parameters contained in the global network judgment rule. After that, the vehicle-mounted control system compares the multiple second network state parameters with the corresponding state parameter thresholds to obtain multiple first comparison results, and screens the target second network state parameters that reach the state parameter threshold based on the multiple first comparison results. Then, the vehicle-mounted control system reads the global network environment judgment rule to obtain the first quantity threshold, and when it is detected that the number of target second network state parameters reaches the first quantity threshold, it determines that the network environment in which the vehicle-mounted communication module is located is a weak network environment. Finally, the vehicle-mounted control system determines the above-mentioned first network optimization strategy as the target network optimization strategy to be executed, and controls the vehicle-mounted communication device Tx to perform the cell switching operation according to the first network optimization strategy.

[0073] Exemplarily, for example, when the vehicle control system detects that the module state of the above-mentioned vehicle computing module is in an idle state, the vehicle control system detects the vehicle communication device Tx to obtain multiple second network state parameters such as RSSI, delay, and packet loss rate generated by the vehicle communication device Tx. After that, the vehicle control system obtains the global network environment judgment rule sent by the cloud server, and reads the global network environment judgment rule to determine the network state parameter thresholds corresponding to each of the multiple second network state parameters. After that, the vehicle control system compares the multiple second network state parameters with the respective corresponding network state parameter thresholds to obtain multiple first comparison results, and determines the target second network state parameters that reach the network state parameter threshold according to the multiple first comparison results. Then, the vehicle control system determines the first quantity threshold through the global network environment judgment rule, and when it is detected that the number of the target second network state parameters reaches the first quantity threshold (for example, 3 groups), it determines that the vehicle communication device Tx is in a weak network environment. Finally, the vehicle control system determines the above-mentioned first network optimization strategy as the target network optimization strategy, and controls the vehicle communication device Tx to perform the cell switching operation according to the first network optimization strategy.

[0074] It should be noted that the deep residual network configured in the cloud server can be trained based on the network status parameters and network environment uploaded by the massive vehicle end to obtain the initial network environment judgment rules. The cloud server then uses the knowledge distillation technology to process the initial network environment judgment rules to generate lightweight global network environment judgment rules, and then sends the global network environment judgment rules to the vehicle. It is understandable that the global network environment judgment rules generated by the knowledge distillation technology have the characteristics of small size, which ensures that the bandwidth is under great pressure during the issuance of the global network environment judgment rules, further improving the efficiency of network optimization operations.

[0075] In this way, the vehicle can more accurately judge the network environment in which the vehicle is located based on the collected network status data, thereby screening out a network optimization strategy that matches the network environment and further improving the efficiency of network optimization operations.

[0076] Based on the various embodiments of the present application, a fourth embodiment of the present application is proposed here. In the fourth embodiment of the present application, the same or similar contents as the above embodiments can be referred to the above introduction, and will not be repeated later. On this basis, after the above step B30, the network optimization method of the present application can also include steps B60~B70: Step B60: when it is detected that the number of the target network status parameters reaches a second number threshold, determining that the network environment corresponding to the vehicle-mounted communication module is a network change environment, wherein the second number threshold is greater than the first number threshold; Step B70: Determine the second network optimization strategy as the target network optimization strategy, and perform network optimization operations according to the target network optimization strategy.

[0077] It should be noted that the second quantity threshold is the minimum number of parameters exceeding the standard required to determine the network change environment, and its value is greater than the above-mentioned first quantity threshold (for example, if ≥4 parameters exceed the threshold, it is determined that the vehicle communication module is in a network change environment).

[0078] In this embodiment, after screening out the above-mentioned target second network status parameters, the vehicle control system further reads the above-mentioned global network judgment rule to determine a second quantity threshold that is greater than the above-mentioned first quantity threshold. When the vehicle control system detects that the number of target second network status parameters reaches the second quantity threshold, it determines that the network environment in which the vehicle communication module is located is a network change environment. Finally, the vehicle control system determines the above-mentioned second network optimization strategy as the target network optimization strategy to be executed, and controls the vehicle communication device Tx to perform a connection mode switching operation according to the second network optimization strategy.

[0079] Exemplarily, for example, after screening out the above-mentioned target second network status parameter, the vehicle-mounted control system further reads the above-mentioned global network judgment rule to determine a second quantity threshold (for example, 4 groups) that is greater than the above-mentioned first quantity threshold. When the vehicle-mounted control system detects that the number of target second network status parameters reaches the second quantity threshold, it determines that the network environment in which the vehicle-mounted communication device Tx is located is a network change environment (for example, the vehicle enters a basement scene from a normal driving scene). Finally, the vehicle-mounted control system determines the above-mentioned second network optimization strategy as the target network optimization strategy, and controls the vehicle-mounted communication device Tx to send a mode switching request to the base station according to the second network optimization strategy, thereby turning off the 5G RF module configured in the vehicle, activating the 4G module and connecting to the specified frequency band, so that the vehicle's connection mode is switched from the 5G mode to the 4G low-frequency band mode.

[0080] In this way, the vehicle can more accurately judge the network environment in which the vehicle is located based on the collected network status data, thereby screening out a network optimization strategy that matches the network environment and further improving the efficiency of network optimization operations.

[0081] This application also provides a network optimization device, please refer to Figure 4 The network optimization device is applied to a vehicle, the vehicle comprises a vehicle-mounted communication module and a vehicle-mounted computing module, and the device comprises: The user behavior detection module 10 detects the module state of the vehicle-mounted computing module, wherein the module state is a use state or an idle state; The jamming phenomenon detection module 20: when detecting that the module state is the use state, reading the interaction log of the vehicle-mounted computing module; The network optimization execution module 30: when it is determined according to the interaction log that the on-board computing module has a network lag phenomenon, the network optimization operation is performed according to the target network optimization strategy, wherein the target network optimization strategy is the first network optimization strategy or the second network optimization strategy.

[0082] In a feasible implementation manner, the above-mentioned jamming phenomenon detection module 20 is further used for: Determine the number of screen clicks and the screen click time contained in the interaction log, and determine the user operation frequency according to the number of screen clicks and the screen click time; When it is detected that the user operation frequency reaches a preset click frequency threshold, it is determined that the vehicle-mounted computing module has a network jam phenomenon, and the step of performing the network optimization operation according to the target network optimization strategy is executed.

[0083] In a feasible implementation manner, the vehicle is communicatively connected to a cloud server, and the above-mentioned jamming phenomenon detection module 20 is further used for: When it is detected that the module state is the use state, determining a plurality of first network state parameters corresponding to the vehicle-mounted computing module; Sending the plurality of the first network status parameters to the cloud server, and receiving a network environment detection result issued by the cloud server, wherein the network environment detection result is generated by a lightweight timing prediction model deployed in the cloud server based on the plurality of the first network status parameters; A target network optimization strategy is determined according to the network environment detection result, and a network optimization operation is performed according to the target network optimization strategy.

[0084] In a feasible implementation manner, the above-mentioned jamming phenomenon detection module 20 is further used for: When it is detected that the network environment detection result is that the vehicle-mounted computing module is in a weak network environment, a preset first network optimization strategy is determined as a target network optimization strategy, wherein the first network optimization strategy is a network optimization strategy for switching a communication cell corresponding to the vehicle; When it is detected that the network environment detection result is that the on-board computing module is in a network change environment, the preset second network optimization strategy is determined as the target network optimization strategy, wherein the second network optimization strategy is a network optimization strategy for switching the network connection mode corresponding to the vehicle.

[0085] In a feasible implementation manner, the vehicle is in communication connection with the target mobile terminal, and the network optimization execution module 30 is further used to: When detecting that the target network optimization strategy is the first network optimization strategy, receiving a cell feature database sent by the target mobile terminal; The cell feature database is queried based on a plurality of first network status parameters to determine a target cell, and the vehicle is connected to the target cell through the vehicle communication module.

[0086] In a feasible implementation manner, the network optimization execution module 30 is further used to: In the case where it is detected that the target network optimization strategy is the second network optimization strategy, determining a preset target network connection standard; The current network connection mode corresponding to the vehicle is switched to the target network connection mode through the vehicle-mounted communication module.

[0087] In a feasible implementation manner, the above-mentioned jamming phenomenon detection module 20 is further used for: When detecting that the module state is the idle state, determining a plurality of second network state parameters corresponding to the vehicle-mounted communication module; Determine a preset global network environment judgment rule, and determine a state parameter threshold corresponding to each of a plurality of second network state parameters included in the global network environment judgment rule; Comparing the plurality of second network status parameters with the respective corresponding status parameter thresholds to obtain a plurality of first comparison results, and determining a target network status parameter based on the plurality of first comparison results, wherein the target network status parameter is a second network status parameter that reaches the status parameter threshold; When it is detected that the number of the target network status parameters reaches a first number threshold, determining that the network environment corresponding to the vehicle-mounted communication module is a weak network environment; The first network optimization strategy is determined as a target network optimization strategy, and a network optimization operation is performed according to the target network optimization strategy.

[0088] In a feasible implementation manner, the above-mentioned jamming phenomenon detection module 20 is further used for: In the case where it is detected that the number of the target network state parameters reaches a second number threshold, determining that the network environment corresponding to the vehicle-mounted communication module is a network change environment, wherein the second number threshold is greater than the first number threshold; The second network optimization strategy is determined as the target network optimization strategy, and the network optimization operation is performed according to the target network optimization strategy.

[0089] The network optimization device provided by the present application adopts the network optimization method in the above embodiment, which can solve the technical problem of low efficiency of network optimization operation in the related technology. Compared with the prior art, the beneficial effects of the network optimization device provided by the present application are the same as the beneficial effects of the network optimization method provided by the above embodiment, and the other technical features in the network optimization device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0090] The present application provides a vehicle, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the network optimization method in the above-mentioned embodiment one.

[0091] Reference below Figure 5 , which shows a schematic diagram of the structure of a vehicle suitable for implementing the embodiments of the present application. The vehicle in the embodiments of the present application may include, but is not limited to, a vehicle with an on-board computing module and an on-board communication module configured therein, or a mobile terminal, a data storage control terminal, a PC, or other terminals connected to an electronic control unit of the vehicle. Figure 5 The vehicle shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0092] like Figure 5 As shown, the vehicle may include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which may perform various appropriate actions and processes according to a program stored in a read-only memory 1002 or a program loaded from a storage device 1003 to a random access memory 1004. Various programs and data required for vehicle operation are also stored in the random access memory 1004. The processing device 1001, the read-only memory 1002, and the random access memory 1004 are connected to each other via a bus 1005. An input / output interface 1006 is also connected to the bus. Generally, the following systems may be connected to the input / output interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 may allow the vehicle to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a vehicle with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have instead.

[0093] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a read-only memory 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0094] The vehicle provided by the present application adopts the network optimization method in the above embodiment, which can solve the technical problem of low efficiency of network optimization operation in the related technology. Compared with the prior art, the beneficial effects of the vehicle provided by the present application are the same as the beneficial effects of the network optimization method provided by the above embodiment, and the other technical features in the vehicle are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0095] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0096] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0097] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, wherein the computer-readable program instructions are used to execute the network optimization method in the above-mentioned embodiment.

[0098] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0099] The computer-readable storage medium may be included in the vehicle, or may exist independently without being installed in the vehicle.

[0100] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the vehicle, the vehicle: detects the module status of the on-board computing module, wherein the module status is a use status or an idle status; when it is detected that the module status is the use status, reads the interaction log of the on-board computing module; when it is determined according to the interaction log that the on-board computing module has a network lag phenomenon, performs a network optimization operation according to a target network optimization strategy, wherein the target network optimization strategy is a first network optimization strategy or a second network optimization strategy.

[0101] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0102] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0103] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0104] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned network optimization method, and can solve the technical problem of low efficiency of network optimization operation in related technologies. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the network optimization method provided in the above-mentioned embodiment, and will not be repeated here.

[0105] The present application also provides a computer program product, including a computer program, which implements the steps of the above-mentioned network optimization method when executed by a processor.

[0106] The computer program product provided by this application can solve the technical problem of low efficiency of network optimization operation in related technologies. Compared with the prior art, the beneficial effects of the computer program product provided by this application are the same as the beneficial effects of the network optimization method provided by the above embodiment, which will not be repeated here.

[0107] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A network optimization method, characterized in that: The network optimization method is applied to a vehicle, wherein the vehicle comprises an on-board communication module and an on-board computing module, and the network optimization method comprises: Detecting a module state of the vehicle-mounted computing module, wherein the module state is a use state or an idle state; When it is detected that the module state is the use state, reading the interaction log of the vehicle-mounted computing module; When it is determined according to the interaction log that the on-board computing module has a network lag phenomenon, a network optimization operation is performed according to a target network optimization strategy, wherein the target network optimization strategy is a first network optimization strategy or a second network optimization strategy.

2. The network optimization method according to claim 1, characterized in that: After the step of reading the interaction log of the vehicle-mounted computing module, the method further includes: Determine the number of screen clicks and the screen click time contained in the interaction log, and determine the user operation frequency according to the number of screen clicks and the screen click time; When it is detected that the user operation frequency reaches a preset click frequency threshold, it is determined that the vehicle-mounted computing module has a network jam phenomenon, and the step of performing the network optimization operation according to the target network optimization strategy is executed.

3. The network optimization method according to claim 1, characterized in that: The vehicle is communicatively connected to the cloud server, and after the step of detecting the module status of the vehicle-mounted computing module, the method further includes: When it is detected that the module state is the use state, determining a plurality of first network state parameters corresponding to the vehicle-mounted computing module; Sending the plurality of the first network status parameters to the cloud server, and receiving a network environment detection result issued by the cloud server, wherein the network environment detection result is generated by a lightweight timing prediction model deployed in the cloud server based on the plurality of the first network status parameters; A target network optimization strategy is determined according to the network environment detection result, and a network optimization operation is performed according to the target network optimization strategy.

4. The network optimization method according to claim 3, characterized in that: The step of determining the target network optimization strategy according to the network environment detection result includes: When it is detected that the network environment detection result is that the vehicle-mounted computing module is in a weak network environment, a preset first network optimization strategy is determined as a target network optimization strategy, wherein the first network optimization strategy is a network optimization strategy for switching a communication cell corresponding to the vehicle; When it is detected that the network environment detection result is that the on-board computing module is in a network change environment, the preset second network optimization strategy is determined as the target network optimization strategy, wherein the second network optimization strategy is a network optimization strategy for switching the network connection mode corresponding to the vehicle.

5. The network optimization method according to claim 1, characterized in that: The vehicle is communicatively connected to the target mobile terminal, and the step of performing the network optimization operation according to the target network optimization strategy includes: When detecting that the target network optimization strategy is the first network optimization strategy, receiving a cell feature database sent by the target mobile terminal; The cell feature database is queried based on a plurality of first network status parameters to determine a target cell, and the vehicle is connected to the target cell through the vehicle communication module.

6. The network optimization method according to claim 5, characterized in that: The step of performing the network optimization operation according to the target network optimization strategy also includes: In the case where it is detected that the target network optimization strategy is the second network optimization strategy, determining a preset target network connection standard; The current network connection mode corresponding to the vehicle is switched to the target network connection mode through the vehicle-mounted communication module.

7. The network optimization method according to any one of claims 1 to 6, characterized in that: After the step of detecting the module status of the vehicle-mounted computing module, the method further includes: When detecting that the module state is the idle state, determining a plurality of second network state parameters corresponding to the vehicle-mounted communication module; Determine a preset global network environment judgment rule, and determine a state parameter threshold corresponding to each of a plurality of second network state parameters included in the global network environment judgment rule; Comparing the plurality of second network status parameters with the respective corresponding status parameter thresholds to obtain a plurality of first comparison results, and determining a target network status parameter based on the plurality of first comparison results, wherein the target network status parameter is a second network status parameter that reaches the status parameter threshold; When it is detected that the number of the target network status parameters reaches a first number threshold, determining that the network environment corresponding to the vehicle-mounted communication module is a weak network environment; The first network optimization strategy is determined as a target network optimization strategy, and a network optimization operation is performed according to the target network optimization strategy.

8. The network optimization method according to claim 7, characterized in that: After the step of determining the target network state parameter based on the plurality of first comparison results, the method further includes: In the case where it is detected that the number of the target network state parameters reaches a second number threshold, determining that the network environment corresponding to the vehicle-mounted communication module is a network change environment, wherein the second number threshold is greater than the first number threshold; The second network optimization strategy is determined as the target network optimization strategy, and the network optimization operation is performed according to the target network optimization strategy.

9. A vehicle, characterized in that: The vehicle comprises: an on-board communication module, an on-board computing module, a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the network optimization method as described in any one of claims 1 to 8.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the network optimization method according to any one of claims 1 to 8 are implemented.

11. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of the network optimization method according to any one of claims 1 to 8 are implemented.

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