Vehicle communication network switching method and device, equipment, storage medium and product

Abstract

The invention discloses a vehicle communication network switching method and device, equipment, a storage medium and a product. The method comprises the following steps: acquiring first network state data of a current communication network of a vehicle and second network state data of a standby communication network in a historical time period according to current vehicle driving time; inputting the first network state data into a network state prediction model obtained by pre-training to obtain predicted network state data output by the model in a future time period; according to the predicted network state data, whether network switching is carried out on the current communication network of the vehicle is judged; if yes, determining a target communication network based on a network state prediction model according to second network state data of the standby communication network; and switching the current communication network of the vehicle to the target communication network. According to the technical scheme of the embodiment of the invention, the switching delay of the vehicle-mounted communication network is reduced, and the situation of communication interruption is avoided.

Description

Technical Field

[0001] The present invention relates to the field of automobile communication technology, and in particular to a vehicle communication network switching method, device, equipment, storage medium and product. Background Art

[0002] In the current vehicle communication system, vehicles often rely on a single network connection to communicate with other vehicles, transportation infrastructure, cloud platforms, etc. This communication method is effective under certain conditions, but because vehicles often encounter problems such as weak network signals, network congestion, or switching delays during driving, it may bring instability to key applications such as autonomous driving, vehicle networking, and remote services.

[0003] Existing in-vehicle communication systems can support switching between different networks, but most of them are determined based on simple rules. This method of switching between different networks will cause a certain delay, affecting the continuity of communication. When switching between multiple networks, communication interruptions or high delays often occur, especially in high-speed driving environments. Summary of the invention

[0004] The present invention provides a vehicle communication network switching method, device, equipment, storage medium and product to reduce the vehicle communication network switching delay and avoid communication interruption.

[0005] According to one aspect of the present invention, a vehicle communication network switching method is provided, the method comprising:

[0006] According to the current vehicle driving time, obtaining first network status data of the current communication network of the own vehicle and second network status data of the backup communication network in the historical time period;

[0007] Inputting the first network status data into a pre-trained network status prediction model to obtain predicted network status data for a future time period output by the model;

[0008] Determining whether to switch the current communication network of the own vehicle according to the predicted network status data;

[0009] If yes, determining the target communication network based on the network status prediction model according to the second network status data of the backup communication network;

[0010] The current communication network of the host vehicle is switched to the target communication network.

[0011] According to another aspect of the present invention, a vehicle communication network switching device is provided, the device comprising:

[0012] A status data acquisition module, used to acquire first network status data of the current communication network of the own vehicle and second network status data of the backup communication network in a historical time period according to the current vehicle driving time;

[0013] A network status prediction module, used for inputting the first network status data into a pre-trained network status prediction model to obtain predicted network status data for a future time period output by the model;

[0014] A network switching judgment module, used to judge whether to switch the current communication network of the own vehicle according to the predicted network status data;

[0015] a target network determination module, configured to determine a target communication network based on the network state prediction model according to the second network state data of the backup communication network if a network switch is performed on the current communication network of the own vehicle;

[0016] The network switching module is used to switch the current communication network of the own vehicle to the target communication network.

[0017] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0018] at least one processor; and

[0019] a memory communicatively connected to the at least one processor; wherein,

[0020] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the vehicle communication network switching method described in any embodiment of the present invention.

[0021] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the vehicle communication network switching method described in any embodiment of the present invention when executed.

[0022] The technical solution of the embodiment of the present invention obtains the first network status data of the current communication network of the own vehicle and the second network status data of the backup communication network in the historical time period according to the current vehicle driving time; inputs the first network status data into the pre-trained network status prediction model to obtain the predicted network status data in the future time period output by the model; determines whether to perform network switching on the current communication network of the own vehicle according to the predicted network status data, and if so, determines the target communication network based on the network status prediction model according to the second network status data of the backup communication network; switches the current communication network of the own vehicle to the target communication network. The above technical solution realizes the prediction of the communication network status in the future time period during the vehicle driving process, so that the vehicle can switch the communication network in advance, realizes seamless network switching, thereby reducing the energy consumption of the vehicle communication system, improving the safety and stability of autonomous driving, reducing the switching delay of the vehicle communication network, and avoiding the occurrence of communication interruptions.

[0023] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 is a flow chart of a vehicle communication network switching method provided according to Embodiment 1 of the present invention;

[0026] Figure 2 is a flow chart of a vehicle communication network switching method provided according to Embodiment 2 of the present invention;

[0027] Figure 3 is a schematic diagram of the structure of a vehicle communication network switching device provided according to Embodiment 3 of the present invention;

[0028] Figure 4 It is a structural schematic diagram of an electronic device for implementing the vehicle communication network switching method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] Embodiment 1

[0032] Figure 1 This is a flow chart of a vehicle communication network switching method provided in the first embodiment of the present invention. This embodiment is applicable to the case of seamless switching of communication networks during vehicle driving. The method can be executed by a vehicle communication network switching device. The vehicle communication network switching device can be implemented in the form of hardware and / or software. The vehicle communication network switching device can be configured in an electronic device. Figure 1 As shown, the method includes:

[0033] S110. Acquire first network status data of a current communication network and second network status data of a backup communication network of the own vehicle in a historical time period according to the current vehicle driving time.

[0034] The historical time period may be a historical time within a certain past time range based on the current vehicle travel time. For example, if the current vehicle travel time is 2024 / 10 / 18 / 09:00, the historical time period may be 2024 / 10 / 18 / 00:00 to 2024 / 10 / 18 / 08:59.

[0035] The current communication network may be the communication network currently used by the vehicle-mounted communication system of the own vehicle; the backup communication network may be other communication networks supported by the vehicle-mounted communication system of the own vehicle except the current communication network. The communication networks supported by the vehicle-mounted communication system may include wireless communication networks, mobile communication networks, satellite communication networks, etc. For example, if the current communication network of the own vehicle in the current vehicle driving time period is a wireless communication network, the backup communication network may include a mobile communication network and a satellite communication network, etc.

[0036] The network status data may include network signal strength, network delay, network bandwidth, etc. The first network status data is the network status data of the vehicle itself in the current communication network; the second network status data is the network status data of the vehicle's own backup communication network.

[0037] S120: Input the first network status data into a pre-trained network status prediction model to obtain predicted network status data for a future time period output by the model.

[0038] The network status prediction model may be a model pre-trained by relevant technical personnel for predicting network status in future time periods, for example, it may be a model for predicting network delay, network signal strength, and network bandwidth.

[0039] The network status prediction model may include a signal strength prediction model, a network delay prediction model, and a network bandwidth prediction model. The signal strength prediction model is used to predict the network signal strength; the network delay prediction model is used to predict the network delay; and the network bandwidth prediction model is used to predict the network bandwidth.

[0040] In an optional embodiment, the first network status data includes network signal strength, network delay and network bandwidth; the network status prediction model includes a signal strength prediction model, a network delay prediction model and a network bandwidth prediction model.

[0041] Among them, the signal strength prediction model, the network delay prediction model and the network bandwidth prediction model can be pre-trained by relevant technical personnel. Taking the signal strength prediction model as an example, the training method of the signal strength prediction model can be as follows:

[0042] Obtain historical signal strength data in historical time periods, where the historical signal strength data is time series data. Input the time series historical strength data into a pre-built network model, for example, the network model can be an LSTM (Long Short-Term Memory) model, to obtain the prediction results of the model output. According to the prediction results of the model output and the actual results corresponding to the historical signal strength data, the network model is trained until the preset iteration threshold is reached, or until the loss value no longer changes.

[0043] The model training method of the network delay prediction model and the network bandwidth prediction model is the same as the model training method of the signal strength prediction model, and the historical network delay data and the historical bandwidth data are used for model training respectively, which will not be described in detail in this embodiment.

[0044] Accordingly, the first network status data is input into a pre-trained network status prediction model to obtain predicted network status data for a future time period output by the model, including:

[0045] Step a1: input the network signal strength into a signal strength prediction model to obtain predicted signal strength data for a future time period output by the model.

[0046] Step a2: input the network delay into the network delay prediction model to obtain the predicted network delay data in the future time period output by the model.

[0047] Step a3: input the network bandwidth into the network bandwidth prediction model to obtain the predicted network bandwidth data for the future time period output by the model.

[0048] Step a4: Generate predicted network status data including predicted signal strength data, predicted network delay data and predicted network bandwidth data.

[0049] S130: Determine whether to switch the current communication network of the own vehicle according to the predicted network status data.

[0050] In an optional embodiment, based on the predicted network status data, it is determined whether to perform a network switch on the current communication network of the own vehicle, including: if the predicted signal strength data is less than a preset signal strength threshold, then the network switch is performed on the current communication network of the own vehicle; and / or, if the predicted network delay data is greater than a preset network delay threshold, then the network switch is performed on the current communication network of the own vehicle; and / or, if the predicted network bandwidth data is less than a preset network bandwidth threshold, then the network switch is performed on the current communication network of the own vehicle.

[0051] Among them, the signal strength threshold, network delay threshold and network bandwidth threshold can be pre-set by relevant technical personnel according to actual needs.

[0052] Optionally, if the predicted signal strength data is not less than a preset signal strength threshold, and the predicted network delay data is not greater than a preset network delay threshold, and the predicted network bandwidth data is not less than a preset network bandwidth threshold, then no network switching is performed on the current communication network of the vehicle itself.

[0053] It should be noted that in order to further improve the accuracy of determining whether to perform a network switch on the current communication network of the own vehicle, the speed and position of the own vehicle may also be considered.

[0054] In an optional embodiment, based on the current vehicle driving time, vehicle driving data of the own vehicle in a historical time period is obtained; the vehicle driving data includes the vehicle driving speed and the vehicle geographic location; the vehicle driving speed and the vehicle geographic location are input into a pre-trained network stability prediction model to obtain the predicted network stability data for a future time period output by the model; accordingly, judging whether to perform a network switch on the current communication network of the own vehicle based on the predicted network status data includes: judging whether to perform a network switch on the current communication network of the own vehicle based on the predicted network status data and the predicted network stability data.

[0055] The network stability prediction model can be obtained by relevant technical personnel through model training in advance. Specifically, the model training method of the network stability prediction model can be as follows:

[0056] Collect the vehicle speed and vehicle geographic location in the historical time period, as well as the network stability index parameter values ​​under the corresponding vehicle speed and vehicle geographic location. And construct a sample training set in the form of a time series. Among them, the higher the network stability value, the more stable the network state; the lower the network stability value, the more unstable the network state. For example, the sample training set can be expressed as Table 1:

[0057] Table 1

[0058] Timestamp longitude latitude speed Network stability 2024-10-01 08:00 116.404 39.915 50km / h 50 2024-10-01 08:05 116.405 39.916 55km / h 51 …… …… …… …… ……

[0059] The sample training set is input into the pre-built LSTM network model for model training until the model training completion conditions are met to obtain a network stability prediction model.

[0060] S140: If yes, determine the target communication network according to the second network status data of the backup communication network and based on the network status prediction model.

[0061] If it is determined to switch the current communication network of the vehicle, the target communication network is determined based on the second network status data of the backup communication network and the network status prediction model. There may be at least one backup communication network.

[0062] In an optional embodiment, according to the second network status data of the backup communication network, based on a network status prediction model, the target communication network is determined, including: inputting the second network status data of the backup communication network into the network status prediction model to obtain the predicted network status data of the backup communication network in a future time period output by the model; and determining the target communication network according to the predicted network status data of the backup communication network in the future time period.

[0063] Specifically, the second network state of the backup communication network includes network signal strength, network delay and network bandwidth. The network signal strength of the backup communication network is input into the signal strength prediction model to obtain the predicted signal strength data for the future time period output by the model; and the network delay of the backup communication network is input into the network delay prediction model to obtain the predicted network delay data for the future time period output by the model; and the network bandwidth of the backup communication network is input into the network bandwidth prediction model to obtain the predicted network bandwidth data for the future time period output by the model.

[0064] The target communication network is determined according to the predicted signal strength data, predicted network delay data and predicted network bandwidth data of the backup communication network. Specifically, the backup communication network with high predicted signal strength, small delay and large bandwidth can be selected as the target communication network.

[0065] S150: Switch the current communication network of the own vehicle to the target communication network.

[0066] The technical solution of the embodiment of the present invention obtains the first network status data of the current communication network of the own vehicle and the second network status data of the backup communication network in the historical time period according to the current vehicle driving time; inputs the first network status data into the pre-trained network status prediction model to obtain the predicted network status data in the future time period output by the model; determines whether to perform network switching on the current communication network of the own vehicle according to the predicted network status data, and if so, determines the target communication network based on the network status prediction model according to the second network status data of the backup communication network; switches the current communication network of the own vehicle to the target communication network. The above technical solution realizes the prediction of the communication network status in the future time period during the vehicle driving process, so that the vehicle can switch the communication network in advance, realizes seamless network switching, thereby reducing the energy consumption of the vehicle communication system, improving the safety and stability of autonomous driving, reducing the switching delay of the vehicle communication network, and avoiding the occurrence of communication interruptions.

[0067] Embodiment 2

[0068] Figure 2 This is a flow chart of a vehicle communication network switching method provided in Embodiment 2 of the present invention. This embodiment provides a preferred example based on the above embodiments.

[0069] like Figure 2 As shown, the method comprises the following specific steps:

[0070] S21. According to the current vehicle driving time, obtain the network signal strength, network delay and network bandwidth of the current communication network of the own vehicle in the historical time period;

[0071] S22, inputting the network signal strength into a signal strength prediction model to obtain a predicted signal strength in a future time period output by the model;

[0072] S23, determining whether the predicted signal strength is greater than a preset signal strength threshold, if so, executing S24; if not, executing S29;

[0073] S24, inputting the network delay into the network delay prediction model to obtain the predicted network delay in the future time period output by the model;

[0074] S25, determining whether the predicted network delay is less than a preset network delay threshold, if so, executing S26; if not, executing S29;

[0075] S26, inputting the network bandwidth into the network bandwidth prediction model to obtain the predicted network bandwidth in the future time period output by the model;

[0076] S27, determining whether the predicted network bandwidth is greater than a preset network bandwidth threshold, if so, executing S28; if not, executing S29;

[0077] S28: No network switching is performed, and the above model is updated to enter the next detection cycle;

[0078] S29, obtaining the network signal strength, network delay and network bandwidth of the backup communication network, and determining the target communication network according to the network signal strength, network delay and network bandwidth of the backup communication network, and switching the current communication network to the target communication network.

[0079] Embodiment 3

[0080] Figure 3The present invention provides a vehicle communication network switching device according to the third embodiment of the present invention. The vehicle communication network switching device provided by the embodiment of the present invention can be applied to the situation where the communication network is seamlessly switched during the driving process of the vehicle. The vehicle communication network switching device can be implemented in the form of hardware and / or software, such as Figure 3 As shown, the device specifically includes: a state data acquisition module 301, a network state prediction module 302, a network switching judgment module 303, a target network determination module 304 and a network switching module 305. Among them,

[0081] The status data acquisition module 301 is used to acquire the first network status data of the current communication network of the own vehicle and the second network status data of the backup communication network in the historical time period according to the current vehicle driving time;

[0082] A network status prediction module 302 is used to input the first network status data into a pre-trained network status prediction model to obtain predicted network status data for a future time period output by the model;

[0083] A network switching judgment module 303 is used to judge whether to switch the current communication network of the own vehicle according to the predicted network status data;

[0084] A target network determination module 304 is used to determine a target communication network based on the network state prediction model according to the second network state data of the backup communication network if a network switch is performed on the current communication network of the own vehicle;

[0085] The network switching module 305 is used to switch the current communication network of the own vehicle to the target communication network.

[0086] The technical solution of the embodiment of the present invention obtains the first network status data of the current communication network of the own vehicle and the second network status data of the backup communication network in the historical time period according to the current vehicle driving time; inputs the first network status data into the pre-trained network status prediction model to obtain the predicted network status data in the future time period output by the model; determines whether to perform network switching on the current communication network of the own vehicle according to the predicted network status data, and if so, determines the target communication network based on the network status prediction model according to the second network status data of the backup communication network; switches the current communication network of the own vehicle to the target communication network. The above technical solution realizes the prediction of the communication network status in the future time period during the vehicle driving process, so that the vehicle can switch the communication network in advance, realizes seamless network switching, thereby reducing the energy consumption of the vehicle communication system, improving the safety and stability of autonomous driving, reducing the switching delay of the vehicle communication network, and avoiding the occurrence of communication interruptions.

[0087] Optionally, the first network status data includes network signal strength, network delay and network bandwidth; the network status prediction model includes a signal strength prediction model, a network delay prediction model and a network bandwidth prediction model;

[0088] Accordingly, the network status prediction module 302 is specifically used for:

[0089] Inputting the network signal strength into the signal strength prediction model to obtain predicted signal strength data for a future time period output by the model; and

[0090] Inputting the network delay into the network delay prediction model to obtain predicted network delay data for a future time period output by the model; and

[0091] Inputting the network bandwidth into the network bandwidth prediction model to obtain predicted network bandwidth data for a future time period output by the model;

[0092] Generate predicted network status data including the predicted signal strength data, the predicted network delay data, and the predicted network bandwidth data.

[0093] Optionally, the network switching determination module 303 includes:

[0094] a first network switching unit, configured to switch the current communication network of the vehicle if the predicted signal strength data is less than a preset signal strength threshold; and / or

[0095] a second network switching unit, configured to switch the current communication network of the vehicle if the predicted network delay data is greater than a preset network delay threshold; and / or

[0096] The third network switching unit is used to switch the current communication network of the own vehicle if the predicted network bandwidth data is less than a preset network bandwidth threshold.

[0097] Optionally, the network switching determination module 303 includes:

[0098] The fourth network switching unit is used to not perform network switching on the current communication network of the own vehicle if the predicted signal strength data is not less than a preset signal strength threshold, the predicted network delay data is not greater than a preset network delay threshold, and the predicted network bandwidth data is not less than a preset network bandwidth threshold.

[0099] Optionally, the device further comprises:

[0100] A driving data acquisition module is used to acquire the vehicle driving data of the own vehicle in a historical time period according to the current vehicle driving time; the vehicle driving data includes the vehicle driving speed and the vehicle geographical location;

[0101] A stability prediction module, used to input the vehicle speed and the vehicle geographic location into a pre-trained network stability prediction model to obtain predicted network stability data for a future time period output by the model;

[0102] Accordingly, the network switching determination module 303 includes:

[0103] The fifth network switching unit is used to determine whether to perform a network switch on the current communication network of the own vehicle based on the predicted network status data and the predicted network stability data.

[0104] Optionally, the target network determination module 304 is specifically configured to:

[0105] Inputting the second network status data of the backup communication network into the network status prediction model to obtain the predicted network status data of the backup communication network in a future time period output by the model;

[0106] The target communication network is determined according to the predicted network status data of the backup communication network in a future time period.

[0107] The vehicle communication network switching device provided in the embodiment of the present invention can execute the vehicle communication network switching method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0108] Embodiment 4

[0109] Figure 4 A schematic diagram of the structure of an electronic device 40 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0110] like Figure 4As shown, the electronic device 40 includes at least one processor 41, and a memory connected to the at least one processor 41, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 41 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 42 or the computer program loaded from the storage unit 48 to the random access memory (RAM) 43. In the RAM 43, various programs and data required for the operation of the electronic device 40 can also be stored. The processor 41, the ROM 42, and the RAM 43 are connected to each other through a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0111] A number of components in the electronic device 40 are connected to the I / O interface 45, including: an input unit 46, such as a keyboard, a mouse, etc.; an output unit 47, such as various types of displays, speakers, etc.; a storage unit 48, such as a disk, an optical disk, etc.; and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0112] The processor 41 may be a variety of general and / or dedicated processing components with processing and computing capabilities. Some examples of the processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 41 executes the various methods and processes described above, such as a vehicle communication network switching method.

[0113] In some embodiments, the vehicle communication network switching method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 40 via the ROM 42 and / or the communication unit 49. When the computer program is loaded into the RAM 43 and executed by the processor 41, one or more steps of the vehicle communication network switching method described above may be performed. Alternatively, in other embodiments, the processor 41 may be configured to execute the vehicle communication network switching method in any other appropriate manner (e.g., by means of firmware).

[0114] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0115] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0116] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0117] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0118] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0119] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0120] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0121] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A vehicle communication network switching method, characterized in that: include: According to the current vehicle driving time, obtaining first network status data of the current communication network of the own vehicle and second network status data of the backup communication network in the historical time period; Inputting the first network status data into a pre-trained network status prediction model to obtain predicted network status data for a future time period output by the model; Determining whether to switch the current communication network of the own vehicle according to the predicted network status data; If yes, determining the target communication network based on the network status prediction model according to the second network status data of the backup communication network; The current communication network of the host vehicle is switched to the target communication network.

2. The method according to claim 1, characterized in that The first network status data includes network signal strength, network delay and network bandwidth; the network status prediction model includes a signal strength prediction model, a network delay prediction model and a network bandwidth prediction model; Accordingly, the step of inputting the first network status data into a pre-trained network status prediction model to obtain predicted network status data for a future time period output by the model includes: Inputting the network signal strength into the signal strength prediction model to obtain predicted signal strength data for a future time period output by the model; and Inputting the network delay into the network delay prediction model to obtain predicted network delay data for a future time period output by the model; and Inputting the network bandwidth into the network bandwidth prediction model to obtain predicted network bandwidth data for a future time period output by the model; Generate predicted network status data including the predicted signal strength data, the predicted network delay data, and the predicted network bandwidth data.

3. The method according to claim 2, characterized in that The determining whether to switch the current communication network of the vehicle according to the predicted network status data includes: If the predicted signal strength data is less than a preset signal strength threshold, switching the current communication network of the own vehicle; and / or, If the predicted network delay data is greater than a preset network delay threshold, switching the current communication network of the own vehicle; and / or, If the predicted network bandwidth data is less than a preset network bandwidth threshold, a network switch is performed on the current communication network of the own vehicle.

4. The method according to claim 2, characterized in that: The determining whether to switch the current communication network of the vehicle according to the predicted network status data includes: If the predicted signal strength data is not less than the preset signal strength threshold, and the predicted network delay data is not greater than the preset network delay threshold, and the predicted network bandwidth data is not less than the preset network bandwidth threshold, the current communication network of the vehicle will not be switched.

5. The method according to claim 2, characterized in that: The method further comprises: According to the current vehicle driving time, the vehicle driving data of the own vehicle in the historical time period is obtained; the vehicle driving data includes the vehicle driving speed and the vehicle geographical location; Inputting the vehicle speed and the vehicle geographic location into a pre-trained network stability prediction model to obtain predicted network stability data for a future time period output by the model; Accordingly, judging whether to switch the current communication network of the own vehicle according to the predicted network status data includes: According to the predicted network status data and the predicted network stability data, it is determined whether to perform a network switch on the current communication network of the own vehicle.

6. The method according to claim 1, characterized in that The determining the target communication network according to the second network status data of the backup communication network and based on the network status prediction model comprises: Inputting the second network status data of the backup communication network into the network status prediction model to obtain the predicted network status data of the backup communication network in a future time period output by the model; The target communication network is determined according to the predicted network status data of the backup communication network in a future time period.

7. A vehicle communication network switching device, characterized in that: include: A status data acquisition module, used to acquire first network status data of the current communication network of the own vehicle and second network status data of the backup communication network in a historical time period according to the current vehicle driving time; A network status prediction module, used for inputting the first network status data into a pre-trained network status prediction model to obtain predicted network status data for a future time period output by the model; A network switching judgment module, used to judge whether to switch the current communication network of the own vehicle according to the predicted network status data; a target network determination module, configured to determine a target communication network based on the network state prediction model according to the second network state data of the backup communication network if a network switch is performed on the current communication network of the own vehicle; The network switching module is used to switch the current communication network of the own vehicle to the target communication network.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the vehicle communication network switching method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the vehicle communication network switching method according to any one of claims 1 to 6 when executed.

10. A computer program product, characterized in that The computer program product comprises a computer program, which, when executed by a processor, implements the vehicle communication network switching method according to any one of claims 1 to 6.

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