A vehicle network resource allocation method, device, equipment and medium

Abstract

The present application discloses a vehicle network resource allocation method, device, equipment and medium, which can be applied to business scenarios such as ports, ports, road freight, urban distribution, mines, airports, etc. The method includes: identifying the autonomous driving level of the target vehicle, selecting a designated channel corresponding to the autonomous driving level from each preset channel according to the autonomous driving level of the target vehicle, and then dividing the network resources required by the target vehicle from the total resources of the designated channel, and sending it to the target vehicle. The total resources of the above-mentioned preset channels are different, so the total network resources can be intelligently allocated according to the autonomous driving level of the target vehicle to improve the utilization rate of network resources.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of autonomous driving technology, and specifically to a vehicle network resource allocation method, device, equipment and medium. Background Art

[0002] With the development of science and technology, the application of many technologies in vehicle driving has been continuously deepened, making the vehicle more and more intelligent. At present, there are multiple levels of vehicle automation, and the higher the level, the higher the autonomous driving capability. For example, the lowest level of vehicles are non-automated vehicles, which require manual operation, while the highest level of vehicles are fully automated vehicles, whose autonomous driving systems can complete all driving tasks and cope with all road conditions under any circumstances.

[0003] Currently, most vehicles on the road have different levels of autonomous driving. Vehicles with different driving functions require different network resources and have different security requirements for the network. Most related technologies use the system's preset main channel, or use a backup channel when the main channel is congested, to uniformly allocate system network resources for vehicles with different levels / functions of autonomous driving. In the above allocation method, vehicles with different levels / functions of autonomous driving share the resources of the same channel, which has a low resource utilization rate. Summary of the invention

[0004] Embodiments of the present application provide a vehicle network resource allocation method, device, equipment and medium for improving network resource utilization.

[0005] In a first aspect, an embodiment of the present application provides a vehicle network resource allocation method, the method comprising:

[0006] In response to a network resource request of a target vehicle, obtaining an autonomous driving level of the target vehicle;

[0007] selecting a designated channel from among the preset channels according to the autonomous driving level;

[0008] The network resources required by the target vehicle are divided from the total amount of resources of the designated channel and sent to the target vehicle; wherein the total amount of resources of each preset channel is different.

[0009] The embodiment of the present application selects a designated channel corresponding to the automatic driving level from each preset channel according to the automatic driving level of the target vehicle, and then divides the network resources required by the target vehicle from the total resources of the designated channel, and sends it to the target vehicle. The total resources of the above preset channels are different, so the total network resources can be intelligently allocated according to the automatic driving level of the target vehicle to improve the utilization rate of network resources.

[0010] In some possible embodiments, before dividing the network resources required by the target vehicle from the total amount of resources of the designated channel, the method further includes:

[0011] Determining that a current channel congestion rate of the designated channel is less than a first threshold;

[0012] After selecting the designated channel of the target vehicle from the preset channels according to the autonomous driving level, the method further includes:

[0013] If the channel congestion rate of the designated channel is not less than the first threshold, selecting a backup channel based on the autonomous driving level and channel information of each preset channel; the channel information at least includes bandwidth, channel congestion rate and network security of each preset channel;

[0014] The network resources required by the target vehicle are divided out from the total resources of the standby channel and sent to the target vehicle.

[0015] The embodiment of the present application determines whether to use the designated channel to execute the distribution of network resources according to the current channel congestion rate of the designated channel. If the channel congestion rate meets the threshold, the backup channel for distributing network resources is intelligently selected based on the target vehicle's autonomous driving level and the channel information of each preset channel to avoid slow network speed due to excessively high channel congestion rate, thereby affecting the user experience.

[0016] In some possible embodiments, each preset channel includes a plurality of preset sub-channels, and dividing the network resources required by the target vehicle from the total resources of the designated channel includes:

[0017] If the network resource request indicates that the target vehicle is performing a firmware upgrade, a preset sub-channel with the highest network security in the designated channel is used as a target channel;

[0018] If the network resource request indicates that the target vehicle is performing a software upgrade, determining the target channel from each of the preset sub-channels based on the bandwidth of each of the preset sub-channels and network security;

[0019] The network resources required by the target vehicle are divided from the total resources of the target channel and sent to the target vehicle.

[0020] Each preset channel in the embodiment of the present application also includes multiple preset sub-channels. After selecting a designated channel from each preset channel, the preset sub-channel can be intelligently allocated to the target vehicle according to the purpose of the network resources requested by the target vehicle. For example, when the target vehicle performs a firmware upgrade and has a higher requirement for privacy, the preset sub-channel with the highest network security should be selected as the target channel. When the target vehicle performs a software upgrade and has a higher requirement for network speed, the bandwidth and network security of each preset sub-channel should be comprehensively considered to reasonably allocate the applicable target channel.

[0021] In some possible embodiments, before determining the target channel from each of the preset sub-channels based on the bandwidth and network security of each of the preset sub-channels, the method further includes:

[0022] Detecting a current channel congestion rate of each of the preset sub-channels, and taking the preset sub-channels whose channel congestion rate is less than a second threshold as channels to be selected;

[0023] The determining the target channel from each of the preset sub-channels based on the bandwidth and network security of each of the preset sub-channels includes:

[0024] The target channel is determined from the preset sub-channels according to the network security and bandwidth of each channel to be selected.

[0025] Before selecting a target channel from each preset sub-channel, the embodiment of the present application needs to determine a candidate channel according to the channel congestion rate of each preset sub-channel, and then select the target channel from the candidate channels, so as to avoid slow network speed due to excessively high channel congestion rate, thereby affecting user experience.

[0026] In some possible embodiments, before dividing the network resources required by the target vehicle from the total resources of the target channel, the method further includes:

[0027] If the network resource request indicates that the target vehicle is performing a firmware upgrade and the channel congestion rate of the selected target channel is not less than a third threshold, a prompt message indicating current network congestion and suggesting upgrading later is sent to the user.

[0028] Before dividing the network resources required by the target vehicle from the total resources of the target channel, the embodiment of the present application needs to determine whether the channel congestion rate of the target channel meets a preset threshold. If so, a prompt message indicating the current network congestion needs to be sent to the user to remind the user that the current network is relatively congested.

[0029] In some possible embodiments, each preset channel corresponds to a different autonomous driving level; the higher the autonomous driving level, the larger the bandwidth of the preset channel corresponding to the autonomous driving level.

[0030] In the embodiment of the present application, a corresponding autonomous driving level is set for each preset channel. The higher the autonomous driving level, the larger the corresponding preset channel bandwidth. In this way, the total network resources are divided according to the degree of demand for network resources by vehicles of different autonomous driving levels, thereby improving the utilization rate of network resources.

[0031] In a second aspect, an embodiment of the present application provides a vehicle network resource allocation device, the device comprising:

[0032] a level acquisition module, configured to execute in response to a network resource request of a target vehicle, and acquire an autonomous driving level of the target vehicle;

[0033] a designated channel module, configured to select a designated channel from various preset channels according to the autonomous driving level;

[0034] The resource allocation module is configured to divide the network resources required by the target vehicle from the total amount of resources of the designated channel and distribute them to the target vehicle; wherein the total amount of resources of each preset channel is different.

[0035] In some possible embodiments, before dividing the network resources required by the target vehicle from the total amount of resources of the designated channel, the resource allocation module is further configured to:

[0036] Determining that a current channel congestion rate of the designated channel is less than a first threshold;

[0037] After executing the step of selecting the designated channel of the target vehicle from the preset channels according to the autonomous driving level, the designated channel module is further configured to:

[0038] If the channel congestion rate of the designated channel is not less than the first threshold, selecting a backup channel based on the autonomous driving level and channel information of each preset channel; the channel information at least includes bandwidth, channel congestion rate and network security of each preset channel;

[0039] The network resources required by the target vehicle are divided out from the total resources of the standby channel and sent to the target vehicle.

[0040] In some possible embodiments, each preset channel includes a plurality of preset sub-channels, and to perform the division of the network resources required by the target vehicle from the total resources of the designated channel, the resource allocation module is configured as follows:

[0041] If the network resource request indicates that the target vehicle is performing a firmware upgrade, a preset sub-channel with the highest network security in the designated channel is used as a target channel;

[0042] If the network resource request indicates that the target vehicle is performing a software upgrade, determining the target channel from each of the preset sub-channels based on the bandwidth of each of the preset sub-channels and network security;

[0043] The network resources required by the target vehicle are divided from the total resources of the target channel and sent to the target vehicle.

[0044] In some possible embodiments, before performing the step of determining the target channel from each of the preset sub-channels based on the bandwidth and network security of each of the preset sub-channels, the resource allocation module is further configured to:

[0045] Detecting a current channel congestion rate of each of the preset sub-channels, and taking the preset sub-channels whose channel congestion rate is less than a second threshold as channels to be selected;

[0046] To determine the target channel from each of the preset sub-channels based on the bandwidth and network security of each of the preset sub-channels, the resource allocation module is configured to:

[0047] The target channel is determined from the preset sub-channels according to the network security and bandwidth of each channel to be selected.

[0048] In some possible embodiments, before dividing the network resources required by the target vehicle from the total amount of resources of the target channel, the resource allocation module is further configured to:

[0049] If the network resource request indicates that the target vehicle is performing a firmware upgrade and the channel congestion rate of the selected target channel is not less than a third threshold, a prompt message indicating current network congestion and suggesting upgrading later is sent to the user.

[0050] In some possible embodiments, each preset channel corresponds to a different autonomous driving level; the higher the autonomous driving level, the larger the bandwidth of the preset channel corresponding to the autonomous driving level.

[0051] In a third aspect, an embodiment of the present application provides an electronic device, including:

[0052] A memory for storing program instructions;

[0053] The processor is used to call the program instructions stored in the memory, and execute the steps included in any one of the methods in the first aspect according to the obtained program instructions.

[0054] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes any one of the methods described in the first aspect.

[0055] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes: a computer program code, when the computer program code is run on a computer, the computer executes any one of the methods described in the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 A schematic diagram of an application scenario provided for an embodiment of the present application;

[0057] Figure 2 An overall flow chart of a vehicle network resource allocation method provided in an embodiment of the present application;

[0058] Figure 3 A schematic diagram of the correspondence between preset channels and levels provided in an embodiment of the present application;

[0059] Figure 4 Another schematic diagram of the correspondence between preset channels and levels provided in an embodiment of the present application;

[0060] Figure 5 A schematic diagram of selecting a target channel provided in an embodiment of the present application;

[0061] Figure 6 A flow chart of network resource allocation provided in an embodiment of the present application;

[0062] Figure 7 A structural diagram of a vehicle network resource allocation device 700 provided in an embodiment of the present application;

[0063] Figure 8 A schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical scheme and advantages of the present application clearer, the technical scheme in the embodiment of the present application will be clearly and completely described below in conjunction with the drawings in the embodiment of the present application. Obviously, the described embodiment is only a part of the embodiment of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application. In the absence of conflict, the embodiments in the present application and the features in the embodiments can be arbitrarily combined with each other. In addition, although the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in an order different from that here.

[0065] The terms "first" and "second" in the specification and claims of the present application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the term "comprising" and any of their variations are intended to cover non-exclusive protection. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units that are not listed, or optionally also includes other steps or units inherent to these processes, methods, products or devices. "Multiple" in the present application can mean at least two, for example, two, three or more, and the embodiments of the present application are not limited.

[0066] In the technical solution of this application, the collection, dissemination, and use of data are in compliance with the requirements of relevant national laws and regulations.

[0067] The "Automobile Driving Automation Classification Standard" clearly stipulates that based on the degree to which the driving automation system can perform dynamic driving tasks, according to the role allocation in performing dynamic driving tasks and whether there are design operating condition restrictions, driving automation is divided into L0 to L5 levels. For example:

[0068] Level L0 belongs to "emergency assistance". The onboard system of vehicles at this level only provides emergency assistance functions such as lane departure warning, front collision warning, and automatic emergency braking. It can be seen that at this level, the vehicle provides more of a safety protection function.

[0069] Level 1 is "partial driving assistance", which means that the driver and the system jointly control the driving rights. The system of this level of vehicle can control the vehicle horizontally or longitudinally under the designed operating conditions. For example, vehicles with adaptive cruise control functions commonly seen in daily life are Level 1 vehicles.

[0070] Level 2 is "combined driving assistance". The system of this level of vehicle basically has the ability to master driving rights, and the system can control the vehicle horizontally and longitudinally under the designed operating conditions. For example, a vehicle with both lane keeping and adaptive cruise control is a Level 2 vehicle.

[0071] Level 3 is "conditional autonomous driving". Vehicles at this level can automatically accelerate, decelerate and steer in specific environments without the need for driver input. The driver does not need to monitor the vehicle's surroundings, but must be ready to take over the vehicle at any time to deal with road conditions that the autonomous driving cannot handle.

[0072] Level 4 is "highly automated driving". Except for some special circumstances, vehicles at this level generally do not require human intervention. Self-driving cars that rely on special maps belong to Level 4 automated driving. As long as there is a map, these cars can achieve fully automated driving without human intervention.

[0073] Level 5 is "fully autonomous driving". Under all conditions, the autonomous driving system of this level of vehicle can complete all driving tasks and cope with all road conditions. There is no cockpit anymore. The car is like an extremely intelligent robot, fully automated, fully adaptive driving, and adaptable to any driving scenario.

[0074] In different classification standards, the subdivision standards of autonomous driving levels may be slightly different. The above is only one way of expression. There may be other classification standards, and the embodiments of the present application do not limit this.

[0075] In actual applications, vehicles need to request network resources from the cloud system to perform network tasks such as autonomous driving, navigation, and software and hardware upgrades. Currently, there is a lack of technical solutions for the rational allocation of network resources. After the vehicle sends a resource request, the cloud system usually uses the preset main channel, or uses the backup channel when the main channel is congested, to uniformly allocate all the system's network resources to vehicles of different autonomous driving levels. Generally, the higher the automated driving capability of a vehicle, the higher its dependence on the network and the more network resources it requires. In the above allocation method, vehicles of different autonomous driving levels share all the network resources of the cloud system, resulting in low resource utilization.

[0076] To solve the above problems, the method proposed in the embodiment of the present application includes: by identifying the automatic driving level of the target vehicle, selecting a designated channel corresponding to the automatic driving level from each preset channel according to the automatic driving level of the target vehicle, and then dividing the network resources required by the target vehicle from the total resources of the designated channel, and sending it to the target vehicle. The total resources of the above preset channels are different, so the total network resources can be intelligently allocated according to the automatic driving level of the target vehicle to improve the utilization rate of network resources.

[0077] See also Figure 1 , is a schematic diagram of an application scenario according to an embodiment of the present application.

[0078] like Figure 1 As shown, the application scenario may include, for example, a network 10, a vehicle 20, and a server 30. Among them: the vehicle 20 includes Figure 1 The vehicles shown in the figure, such as a car 20_1, a truck 20_2, and a bus 20_n, have different levels of autonomous driving.

[0079] exist Figure 1In the application scenario shown, the server 30 contains multiple network slices, each of which corresponds to a unique channel. After the vehicle 20 sends a network resource request to the server 30 through the network 10, the server 30 identifies the autonomous driving level of the vehicle 20 and selects a network slice corresponding to the autonomous driving level according to the autonomous driving level of the vehicle 20. Then, the network resources required by the vehicle 20 are sent to the designated channel of the network slice.

[0080] In some possible embodiments, each network slice corresponds to a unique channel. The channel of each network slice supports the use of vehicles with a specified level of autonomous driving, and different channels correspond to different levels of autonomous driving for vehicles.

[0081] It should be noted that the description in this application only details a single server or terminal device, but those skilled in the art should understand that Figure 1 The server 30 shown is intended to represent the operation of the server involved in the technical solution of the present application. The individual servers are described in detail at least for the convenience of explanation, and do not imply any limitation on the number, type or location of the servers. It should be noted that if additional modules are added to the illustrated environment or individual modules are removed from it, the underlying concepts of the example embodiments of the present application will not be changed.

[0082] Figure 2 A vehicle network resource allocation method provided by an embodiment of the present application is schematically shown. Figure 2 As shown, the following steps are included:

[0083] Step 201: In response to a network resource request of a target vehicle, obtaining an autonomous driving level of the target vehicle;

[0084] As mentioned above, in actual applications, most vehicles have the ability to request network resources from the cloud system to perform network tasks such as autonomous driving, navigation, software and hardware upgrades, etc. Specifically, the driver needs to request network resources from the cloud system through smart devices such as smartphones and on-board computer lights to perform corresponding network tasks based on the network resources allocated by the system. When the vehicle in the embodiment of the present application sends a network resource request, it needs to simultaneously send the vehicle's own autonomous driving level.

[0085] Step 202: selecting a designated channel from among the preset channels according to the autonomous driving level;

[0086] Taking into account the actual application, vehicles with different driving functions require different network resources and have different security requirements for the network. For example, vehicles that do not have automated driving capabilities require fewer network resources, while vehicles with automated driving capabilities are relatively more dependent on the network and require more network resources. The embodiment of the present application pre-uses network hard slicing technology to divide the total network resources into multiple network slices, and each network slice is set with a corresponding preset channel and a corresponding autonomous driving level. The total amount of resources corresponding to each preset channel (i.e., the network slice volume) is different. Therefore, after determining the autonomous driving level of the target vehicle through the above step 201, the designated channel corresponding to the autonomous driving level of the target vehicle can be selected from each preset channel according to the corresponding relationship between the autonomous driving level and the preset channel.

[0087] Considering that the lowest level of vehicles requires the least network resources, they only need to complete basic networking functions. As the level of autonomous driving increases, the network resources required by vehicles and the security requirements for the network are also getting higher and higher. Based on this, the corresponding preset channels can be allocated for transmission according to different levels of autonomous driving, as follows: Figure 3 As shown, the autonomous driving levels L0 to L5 correspond to preset channels M0 to M5 respectively. As the sequence number in M0 to M5 increases, the total amount of resources corresponding to the preset channel increases, the bandwidth increases, and the network security increases. In addition, the preset channels do not affect each other to avoid interference.

[0088] In addition, considering that vehicles at levels L0 to L2 in the "Automotive Driving Automation Classification Standard" do not have the ability to perform autonomous driving in a specific environment, their demand for network resources is relatively low compared to higher levels. Figure 4 As shown, vehicles L0 to L2 share the same preset channel M0, while L3 to L5 correspond to preset channels M1 to M3 respectively. It should be understood that the setting of the preset channels and the corresponding automatic driving levels in the above embodiments can be determined based on actual conditions, and it is necessary to ensure that the higher the automatic driving level, the greater the total amount of resources of the corresponding preset channels, the greater the bandwidth and the higher the network security. In this way, the waste of total network resources can be avoided and the safety of vehicle operation can be improved.

[0089] Step 203: dividing the network resources required by the target vehicle from the total amount of resources of the designated channel, and sending them to the target vehicle; wherein the total amount of resources of each preset channel is different.

[0090] Considering that the higher the channel occupancy rate, the less the total amount of resources that can be allocated to the channel, even if the channel bandwidth is large, the network speed will be very slow when performing network tasks based on the channel. In order to use more application scenarios, before executing step 203 of the embodiment of the present application to divide the network resources required by the target vehicle from the total amount of resources of the designated channel, the current channel congestion rate of the designated channel needs to be compared with the first threshold. If the channel congestion rate of the designated channel is not less than the first threshold, it means that the total amount of resources that can be allocated to the designated channel is low, and it takes a long time to occupy the designated channel to perform network tasks.

[0091] At this time, a backup channel can be selected based on the target vehicle's autonomous driving level and the channel information of each preset channel. The above channel information may include the bandwidth, channel congestion rate and network security of each preset channel. Based on the above information, a backup channel with a low channel congestion rate and high network speed and network security is selected from each preset channel, and then the network resources required by the target vehicle are divided from the total resources of the backup channel and sent to the target vehicle. Specifically, Figure 5 As shown, for example, the automatic driving level L3 corresponds to the preset channel M3. However, since the channel congestion rate of M3 is relatively high, channels M0 to M2 and M5 whose channel congestion rates are less than the first threshold can be selected from the remaining preset channels, and then the preset channel M2 whose network security and bandwidth are slightly lower than M3 can be selected as the alternative channel.

[0092] In the embodiment of the present application, each preset channel includes multiple preset sub-channels, and the channel information (total resources, bandwidth, and network security) of each preset sub-channel is at least different. When executing the above step 203 to divide the network resources required by the target vehicle from the total resources of the designated channel, the target channel can be selected from the multiple preset sub-channels of the designated channel according to the purpose of the target vehicle requesting the network resources, and the network resources required by the target vehicle can be divided from the total resources of the target channel.

[0093] Specifically, most of the network tasks performed by vehicles are OTA tasks, and OTA is an over-the-air download technology. It remotely upgrades the vehicle's hardware and software through the mobile communication interface. OTA tasks can be further divided into firmware upgrades (FOTA) and software upgrades (SOTA). FOTA upgrades often some on-board firmware. The amount of network data is limited and the network security performance is required to be the highest. Therefore, at this time, regardless of the size of the network resources requested by the target vehicle, a channel with high network security performance should be selected for transmission. Therefore, if the network resource request of the target vehicle is characterized by a firmware upgrade, the channel with the highest network security should be selected from the preset sub-channels of the specified channel as the preset sub-channel.

[0094] In addition, the preset sub-channel as the target channel can be selected according to the amount of data while ensuring security. Specifically, when the target vehicle is undergoing a firmware upgrade, the candidate sub-channel that meets the requirements for firmware upgrade can be selected from each preset sub-channel based on the comparison relationship between the network security of each preset sub-channel and the threshold. Then, based on the specific type of firmware upgrade, the target channel is selected according to the bandwidth of each candidate sub-channel. For example, if the driver information of the small plug-in corresponding to the on-board chip is upgraded, a candidate sub-channel with high security and relatively small bandwidth is selected for transmission. If the driver information of the entire vehicle is upgraded, a candidate sub-channel with high security performance and relatively large bandwidth is selected for data transmission.

[0095] SOTA refers to upgrading the vehicle software, which usually requires a high network speed. If the network resource request of the target vehicle represents the execution of a software upgrade, the bandwidth and network security of each preset sub-channel can be comprehensively considered, and then the target channel can be determined from each preset sub-channel. For example, when the target vehicle upgrades the entertainment system through SOTA, the entertainment system has relatively low requirements for network security. Considering the particularity of the entertainment system, the amount of data transmitted is large. At this time, a preset sub-channel with a larger bandwidth can be selected as the target channel.

[0096] In some possible embodiments, before determining the target channel from each preset sub-channel based on the bandwidth and network security of each preset sub-channel, it is necessary to detect the current channel congestion rate of each preset sub-channel, and use the preset sub-channel whose channel congestion rate is less than the second threshold as the candidate channel. Then, the target channel is determined from each preset sub-channel based on the network security and bandwidth of each candidate channel to avoid slow network speed due to excessively high channel congestion rate, thereby affecting the user experience.

[0097] Furthermore, since FOTA has high requirements for network security, it is not convenient to adaptively switch channels according to the channel congestion rate as in the above-mentioned SOTA. Therefore, if the network resource request of the target vehicle indicates that the target vehicle is performing a firmware upgrade, if the channel congestion rate of the selected target channel is not less than the third threshold, a prompt message indicating the current network congestion needs to be sent to the user to inform the user that the current network speed is slow and it is recommended to upgrade later.

[0098] To facilitate understanding of how to allocate network resources to the target vehicle based on the autonomous driving level in the above process of the embodiment of the present application, the network resource allocation process of the embodiment of the present application is schematically illustrated below, as follows: Figure 6 As shown, including:

[0099] Step 601: Obtain the autonomous driving level of the target vehicle;

[0100] Step 602: Selecting a corresponding designated channel according to the autonomous driving level of the target vehicle;

[0101] Step 603: whether the current channel congestion rate of the designated channel is less than a first threshold;

[0102] Step 604: If it is not less than the first threshold, a backup channel is selected based on the autonomous driving level and the channel information of each preset channel, and the following step 605 is executed; the channel information at least includes the bandwidth, channel congestion rate and network security of each preset channel;

[0103] Step 605: Whether the vehicle performs OTA upgrade;

[0104] Step 606: If not executed, the network resources required by the target vehicle are divided from the total amount of resources corresponding to the currently selected designated channel / backup channel, and sent to the target vehicle.

[0105] Step 607: If it is executed and it is a FOTA upgrade, then a preset sub-channel with the highest network security is selected from the currently selected designated channel / backup channel as the target channel;

[0106] Step 608: divide the network resources required by the target vehicle from the total resources of the target channel and send them to the target vehicle.

[0107] Step 609: If executed and it is a SOTA upgrade, determine the channel to be selected according to the current channel congestion rate of each preset sub-channel;

[0108] Step 610: Determine the target channel based on the bandwidth and network security of each candidate channel, and execute the above step 608.

[0109] Based on the same inventive concept, the embodiment of the present application provides a vehicle network resource allocation device 700, specifically as follows Figure 7 As shown, including:

[0110] The level acquisition module 701 is configured to execute in response to a network resource request of a target vehicle and acquire the autonomous driving level of the target vehicle;

[0111] The designated channel module 702 is configured to select a designated channel from various preset channels according to the autonomous driving level;

[0112] The resource allocation module 703 is configured to divide the network resources required by the target vehicle from the total amount of resources of the designated channel and distribute them to the target vehicle; wherein the total amount of resources of each preset channel is different.

[0113] In some possible embodiments, before dividing the network resources required by the target vehicle from the total amount of resources of the designated channel, the resource allocation module 703 is further configured to:

[0114] Determining that a current channel congestion rate of the designated channel is less than a first threshold;

[0115] After executing the step of selecting the designated channel of the target vehicle from the preset channels according to the autonomous driving level, the designated channel module 702 is further configured to:

[0116] If the channel congestion rate of the designated channel is not less than the first threshold, selecting a backup channel based on the autonomous driving level and channel information of each preset channel; the channel information at least includes bandwidth, channel congestion rate and network security of each preset channel;

[0117] The network resources required by the target vehicle are divided out from the total resources of the standby channel and sent to the target vehicle.

[0118] In some possible embodiments, each preset channel includes a plurality of preset sub-channels, and to perform the division of the network resources required by the target vehicle from the total resources of the designated channel, the resource allocation module 703 is configured as follows:

[0119] If the network resource request indicates that the target vehicle is performing a firmware upgrade, a preset sub-channel with the highest network security in the designated channel is used as a target channel;

[0120] If the network resource request indicates that the target vehicle is performing a software upgrade, determining the target channel from each of the preset sub-channels based on the bandwidth of each of the preset sub-channels and network security;

[0121] The network resources required by the target vehicle are divided from the total resources of the target channel and sent to the target vehicle.

[0122] In some possible embodiments, before determining the target channel from each of the preset sub-channels based on the bandwidth and network security of each of the preset sub-channels, the resource allocation module 703 is further configured to:

[0123] Detecting a current channel congestion rate of each of the preset sub-channels, and taking the preset sub-channels whose channel congestion rate is less than a second threshold as channels to be selected;

[0124] To determine the target channel from each of the preset sub-channels based on the bandwidth and network security of each of the preset sub-channels, the resource allocation module 703 is configured as follows:

[0125] The target channel is determined from the preset sub-channels according to the network security and bandwidth of each channel to be selected.

[0126] In some possible embodiments, before dividing the network resources required by the target vehicle from the total amount of resources of the target channel, the resource allocation module 703 is further configured to:

[0127] If the network resource request indicates that the target vehicle is performing a firmware upgrade and the channel congestion rate of the selected target channel is not less than a third threshold, a prompt message indicating current network congestion and suggesting upgrading later is sent to the user.

[0128] In some possible embodiments, each preset channel corresponds to a different autonomous driving level; the higher the autonomous driving level, the larger the bandwidth of the preset channel corresponding to the autonomous driving level.

[0129] Refer to the following Figure 8 The electronic device 130 according to this embodiment of the present application is described. Figure 8 The electronic device 130 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.

[0130] like Figure 8 As shown, the electronic device 130 is in the form of a general electronic device. The components of the electronic device 130 may include but are not limited to: the at least one processor 131, the at least one memory 132, and a bus 133 connecting different system components (including the memory 132 and the processor 131).

[0131] Bus 133 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a processor, or a local bus using any of a variety of bus architectures.

[0132] The memory 132 may include a readable medium in the form of a volatile memory, such as a random access memory (RAM) 1321 and / or a cache memory 1322 , and may further include a read-only memory (ROM) 1323 .

[0133] The memory 132 may also include a program / utility 1325 having a set (at least one) of program modules 1324, such program modules 1324 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0134] The electronic device 130 may also communicate with one or more external devices 134 (e.g., keyboards, pointing devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 130, and / or communicate with any device that enables the electronic device 130 to communicate with one or more other electronic devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 135. Furthermore, the electronic device 130 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 136. As shown, the network adapter 136 communicates with other modules for the electronic device 130 via a bus 133. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 130, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0135] In an exemplary embodiment, a computer-readable storage medium including instructions is also provided, such as a memory 132 including instructions, and the instructions can be executed by the processor 131 of the device 400 to complete the above method. Alternatively, the computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0136] In an exemplary embodiment, a computer program product is also provided, including a computer program / instruction, which, when executed by the processor 131, implements any of the vehicle network resource allocation methods provided in the present application.

[0137] In an exemplary embodiment, various aspects of a vehicle network resource allocation method provided by the present application can also be implemented in the form of a program product, which includes program code. When the program product is run on a computer device, the program code is used to enable the computer device to execute the steps of a vehicle network resource allocation method according to various exemplary embodiments of the present application described above in this specification.

[0138] The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable 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 thereof.

[0139] The program product for vehicle network resource allocation of the embodiment of the present application can adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be run on an electronic device. However, the program product of the present application is not limited to this. In this document, a readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, device or device.

[0140] A readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, wherein readable program code is carried. Such propagated data signals may take a variety of forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination of the foregoing. A readable signal medium may also be any readable medium other than a readable storage medium, which may transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0141] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0142] The program code for performing the operation of the present application can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and also conventional procedural programming languages ​​such as language or similar programming languages. The program code can be executed entirely on the user electronic device, partially on the user device, as an independent software package, partially on the user electronic device and partially on the remote electronic device, or completely on the remote electronic device or server. In the case of a remote electronic device, the remote electronic device can be connected to the user electronic device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external electronic device (for example, using an Internet service provider to connect through the Internet).

[0143] It should be noted that, although several units or subunits of the device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to the embodiments of the present application, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided into multiple units to be embodied.

[0144] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0145] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable image scaling device to produce a machine, so that the instructions executed by the processor of the computer or other programmable image scaling device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0146] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable image scaling device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, the instruction device being implemented in the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0147] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0148] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A vehicle network resource allocation method, characterized in that: The method comprises: In response to a network resource request of a target vehicle, obtaining an autonomous driving level of the target vehicle; Selecting a designated channel from the preset channels according to the autonomous driving level; wherein the total amount of resources of the preset channels is different; and each preset channel corresponds to a unique network slice; If the current channel congestion rate of the designated channel is less than a first threshold, dividing the network resources required by the target vehicle from the total resources of the designated channel and sending them to the target vehicle; If the channel congestion rate of the designated channel is not less than the first threshold, a backup channel is selected from each preset channel based on the autonomous driving level and the channel information of each preset channel; and the network resources required by the target vehicle are divided from the total resources of the backup channel and sent to the target vehicle; the channel information includes at least the bandwidth, channel congestion rate and network security of each preset channel.

2. The method according to claim 1, characterized in that Each preset channel includes a plurality of preset sub-channels, and the network resources required by the target vehicle are divided from the total resources of the designated channel, including: If the network resource request indicates that the target vehicle is performing a firmware upgrade, a preset sub-channel with the highest network security in the designated channel is used as a target channel; If the network resource request indicates that the target vehicle is performing a software upgrade, determining the target channel from each of the preset sub-channels based on the bandwidth of each of the preset sub-channels and network security; The network resources required by the target vehicle are divided from the total resources of the target channel and sent to the target vehicle.

3. The method according to claim 2, characterized in that Before determining the target channel from each of the preset sub-channels based on the bandwidth and network security of each of the preset sub-channels, the method further includes: Detecting a current channel congestion rate of each of the preset sub-channels, and taking the preset sub-channels whose channel congestion rate is less than a second threshold as channels to be selected; The determining the target channel from each of the preset sub-channels based on the bandwidth and network security of each of the preset sub-channels includes: The target channel is determined from the preset sub-channels according to the network security and bandwidth of each channel to be selected.

4. The method according to claim 3, characterized in that Before dividing the network resources required by the target vehicle from the total amount of resources of the target channel, the method further includes: If the network resource request indicates that the target vehicle is performing a firmware upgrade and the channel congestion rate of the selected target channel is not less than a third threshold, a prompt message indicating current network congestion and suggesting upgrading later is sent to the user.

5. The method according to any one of claims 1 to 4, characterized in that: Each preset channel corresponds to a different level of autonomous driving; the higher the level of autonomous driving, the larger the bandwidth of the preset channel corresponding to the level of autonomous driving.

6. A vehicle network resource allocation device, characterized in that: The device comprises: a level acquisition module, configured to execute in response to a network resource request of a target vehicle, and acquire an autonomous driving level of the target vehicle; A designated channel module is configured to select a designated channel from preset channels according to the autonomous driving level; wherein the total amount of resources of each preset channel is different; and each preset channel corresponds to a unique network slice; a resource allocation module configured to divide the network resources required by the target vehicle from the total resources of the designated channel and distribute them to the target vehicle if the current channel congestion rate of the designated channel is less than a first threshold; If the channel congestion rate of the designated channel is not less than the first threshold, a backup channel is selected from each preset channel based on the autonomous driving level and the channel information of each preset channel; and the network resources required by the target vehicle are divided from the total resources of the backup channel and sent to the target vehicle; the channel information includes at least the bandwidth, channel congestion rate and network security of each preset channel.

7. An electronic device, characterized in that: include: A memory for storing program instructions; A processor is used to call the program instructions stored in the memory, and execute the steps included in any one of the methods of claims 1-5 according to the obtained program instructions.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes the method according to any one of claims 1 to 5.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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