Sensor transmission parameter adjustment method, device, equipment and storage medium

Abstract

The present application provides a sensor transmission parameter adjustment method, apparatus, device, and storage medium, including: predicting the remaining capacity of the network to which the target vehicle belongs; determining whether to adjust the transmission parameters of at least one sensor group on the target vehicle based on the remaining capacity of the network to which the target vehicle belongs; if it is determined that the transmission parameters of at least one sensor group should be adjusted, determining the target transmission parameters of the at least one sensor group; and sending the target transmission parameters of the at least one sensor group to the target vehicle so that the target vehicle adjusts the transmission parameters of the at least one sensor group to the corresponding target transmission parameters. This reduces uplink resource consumption, ensures the normal operation of remote control, and enables the deployment of more autonomous driving vehicles under limited network resource conditions.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of vehicle networking technology, and in particular to a sensor transmission parameter adjustment method, device, equipment, and storage medium. Background Art

[0002] In scenarios such as smart parks, smart ports, and smart mines, the use of autonomous vehicles for material or container transportation has become a trend. In traditional autonomous vehicle operations, a safety officer is required to ride in the vehicle to take over in the event of an emergency. In some new unmanned driving scenarios, in order to further reduce the number and workload of safety officers, remote control can be adopted. That is, the autonomous vehicle can use its own sensors to report sensor data to the rear controller via a wireless network. When the autonomous vehicle encounters an emergency, needs to drive out of the calibrated operating area, or the network is stuck or fluctuating, the rear controller will take over the autonomous vehicle through remote control. When driving normally, the vehicle usually operates in an unmanned mode.

[0003] Due to the limitations of wireless networks in network planning and network optimization, their uplink resource allocation is very limited. Therefore, how to reduce uplink resource consumption to ensure the normal implementation of remote control and enable the deployment of more autonomous driving vehicles under limited network resource conditions is a technical problem that needs to be urgently solved in this application. Summary of the Invention

[0004] The present application provides a sensor transmission parameter adjustment method, apparatus, device and storage medium to reduce uplink resource consumption. On the one hand, this can ensure the normal implementation of remote control, and on the other hand, it can enable the deployment of more autonomous driving vehicles under limited network resource conditions.

[0005] In a first aspect, a sensor transmission parameter adjustment method is provided, comprising: predicting the remaining capacity of a network to which a target vehicle belongs; determining whether to adjust the transmission parameters of at least one sensor group on the target vehicle based on the remaining capacity of the network to which the target vehicle belongs; if it is determined to adjust the transmission parameters of at least one sensor group, determining a target transmission parameter of the at least one sensor group; and sending the target transmission parameter of the at least one sensor group to the target vehicle so that the target vehicle adjusts the transmission parameter of the at least one sensor group to the corresponding target transmission parameter.

[0006] In a second aspect, a sensor transmission parameter adjustment method is provided, including: obtaining a target transmission parameter of at least one sensor group of a target vehicle; adjusting the transmission parameter of the at least one sensor group to a corresponding target transmission parameter, wherein the target transmission parameter of the at least one sensor group is a transmission parameter of the at least one sensor group obtained by adjusting the transmission parameter of the at least one sensor group based on the remaining capacity of the network to which the target vehicle belongs.

[0007] In a third aspect, a server is provided, comprising: a prediction module, a judgment module, a determination module, and a sending module, wherein the prediction module is used to predict the remaining capacity of the network to which the target vehicle belongs; the judgment module is used to determine whether to adjust the transmission parameters of at least one sensor group on the target vehicle based on the remaining capacity of the network to which the target vehicle belongs; the determination module is used to determine the target transmission parameters of at least one sensor group if the judgment module determines to adjust the transmission parameters of at least one sensor group; and the sending module is used to send the target transmission parameters of at least one sensor group to the target vehicle, so that the target vehicle adjusts the transmission parameters of at least one sensor group to the corresponding target transmission parameters.

[0008] In a fourth aspect, an autonomous driving vehicle is provided, comprising: an acquisition module and an adjustment module, wherein the acquisition module is used to acquire the target transmission parameters of at least one sensor group of the autonomous driving vehicle; the adjustment module is used to adjust the transmission parameters of the at least one sensor group to corresponding target transmission parameters, wherein the target transmission parameters of the at least one sensor group are the transmission parameters of the at least one sensor group determined by adjusting the transmission parameters of the at least one sensor group based on the remaining capacity of the network to which the autonomous driving vehicle belongs.

[0009] In a fifth aspect, a server is provided, comprising: a processor and a memory, wherein the memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to execute the method in the first aspect or its various implementations.

[0010] In a sixth aspect, an autonomous driving vehicle is provided, comprising: a processor and a memory, the memory being used to store a computer program, the processor being used to call and run the computer program stored in the memory, and executing the method as in the second aspect or its various implementations.

[0011] In a seventh aspect, a computer-readable storage medium is provided for storing a computer program, wherein the computer program enables a computer to execute the method as in the first aspect, the second aspect or any implementation thereof.

[0012] In an eighth aspect, a computer program product is provided, comprising computer program instructions, which enable a computer to execute the method in the first aspect, the second aspect, or any implementation thereof.

[0013] In a ninth aspect, a computer program is provided, which enables a computer to execute the method in the first aspect, the second aspect, or any implementation thereof.

[0014] Through the technical solution of the present application, the first server can predict the remaining capacity of the network and determine whether the sensor parameters need to be adjusted based on the remaining capacity. If the sensor parameters need to be adjusted, the sensor parameters are adjusted to reduce the uplink resource consumption. On the one hand, it can ensure the normal progress of remote control, and on the other hand, it can enable more autonomous driving vehicles to be deployed under limited network resource conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] 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.

[0016] Figure 1 An application scenario diagram provided for an embodiment of the present application;

[0017] Figure 2 Another application scenario diagram provided for an embodiment of the present application;

[0018] Figure 3 A flow chart of a sensor transmission parameter adjustment method provided in an embodiment of the present application;

[0019] Figure 4 A flowchart of another sensor transmission parameter adjustment method provided in an embodiment of the present application;

[0020] Figure 5 A flowchart of another sensor transmission parameter adjustment method provided in an embodiment of the present application;

[0021] Figure 6 A flowchart of another sensor transmission parameter adjustment method provided in an embodiment of the present application;

[0022] Figure 7 A flowchart of another sensor transmission parameter adjustment method provided in an embodiment of the present application;

[0023] Figure 8 A schematic diagram of a server provided in an embodiment of the present application;

[0024] Figure 9A schematic diagram of an autonomous driving vehicle provided in an embodiment of the present application;

[0025] Figure 10 It is a schematic block diagram of an electronic device 1000 provided in an embodiment of the present application. DETAILED DESCRIPTION

[0026] As mentioned above, due to the limitations of wireless networks in network planning and network optimization, their uplink resource allocation is very limited. Therefore, how to reduce uplink resource consumption to ensure the normal implementation of remote control and enable more autonomous driving vehicles to be deployed under limited network resource conditions is a technical problem that needs to be urgently solved in this application.

[0027] In order to solve the above technical problems, the inventive concept of this application is: the server can predict the remaining capacity of the network, and determine whether the sensor parameters need to be adjusted based on the remaining capacity. If the sensor parameters need to be adjusted, the sensor parameters are adjusted to reduce the uplink resource consumption. On the one hand, it can ensure the normal progress of remote control, and on the other hand, it can enable more autonomous driving vehicles to be deployed under limited network resource conditions.

[0028] It should be understood that the technical solution of this application can be applied to the following scenarios, but is not limited to:

[0029] For example, Figure 1 An application scenario diagram provided in an embodiment of the present application, such as Figure 1 As shown, the autonomous driving vehicle 110 can communicate with the server 120, and the server 120 can communicate with the client 130, wherein the client 130 can provide data of the autonomous driving vehicle 110, such as sensor data, etc., to the background driver.

[0030] In some implementations, Figure 1 The application scenarios shown may also include: base stations, core network side equipment, etc. In addition, Figure 1 An autonomous driving vehicle, a server, and a client are shown as an example. In fact, other numbers of autonomous driving vehicles, servers, and clients may be included, and this application does not impose any restrictions on this.

[0031] For example, Figure 2 Another application scenario diagram provided in the embodiment of the present application is as follows: Figure 2As shown, the autonomous vehicle 210 can communicate with the first server 220 and the operator server 230. The first server 220 and the operator server 230 can communicate with each other. For example, the first server 220 can obtain wireless operator-side data of the autonomous vehicle 210 from the operator server 230. The first server 220 can communicate with the client 240, wherein the client 240 can provide data of the autonomous vehicle 210, such as sensor data, to the backend driver.

[0032] In some implementations, Figure 2 The application scenarios shown may also include: base stations, core network side equipment, etc. In addition, Figure 2 An autonomous driving vehicle, a first server, an operator server and a client are shown as an example. In fact, other numbers of autonomous driving vehicles, first servers, operator servers and clients may be included, and this application does not impose any restrictions on this.

[0033] In some implementations, Figure 1 The server 120 and Figure 2 The first server 220 in the example may be an edge server or a central server.

[0034] With the rapid development of the Internet and its applications, most companies have established their own websites to enhance external communications and accelerate business processes. Customers have increasingly higher requirements for the response time of website system access, website content, and the reliability and immediacy of the services provided. As a result, a system that supports the entire website with a single server can no longer meet customer needs. Instead, a group of servers with a two- to three-tier architecture is used. The first tier is the front-end server that directly contacts the user, also known as the edge server.

[0035] In some implementations, Figure 1 Server 120, Figure 2 The first server 220 and the operator server 230 can be independent physical servers, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. This application does not impose any restrictions on this.

[0036] The technical solution of this application will be described in detail below:

[0037] Figure 3 A flow chart of a sensor transmission parameter adjustment method provided in an embodiment of the present application, wherein the method can be performed as follows Figure 1 The server 120 shown or Figure 2 The first server 220 in the embodiment is executed, and this application does not limit this. Figure 2Taking the first server shown in the figure as an example, the sensor transmission parameter adjustment method is exemplarily described. Figure 3 As shown, the method includes the following steps:

[0038] S310: Predicting the remaining capacity of the network to which the target vehicle belongs;

[0039] S320: Determine whether to adjust the transmission parameters of at least one sensor group on the target vehicle based on the remaining capacity of the network to which the target vehicle belongs;

[0040] S330: If it is determined to adjust the transmission parameter of at least one sensor group, determine a target transmission parameter of the at least one sensor group;

[0041] S340: Sending a target transmission parameter of at least one sensor group to the target vehicle, so that the target vehicle adjusts the transmission parameter of the at least one sensor group to the corresponding target transmission parameter.

[0042] The target vehicle can be an autonomous vehicle that can be remotely controlled by a human operator in the event of an emergency, needing to leave its designated operating area, or experiencing network lag or fluctuations. During normal operation, the autonomous vehicle typically operates in an unmanned mode.

[0043] In some implementations, the network to which the target vehicle belongs may be a fourth generation mobile communication technology (4G), a fifth generation mobile communication technology (5G), or a wireless fidelity (WiFi) technology network, etc., and this application does not impose any restrictions on this.

[0044] It should be understood that, in this application, the network to which the target vehicle belongs is also referred to as the target vehicle home network, etc., and this application does not impose any restrictions on this.

[0045] It should be understood that, in this application, the remaining capacity of the network to which the target vehicle belongs refers to the available capacity of the network to which the target vehicle belongs. This capacity is also called bandwidth or transmission rate, etc., and its unit can be Megabits per second (Mbps), but is not limited to this.

[0046] It should be understood that the first server may determine whether to adjust the transmission parameters of at least one sensor group by any of the following implementable methods, but is not limited thereto:

[0047] Implementation method 1: If the remaining capacity of the network to which the target vehicle belongs is less than or equal to a preset threshold, determine to adjust the transmission parameters of at least one sensor group.

[0048] A second implementation method is to adjust the transmission parameters of at least one sensor group if the remaining capacity of the network to which the target vehicle belongs is less than a preset threshold.

[0049] In some implementations, the preset threshold may be pre-configured or dynamically configured by the base station for the target vehicle, or may be predefined, and this application does not impose any restrictions thereon. The preset threshold may be 30%, 20%, or the like of the total capacity of the network to which the target vehicle belongs, and this application does not impose any restrictions thereon. For example, if the total capacity of the network to which the target vehicle belongs is 200 Mbps, then the preset threshold may be 60 Mbps or 40 Mbps. For example, if the total capacity of the network to which the target vehicle belongs is 300 Mbps, then the preset threshold may be 90 Mbps or 60 Mbps.

[0050] In some implementations, some or all of the sensors of the target vehicle may be divided into multiple groups by the first server, and each sensor group may include one or more sensors. When each sensor group includes one sensor, it can be understood that the first server has not divided some or all of the sensors of the target vehicle into groups.

[0051] In some implementations, the first server can group each sensor according to its function or characteristics, but is not limited to this: for example, assuming that the target vehicle includes: five cameras, two of the five cameras are located at the front of the target vehicle to capture the forward movement so that the rear controller can observe the forward route of the target vehicle; two cameras are located on the left and right sides of the target vehicle to capture the side of the target vehicle so that when the target vehicle changes lanes, the rear controller can observe the side vehicles and judge the dangers on the side when driving; another camera is located at the rear of the target vehicle, mainly used to capture the rear reversing situation so that when the target vehicle reverses, the rear controller can observe the reverse route. Based on this, the first server can group the five cameras according to their power supply, such as grouping the two cameras located at the front of the target vehicle into a group and calling it the first group of cameras. For the rear controller, most of the time, the information collected by the first group of cameras is the most critical, so a clearer video stream is also required. The first server can group the cameras located on the left and right sides of the target vehicle into a group called the second camera group. When the target vehicle is moving normally, the rear controller's demand for real-time side images (resolution, clarity, etc.) is weaker than that of the first camera group. However, when the target vehicle changes lanes or when other vehicles approach, the rear controller's demand for real-time side images increases. Another server can group the cameras located at the rear of the target vehicle into a group called the third camera group. When the target vehicle is moving normally, the rear controller's demand for real-time rear images is lower, but when the target vehicle is reversing, the rear controller's demand for real-time rear images increases.

[0052] It should be understood that the target vehicle may have more than one type of sensor. For example, the target vehicle may include not only the five cameras mentioned above, but also four millimeter-wave radars, two of which are located at the front of the target vehicle, and the other two at the rear. Based on this, the first server may also group the two millimeter-wave radars at the front of the target vehicle into one group, and the other two at the rear into another group.

[0053] It should be understood that different types of sensor groups correspond to different types of transmission parameters. For example, for the first, second, and third camera groups described above, the corresponding transmission parameter type is at least one of bit rate and resolution. In other words, the first server determines whether to adjust at least one of the bit rate and resolution for these three camera groups based on the remaining capacity of the target vehicle's network. For another example, for the two millimeter-wave radar groups described above, the corresponding transmission parameter type is transmission rate. In other words, the first server determines whether to adjust the transmission rates of these two millimeter-wave radar groups based on the remaining capacity of the target vehicle's network.

[0054] It should be understood that, for any of the above sensor groups, the corresponding target transmission parameter refers to the transmission parameter to which the sensor group is to be adjusted.

[0055] In some implementations, the target transmission parameters of the sensors in each sensor group determined by the first server may be the same or different. For example, for two cameras in the first group of cameras, the target transmission parameters corresponding to the two cameras may be the same or different.

[0056] In some implementations, after the target vehicle receives the target transmission parameters of at least one sensor group sent by the first server, the target vehicle may transmit data in accordance with the target transmission parameters of the at least one sensor group. For example, for the first group of cameras described above, the target vehicle may transmit data to the first server in accordance with the target resolution of the first group of cameras. Alternatively, after the target vehicle receives the target transmission parameters of at least one sensor group sent by the first server, the target vehicle may further adjust the target transmission parameters of the at least one sensor group and transmit data to the first server based on the adjusted target transmission parameters.

[0057] In summary, in this application, the first server can predict the remaining capacity of the network and determine whether the sensor parameters need to be adjusted based on the remaining capacity. If the sensor parameters need to be adjusted, the sensor parameters are adjusted to reduce uplink resource consumption. On the one hand, it can ensure the normal progress of remote control, and on the other hand, it can enable more autonomous driving vehicles to be deployed under limited network resource conditions.

[0058] In some implementations, the first server may obtain application layer data of at least one sensor group. Accordingly, one implementation of S310 is: the first server predicts the remaining capacity of the network to which the target vehicle belongs based on the application layer data of at least one sensor group.

[0059] For example, Figure 4 A flowchart of another sensor transmission parameter adjustment method provided in an embodiment of the present application, wherein the method can be performed as follows Figure 1 The server 120 shown or Figure 2 The first server 220 in the embodiment is executed, and this application does not limit this. Figure 2 Taking the first server shown in the figure as an example, the sensor transmission parameter adjustment method is exemplarily described. Figure 4 As shown, the method includes the following steps:

[0060] S410: Acquire application layer data of at least one sensor group;

[0061] S420: Predicting the remaining capacity of the network to which the target vehicle belongs based on application layer data of at least one sensor group;

[0062] S430: Determine whether to adjust the transmission parameters of at least one sensor group on the target vehicle according to the remaining capacity of the network to which the target vehicle belongs;

[0063] S440: If it is determined to adjust the transmission parameter of at least one sensor group, determine a target transmission parameter of the at least one sensor group;

[0064] S450: Sending a target transmission parameter of at least one sensor group to a target vehicle, so that the target vehicle adjusts the transmission parameter of at least one sensor group to the corresponding target transmission parameter.

[0065] It should be understood that S430 to S450 are the same as the above-mentioned S320 to S340, and their contents and effects can be referred to the explanations of S320 to S340, and this application will not go into details therein.

[0066] The following describes S410 and S420:

[0067] It should be understood that, for any sensor group, the first server treats the sensors in the group as a whole to collect statistics on the application layer data of the group, wherein the application layer data may include at least one of the following items, but is not limited to: packet loss rate, consumed bandwidth, data transmission delay, and freeze rate.

[0068] In some implementations, the first server may obtain the application layer data of each sensor group from the target vehicle, or may obtain the application layer data of each sensor group from an application server, which is not limited in this application.

[0069] It should be understood that the application server can be Figure 1 The client 130 or Figure 2 The server corresponding to the client 240 shown, for example, the application server is a server corresponding to a certain video client.

[0070] In some possible implementations, there is a first mapping relationship between the joint data consisting of the application layer data of the at least one sensor group and the remaining capacity of the network to which the target vehicle belongs; based on this, the first server can predict the remaining capacity of the network to which the target vehicle belongs based on the joint data consisting of the application layer data of the at least one sensor group and the first mapping relationship.

[0071] For example, assuming that the at least one sensor group is the first, second, and third camera groups, and the packet loss rates corresponding to the three camera groups are A, B, and C, respectively, and the remaining capacity of the target vehicle's network corresponding to A, B, and C is 40% of the total capacity of the target vehicle's network, then the first server predicts that the remaining capacity of the target vehicle's network is 40% of the total capacity of the target vehicle's network.

[0072] In other possible implementations, there is a second mapping relationship between the application layer data of the at least one sensor group and the remaining capacity of the network to which the target vehicle belongs; based on this, the first server can first determine multiple remaining capacities of the network to which the target vehicle belongs based on the application layer data of the at least one sensor group and the second mapping relationship, and then select a remaining capacity from these multiple remaining capacities to predict the remaining capacity of the network to which the target vehicle belongs.

[0073] In some implementations, the first server may select a remaining capacity from the plurality of remaining capacities in the following selection manner, but is not limited thereto:

[0074] Implementation method 1: The first server may randomly select a remaining capacity from multiple remaining capacities.

[0075] Implementation method 2: The first server may select a minimum remaining capacity from multiple remaining capacities.

[0076] For example, assuming the at least one sensor group is the first, second, and third camera groups, and the packet loss rates corresponding to the three camera groups are A, B, and C, respectively, and the remaining capacities of the target vehicle's network corresponding to A, B, and C are 20% of the total capacity of the target vehicle's network, 30% of the total capacity of the target vehicle's network, and 40% of the total capacity of the target vehicle's network, respectively. Based on this, the first server can select the minimum of these three remaining capacities, namely 20% of the total capacity of the target vehicle's network, as the predicted remaining capacity of the target vehicle's network.

[0077] In summary, in this application, the first service can obtain application layer data of at least one sensor group; and based on the application layer data of at least one sensor group, accurately predict the remaining capacity of the network to which the target vehicle belongs, further ensuring the normal progress of remote control and enabling more autonomous driving vehicles to be deployed under limited network resource conditions.

[0078] In some possible implementations, the first server may obtain application layer data of at least one sensor group and data of the target vehicle on the wireless operator side. Accordingly, one possible implementation of S310 is: the first server predicts the remaining capacity of the network to which the target vehicle belongs based on the application layer data of at least one sensor group and data of the target vehicle on the wireless operator side.

[0079] For example, Figure 5 A flow chart of another sensor transmission parameter adjustment method provided in an embodiment of the present application, wherein the method can be performed as follows Figure 1 The server 120 shown or Figure 2 The first server 220 in the embodiment is executed, and this application does not limit this. Figure 2 Taking the first server shown in the figure as an example, the sensor transmission parameter adjustment method is exemplarily described. Figure 5 As shown, the method includes the following steps:

[0080] S510: Acquire application layer data of at least one sensor group and data of the target vehicle on the wireless operator side;

[0081] S520: Predicting the remaining capacity of the network to which the target vehicle belongs based on the application layer data of the at least one sensor group and the data of the target vehicle on the wireless operator side;

[0082] S530: Determine whether to adjust the transmission parameters of at least one sensor group on the target vehicle based on the remaining capacity of the network to which the target vehicle belongs;

[0083] S540: If it is determined to adjust the transmission parameter of at least one sensor group, determine a target transmission parameter of the at least one sensor group;

[0084] S550: Sending a target transmission parameter of at least one sensor group to the target vehicle, so that the target vehicle adjusts the transmission parameter of the at least one sensor group to the corresponding target transmission parameter.

[0085] It should be understood that S530 to S550 are the same as the above-mentioned S320 to S340, and their contents and effects can be referred to the explanations of S320 to S340, and this application will not go into details therein.

[0086] The following describes S510 and S520:

[0087] It should be understood that the first server may predict the remaining capacity of the network to which the target vehicle belongs by any of the following achievable methods, but is not limited thereto:

[0088] A first implementation method is as follows: the first server predicts the vehicle to be switched in the network to which the target vehicle belongs based on application layer data of at least one sensor group and data of the target vehicle on the wireless operator side; predicts the network capacity occupied by the vehicle to be switched in the network to which the target vehicle belongs; and calculates the sum of the current remaining capacity of the network to which the target vehicle belongs and the network capacity occupied by the vehicle to be switched to predict the remaining capacity of the network to which the target vehicle belongs.

[0089] A second achievable method is as follows: the first server predicts the vehicles in operation in the network to which the target vehicle belongs based on application layer data of at least one sensor group and data of the target vehicle on the wireless operator side; predicts the network capacity occupied by the vehicles in operation in the network to which the target vehicle belongs; and calculates the difference between the total capacity of the network to which the target vehicle belongs and the network capacity occupied by the vehicles in operation to predict the remaining capacity of the network to which the target vehicle belongs.

[0090] In some implementations, the data of the target vehicle on the wireless operator side includes: (1) a threshold value corresponding to application layer data of at least one sensor group, but is not limited thereto.

[0091] In some implementations, the data of the target vehicle on the wireless operator side further includes at least one of the following, but is not limited to:

[0092] (2) The signal strength of the cell to which the target vehicle belongs and its neighboring cells;

[0093] (3) The current remaining capacity of the cell to which the target vehicle belongs and its neighboring cells.

[0094] It should be understood that the cell to which the target vehicle belongs can also be understood as the network to which the target vehicle belongs. Furthermore, the current remaining capacity of the cell to which the target vehicle belongs in item (3) may be different from the remaining capacity of the network to which the target vehicle belongs as predicted by the first server. In this embodiment, the remaining capacity of the network to which the target vehicle belongs as predicted by the first server can be obtained based on the current remaining capacity of the cell to which the target vehicle belongs.

[0095] The following describes the first possible implementation method:

[0096] Assuming that the data of the target vehicle on the wireless operator side includes: a threshold value corresponding to the application layer data of at least one sensor group, that is, item (1) above, then for any vehicle among all vehicles in the network to which the target vehicle belongs, if there is at least one sensor group whose application layer data is greater than the corresponding threshold value, then the vehicle is determined to be the vehicle to be switched.

[0097] Assume that the data of the target vehicle on the wireless operator side includes: a threshold value corresponding to application layer data of at least one sensor group, and the signal strength of the cell to which the target vehicle belongs and the neighboring cell of the cell, that is, items (1) and (2) above. Then, if the signal strength of the cell to which the target vehicle belongs is lower than the signal strength of the neighboring cell, and for any vehicle among all vehicles in the network to which the target vehicle belongs, there is at least one sensor group on the vehicle with application layer data greater than the corresponding threshold value, then the vehicle is determined to be the vehicle to be switched.

[0098] Assume that the data of the target vehicle on the wireless operator side includes: a threshold value corresponding to application layer data of at least one sensor group, and the current remaining capacity of the cell to which the target vehicle belongs and the neighboring cells of the cell, that is, items (1) and (3) above. Then, if the current remaining capacity of the cell to which the target vehicle belongs is lower than the current remaining capacity of the neighboring cells, and for any vehicle among all vehicles in the network to which the target vehicle belongs, there is at least one sensor group on the vehicle with application layer data greater than the corresponding threshold value, then the vehicle is determined to be the vehicle to be switched.

[0099] Assume that the data of the target vehicle on the wireless operator side includes: a threshold value corresponding to application layer data of at least one sensor group, the signal strength of the cell to which the target vehicle belongs and the neighboring cells of the cell, and the current remaining capacity of the cell to which the target vehicle belongs and the neighboring cells of the cell, that is, the above items (1), (2) and (3), then if the signal strength of the cell to which the target vehicle belongs is lower than the signal strength of the neighboring cells, the current remaining capacity of the cell to which the target vehicle belongs is lower than the current remaining capacity of the neighboring cells, and for any vehicle among all vehicles in the network to which the target vehicle belongs, there is at least one sensor group on the vehicle with application layer data greater than the corresponding threshold value, then the vehicle is determined to be the vehicle to be switched.

[0100] It should be understood that if the application layer data corresponding to any sensor group includes multiple items, for example, the application layer data corresponding to the first group of cameras mentioned above includes packet loss rate and delay, then the threshold value corresponding to the application layer data here is actually a vector. For example, the threshold value includes the threshold value corresponding to the packet loss rate and the threshold value corresponding to the delay. Accordingly, the application layer data of the sensor group is greater than the corresponding threshold value, which means that the packet loss rate of the sensor group is greater than the corresponding packet loss rate threshold value, and the delay of the sensor group is greater than the corresponding delay threshold value.

[0101] Furthermore, assuming that the network capacity occupied by each vehicle to be switched is known, the first server can determine the network capacity occupied by all vehicles to be switched in the network to which the target vehicle belongs. For example, assuming that there are 3 vehicles to be switched in the network to which the target vehicle belongs, and the network capacity occupied by each vehicle to be switched is 20Mbps, then the network capacity occupied by all vehicles to be switched in the network to which the target vehicle belongs is 60Mbps. Furthermore, assuming that the current remaining capacity of the network to which the target vehicle belongs is 80Mbps, the first server can calculate the sum of the current remaining capacity of the network to which the target vehicle belongs and the network capacity occupied by the vehicles to be switched, that is, 60Mbps+80Mbps=140Mbps, and the 140Mbps is the remaining capacity of the network to which the target vehicle belongs predicted by the first server.

[0102] The following describes the second possible implementation method:

[0103] Assuming that the data of the target vehicle on the wireless operator side includes: a threshold value corresponding to the application layer data of at least one sensor group, that is, item (1) above, then for any vehicle among all vehicles, if the application layer data of each sensor group on the vehicle is less than or equal to the corresponding threshold value, the vehicle is determined to be a vehicle in a running state.

[0104] Assume that the data of the target vehicle on the wireless operator side includes: a threshold value corresponding to application layer data of at least one sensor group, and the signal strength of the cell to which the target vehicle belongs and the neighboring cell of the cell, that is, items (1) and (2) above. Then, if the signal strength of the cell to which the target vehicle belongs is greater than or equal to the signal strength of the neighboring cell, and for any vehicle among all vehicles, if the application layer data of each sensor group on the vehicle is less than or equal to the corresponding threshold value, then the vehicle is determined to be a vehicle in a running state.

[0105] Assume that the data of the target vehicle on the wireless operator side includes: a threshold value corresponding to application layer data of at least one sensor group, and the current remaining capacity of the cell to which the target vehicle belongs and the neighboring cells of the cell, that is, items (1) and (3) above. Then, if the current remaining capacity of the cell to which the target vehicle belongs is greater than or equal to the current remaining capacity of the neighboring cells, and for any vehicle among all vehicles, if the application layer data of each sensor group on the vehicle is less than or equal to the corresponding threshold value, then the vehicle is determined to be a vehicle in a running state.

[0106] Assume that the data of the target vehicle on the wireless operator side includes: a threshold value corresponding to application layer data of at least one sensor group, the signal strength of the cell to which the target vehicle belongs and the neighboring cells of the cell, and the current remaining capacity of the cell to which the target vehicle belongs and the neighboring cells of the cell, that is, the above items (1), (2) and (3), then if the signal strength of the cell to which the target vehicle belongs is greater than or equal to the signal strength of the neighboring cell, the current remaining capacity of the cell to which the target vehicle belongs is greater than or equal to the current remaining capacity of the neighboring cell, and for any vehicle among all vehicles, if the application layer data of each sensor group on the vehicle is less than or equal to the corresponding threshold value, then the vehicle is determined to be a vehicle in a running state.

[0107] It should be understood that if the application layer data corresponding to any sensor group includes multiple items, for example, the application layer data corresponding to the first group of cameras mentioned above includes packet loss rate and delay, then the threshold value corresponding to the application layer data here is actually a vector, for example, the threshold value includes the threshold value corresponding to the packet loss rate and the threshold value corresponding to the delay. Accordingly, for any sensor group, the application layer data of the sensor group is less than or equal to the corresponding threshold value, which means that the packet loss rate of the sensor group is less than or equal to the corresponding packet loss rate threshold value, and the delay of the sensor group is less than or equal to the corresponding delay threshold value.

[0108] Furthermore, assuming that the network capacity occupied by each running vehicle is known, the first server can determine the network capacity occupied by all running vehicles in the network to which the target vehicle belongs. For example, assuming that there are 3 running vehicles in the network to which the target vehicle belongs, and the network capacity occupied by each running vehicle is 20Mbps, then the network capacity occupied by all running vehicles in the network to which the target vehicle belongs is 60Mbps. Furthermore, assuming that the total capacity of the network to which the target vehicle belongs is 200Mbps, the first server can calculate the difference between the current remaining capacity of the network to which the target vehicle belongs and the network capacity occupied by all running vehicles in the network, that is, 200Mbps-60Mbps=140Mbps, and the 140Mbps is the remaining capacity of the network to which the target vehicle belongs predicted by the first server.

[0109] In summary, in this application, the first service can obtain the application layer data of at least one sensor group and the data of the target vehicle on the wireless operator side; and based on the application layer data of at least one sensor group and the data of the target vehicle on the wireless operator side, accurately predict the remaining capacity of the network to which the target vehicle belongs, further ensuring the normal progress of remote control and enabling more autonomous driving vehicles to be deployed under limited network resource conditions.

[0110] In some implementations, the first server may directly determine the target transmission parameter of the at least one sensor group.

[0111] Exemplarily, it is assumed that the at least one sensor group is the first group of cameras, the second group of cameras, and the third group of cameras. If the first server determines to adjust the transmission parameters of at least one sensor group, then the first server can reduce the current transmission parameters of the at least one sensor group by a certain percentage to obtain the transmission parameters of the at least one sensor group. For example: assuming that the resolutions of the first group of cameras, the second group of cameras, and the third group of cameras are 720p, 1080p, and 1080p, respectively, and the first server determines to adjust the transmission parameters of the three camera groups, then the first server can reduce the current transmission parameters of the three camera groups by 10%, and the resolution of the first group of cameras can be 720-72=648p, and the resolutions of the second and third groups of cameras can be 1080-108=972p.

[0112] In some implementations, the first server may directly determine the transmission parameter interval of at least one sensor group. Furthermore, for any sensor group in the at least one sensor group, the first server may determine, based on application layer data of the sensor group, a target transmission parameter corresponding to the sensor group within the transmission parameter interval corresponding to the sensor group.

[0113] In some implementations, the first server may divide the application layer data into multiple intervals, which correspond one-to-one to the multiple data in the transmission parameter interval. For example, the multiple intervals are arranged in order from small to large, and the multiple data in the corresponding transmission parameter interval are arranged from large to small.

[0114] Exemplarily, assume that the at least one sensor group is the first, second, and third groups of cameras. If the first server determines to adjust the transmission parameters of at least one sensor group, the first server may determine a transmission parameter range for the at least one sensor group. For example, assume that the first server determines that the resolution range corresponding to the first group of cameras is [720p, 1080p], and that the resolution ranges corresponding to the second and third groups of cameras are both [480p, 720p]. Assuming that the first server determines that the packet loss rate corresponding to the first group of cameras is 5%, the target transmission parameter corresponding to the 5% packet loss rate may be 1080p. Assuming that the first server determines that the packet loss rate corresponding to the second group of cameras is 8%, the target transmission parameter corresponding to the 8% packet loss rate may be 600p. Assuming that the first server determines that the packet loss rate corresponding to the third group of cameras is 10%, the target transmission parameter corresponding to the 10% packet loss rate may be 480p.

[0115] In some implementations, the first server may directly determine a transmission parameter interval for at least one sensor group. Furthermore, for any sensor group in the at least one sensor group, the first server may determine a target transmission parameter corresponding to the sensor group within the transmission parameter interval corresponding to the sensor group based on application layer data of the sensor group and wireless carrier-side data of the target vehicle.

[0116] In some implementations, as described above, the wireless operator-side data of the target vehicle may include: a threshold value corresponding to the application layer data of at least one sensor group. Then, for any sensor group, the first server may determine whether the application layer data of the sensor group is greater than the corresponding threshold value. If the application layer data of the sensor group is greater than the corresponding threshold value, the first server may take the left endpoint of the transmission parameter interval of the sensor group. If the application layer data of the sensor group is less than or equal to the corresponding threshold value, the first server may take the right endpoint of the transmission parameter interval of the sensor group.

[0117] For example, assuming that the at least one sensor group is the first, second, and third camera groups. If the first server determines to adjust the transmission parameters of at least one sensor group, the first server may determine a transmission parameter range for the at least one sensor group. For example, assuming that the first server determines that the resolution range corresponding to the first camera group is [720p, 1080p], and determines that the resolution ranges corresponding to the second and third camera groups are both [480p, 720p]. assuming that the first server determines that the packet loss rate corresponding to the first camera group is 5%, which is less than the 6% threshold corresponding to the packet loss rate, then the right endpoint of the target transmission parameters [720p, 1080p] for the first camera group is determined to be 1080p. assuming that the first server determines that the packet loss rate corresponding to the second camera group is 8%, which is greater than the 6% threshold corresponding to the packet loss rate, then the left endpoint of the target transmission parameters [480p, 720p] for the second camera group is determined to be 480p. Assume that the first server determines that the packet loss rate corresponding to the third group of cameras is 10%, which is greater than the threshold value of 6% corresponding to the packet loss rate, then the left endpoint of the target transmission parameter [480p, 720p] corresponding to the third group of cameras is determined to be 480p.

[0118] In some implementations, the first server may obtain status information of the target vehicle; and directly determine target transmission parameters of at least one sensor group based on the status information of the target vehicle.

[0119] In some implementations, the status information of the target vehicle includes: the target vehicle is in a remote control state or an automatic driving state, and the status information also includes any of the following items, but is not limited to: queuing state, standby state, moving state, lane changing state, and reversing state.

[0120] For example, it is assumed that the at least one sensor group is the first group of cameras, the second group of cameras, and the third group of cameras. If the first server determines that the target vehicle is moving normally, the first server may use a resolution of 1080p and a bit rate of 6 Mbps for the first group of cameras. The second group of cameras and the third group of cameras both use a resolution of 720p and a bit rate of 2 Mbps. When the target vehicle is waiting in line for the gantry crane to place a container. That is, in the scenario of a container truck carrying containers in a port, the first group of cameras, the second group of cameras, and the third group of cameras may all use a medium resolution and a medium bit rate, for example, a resolution of 800p and a bit rate of 4 Mbps may all be used for the first group of cameras, the second group of cameras, and the third group of cameras. When the target vehicle changes lanes, the first server may increase the resolution and bit rate of the second group of cameras, for example, a resolution of 800p and a bit rate of 4 Mbps may be used for the first group of cameras and the third group of cameras. The second camera group uses a 1080p resolution and a 6Mbps bitrate. When the target vehicle is in autonomous driving mode, it can autonomously trigger the adjustment of the resolution and bitrate of each camera group. When the target vehicle is in remote control mode, the adjustment of the resolution and bitrate of each camera group can be triggered by the turn signal or other means. If the target vehicle is reversing, the first server can increase the resolution and bitrate of the third camera group. For example, the first and second cameras use an 800p resolution and a 4Mbps bitrate. The third camera group uses a 1080p resolution and a 6Mbps bitrate.

[0121] In some possible implementations, the first server can obtain status information of the target vehicle; and based on the status information of the target vehicle, directly determine the transmission parameter interval of at least one sensor group. Furthermore, the first server can determine the target transmission parameter corresponding to the sensor group in the transmission parameter interval corresponding to the sensor group based on the application layer data of the sensor group for any sensor group in the at least one sensor group.

[0122] It should be understood that this implementation can be Figure 3 、 Figure 4 or Figure 5 The corresponding embodiments are combined with Figure 3 The corresponding embodiments are combined for exemplary description:

[0123] Figure 6A flow chart of another sensor transmission parameter adjustment method provided in an embodiment of the present application, wherein the method can be performed as follows Figure 1 The server 120 shown or Figure 2 The first server 220 in the embodiment is executed, and this application does not limit this. Figure 2 Taking the first server shown in the figure as an example, the sensor transmission parameter adjustment method is exemplarily described. Figure 6 As shown, the method includes the following steps:

[0124] S610: Predicting the remaining capacity of the network to which the target vehicle belongs;

[0125] S620: Determine whether to adjust the transmission parameters of at least one sensor group on the target vehicle based on the remaining capacity of the network to which the target vehicle belongs;

[0126] S630: If it is determined to adjust the transmission parameters of at least one sensor group, then obtaining the state information of the target vehicle and determining the transmission parameter interval of at least one sensor group according to the state information of the target vehicle;

[0127] S640: For any sensor group in the at least one sensor group, determine, according to application layer data of the sensor group, a target transmission parameter corresponding to the sensor group in a transmission parameter interval corresponding to the sensor group;

[0128] S650: Sending a target transmission parameter of at least one sensor group to the target vehicle, so that the target vehicle adjusts the transmission parameter of the at least one sensor group to the corresponding target transmission parameter.

[0129] It should be understood that S610, S620 and S650 can refer to Figure 3 The explanation of the corresponding embodiments will not be repeated in this application.

[0130] The following is an exemplary description of S630 and S640:

[0131] For example, when the target vehicle is in normal motion, the first server may determine that the resolution range for the first camera group is [720p, 1080p] and the bit rate range is [4Mbps, 6Mbps]; the resolution range for the second camera group is [480p, 720p] and the bit rate range is [1Mbps, 2Mbps]; and the resolution range for the third camera group is [480p, 720p] and the bit rate range is [1Mbps, 2Mbps]. When the target vehicle is waiting in line for a gantry crane to place a container, such as in a container truck transporting containers at a port, the first, second, and third camera groups can all use a medium resolution range and a medium bit rate range. For example, the first, second, and third camera groups can all use a resolution of [720p, 800p] and a bit rate of [4Mbps, 6Mbps]. When the target vehicle changes lanes, the first server can increase the resolution range and bitrate range of the second camera group. For example, the first and third cameras can both use a resolution of [720p, 800p] and a bitrate of [4Mbps, 6Mbps]. The second camera group can use a resolution of [720p, 1080p] and a bitrate of [4Mbps, 6Mbps]. If the target vehicle reverses, the first server can increase the resolution and bitrate of the third camera group. For example, the first and second cameras can both use a resolution of [720p, 800p] and a bitrate of [4Mbps, 6Mbps]. The third camera group can use a resolution of [720p, 1080p] and a bitrate of [4Mbps, 6Mbps].

[0132] In some implementations, the first server may divide the application layer data into multiple intervals, which correspond one-to-one to the multiple data in the transmission parameter interval. For example, the multiple intervals are arranged in order from small to large, and the multiple data in the corresponding transmission parameter interval are arranged from large to small.

[0133] For example, assume that the at least one sensor group is the first, second, and third camera groups. If the first server determines to adjust the transmission parameters of at least one sensor group, the first server may determine the transmission parameter range for the at least one sensor group based on the target vehicle's status information. For example, assume that the first server determines that the resolution range corresponding to the first camera group is [720p, 1080p], and that the resolution ranges corresponding to the second and third camera groups are both [480p, 720p]. Assuming that the first server determines that the packet loss rate corresponding to the first camera group is 5%, the target transmission parameter corresponding to the 5% packet loss rate may be 1080p. Assuming that the first server determines that the packet loss rate corresponding to the second camera group is 8%, the target transmission parameter corresponding to the 8% packet loss rate may be 600p. Assuming that the first server determines that the packet loss rate corresponding to the third camera group is 10%, the target transmission parameter corresponding to the 10% packet loss rate may be 480p.

[0134] In some possible implementations, the first server can obtain status information of the target vehicle; and based on the status information of the target vehicle, directly determine the transmission parameter interval of at least one sensor group. Furthermore, the first server can determine the target transmission parameter in the transmission parameter interval corresponding to the sensor group for any sensor group in the at least one sensor group based on the application layer data of the sensor group and the wireless operator side data of the target vehicle.

[0135] It should be understood that this implementation can be Figure 3 、 Figure 4 or Figure 5 The corresponding embodiments are combined with Figure 3 The corresponding embodiments are combined for exemplary description:

[0136] Figure 7 A flow chart of another sensor transmission parameter adjustment method provided in an embodiment of the present application, wherein the method can be performed as follows Figure 1 The server 120 shown or Figure 2 The first server 220 in the embodiment is executed, and this application does not limit this. Figure 2 Taking the first server shown in the figure as an example, the sensor transmission parameter adjustment method is exemplarily described. Figure 7 As shown, the method includes the following steps:

[0137] S710: Predicting the remaining capacity of the network to which the target vehicle belongs;

[0138] S720: Determine whether to adjust the transmission parameters of at least one sensor group on the target vehicle based on the remaining capacity of the network to which the target vehicle belongs;

[0139] S730: If it is determined to adjust the transmission parameters of at least one sensor group, then obtaining the state information of the target vehicle and determining the transmission parameter interval of at least one sensor group based on the state information of the target vehicle;

[0140] S740: For any sensor group in the at least one sensor group, determine a target transmission parameter in a transmission parameter interval corresponding to the sensor group according to application layer data of the sensor group and wireless operator-side data of the target vehicle;

[0141] S750: Sending a target transmission parameter of at least one sensor group to the target vehicle, so that the target vehicle adjusts the transmission parameter of the at least one sensor group to the corresponding target transmission parameter.

[0142] It should be understood that S710, S720 and S750 can refer to Figure 3 The explanation of the corresponding embodiments will not be repeated in this application.

[0143] The following is an exemplary description of S730 and S740:

[0144] For example, when the target vehicle is in normal motion, the first server may determine that the resolution range for the first camera group is [720p, 1080p] and the bit rate range is [4Mbps, 6Mbps]; the resolution range for the second camera group is [480p, 720p] and the bit rate range is [1Mbps, 2Mbps]; and the resolution range for the third camera group is [480p, 720p] and the bit rate range is [1Mbps, 2Mbps]. When the target vehicle is waiting in line for a gantry crane to place a container, such as in a container truck transporting containers at a port, the first, second, and third camera groups can all use a medium resolution range and a medium bit rate range. For example, the first, second, and third camera groups can all use a resolution of [720p, 800p] and a bit rate of [4Mbps, 6Mbps]. When the target vehicle changes lanes, the first server can increase the resolution range and bitrate range of the second camera group. For example, the first and third cameras can both use a resolution of [720p, 800p] and a bitrate of [4Mbps, 6Mbps]. The second camera group can use a resolution of [720p, 1080p] and a bitrate of [4Mbps, 6Mbps]. If the target vehicle reverses, the first server can increase the resolution and bitrate of the third camera group. For example, the first and second cameras can both use a resolution of [720p, 800p] and a bitrate of [4Mbps, 6Mbps]. The third camera group can use a resolution of [720p, 1080p] and a bitrate of [4Mbps, 6Mbps].

[0145] In some implementations, as described above, the wireless operator-side data of the target vehicle may include: a threshold value corresponding to the application layer data of at least one sensor group. Then, for any sensor group, the first server may determine whether the application layer data of the sensor group is greater than the corresponding threshold value. If the application layer data of the sensor group is greater than the corresponding threshold value, the first server may take the left endpoint of the transmission parameter interval of the sensor group. If the application layer data of the sensor group is less than or equal to the corresponding threshold value, the first server may take the right endpoint of the transmission parameter interval of the sensor group.

[0146] For example, assuming that the at least one sensor group is the first, second, and third camera groups. If the first server determines to adjust the transmission parameters of at least one sensor group, the first server may determine a transmission parameter range for the at least one sensor group. For example, assuming that the first server determines that the resolution range corresponding to the first camera group is [720p, 1080p], and determines that the resolution ranges corresponding to the second and third camera groups are both [480p, 720p]. assuming that the first server determines that the packet loss rate corresponding to the first camera group is 5%, which is less than the 6% threshold corresponding to the packet loss rate, then the right endpoint of the target transmission parameters [720p, 1080p] for the first camera group is determined to be 1080p. assuming that the first server determines that the packet loss rate corresponding to the second camera group is 8%, which is greater than the 6% threshold corresponding to the packet loss rate, then the left endpoint of the target transmission parameters [480p, 720p] for the second camera group is determined to be 480p. Assume that the first server determines that the packet loss rate corresponding to the third group of cameras is 10%, which is greater than the threshold value of 6% corresponding to the packet loss rate, then the left endpoint of the target transmission parameter [480p, 720p] corresponding to the third group of cameras is determined to be 480p.

[0147] In summary, in the present application, the first server can directly determine the target transmission parameter of at least one sensor group; or the first server can directly determine the transmission parameter interval of at least one sensor group, and determine the target transmission parameter in the transmission parameter interval based on the application data of at least one sensor group; or the first server can directly determine the transmission parameter interval of at least one sensor group, and determine the target transmission parameter in the transmission parameter interval based on the application data of at least one sensor group and the wireless operator side data; or the first server can determine the target transmission parameter of at least one sensor group based on the status information of the target vehicle; or the first server can determine the transmission parameter interval of at least one sensor group based on the status information of the target vehicle, and determine the target transmission parameter in the transmission parameter interval based on the application data of at least one sensor group; or the first server can determine the transmission parameter interval of at least one sensor group based on the status information of the target vehicle, and determine the target transmission parameter in the transmission parameter interval based on the application data of at least one sensor group and the wireless operator side data. In this way, the accuracy of the target transmission parameter can be ensured, the normal operation of remote control can be guaranteed, and more autonomous driving vehicles can be deployed under limited network resources.

[0148] Figure 8 A schematic diagram of a server provided in an embodiment of the present application, the server may be as follows Figure 1 The server 120 shown or Figure 2 The first server 220 in, but not limited to, includes:

[0149] The prediction module 801 is used to predict the remaining capacity of the network to which the target vehicle belongs.

[0150] The judgment module 802 is configured to judge whether to adjust the transmission parameters of at least one sensor group on the target vehicle according to the remaining capacity of the network to which the target vehicle belongs.

[0151] The determination module 803 is configured to determine a target transmission parameter of the at least one sensor group if the judgment module determines to adjust the transmission parameter of the at least one sensor group.

[0152] The sending module 804 is configured to send the target transmission parameter of at least one sensor group to the target vehicle, so that the target vehicle adjusts the transmission parameter of the at least one sensor group to the corresponding target transmission parameter.

[0153] In some implementations, the server further includes a first acquisition module 805 configured to acquire application layer data of at least one sensor group. Accordingly, the prediction module 801 is specifically configured to predict the remaining capacity of the network to which the target vehicle belongs based on the application layer data of at least one sensor group.

[0154] In some implementations, a first mapping relationship exists between the combined data consisting of the application layer data of at least one sensor group and the remaining capacity of the network to which the target vehicle belongs. Accordingly, prediction module 801 is specifically configured to predict the remaining capacity of the network to which the target vehicle belongs based on the combined data consisting of the application layer data of at least one sensor group and the first mapping relationship.

[0155] In some implementations, the server further includes a second acquisition module 806 configured to acquire application layer data from at least one sensor group and data on the target vehicle from the wireless carrier. Accordingly, the prediction module 801 is specifically configured to predict the remaining capacity of the target vehicle's network based on the application layer data from the at least one sensor group and the data on the target vehicle from the wireless carrier.

[0156] In some implementations, the prediction module 801 is specifically configured to: predict a vehicle to be switched to in the target vehicle's network based on application layer data from at least one sensor group and data of the target vehicle on the wireless carrier side; predict the network capacity occupied by the vehicle to be switched to in the target vehicle's network; and calculate the sum of the current remaining capacity of the target vehicle's network and the network capacity occupied by the vehicle to be switched to obtain the remaining capacity of the target vehicle's network.

[0157] In some implementations, the wireless operator-side data includes a threshold value corresponding to application layer data of at least one sensor group. Prediction module 801 is specifically configured to: for any of all vehicles, if application layer data of at least one sensor group on the vehicle exceeds the corresponding threshold value, determine the vehicle as a vehicle to be switched.

[0158] In some implementations, the prediction module 801 is specifically configured to: predict the number of vehicles in operation on the target vehicle's network based on application layer data from at least one sensor packet and data of the target vehicle on the wireless carrier side; predict the network capacity occupied by the vehicles in operation on the target vehicle's network; and calculate the difference between the total capacity of the target vehicle's network and the network capacity occupied by the vehicles in operation to predict the remaining capacity of the target vehicle's network.

[0159] In some implementations, the wireless carrier-side data includes a threshold value corresponding to application layer data of at least one sensor group. Prediction module 801 is specifically configured to: determine that the first vehicle is in a running state if the application layer data of each sensor group on the first vehicle is less than or equal to the corresponding threshold value, where the first vehicle is any of all vehicles.

[0160] In some implementations, the judgment module 802 is specifically configured to: if the remaining capacity of the network to which the target vehicle belongs is less than or equal to a preset threshold, determine to adjust the transmission parameters of at least one sensor group.

[0161] In some implementations, the server further includes: a third acquisition module 807 for acquiring state information of the target vehicle. Accordingly, the determination module 803 is specifically configured to: determine target transmission parameters of at least one sensor group according to the state information of the target vehicle.

[0162] In some implementations, the server further includes a fourth acquisition module 808 configured to acquire application layer data of at least one sensor group. Accordingly, the determination module 803 is specifically configured to determine a transmission parameter interval corresponding to the at least one sensor group based on the target vehicle's status information. The target transmission parameter is determined within the transmission parameter interval corresponding to the first sensor group based on the application layer data of the first sensor group and the target vehicle's wireless carrier-side data. The first sensor group is any sensor group from the at least one sensor group.

[0163] In some implementations, the server further includes a fifth acquisition module 809 configured to acquire application layer data from at least one sensor group and wireless carrier-side data from the target vehicle. Accordingly, the determination module 803 is specifically configured to determine a transmission parameter interval corresponding to the at least one sensor group based on the target vehicle's status information. For each sensor group in the at least one sensor group, the target transmission parameter is determined within the transmission parameter interval corresponding to the sensor group based on the application layer data of the sensor group and the wireless carrier-side data from the target vehicle.

[0164] In some implementations, the server further includes: a receiving module 810, configured to receive data transmitted by a target vehicle according to target transmission parameters of at least one sensor group.

[0165] It should be understood that the device embodiment and the method embodiment may correspond to each other, and similar descriptions may refer to the method embodiment. To avoid repetition, they will not be described here. Specifically, Figure 8 The server shown can execute the above server-side method embodiment, and Figure 8 The aforementioned and other operations and / or functions of each module in the server shown are respectively for implementing the corresponding processes of the above-mentioned server-side method embodiment, and for the sake of brevity, they are not repeated here.

[0166] The above description of the method embodiment of the server side of the embodiment of the present application is described from the perspective of the functional module in conjunction with the accompanying drawings. It should be understood that the functional module can be implemented in the form of hardware, can be implemented by instructions in the form of software, and can also be implemented by a combination of hardware and software modules. Specifically, the steps of the method embodiment in the embodiment of the present application can be completed by the hardware integrated logic circuit and / or software instructions in the processor, and the steps of the method disclosed in the embodiment of the present application can be directly reflected as being executed by a hardware decoding processor, or can be executed by a combination of hardware and software modules in the decoding processor. Optionally, the software module can be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps in the above method embodiment in conjunction with its hardware.

[0167] Figure 9 A schematic diagram of an autonomous driving vehicle provided in an embodiment of the present application, the autonomous driving vehicle may be the target vehicle in the above method embodiment, but is not limited thereto, such as Figure 9 As shown, the autonomous driving vehicle includes:

[0168] The acquisition module 910 is used to obtain target transmission parameters of at least one sensor group of the autonomous driving vehicle.

[0169] The adjustment module 920 is configured to adjust the transmission parameters of at least one sensor group to corresponding target transmission parameters.

[0170] Among them, the target transmission parameter of at least one sensor group is the transmission parameter of at least one sensor group determined by adjusting the transmission parameter of at least one sensor group according to the remaining capacity of the network to which the autonomous driving vehicle belongs.

[0171] In some implementations, the server further includes: a transmission module 930, configured to transmit data to the server according to target transmission parameters of at least one sensor group.

[0172] It should be understood that the device embodiment and the method embodiment may correspond to each other, and similar descriptions may refer to the method embodiment. To avoid repetition, they will not be described here. Specifically, Figure 9 The autonomous driving vehicle shown can execute the above-mentioned method embodiment on the target vehicle side, and Figure 9 The aforementioned and other operations and / or functions of each module in the autonomous driving vehicle shown are respectively for implementing the corresponding processes in the method embodiment on the target vehicle side mentioned above. For the sake of brevity, they will not be repeated here.

[0173] The above describes the autonomous driving vehicle of the embodiment of the present application from the perspective of functional modules in conjunction with the accompanying drawings. It should be understood that the functional module can be implemented in hardware form, can be implemented by instructions in software form, or can be implemented by a combination of hardware and software modules. Specifically, the steps of the method embodiment in the embodiment of the present application can be completed by the hardware integrated logic circuit and / or software form instructions in the processor. The steps of the method disclosed in the embodiment of the present application can be directly embodied as being executed by a hardware decoding processor, or can be executed by a combination of hardware and software modules in the decoding processor. Optionally, the software module can be located in a mature storage medium in the art such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps in the above method embodiment in combination with its hardware.

[0174] Figure 10 1 is a schematic block diagram of an electronic device 1000 provided in an embodiment of the present application. The electronic device 1000 may be the aforementioned server or target vehicle, and the present application does not impose any limitation thereto.

[0175] like Figure 10 As shown, the electronic device 1000 may include:

[0176] The memory 1010 and the processor 1020 are configured to store computer programs and transmit the program code to the processor 1020. In other words, the processor 1020 can call and execute the computer program from the memory 1010 to implement the method in the embodiment of the present application.

[0177] For example, the processor 1020 may be configured to execute the above method embodiments according to instructions in the computer program.

[0178] In some embodiments of the present application, the processor 1020 may include but is not limited to:

[0179] General-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc.

[0180] In some embodiments of the present application, the memory 1010 includes but is not limited to:

[0181] Volatile memory and / or non-volatile memory. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus random access memory (DR RAM).

[0182] In some embodiments of the present application, the computer program may be divided into one or more modules, which are stored in the memory 1010 and executed by the processor 1020 to implement the method provided by the present application. The one or more modules may be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program in the electronic device.

[0183] like Figure 10 As shown, the electronic device may further include:

[0184] The transceiver 1030 may be connected to the processor 1020 or the memory 1010 .

[0185] The processor 1020 may control the transceiver 1030 to communicate with other devices. Specifically, the processor 1020 may send information or data to other devices or receive information or data sent by other devices. The transceiver 1030 may include a transmitter and a receiver. The transceiver 1030 may further include one or more antennas.

[0186] It should be understood that the various components in the electronic device are connected via a bus system, wherein the bus system includes not only a data bus but also a power bus, a control bus and a status signal bus.

[0187] The present application also provides a computer storage medium having a computer program stored thereon, which, when executed by a computer, enables the computer to perform the method of the above-mentioned method embodiment. In other words, the present application also provides a computer program product containing instructions, which, when executed by a computer, enables the computer to perform the method of the above-mentioned method embodiment.

[0188] When software is used for implementation, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a digital video disc (DVD)), or a semiconductor medium (e.g., a solid state drive (SSD)).

Claims

1. A method for adjusting sensor transmission parameters, characterized in that: include: Predict the remaining capacity of the network to which the target vehicle belongs; Determining whether to adjust transmission parameters of at least one sensor group on the target vehicle according to the remaining capacity of the network to which the target vehicle belongs; If it is determined to adjust the transmission parameter of the at least one sensor group, determining a target transmission parameter of the at least one sensor group; sending a target transmission parameter of the at least one sensor group to the target vehicle, so that the target vehicle adjusts the transmission parameter of the at least one sensor group to the corresponding target transmission parameter; Before determining the target transmission parameter of the at least one sensor group, the method further includes: Acquiring status information of the target vehicle and application layer data of the at least one sensor group; The determining of the target transmission parameter of the at least one sensor group comprises: determining, based on the state information of the target vehicle, a transmission parameter interval corresponding to the at least one sensor group; For any sensor group among the at least one sensor group, a target transmission parameter corresponding to the sensor group is determined in a transmission parameter interval corresponding to the sensor group according to application layer data of the sensor group.

2. The method according to claim 1, characterized in that Before predicting the remaining capacity of the network to which the target vehicle belongs, the method further includes: obtaining application layer data of the at least one sensor packet; The predicting of the remaining capacity of the network to which the target vehicle belongs includes: The remaining capacity of the network to which the target vehicle belongs is predicted based on the application layer data of the at least one sensor group.

3. The method according to claim 2, characterized in that There is a first mapping relationship between the joint data consisting of the application layer data of the at least one sensor group and the remaining capacity of the network to which the target vehicle belongs; The predicting, based on the application layer data of the at least one sensor group, the remaining capacity of the network to which the target vehicle belongs, comprises: The remaining capacity of the network to which the target vehicle belongs is predicted based on the joint data composed of the application layer data of the at least one sensor group and the first mapping relationship.

4. The method according to claim 1, wherein Before predicting the remaining capacity of the network to which the target vehicle belongs, the method further includes: Obtaining application layer data of the at least one sensor group and data of the target vehicle at a wireless operator side; The predicting of the remaining capacity of the network to which the target vehicle belongs includes: The remaining capacity of the network to which the target vehicle belongs is predicted based on the application layer data of the at least one sensor group and the data of the target vehicle at the wireless operator side.

5. The method according to claim 4, characterized in that The predicting, based on the application layer data of the at least one sensor group and the data of the target vehicle on the wireless operator side, of the remaining capacity of the network to which the target vehicle belongs includes: predicting a vehicle to be switched in a network to which the target vehicle belongs based on application layer data of the at least one sensor group and data of the target vehicle on a wireless operator side; Predicting the network capacity occupied by the vehicle to be switched in the network to which the target vehicle belongs; The sum of the current remaining capacity of the network to which the target vehicle belongs and the network capacity occupied by the vehicle to be switched is calculated to predict the remaining capacity of the network to which the target vehicle belongs.

6. The method according to claim 5, characterized in that The data on the wireless operator side includes a threshold value corresponding to the application layer data of the at least one sensor group; The determining, based on the application layer data of the at least one sensor group and the data of the target vehicle on the wireless operator side, a vehicle to be switched in the network to which the target vehicle belongs, includes: For any vehicle among all vehicles in the network to which the target vehicle belongs, if there is application layer data of at least one sensor group on the vehicle that is greater than a corresponding threshold value, the vehicle is determined to be a vehicle to be switched.

7. The method according to claim 4, characterized in that The predicting, based on the application layer data of the at least one sensor group and the data of the target vehicle on the wireless operator side, of the remaining capacity of the network to which the target vehicle belongs includes: predicting, based on the application layer data of the at least one sensor group and the data of the target vehicle on the wireless operator side, vehicles in a running state in the network to which the target vehicle belongs; Predicting the network capacity occupied by running vehicles in the network to which the target vehicle belongs; The difference between the total capacity of the network to which the target vehicle belongs and the network capacity occupied by the vehicles in operation is calculated to predict the remaining capacity of the network to which the target vehicle belongs.

8. The method according to claim 7, characterized in that The data on the wireless operator side includes a threshold value corresponding to the application layer data of the at least one sensor group; The predicting, based on the application layer data of the at least one sensor group and the data of the target vehicle on the wireless operator side, a vehicle in a running state in the network to which the target vehicle belongs, includes: If the application layer data of each sensor group on the first vehicle is less than or equal to the corresponding threshold value, it is determined that the first vehicle is a vehicle in a running state, and the first vehicle is any vehicle in all vehicles in the network to which the target vehicle belongs.

9. The method according to any one of claims 1 to 8, characterized in that The determining whether to adjust the transmission parameters of at least one sensor group on the target vehicle according to the remaining capacity of the network to which the target vehicle belongs includes: If the remaining capacity of the network to which the target vehicle belongs is less than or equal to a preset threshold, it is determined to adjust the transmission parameters of the at least one sensor group.

10. The method according to any one of claims 1 to 8, characterized in that Before determining, for any sensor group among the at least one sensor group, the target transmission parameter corresponding to the sensor group in the transmission parameter interval corresponding to the sensor group according to the application layer data of the sensor group, the method further includes: Acquiring data from a wireless operator of the target vehicle; The determining, for any sensor group among the at least one sensor group, a target transmission parameter corresponding to the sensor group in a transmission parameter interval corresponding to the sensor group according to application layer data of the sensor group, includes: The target transmission parameter corresponding to the sensor group is determined in the transmission parameter interval corresponding to the sensor group according to the application layer data of the sensor group and the data on the wireless operator side of the target vehicle.

11. The method according to any one of claims 1 to 8, characterized in that After sending the target transmission parameter of the at least one sensor group to the target vehicle, the method further includes: Receive data transmitted by the target vehicle according to the target transmission parameters of the at least one sensor group.

12. A method for adjusting sensor transmission parameters, characterized in that: include: obtaining target transmission parameters of at least one sensor group of a target vehicle; adjusting a transmission parameter of the at least one sensor group to a corresponding target transmission parameter; The target transmission parameter of the at least one sensor group is a transmission parameter of the at least one sensor group obtained by adjusting the transmission parameter of the at least one sensor group according to the remaining capacity of the network to which the target vehicle belongs; The target transmission parameter of the at least one sensor group is determined in the following manner: determining, based on the state information of the target vehicle, a transmission parameter interval corresponding to the at least one sensor group; For any sensor group among the at least one sensor group, a target transmission parameter corresponding to the sensor group is determined in a transmission parameter interval corresponding to the sensor group according to application layer data of the sensor group.

13. The method according to claim 12, characterized in that After adjusting the transmission parameter of the at least one sensor group to the corresponding target transmission parameter, the method further includes: Data is transmitted to the server according to the target transmission parameters of the at least one sensor group.

14. A server, characterized in that: include: A prediction module, used to predict the remaining capacity of the network to which the target vehicle belongs; a determination module, configured to determine whether to adjust a transmission parameter of at least one sensor group on the target vehicle according to a remaining capacity of a network to which the target vehicle belongs; a determining module, configured to determine a target transmission parameter of the at least one sensor group if the judging module determines to adjust the transmission parameter of the at least one sensor group; a sending module, configured to send the target transmission parameter of the at least one sensor group to the target vehicle, so that the target vehicle adjusts the transmission parameter of the at least one sensor group to the corresponding target transmission parameter; an acquisition module, configured to acquire the state information of the target vehicle and the application layer data of the at least one sensor group before the determination module determines the target transmission parameter of the at least one sensor group; The determining module is specifically configured to: determining, based on the state information of the target vehicle, a transmission parameter interval corresponding to the at least one sensor group; For any sensor group among the at least one sensor group, a target transmission parameter corresponding to the sensor group is determined in a transmission parameter interval corresponding to the sensor group according to application layer data of the sensor group.

15. An autonomous driving vehicle, characterized in that: include: an acquisition module, configured to acquire target transmission parameters of at least one sensor group of the autonomous driving vehicle; an adjusting module, configured to adjust the transmission parameters of the at least one sensor group to corresponding target transmission parameters; The target transmission parameter of the at least one sensor group is a transmission parameter of the at least one sensor group determined by adjusting the transmission parameter of the at least one sensor group according to the remaining capacity of the network to which the autonomous driving vehicle belongs; The target transmission parameter of the at least one sensor group is determined in the following manner: determining, based on the state information of the autonomous driving vehicle, a transmission parameter interval corresponding to the at least one sensor group; For any sensor group among the at least one sensor group, a target transmission parameter corresponding to the sensor group is determined in a transmission parameter interval corresponding to the sensor group according to application layer data of the sensor group.

16. A server, characterized in that: include: A processor and a memory, the memory being used to store a computer program, the processor being used to call and run the computer program stored in the memory to execute the method according to any one of claims 1 to 11.

17. An autonomous driving vehicle, characterized in that: include: A processor and a memory, the memory being used to store a computer program, the processor being used to call and run the computer program stored in the memory so as to enable the autonomous driving vehicle to execute the method according to any one of claims 12 to 13.

18. A computer-readable storage medium, characterized in that Used to store a computer program, wherein the computer program causes a computer to execute the method according to any one of claims 1 to 13.

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