Cloud service system-based vehicle management method and cloud service system

Abstract

The present application discloses a cloud service system-based vehicle management method and a cloud service system, which can reduce the cost of vehicle management to a certain extent. The method of the present application comprises: when a lessor needs to manage a plurality of vehicles thereof via a cloud, the lessor can send a vehicle management request for the plurality of vehicles to a cloud management platform; and the cloud management platform can create a cloud instance for managing the plurality of vehicles on the basis of the vehicle management request. When a first vehicle among the plurality of vehicles uploads first information to the cloud instance and a second vehicle uploads second information to the cloud instance, the cloud instance can determine, on the basis of the first information and the second information, that the first vehicle is an unmanned vehicle and the second vehicle is a manned vehicle, the first vehicle and the second vehicle travel in the same direction, and a distance between the first vehicle and the second vehicle is less than a preset distance, and then the cloud instance can control the first vehicle to travel to a target location located between the first vehicle and the second vehicle.

Description

A vehicle management method based on a cloud service system and the cloud service system

[0001] This application claims priority to Chinese Patent Application No. 202510233954.5, filed on February 27, 2025, entitled "A Vehicle Management Method Based on a Cloud Service System and a Cloud Service System", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of cloud technology, and in particular to a vehicle management method and a cloud service system based on a cloud service system. Background Technology

[0003] With the rapid development of computer technology, more and more users are choosing various computing devices to complete their own business operations. For example, in certain operational scenarios, tenants often need to use vehicle-side and roadside computing devices to manage vehicles in the actual working environment, so as to avoid mutual interference between vehicles and ensure that the user's business can be completed smoothly.

[0004] In related technologies, if there are manned and unmanned vehicles in a user's work environment, the unmanned vehicle can obtain information about various vehicles in the work environment through its own computing devices and roadside computing devices, and conduct comprehensive analysis of this information to determine the relative position between itself and the manned vehicles, thereby determining its own driving path to avoid collisions with the manned vehicles.

[0005] In the above process, if the road in the actual working environment is expanded or adjusted, users often need to deploy new roadside equipment for the expanded or adjusted road, resulting in high vehicle management costs. Summary of the Invention

[0006] This application provides a vehicle management method and a cloud service system based on a cloud service system. Tenants do not need to deploy roadside equipment in the operating environment of the vehicle, which can reduce the cost of vehicle management to a certain extent.

[0007] This application provides a vehicle management method based on a cloud service system. The cloud service system for implementing this method includes infrastructure that provides cloud services to tenants and a cloud management platform that manages the infrastructure. The method includes:

[0008] When a tenant needs to manage multiple vehicles using the cloud, the tenant can input the vehicle management request set by the tenant into the vehicle management interface provided by the cloud management platform. Therefore, the cloud management platform can receive the vehicle management request sent by the tenant through the vehicle management interface. The vehicle management request is used to indicate the multiple vehicles to be managed by the tenant.

[0009] Next, the cloud management platform can create cloud instances in the infrastructure to manage these multiple vehicles and establish communication connections between the cloud instances and these multiple vehicles.

[0010] Then, the first vehicle among these multiple vehicles can send a first message to the cloud instance, and the second vehicle among these multiple vehicles can send a second message to the cloud instance. The first vehicle is an unmanned vehicle, and the second vehicle is a manned vehicle.

[0011] Subsequently, based on the first and second information, the cloud instance can determine that the first vehicle and the second vehicle are traveling in the same direction and that the distance between the first vehicle and the second vehicle is less than a preset distance. Therefore, the cloud instance can determine that the first vehicle is following the second vehicle. Thus, the cloud management can determine the target location located between the first vehicle and the second vehicle and notify the first vehicle to travel to the target location to prevent a collision between the first vehicle and the second vehicle.

[0012] As can be seen from the above method, since the tenant can determine that the first vehicle is following the second vehicle based on the first vehicle's first information and the second vehicle's second information through the cloud instance in the cloud, in order to avoid a collision between the first vehicle and the second vehicle, the cloud instance can guide the first vehicle to a target location between the two vehicles so that the first vehicle and the second vehicle maintain a certain distance. Therefore, on the basis of avoiding a collision between the first vehicle and the second vehicle, the tenant does not need to deploy roadside equipment in the working environment where the first vehicle and the second vehicle are located, which can reduce the cost of vehicle management to a certain extent.

[0013] In one possible implementation, the first information includes a first identifier of a first vehicle, and the second information includes a second identifier of a second vehicle. The first identifier indicates that the first vehicle is an unmanned vehicle, and the second identifier indicates that the second vehicle is a manned vehicle. In the aforementioned implementation, the first information uploaded by the first vehicle may include the first identifier of the first vehicle, and the second information uploaded by the second vehicle may include the second identifier of the second vehicle. Therefore, the cloud instance can accurately determine that the first vehicle is an unmanned vehicle based on the first identifier and accurately determine that the second vehicle is a manned vehicle based on the second identifier.

[0014] In one possible implementation, the first information further includes the first predicted coordinates of the positioning device of the first vehicle in a preset reference coordinate system, and the second information further includes the second predicted coordinates of the positioning device of the second vehicle in the reference coordinate system. The cloud instance determines that the distance between the first vehicle and the second vehicle is less than a preset distance based on the first and second information, including: the cloud instance obtaining the distance between the first vehicle and the second vehicle based on the first and second predicted coordinates; and the cloud instance determining that the distance between the first vehicle and the second vehicle is less than the preset distance. In the aforementioned implementation, since the first information further includes the first predicted coordinates of the positioning device of the first vehicle in the preset reference coordinate system, and the second information further includes the second predicted coordinates of the positioning device of the second vehicle in the reference coordinate system, the cloud instance can calculate the distance between the first vehicle and the second vehicle based on the first and second predicted coordinates. After determining that the first vehicle and the second vehicle are traveling in the same direction, if the distance between the first vehicle and the second vehicle is less than the preset distance, the cloud instance can determine that the first vehicle is following the second vehicle. Therefore, this cloud instance can automatically identify the scenario where the first vehicle is following the second vehicle based on the first information of the first vehicle and the second information of the second vehicle it collects, and then control the driving of the first vehicle in this scenario, that is, guide the first vehicle to drive safely continuously.

[0015] In one possible implementation, the method further includes: a cloud instance receiving third information sent by a first vehicle and fourth information sent by a second vehicle, wherein the third information precedes the first information and the fourth information precedes the second information; the third information includes the third predicted coordinates of the positioning device of the first vehicle in a reference coordinate system, and the fourth information includes the fourth predicted coordinates of the positioning device of the second vehicle in the reference coordinate system; the cloud instance determines that the first vehicle and the second vehicle are traveling in the same direction based on the first, second, third, and fourth predicted coordinates. In the aforementioned implementation, before sending the first and second information, the first vehicle may also send the third information to the cloud instance, and the second vehicle may also send the fourth information to the cloud instance. The third information may include the third predicted coordinates of the positioning device of the first vehicle in the reference coordinate system, and the fourth information may include the fourth predicted coordinates of the positioning device of the second vehicle in the reference coordinate system. Based on this, after receiving the first, second, third, and fourth information, the cloud instance can obtain the first, second, third, and fourth predicted coordinates from these information, and thus the cloud instance can determine that the first vehicle and the second vehicle are traveling in the same direction using these predicted coordinates. Therefore, this cloud instance can accurately identify the scenario where the first vehicle is following the second vehicle based on the first and third information of the first vehicle and the second and fourth information of the second vehicle collected at different times. In this scenario, the instance can control the driving of the first vehicle and guide it to continue driving while ensuring safety, thereby ensuring the operational efficiency of the first vehicle and reducing unnecessary stops.

[0016] In one possible implementation, the cloud instance notifying the first vehicle to proceed to the target location includes: the cloud instance acquiring the lanes where the first and second vehicles are located, and projecting the second predicted coordinates onto the centerline of the lanes to obtain the fifth predicted coordinates; the cloud instance determining a sub-centerline between the first and second vehicles from the centerline; the cloud instance determining a sixth predicted coordinate on the sub-centerline based on the fifth predicted coordinates, wherein the sixth predicted coordinate is used as the target location; and the cloud instance notifying the first vehicle to proceed to the target location. In the aforementioned implementation, after determining that the first vehicle is following the second vehicle, the cloud instance can acquire the lane shared by the first and second vehicles, and project the second predicted coordinates onto the centerline of that lane to obtain the fifth predicted coordinates. Next, the cloud instance can select a sub-centerline between the edges of the first and second vehicles from the centerline. Then, the cloud instance can use the fifth predicted coordinates to select the sixth predicted coordinate from the sub-centerline as the target location. In this way, the cloud instance can notify the first vehicle to proceed to a target location with a certain level of safety to avoid collisions between the first and second vehicles during travel, thereby ensuring the normal operation of both vehicles.

[0017] In one possible implementation, the second information further includes the dimensions of the second vehicle, the position of the positioning device of the second vehicle within the second vehicle, the positioning accuracy of the second vehicle, and the safe distance between the two vehicles. The positioning accuracy indicates the difference between the second predicted coordinates and the actual coordinates of the second vehicle in the reference coordinate system. The cloud instance determines the sixth predicted coordinate located on the sub-centerline based on the fifth predicted coordinates by: the cloud instance determining the distance between the fifth and sixth predicted coordinates based on the dimensions, position, positioning accuracy, and safe distance; and the cloud instance determining the sixth predicted coordinate located on the sub-centerline based on the fifth predicted coordinates and the distance between the fifth and sixth predicted coordinates. In the aforementioned implementation, the second information uploaded by the second vehicle may also include the dimensions of the second vehicle, the position of the positioning device of the second vehicle within the second vehicle, the positioning accuracy of the second vehicle, and the safe distance between the two vehicles. After obtaining the fifth predicted coordinates, the cloud instance can use the dimensions of the second vehicle, the position of the positioning device of the second vehicle within the second vehicle, the positioning accuracy of the second vehicle, and the safe distance between the two vehicles to obtain the distance between the fifth and sixth predicted coordinates. Then, the cloud instance can use the fifth predicted coordinate and the distance between the fifth and sixth predicted coordinates to select the sixth predicted coordinate on the sub-center line, which is equivalent to accurately determining the target location to guide the first vehicle to the target location and ensure the driving safety between the first and second vehicles.

[0018] In one possible implementation, a cloud instance comprises a physical server, a virtual machine, a container, a microvirtual machine, or a bare metal server.

[0019] A second aspect of this application provides a cloud service system, which includes infrastructure for providing cloud services to tenants and a cloud management platform for managing the infrastructure. The cloud management platform is configured to receive vehicle management requests sent by tenants, wherein the vehicle management requests are used to instruct multiple vehicles belonging to the tenants. The cloud management platform is further configured to create a cloud instance in the infrastructure for managing the multiple vehicles based on the vehicle management requests. The cloud instance is configured to receive first information sent by a first vehicle and second information sent by a second vehicle among the multiple vehicles, wherein the first vehicle and the second vehicle are traveling in the same direction, the first vehicle is an unmanned vehicle, and the second vehicle is a manned vehicle. The cloud instance is further configured to determine, based on the first information and the second information, that the distance between the first vehicle and the second vehicle is less than a preset distance, and then notify the first vehicle to travel to a target location, wherein the target location is located between the first vehicle and the second vehicle.

[0020] In one possible implementation, the first information includes a first identifier of a first vehicle, and the second information includes a second identifier of a second vehicle, wherein the first identifier indicates that the first vehicle is an unmanned vehicle, and the second identifier indicates that the second vehicle is a manned vehicle.

[0021] In one possible implementation, the first information further includes the first predicted coordinates of the positioning device of the first vehicle in a preset reference coordinate system, and the second information further includes the second predicted coordinates of the positioning device of the second vehicle in the reference coordinate system. The cloud instance is used to obtain the distance between the first vehicle and the second vehicle based on the first predicted coordinates and the second predicted coordinates; the cloud instance determines that the distance between the first vehicle and the second vehicle is less than a preset distance.

[0022] In one possible implementation, the cloud instance is further configured to receive third information sent by the first vehicle and fourth information sent by the second vehicle, wherein the third information precedes the first information and the fourth information precedes the second information; the third information includes the third predicted coordinates of the positioning device of the first vehicle in the reference coordinate system, and the fourth information includes the fourth predicted coordinates of the positioning device of the second vehicle in the reference coordinate system; the cloud instance is further configured to determine, based on the first predicted coordinates, the second predicted coordinates, the third predicted coordinates, and the fourth predicted coordinates, that the first vehicle and the second vehicle are traveling in the same direction.

[0023] In one possible implementation, the cloud instance is used to: obtain the lanes where the first vehicle and the second vehicle are located, and project the second predicted coordinates onto the centerline of the lane to obtain the fifth predicted coordinates; determine a sub-centerline located between the first vehicle and the second vehicle from the centerline; determine a sixth predicted coordinate located on the sub-centerline based on the fifth predicted coordinates, wherein the sixth predicted coordinates are used as the target location; and notify the first vehicle to drive to the target location.

[0024] In one possible implementation, the second information further includes the size of the second vehicle, the position of the positioning device of the second vehicle within the second vehicle, the positioning accuracy of the second vehicle, and the safe distance between the two vehicles, wherein the positioning accuracy is used to indicate the difference between the second predicted coordinates and the actual coordinates of the second vehicle in the reference coordinate system; and a cloud instance is used to: determine the distance between the fifth predicted coordinates and the sixth predicted coordinates based on the size, position, positioning accuracy, and safe distance; and determine the sixth predicted coordinate located on the sub-centerline based on the fifth predicted coordinates and the distance between the fifth predicted coordinates and the sixth predicted coordinates.

[0025] In one possible implementation, a cloud instance comprises a physical server, a virtual machine, a container, a microvirtual machine, or a bare metal server.

[0026] A third aspect of this application provides a computing device cluster, which includes at least one computing device, each computing device including a processor and a memory: the memory is used to store instructions; the processor is used to cause the computing device cluster to perform the method described in the first aspect or any possible implementation of the first aspect according to the instructions.

[0027] A fourth aspect of this application provides a computer storage medium storing one or more instructions that, when executed by one or more computers, cause the one or more computers to perform the method described in the first aspect or any possible implementation of the first aspect.

[0028] A fifth aspect of this application provides a computer program product storing instructions that, when executed by a computer, cause the computer to perform the method described in the first aspect or any possible implementation of the first aspect.

[0029] In this embodiment, when a tenant needs to manage multiple vehicles via the cloud, the tenant can send vehicle management requests for these vehicles to the vehicle management interface provided by the cloud management platform. Based on the vehicle management request, the cloud management platform can create a cloud instance for managing the multiple vehicles. When the first vehicle uploads first information to the cloud instance and the second vehicle uploads second information to the cloud instance, the cloud instance can determine, based on the first and second information, that the first vehicle is an unmanned vehicle and the second vehicle is a manned vehicle. If the first and second vehicles are traveling in the same direction and the distance between the first and second vehicles is less than a preset distance, the cloud instance can control the first vehicle to travel to the target location located between the first and second vehicles. In the aforementioned process, since the tenant can determine that the first vehicle is following the second vehicle based on the first information of the first vehicle and the second information of the second vehicle through the cloud instance in the cloud, in order to avoid the collision between the first vehicle and the second vehicle, the cloud instance can guide the first vehicle to drive to the target location between the two vehicles so that the first vehicle and the second vehicle maintain a certain distance. Therefore, on the basis of avoiding the collision between the first vehicle and the second vehicle, the tenant does not need to deploy roadside equipment in the working environment where the first vehicle and the second vehicle are located, which can reduce the cost of vehicle management to a certain extent. Attached Figure Description

[0030] Figure 1 is a schematic diagram of a cloud service system provided in an embodiment of this application;

[0031] Figure 2 is a flowchart illustrating a vehicle management method based on a cloud service system provided in an embodiment of this application.

[0032] Figure 3 is another structural schematic diagram of the cloud service system provided in the embodiment of this application;

[0033] Figure 4 is a schematic diagram of determining a target location according to an embodiment of this application;

[0034] Figure 5 is a schematic diagram of the structure of a cloud management platform provided in an embodiment of this application;

[0035] Figure 6 is a schematic diagram of a computing device provided in an embodiment of this application;

[0036] Figure 7 is a schematic diagram of a computing device cluster provided in an embodiment of this application;

[0037] Figure 8 is a schematic diagram of computer devices in a computer cluster connected via a network according to an embodiment of this application. Detailed Implementation

[0038] This application provides a vehicle management method and a cloud service system based on a cloud service system. Tenants do not need to deploy roadside equipment in the operating environment of the vehicle, which can reduce the cost of vehicle management to a certain extent.

[0039] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such terms are interchangeable where appropriate; this is merely a way of distinguishing objects with the same attributes in the embodiments of this application. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, so that a process, method, system, product, or apparatus that comprises a series of elements is not necessarily limited to those elements, but may include other elements not explicitly listed or inherent to those processes, methods, products, or apparatuses.

[0040] With the rapid development of computer technology, more and more users are choosing various computing devices to complete their own business operations. For example, in certain operational scenarios, tenants often need to use vehicle-side and roadside computing devices to manage vehicles in the actual working environment, so as to avoid mutual interference between vehicles and ensure that the user's business can be completed smoothly.

[0041] In related technologies, if a user's work environment contains both manned and unmanned vehicles, the unmanned vehicle can first collect information about the vehicles around it using its own computing devices (e.g., information about other unmanned vehicles around it and information about manned vehicles around it), and then obtain information about various vehicles collected by the roadside computing devices (e.g., information about unmanned vehicles around the roadside equipment and information about manned vehicles around the roadside equipment) to comprehensively analyze this information, thereby determining the relative position between itself and the manned vehicles, and thus determining its own driving path to avoid collisions with manned vehicles.

[0042] In the above process, if the road in the actual working environment is expanded or adjusted, users often need to deploy new roadside equipment for the expanded or adjusted road, resulting in high vehicle management costs.

[0043] Furthermore, the roads in actual operating environments are often irregular, requiring users to deploy a large number of roadside devices, which also leads to higher vehicle management costs.

[0044] To address the aforementioned problems, this application provides a vehicle management method based on a cloud service system. This method can be implemented through a cloud service system. Figure 1 is a schematic diagram of the structure of the cloud service system provided in this application embodiment. As shown in Figure 1, the cloud service system includes infrastructure that can provide cloud services and a cloud management platform that manages this infrastructure. The cloud management platform and the infrastructure are described in detail below:

[0045] A cloud management platform can centrally manage the infrastructure of the entire cloud service system (e.g., within the infrastructure, creating cloud instances to provide cloud storage services to a tenant, which can then be used to manage multiple vehicles of that tenant, etc.). The cloud management platform can also be open to tenants outside the cloud service system and respond to their requests. For example, the cloud management platform can provide various interfaces, such as login and vehicle management interfaces, for tenant clients (e.g., the terminal devices used by the tenant or the browsers on those devices) to access. Specifically, the cloud management platform can authenticate a tenant's client through the login interface, allowing the client to log in after successful authentication. Similarly, the cloud management platform can also allow a tenant's client to send vehicle management requests, configured by the tenant, to the cloud management platform for multiple vehicles, based on which the platform can create cloud instances to manage those vehicles. When one of the multiple vehicles, both an unmanned vehicle and a manned vehicle, can upload information to the cloud instance, the cloud instance can determine based on this information that the unmanned vehicle and the manned vehicle are traveling in the same direction and that the distance between the unmanned vehicle and the manned vehicle is less than a preset distance. Then, the cloud instance can control the unmanned vehicle to travel to the target location located between the unmanned vehicle and the manned vehicle.

[0046] The infrastructure comprises multiple cloud instances that provide cloud services to tenants. Each of these cloud instances occupies a certain amount of computing resources (e.g., central processing unit (CPU) and graphics processing unit (GPU), storage resources (e.g., memory and disk), and network resources (e.g., network interface cards). Therefore, these multiple cloud instances of the cloud service system possess a large number of resources, providing tenants with high-quality vehicle management capabilities to meet their vehicle management needs.

[0047] Furthermore, for multiple cloud instances that can provide cloud services to tenants, these cloud instances can be presented in various ways. For example, these cloud instances can be physical servers selected by the cloud management platform, bare metal servers selected by the cloud management platform, virtual machines (VMs) created by the cloud management platform on physical servers using virtualization technology, containers (Docker) created by the cloud management platform on physical servers using virtualization technology, micro VMs created by the cloud management platform on physical servers using virtualization technology, and so on.

[0048] Furthermore, for multiple cloud instances that can provide cloud services to tenants, these cloud instances can be deployed in the same site or different sites. Sites can be presented in various forms, such as a region in the infrastructure, an availability zone in the infrastructure, a data center (DC) in the infrastructure, a room in the infrastructure, a rack in the infrastructure, and so on.

[0049] Based on the aforementioned cloud service system, when a tenant needs to manage multiple vehicles via the cloud, the tenant can send vehicle management requests for these vehicles to the vehicle management interface provided by the cloud management platform. Based on these vehicle management requests, the cloud management platform can create cloud instances for managing multiple vehicles. When one of these vehicles (both driverless and manned) uploads information to the cloud instance, the cloud instance can determine, based on this information, that the driverless and manned vehicles are traveling in the same direction and that the distance between them is less than a preset distance. Then, the cloud instance controls the driverless vehicle to travel to the target location located between the driverless and manned vehicles. In the aforementioned process, since the tenant can determine that the autonomous vehicle is following the manned vehicle based on the information of the autonomous vehicle and the manned vehicle through a cloud instance in the cloud, in order to avoid a collision between the autonomous vehicle and the manned vehicle, the cloud instance can guide the autonomous vehicle to a target location between the two, so that the autonomous vehicle and the manned vehicle maintain a certain distance. Therefore, based on the premise that a collision between the autonomous vehicle and the manned vehicle can be avoided, the tenant does not need to deploy roadside equipment in the operating environment where the autonomous vehicle and the manned vehicle are located, which can reduce the cost of vehicle management to a certain extent. In order to further understand the workflow of the cloud service system, the workflow will be further described below with reference to Figure 2. Figure 2 is a flowchart of a vehicle management method based on a cloud service system provided in the embodiment of this application. As shown in Figure 2, the method can be implemented through the cloud service system shown in Figure 1. The cloud service system includes infrastructure that provides cloud services to tenants and a cloud management platform that manages the infrastructure. The method includes:

[0050] 201. The cloud management platform receives a vehicle management request sent by a tenant, wherein the vehicle management request is used to indicate multiple vehicles of the tenant.

[0051] In this embodiment, when a tenant needs to manage multiple vehicles via the cloud, the cloud management platform can provide a vehicle management interface to the tenant's client (e.g., a vehicle management section on the tenant's interface). The tenant can then input vehicle management requests set by themselves into the vehicle management interface through their client. In this way, the cloud management platform can receive the vehicle management requests sent by the tenant's client through the vehicle management interface, whereby the vehicle management requests indicate the multiple vehicles to be managed by the tenant.

[0052] For example, in an open-pit mine scenario, when a tenant needs to manage multiple vehicles, these vehicles may include several manned vehicles (including manned patrol cars and engineering vehicles, etc.) and several unmanned vehicles (unmanned water trucks, transport vehicles, road rollers, and bulldozers, etc.). The tenant can log in to the cloud management platform, which provides a tenant interface. The tenant interface includes a vehicle management section, so the tenant can enter vehicle management requests into the vehicle management section. The vehicle management request may include the operating scenario of the tenant's multiple vehicles, the type of multiple vehicles, the number of multiple vehicles, and the identification of multiple vehicles, etc. Therefore, the vehicle management request indicates that the tenant needs the cloud to manage these multiple vehicles on their behalf.

[0053] In this way, the cloud management platform can receive vehicle management requests sent by tenants through the vehicle management section.

[0054] 202. Based on vehicle management requests, the cloud management platform creates cloud instances in the infrastructure to manage multiple vehicles.

[0055] Upon receiving a vehicle management request, the cloud management platform can determine that the tenant needs to manage multiple vehicles. Therefore, the cloud management platform can create cloud instances in the infrastructure to manage these multiple vehicles and establish communication connections between the cloud instances and these multiple vehicles. In this way, the cloud instances and these multiple vehicles can communicate with each other, thus enabling vehicle-cloud collaboration.

[0056] As in the example above, as shown in Figure 3 (Figure 3 is another structural schematic diagram of the cloud service system provided in the embodiment of this application), after receiving a vehicle management request, the cloud management platform can select one of the physical servers from the multiple physical servers of the infrastructure, create a virtual machine on the physical server for managing multiple vehicles of the tenant, and then build a communication connection between the virtual machine and these multiple vehicles.

[0057] 203. The cloud instance receives a first message sent by the first vehicle among multiple vehicles and a second message sent by the second vehicle among multiple vehicles. The first vehicle and the second vehicle are traveling in the same direction. The first vehicle is an unmanned vehicle and the second vehicle is a manned vehicle.

[0058] Since these multiple vehicles have established communication connections with the cloud instance, they can continuously send information to the cloud instance. Suppose that at the current moment, the first vehicle among these multiple vehicles can send a first message to the cloud instance, and the second vehicle among these multiple vehicles can send a second message to the cloud instance. Here, the first vehicle is an unmanned vehicle, and the second vehicle is a manned vehicle.

[0059] Specifically, the first and second information can be presented in the following ways:

[0060] (1) The first information may include the first identifier of the first vehicle and the first predicted coordinates of the positioning device of the first vehicle in a preset reference coordinate system, wherein the first identifier is used to indicate that the first vehicle is an unmanned vehicle, and the first predicted coordinates can be collected in real time by the positioning device of the first vehicle. It should be noted that the reference coordinate system may also be the working environment coordinate system, map coordinate system, or earth coordinate system, etc., which is based on the working environment where the first vehicle and the second vehicle are located.

[0061] (2) The second information may include the second identifier of the second vehicle and the second predicted coordinates of the positioning device of the second vehicle in the reference coordinate system. The second identifier is used to indicate that the second vehicle is a manned vehicle, and the second predicted coordinates can be collected in real time by the positioning device of the second vehicle. It should be noted that since the first identifier and the second identifier indicate different types of vehicles, the first identifier and the second identifier are usually different types of data.

[0062] Continuing with the example above, among these multiple vehicles, assume that driverless vehicle 1 and manned vehicle 2 are traveling in the same lane. At the current moment, driverless vehicle 1 can send information 1 to the virtual machine, and manned vehicle 2 can send information 2 to the virtual machine. Information 1 includes an identifier 1 indicating the driverless vehicle and the predicted coordinates 1 of the driverless vehicle 1's positioning device in the reference coordinate system. Information 2 includes an identifier 2 of the manned vehicle and the predicted coordinates 2 of the driverless vehicle 2's positioning device in the reference coordinate system.

[0063] 204. If the cloud instance determines, based on the first information and the second information, that the distance between the first vehicle and the second vehicle is less than a preset distance, it will notify the first vehicle to drive to the target location, wherein the target location is located between the first vehicle and the second vehicle.

[0064] After obtaining the first and second information, the cloud instance can perform a comprehensive analysis based on the first and second information. It can determine that the first vehicle and the second vehicle are traveling in the same direction and that the distance between the first vehicle and the second vehicle is less than a preset distance (the size of this distance can be set according to actual needs and is not limited here). The cloud instance can determine that the first vehicle is following the second vehicle, then determine the target location located between the first vehicle and the second vehicle, and notify the first vehicle to drive to the target location to prevent the first vehicle and the second vehicle from colliding.

[0065] Specifically, the cloud instance can determine that the first vehicle and the second vehicle are traveling in the same direction by:

[0066] Suppose that at some point before the current time, the first vehicle can send a third piece of information to the cloud instance, and the second vehicle can send a fourth piece of information to the cloud instance. The third piece of information may include the first vehicle's first identifier and the third predicted coordinates of the first vehicle's positioning device in the reference coordinate system, and the fourth piece of information may include the second vehicle's second identifier and the fourth predicted coordinates of the second vehicle's positioning device in the reference coordinate system.

[0067] Therefore, after receiving the first, second, third, and fourth information, the cloud instance can parse this information to obtain the first, second, third, and fourth predicted coordinates. Thus, the cloud instance can determine the trajectory of the first vehicle based on the first and third predicted coordinates, and determine the trajectory of the second vehicle based on the second and fourth predicted coordinates. If the trajectories of the first and second vehicles are similar or identical, the cloud instance can determine that the first and second vehicles are traveling in the same direction.

[0068] As in the example above, at some point before the current time, the driverless vehicle 1 can send information 3 to the virtual machine, and the manned vehicle 2 can send information 4 to the virtual machine. Information 3 includes an identifier 1 for the driverless vehicle and the predicted coordinates 3 of the positioning device of the driverless vehicle 1 in the reference coordinate system. Information 4 includes an identifier 2 of the manned vehicle and the predicted coordinates 4 of the positioning device of the driverless vehicle 2 in the reference coordinate system.

[0069] The virtual machine receives information 1, information 2, information 3, and information 4 (and may even include information previously sent by vehicle 1 and vehicle 2, which will not be elaborated here). It can then parse this information to obtain predicted coordinates 1, 2, 3, and 4. Therefore, the virtual machine can determine the trajectory of the unmanned vehicle 1 based on predicted coordinates 1 and 3 (and may even include more predicted coordinates previously collected by vehicle 1's positioning device, which will not be elaborated here), and determine the trajectory of the manned vehicle 2 based on predicted coordinates 2 and 4 (and may even include more predicted coordinates previously collected by vehicle 2's positioning device, which will not be elaborated here). If the trajectories of vehicle 1 and vehicle 2 are similar or identical, the virtual machine can determine that vehicle 1 and vehicle 2 are traveling in the same direction.

[0070] More specifically, the cloud instance can determine that the distance between the first vehicle and the second vehicle is less than a preset distance by:

[0071] After parsing the first and second information to obtain the first and second predicted coordinates, the cloud instance can calculate the distance between the first vehicle and the second vehicle based on these coordinates. Since the cloud instance has determined that the first and second vehicles are traveling in the same direction, it can detect whether the distance between them is less than a preset distance. If the distance is less than the preset distance, the cloud instance can determine that the first vehicle is following the second vehicle.

[0072] As in the example above, after determining that vehicle 1 and vehicle 2 are traveling in the same direction, the virtual machine can also calculate the distance between vehicle 1 and vehicle 2 based on predicted coordinates 1 and predicted coordinates 2, and detect the difference between the distance and the preset distance. If the distance is less than the preset distance, it means that vehicle 1 is following vehicle 2.

[0073] More specifically, the cloud instance can guide the first vehicle to the target location in the following ways:

[0074] After determining that the distance between the first and second vehicles is less than a preset distance, the cloud instance can obtain the lane shared by the first and second vehicles through its built-in high-precision map, and project the second predicted coordinates onto the centerline of that lane to obtain the fifth predicted coordinates. Next, the cloud instance can select a sub-centerline located between the edges of the first and second vehicles from the centerline. Then, using the fifth predicted coordinates as a reference point, the cloud instance can select one point from the sub-centerline as the sixth predicted coordinate, which can then be used as the target location. In this way, the cloud instance can issue a driving request to the first vehicle, guiding it to the target location.

[0075] More specifically, the cloud instance can determine the target location in the following ways:

[0076] The second information provided by the second vehicle to the cloud instance may also include the size of the second vehicle, the position of the second vehicle's positioning device within the second vehicle, the positioning accuracy of the second vehicle, and the safe distance between the two vehicles (the size of this safe distance can be set according to actual needs and is not limited here). It should be noted that the size of the second vehicle can refer to its length, the position of the second vehicle's positioning device within the second vehicle can be the coordinates of the second vehicle's positioning device in a vehicle coordinate system built around the second vehicle, and the positioning accuracy of the second vehicle is the accuracy of the second vehicle's positioning device, which indicates the difference between the second predicted coordinates collected by the positioning device and the actual coordinates of the second vehicle in the reference coordinate system.

[0077] After obtaining the fifth predicted coordinate, the cloud instance can use the size of the second vehicle, the position of the second vehicle's positioning device within the second vehicle, the positioning accuracy of the second vehicle, and the safe distance between the two vehicles to perform a comprehensive calculation, thereby obtaining the distance between the fifth and sixth predicted coordinates.

[0078] Then, the cloud instance can use the fifth predicted coordinate as a reference point, and select a point on the sub-center line as the sixth predicted coordinate based on the distance between the fifth and sixth predicted coordinates, which is equivalent to determining the target location.

[0079] As in the example above, as shown in Figure 4 (Figure 4 is a schematic diagram of determining the target location provided in the embodiment of this application), after determining that vehicle 1 is following vehicle 2, the virtual machine can determine the predicted coordinates 2 of the positioning device of vehicle 2 in the reference coordinate system (i.e., point P1 in Figure 4) based on information 2, and obtain the lanes where vehicle 1 and vehicle 2 are located from the high-precision map, and project the predicted coordinates 2 onto the center line of the lane, thereby obtaining the predicted coordinates 5 (i.e., point P2 in Figure 4).

[0080] Next, the virtual machine can determine a sub-centerline from the centerline, located between the front edge of vehicle 1 and the rear edge of vehicle 2. Then, based on the length of vehicle 2 in information 2, the position of the positioning device in vehicle 2, the accuracy of the positioning device, and the safe distance between the two vehicles, the virtual machine can determine the distance between predicted coordinates 6 (i.e., point P3 in Figure 4) and predicted coordinates 5. Subsequently, based on this distance, the virtual machine can determine predicted coordinates 6 from the sub-centerline and use predicted coordinates 6 as the target location. In this way, the virtual machine can issue a driving request to vehicle 1 to indicate the target location, so that vehicle 1 can drive to the target location based on the driving request.

[0081] It should be understood that in this embodiment, since the first vehicle and the second vehicle continuously upload information to the cloud instance (e.g., the aforementioned first, second, third, and fourth information), the cloud instance can also continuously issue driving requests to the first vehicle, i.e., continuously update the target location. It should be noted that the frequency with which the first vehicle and the second vehicle upload information to the cloud instance is usually higher than the frequency with which the cloud instance issues driving requests to the first vehicle. In other words, the cloud instance will only issue a driving request to the first vehicle once for every several times that the first vehicle and the second vehicle upload information to the cloud instance.

[0082] It should also be understood that in this embodiment, once the second vehicle stops uploading information to the cloud instance, the cloud instance will no longer issue driving requests to the first vehicle. That is, the cloud instance will no longer update the target location to the first vehicle. Therefore, the first vehicle will eventually stop at the target location indicated by the driving request it most recently received, so that the first vehicle will no longer follow the second vehicle.

[0083] In this embodiment, when a tenant needs to manage multiple vehicles via the cloud, the tenant can send vehicle management requests for these vehicles to the vehicle management interface provided by the cloud management platform. Based on the vehicle management request, the cloud management platform can create a cloud instance for managing the multiple vehicles. When the first vehicle uploads first information to the cloud instance and the second vehicle uploads second information to the cloud instance, the cloud instance can determine, based on the first and second information, that the first vehicle is an unmanned vehicle and the second vehicle is a manned vehicle. If the first and second vehicles are traveling in the same direction and the distance between the first and second vehicles is less than a preset distance, the cloud instance can control the first vehicle to travel to the target location located between the first and second vehicles. In the aforementioned process, since the tenant can determine that the first vehicle is following the second vehicle based on the first information of the first vehicle and the second information of the second vehicle through the cloud instance in the cloud, in order to avoid the collision between the first vehicle and the second vehicle, the cloud instance can guide the first vehicle to drive to the target location between the two vehicles so that the first vehicle and the second vehicle maintain a certain distance. Therefore, on the basis of avoiding the collision between the first vehicle and the second vehicle, the tenant does not need to deploy roadside equipment in the working environment where the first vehicle and the second vehicle are located, which can reduce the cost of vehicle management to a certain extent.

[0084] Furthermore, in this embodiment of the application, the cloud instance can automatically identify the scenario in which the first vehicle is following the second vehicle based on the first information of the first vehicle and the second information of the second vehicle it collects, and perform driving control on the first vehicle in this scenario. Under the premise of ensuring safety, the cloud instance guides the first vehicle to continue driving, thereby ensuring the operating efficiency of the first vehicle and reducing unnecessary stops.

[0085] Furthermore, in this embodiment, since the first vehicle and the second vehicle can continuously upload information to the cloud instance, the cloud instance can issue driving requests to the first vehicle at a certain frequency to update the target location. This can continuously guide the first vehicle to drive safely, thereby ensuring the driving continuity of the first vehicle.

[0086] Furthermore, in this embodiment, if the second vehicle stops uploading information to the cloud instance under certain circumstances (e.g., the positioning device of the second vehicle malfunctions or the second vehicle disconnects from the cloud instance), the cloud instance will no longer update the target location to the first vehicle. This allows the first vehicle to stop at the target location most recently issued by the cloud instance, thus ensuring that the first vehicle will not collide with the second vehicle when the second vehicle malfunctions.

[0087] The above is a detailed description of the vehicle management method based on a cloud service system provided in the embodiments of this application. The following will introduce the cloud management platform provided in the embodiments of this application. Figure 5 is a structural schematic diagram of the cloud management platform provided in the embodiments of this application. As shown in Figure 5, the cloud management platform is set up in the cloud service system, which also includes infrastructure providing cloud services to tenants. The cloud management platform is used to manage the infrastructure. The cloud management platform includes:

[0088] The receiving module 501 is used to receive a vehicle management request sent by a tenant, wherein the vehicle management request is used to indicate multiple vehicles of the tenant; for example, the receiving module 501 is used to implement step 201 in the embodiment shown in FIG2.

[0089] The creation module 502 is also used to create a cloud instance in the infrastructure for managing multiple vehicles based on a vehicle management request; for example, the creation module 502 is used to implement step 202 in the embodiment shown in Figure 2.

[0090] The cloud instance is used to: receive first information sent by a first vehicle among multiple vehicles and second information sent by a second vehicle among multiple vehicles, wherein the first and second vehicles are traveling in the same direction, the first vehicle is an unmanned vehicle, and the second vehicle is a manned vehicle; based on the first and second information, if it is determined that the distance between the first and second vehicles is less than a preset distance, the first vehicle is notified to proceed to a target location, wherein the target location is located between the first and second vehicles. For example, the cloud instance is used to implement steps 203 and 204 in the embodiment shown in Figure 2.

[0091] In one possible implementation, the first information includes a first identifier of a first vehicle, and the second information includes a second identifier of a second vehicle, wherein the first identifier indicates that the first vehicle is an unmanned vehicle, and the second identifier indicates that the second vehicle is a manned vehicle.

[0092] In one possible implementation, the first information further includes the first predicted coordinates of the positioning device of the first vehicle in a preset reference coordinate system, and the second information further includes the second predicted coordinates of the positioning device of the second vehicle in the reference coordinate system. The cloud instance is used to obtain the distance between the first vehicle and the second vehicle based on the first predicted coordinates and the second predicted coordinates; the cloud instance determines that the distance between the first vehicle and the second vehicle is less than a preset distance.

[0093] In one possible implementation, the cloud instance is further configured to receive third information sent by the first vehicle and fourth information sent by the second vehicle, wherein the third information precedes the first information and the fourth information precedes the second information; the third information includes the third predicted coordinates of the positioning device of the first vehicle in the reference coordinate system, and the fourth information includes the fourth predicted coordinates of the positioning device of the second vehicle in the reference coordinate system; the cloud instance is further configured to determine, based on the first predicted coordinates, the second predicted coordinates, the third predicted coordinates, and the fourth predicted coordinates, that the first vehicle and the second vehicle are traveling in the same direction.

[0094] In one possible implementation, the cloud instance is used to: obtain the lanes where the first vehicle and the second vehicle are located, and project the second predicted coordinates onto the centerline of the lane to obtain the fifth predicted coordinates; determine a sub-centerline located between the first vehicle and the second vehicle from the centerline; determine a sixth predicted coordinate located on the sub-centerline based on the fifth predicted coordinates, wherein the sixth predicted coordinates are used as the target location; and notify the first vehicle to drive to the target location.

[0095] In one possible implementation, the second information further includes the size of the second vehicle, the position of the positioning device of the second vehicle within the second vehicle, the positioning accuracy of the second vehicle, and the safe distance between the two vehicles, wherein the positioning accuracy is used to indicate the difference between the second predicted coordinates and the actual coordinates of the second vehicle in the reference coordinate system; and a cloud instance is used to: determine the distance between the fifth predicted coordinates and the sixth predicted coordinates based on the size, position, positioning accuracy, and safe distance; and determine the sixth predicted coordinate located on the sub-centerline based on the fifth predicted coordinates and the distance between the fifth predicted coordinates and the sixth predicted coordinates.

[0096] In one possible implementation, a cloud instance comprises a physical server, a virtual machine, a container, a microvirtual machine, or a bare metal server.

[0097] It should be noted that the information interaction and implementation process between the modules / units of the above-mentioned device are based on the same concept as the method embodiments of this application, and the resulting technical effects are the same as those of the method embodiments of this application. For details, please refer to the description in the method embodiments shown above in the embodiments of this application, and will not be repeated here.

[0098] Please refer to Figure 6, which is a schematic diagram of a computing device provided in an embodiment of this application. As shown in Figure 6, the computing device 600 (which can be used to present the aforementioned cloud management platform or cloud instance, and will be described in the following description as a cloud management platform) includes: a processor 601, a memory 602, a communication interface 603, and a bus 604. The processor 601, the memory 602, and the communication interface 603 are coupled through the bus 604. The memory 602 stores instructions. When the execution instructions in the memory 602 are executed, the computing device 600 executes the method executed by the cloud management platform in the above method embodiment.

[0099] The computing device 600 may be one or more integrated circuits configured to implement the methods described above, such as: one or more application-specific integrated circuits (ASICs), or one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs), or a combination of at least two of these forms of integrated circuits. Furthermore, when the units in the device can be implemented in the form of a processing element scheduler, the processing element may be a general-purpose processor, such as a central processing unit (CPU) or other processor capable of calling programs. Alternatively, these units may be integrated together to implement a system-on-a-chip (SOC).

[0100] Processor 601 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor may be a microprocessor or any conventional processor.

[0101] Memory 602 can be volatile memory or non-volatile memory, or may include both. The 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. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM).

[0102] The memory 602 stores executable program code, and the processor 601 executes this executable program code to implement the functions of the aforementioned receiving module and creation module, thereby realizing the vehicle management method based on the cloud service system described above. That is, the memory 602 stores instructions for executing the aforementioned vehicle management method based on the cloud service system.

[0103] The communication interface 603 uses transceiver modules, such as, but not limited to, network interface cards and transceivers, to enable communication between the computing device 600 and other devices or communication networks.

[0104] In addition to the data bus, the 604 bus can also include a power bus, a control bus, and a status signal bus. The bus can be a Peripheral Component Interconnect Express (PCIe) bus, an Extended Industry Standard Architecture (EISA) bus, a Unified Bus (Ubus or UB), a Compute Express Link (CXL) bus, a Cache Coherent Interconnect for Accelerators (CCIX) bus, etc. The bus can be divided into address bus, data bus, and control bus.

[0105] Please refer to Figure 7, which is a schematic diagram of a computing device cluster provided in an embodiment of this application. As shown in Figure 7, the computing device cluster 700 includes at least one computing device 600.

[0106] As shown in Figure 7, the computing device cluster 700 includes at least one computing device 600. The memory 602 of one or more computing devices 600 in the computing device cluster 700 may store the same instructions for executing the vehicle management method described above based on the cloud service system.

[0107] In some possible implementations, the memory 602 of one or more computing devices 600 in the computing device cluster 700 may also store partial instructions for executing the vehicle management method based on the cloud service system described above. In other words, a combination of one or more computing devices 600 can jointly execute the vehicle management method based on the cloud service system described above.

[0108] It should be noted that the memory 602 in different computing devices 600 within the computing device cluster 700 can store different instructions, each used to execute a portion of the functions of the aforementioned cloud management platform. That is, the instructions stored in the memory 602 of different computing devices 600 can implement the functions of one or more modules, such as the receiving module and the creation module.

[0109] In some possible implementations, one or more computing devices 600 in the computing device cluster 700 can be connected via a network. This network can be a wide area network (WAN) or a local area network (LAN), etc.

[0110] Please refer to Figure 8, which is a schematic diagram of computer devices in a computer cluster provided in an embodiment of this application being connected via a network. As shown in Figure 8, two computing devices 600A and 600B are connected via a network. Specifically, they are connected to the network through the communication interfaces in each computing device.

[0111] In one possible implementation, the memory in computing device 600A stores instructions for performing the functions of modules such as the receiving module. Meanwhile, the memory in computing device 600B stores instructions for performing the functions of modules such as the creation module.

[0112] It should be understood that the functions of computing device 600A shown in Figure 8 can also be performed by multiple computing devices. Similarly, the functions of computing device 600B can also be performed by multiple computing devices.

[0113] This application also relates to a computer storage medium storing a program for signal processing, which, when run on a computer, causes the computer to perform the steps executed by the cloud management platform in the embodiment shown in FIG2.

[0114] This application also relates to a computer program product that stores instructions that, when executed by a computer, cause the computer to perform the steps performed by the cloud management platform in the embodiment shown in FIG2.

[0115] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0116] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0117] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0118] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0119] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A vehicle management method based on a cloud service system, characterized in that, The cloud service system includes infrastructure for providing cloud services to tenants and a cloud management platform for managing the infrastructure. The method includes: The cloud management platform receives a vehicle management request sent by a tenant, wherein the vehicle management request is used to indicate multiple vehicles of the tenant; Based on the vehicle management request, the cloud management platform creates a cloud instance in the infrastructure for managing the multiple vehicles; The cloud instance receives first information sent by a first vehicle among the plurality of vehicles and second information sent by a second vehicle among the plurality of vehicles, wherein the first vehicle and the second vehicle are traveling in the same direction, the first vehicle is an unmanned vehicle, and the second vehicle is a manned vehicle. If the cloud instance determines, based on the first information and the second information, that the distance between the first vehicle and the second vehicle is less than a preset distance, it notifies the first vehicle to drive to the target location, wherein the target location is located between the first vehicle and the second vehicle.

2. The method according to claim 1, characterized in that, The first information includes a first identifier of the first vehicle, and the second information includes a second identifier of the second vehicle. The first identifier is used to indicate that the first vehicle is an unmanned vehicle, and the second identifier is used to indicate that the second vehicle is a manned vehicle.

3. The method according to claim 1 or 2, characterized in that, The first information further includes a first predicted coordinate of the positioning device of the first vehicle in a preset reference coordinate system, and the second information further includes a second predicted coordinate of the positioning device of the second vehicle in the reference coordinate system. The cloud instance determines, based on the first information and the second information, that the distance between the first vehicle and the second vehicle is less than a preset distance by: The cloud instance obtains the distance between the first vehicle and the second vehicle based on the first predicted coordinates and the second predicted coordinates; The cloud instance determines that the distance between the first vehicle and the second vehicle is less than a preset distance.

4. The method according to any one of claims 1 to 3, characterized in that, The method further includes: The cloud instance receives third information sent by the first vehicle and fourth information sent by the second vehicle, wherein the third information is located before the first information and the fourth information is located before the second information. The third information includes the third predicted coordinates of the positioning device of the first vehicle in the reference coordinate system, and the fourth information includes the fourth predicted coordinates of the positioning device of the second vehicle in the reference coordinate system. The cloud instance determines that the first vehicle and the second vehicle are traveling in the same direction based on the first predicted coordinates, the second predicted coordinates, the third predicted coordinates, and the fourth predicted coordinates.

5. The method according to any one of claims 1 to 4, characterized in that, The cloud instance notifies the first vehicle to travel to the target location, including: The cloud instance obtains the lanes where the first vehicle and the second vehicle are located, and projects the second predicted coordinates onto the centerline of the lanes to obtain the fifth predicted coordinates. The cloud instance determines a sub-centerline located between the first vehicle and the second vehicle from the centerline; The cloud instance determines a sixth predicted coordinate located on the sub-center line based on the fifth predicted coordinate, wherein the sixth predicted coordinate is used as the target location; The cloud instance notifies the first vehicle to travel to the target location.

6. The method according to claim 5, characterized in that, The second information also includes the dimensions of the second vehicle, the position of the positioning device of the second vehicle in the second vehicle, the positioning accuracy of the second vehicle, and the safe distance between the two vehicles, wherein the positioning accuracy is used to indicate the difference between the second predicted coordinates and the actual coordinates of the second vehicle in the reference coordinate system; The cloud instance determines the sixth predicted coordinates located on the sub-center line based on the fifth predicted coordinates, including: The cloud instance determines the distance between the fifth predicted coordinate and the sixth predicted coordinate based on the size, the location, the positioning accuracy, and the safety distance; The cloud instance determines the sixth predicted coordinate located on the sub-center line based on the fifth predicted coordinate and the distance between the fifth predicted coordinate and the sixth predicted coordinate.

7. The method according to any one of claims 1 to 6, characterized in that, The cloud instance includes physical servers, virtual machines, containers, microvirtual machines, or bare metal servers.

8. A cloud service system, characterized in that, The cloud service system includes infrastructure that provides cloud services to tenants and a cloud management platform that manages the infrastructure, wherein: The cloud management platform is used to receive vehicle management requests sent by tenants, wherein the vehicle management requests are used to indicate multiple vehicles of the tenant; The cloud management platform is also used to create cloud instances in the infrastructure for managing the multiple vehicles based on the vehicle management request; The cloud instance is used to receive first information sent by a first vehicle among the plurality of vehicles and second information sent by a second vehicle among the plurality of vehicles, wherein the first vehicle and the second vehicle are traveling in the same direction, the first vehicle is an unmanned vehicle, and the second vehicle is a manned vehicle. The cloud instance is further configured to determine, based on the first information and the second information, that the distance between the first vehicle and the second vehicle is less than a preset distance, and then notify the first vehicle to drive to the target location, wherein the target location is located between the first vehicle and the second vehicle.

9. The system according to claim 8, characterized in that, The first information includes a first identifier of the first vehicle, and the second information includes a second identifier of the second vehicle. The first identifier is used to indicate that the first vehicle is an unmanned vehicle, and the second identifier is used to indicate that the second vehicle is a manned vehicle.

10. The system according to claim 8 or 9, characterized in that, The first information further includes the first predicted coordinates of the positioning device of the first vehicle in a preset reference coordinate system, and the second information further includes the second predicted coordinates of the positioning device of the second vehicle in the reference coordinate system. The cloud instance is used to obtain the distance between the first vehicle and the second vehicle based on the first predicted coordinates and the second predicted coordinates. The cloud instance determines that the distance between the first vehicle and the second vehicle is less than a preset distance.

11. The system according to any one of claims 8 to 10, characterized in that, The cloud instance is also used to receive third information sent by the first vehicle and fourth information sent by the second vehicle, wherein the third information is located before the first information and the fourth information is located before the second information. The third information includes the third predicted coordinates of the positioning device of the first vehicle in the reference coordinate system and the fourth information includes the fourth predicted coordinates of the positioning device of the second vehicle in the reference coordinate system. The cloud instance is also used to determine, based on the first predicted coordinates, the second predicted coordinates, the third predicted coordinates, and the fourth predicted coordinates, that the first vehicle and the second vehicle are traveling in the same direction.

12. The system according to any one of claims 8 to 11, characterized in that, The cloud instance is used for: The lanes where the first vehicle and the second vehicle are located are obtained, and the second predicted coordinates are projected onto the center line of the lanes to obtain the fifth predicted coordinates; From the centerline, determine a sub-centerline located between the first vehicle and the second vehicle; Based on the fifth predicted coordinates, a sixth predicted coordinate located on the sub-center line is determined, wherein the sixth predicted coordinate is used as the target location; Inform the first vehicle to proceed to the target location.

13. The system according to claim 12, characterized in that, The second information also includes the dimensions of the second vehicle, the position of the positioning device of the second vehicle in the second vehicle, the positioning accuracy of the second vehicle, and the safe distance between the two vehicles, wherein the positioning accuracy is used to indicate the difference between the second predicted coordinates and the actual coordinates of the second vehicle in the reference coordinate system; The cloud instance is used for: Based on the size, the position, the positioning accuracy, and the safety distance, determine the distance between the fifth predicted coordinate and the sixth predicted coordinate; Based on the fifth predicted coordinate and the distance between the fifth predicted coordinate and the sixth predicted coordinate, the sixth predicted coordinate located on the sub-center line is determined.

14. The system according to any one of claims 8 to 13, characterized in that, The cloud instance includes physical servers, virtual machines, containers, microvirtual machines, or bare metal servers.

15. A computing device cluster, characterized in that, The computing device cluster includes at least one computing device, each computing device including a processor and memory: The memory is used to store instructions; The processor is configured to, according to the instructions, cause the computing device cluster to perform the method of any one of claims 1 to 7.

16. A computer storage medium, characterized in that, The computer storage medium stores one or more instructions that, when executed by one or more computers, cause the one or more computers to perform the method of any one of claims 1 to 7.

17. A computer program product, characterized in that, The computer program product stores instructions that, when executed by a computer, cause the computer to perform the method described in any one of claims 1 to 7.

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