Service control mode determination method and device, equipment, medium and product

Abstract

The invention discloses a service control mode determination method and device, equipment, a medium and a product. The method comprises the following steps: determining feedback control parameters according to the number of service resources and a service task queue of an unmanned vehicle cluster at the current moment; according to the feedback control parameters and a service control mode of the unmanned vehicle cluster at the current moment, determining a service control mode at the next moment; the service control mode comprises a first control mode and a second control mode, the first control mode is a control mode in which task execution interference is not performed on the service task queue, and the second control mode is a control mode in which task execution interference is performed on the service task queue and the scale of the unmanned vehicle cluster is limited. According to the technical scheme, the problem that the utilization rate of unmanned vehicle cluster service resources is low is solved, the random service system theory and the feedback control theory are combined, the utilization of the service resources is optimized, and the operation cost is reduced while the safety of the unmanned vehicle cluster is guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of risk control technology, and in particular to a method, device, equipment, medium and product for determining a service control mode. Background Art

[0002] In actual applications, in order to deal with the anomalies that may be encountered during the operation of unmanned vehicles, the providers of unmanned vehicles usually deploy service personnel to intervene in and control the unmanned vehicles to ensure the safety and reliability of the unmanned vehicles.

[0003] For driverless vehicle clusters, existing technologies usually adopt redundant design and equip a sufficient number of service personnel for abnormal control response. That is, the supply of service personnel should be greater than or equal to the abnormal control demand at any time, and there should not be a situation where there is no service personnel to respond when the abnormal control demand of the driverless vehicle occurs.

[0004] However, the redundant design method leads to low resource utilization of service personnel, increasing the operating costs of unmanned vehicles and the difficulty of management and maintenance. Summary of the invention

[0005] The present invention provides a method, device, equipment, medium and product for determining a service control mode to solve the problem of low utilization rate of service resources of unmanned vehicle clusters. By combining random service system theory and feedback control theory, the utilization of service resources is optimized, and the operating cost is reduced while ensuring the safety of unmanned vehicle clusters.

[0006] According to one aspect of the present invention, a method for determining a service control mode is provided, the method comprising:

[0007] Obtaining the number of service resources and service task queues of the unmanned vehicle cluster at the current moment; wherein the service task queue is used to store service tasks to be completed; the service tasks include intervention tasks and business tasks;

[0008] Determining feedback control parameters according to the number of service resources and the service task queue;

[0009] The service control mode at the next moment is determined according to the feedback control parameters and the service control mode of the unmanned vehicle cluster at the current moment; wherein the service control mode includes a first control mode and a second control mode, the first control mode is a control mode that does not interfere with the task execution of the service task queue, and the second control mode is a control mode that interferes with the task execution of the business tasks in the service task queue and limits the size of the unmanned vehicle cluster.

[0010] According to another aspect of the present invention, a device for determining a service control mode is provided, the device comprising:

[0011] An information acquisition module, used to obtain the number of service resources and service task queues of the unmanned vehicle cluster at the current moment; wherein the service task queue is used to store service tasks to be completed; the service tasks include intervention tasks and business tasks;

[0012] A parameter determination module, used to determine feedback control parameters according to the number of service resources and the service task queue;

[0013] A mode determination module is used to determine the service control mode at the next moment according to the feedback control parameters and the service control mode of the unmanned vehicle cluster at the current moment; wherein the service control mode includes a first control mode and a second control mode, the first control mode is a control mode that does not interfere with the task execution of the service task queue, and the second control mode is a control mode that interferes with the task execution of the business tasks in the service task queue and limits the size of the unmanned vehicle cluster.

[0014] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0015] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for determining the service control mode described in any embodiment of the present invention.

[0016] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for determining a service control mode described in any embodiment of the present invention when executed.

[0017] According to another aspect of the present invention, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the method for determining a service control mode according to any embodiment of the present invention is implemented.

[0018] The technical solution of the embodiment of the present invention is to obtain the number of service resources and the service task queue of the unmanned vehicle cluster at the current moment; wherein the service task queue is used to store the service tasks to be completed; the service tasks include intervention tasks and business tasks; according to the number of service resources and the service task queue, feedback control parameters are determined; according to the feedback control parameters and the service control mode of the unmanned vehicle cluster at the current moment, the service control mode at the next moment is determined; wherein the service control mode includes a first control mode and a second control mode, the first control mode is a control mode that does not interfere with the task execution of the service task queue, and the second control mode is a control mode that interferes with the task execution of the business tasks in the service task queue and limits the size of the unmanned vehicle cluster. This technical solution solves the problem of low utilization of service resources of the unmanned vehicle cluster, optimizes the utilization of service resources by combining the random service system theory with the feedback control theory, and reduces operating costs while ensuring the safety of the unmanned vehicle cluster.

[0019] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] 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.

[0021] Figure 1 is a flow chart of a method for determining a service control mode provided according to Embodiment 1 of the present invention;

[0022] Figure 2 is a flow chart of a method for determining a service control mode according to Embodiment 2 of the present invention;

[0023] Figure 3 is a structural diagram of a device for determining a service control mode according to Embodiment 3 of the present invention;

[0024] Figure 4 It is a structural diagram of an electronic device for implementing the method for determining a service control mode according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. The acquisition, storage, use, processing, etc. of data in the technical solution of this application comply with the relevant provisions of national laws and regulations.

[0027] Embodiment 1

[0028] Figure 1 A flowchart of a method for determining a service control mode is provided for the first embodiment of the present invention. This embodiment is applicable to the background service scenario of an unmanned vehicle, especially the determination of a service control mode. The method can be executed by a device for determining a service control mode, which can be implemented in the form of hardware and / or software, and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0029] S110, obtaining the number of service resources and the service task queue of the unmanned vehicle cluster at the current moment; wherein the service task queue is used to store service tasks to be completed; the service tasks include intervention tasks and business tasks.

[0030] This solution can be executed by the control platform of the unmanned vehicle, and all the unmanned vehicles under the control of the control platform can form an unmanned vehicle cluster. The control platform can establish a service task queue and add the newly generated service task to the service task queue. The service task can be a task that requires the use of service resources, and the service resources can be service personnel or electronic devices that can serve the unmanned vehicle, such as a robot that can guide the unmanned vehicle out of trouble. The number of service resources can be used to characterize the number of resources that can serve the unmanned vehicle, such as the number of service personnel.

[0031] The service tasks may include intervention tasks and business tasks. Among them, the intervention tasks may be tasks for controlling and intervening in the unmanned vehicle when the unmanned vehicle is abnormal, such as unmanned vehicle rescue tasks. The business tasks may be business management tasks for the operation process of the unmanned vehicle, such as tasks for monitoring the driving behavior of the unmanned vehicle. It can be understood that for unmanned vehicles, intervention tasks are more urgent and dangerous than business tasks.

[0032] S120: Determine a feedback control parameter according to the number of service resources and the service task queue.

[0033] The random service system theory is a mathematical theory that studies the queuing phenomenon of the service system in the process of random demand and random service. The feedback control theory is a theory that affects the next action based on the effect of the action after the current action is completed. The characteristic of the feedback control theory is that it can respond to the objective effects caused by each step in the implementation process of the plan decision in a timely manner, and adjust and modify the next implementation plan accordingly, so that the implementation of the plan decision can be coordinated with the original plan itself in a dynamic way.

[0034] The control platform can build a service task queue based on the random service system theory, combine the random service system theory with the feedback control theory, calculate the feedback control parameters according to the number of service resources and the service task queue, and then adjust the service control mode based on the feedback control parameters to ensure the effective use of service resources.

[0035] S130. Determine the service control mode at the next moment based on the feedback control parameters and the service control mode of the unmanned vehicle cluster at the current moment; wherein the service control mode includes a first control mode and a second control mode, the first control mode is a control mode that does not interfere with the task execution of the service task queue, and the second control mode is a control mode that interferes with the task execution of the business tasks in the service task queue and limits the size of the unmanned vehicle cluster.

[0036] It is easy to understand that the control platform can adjust the service control mode at the next moment based on the comparison result of the feedback control parameter and the preset parameter threshold, based on the service control mode of the unmanned vehicle cluster at the current moment, so as to coordinate the service resources with the service tasks. Specifically, the service control mode may include a first control mode and a second control mode. The first control mode is a control mode that does not interfere with the execution of tasks in the service task queue, and the second control mode coordinates service resources by interfering with the execution of business tasks in the service task queue and limiting the size of the unmanned vehicle cluster. Through the second control mode, the control platform can give priority to the safety of the unmanned vehicle cluster at the expense of the timeliness of business tasks when available service resources are insufficient.

[0037] The technical solution of the embodiment of the present invention is to obtain the number of service resources and the service task queue of the unmanned vehicle cluster at the current moment; wherein the service task queue is used to store the service tasks to be completed; the service tasks include intervention tasks and business tasks; according to the number of service resources and the service task queue, feedback control parameters are determined; according to the feedback control parameters and the service control mode of the unmanned vehicle cluster at the current moment, the service control mode at the next moment is determined; wherein the service control mode includes a first control mode and a second control mode, the first control mode is a control mode that does not interfere with the task execution of the service task queue, and the second control mode is a control mode that interferes with the task execution of the business tasks in the service task queue and limits the size of the unmanned vehicle cluster. This technical solution solves the problem of low utilization of service resources of the unmanned vehicle cluster, optimizes the utilization of service resources by combining the random service system theory with the feedback control theory, and reduces operating costs while ensuring the safety of the unmanned vehicle cluster.

[0038] Embodiment 2

[0039] Figure 2 This is a flow chart of a method for determining a service control mode provided in Embodiment 2 of the present invention. This embodiment is refined based on the above embodiment. Figure 2 As shown, the method includes:

[0040] S210. Obtain the number of service resources and service task queue of the unmanned vehicle cluster at the current moment; wherein the service task queue is used to store service tasks to be completed; and the service tasks include intervention tasks and business tasks.

[0041] S220: Determine the number of service tasks in the service task queue.

[0042] Based on the theory of random service systems, the control platform can define X as the interval time distribution of service tasks, X(t) as the interval time of service tasks at target time t, Y as the service time distribution of intervention tasks, Y(t) as the service time of intervention tasks at target time t, Z(t) as the number of service resources at target time t; N(t) as the number of service tasks in the service task queue at target time t, N q (t) represents the number of intervention tasks in the intervention task queue at the target time t; V(t) represents the number of unmanned vehicles in working state in the unmanned vehicle cluster at the target time t; X can obey probability distribution such as Poisson distribution, Erlang distribution or deterministic distribution.

[0043] S230: Taking the difference between the number of the service resources and the number of the service tasks as a feedback control parameter.

[0044] From the perspective of the safety of unmanned vehicle clusters, N q (t) = 0, indicating that the intervention task will be served immediately when it arrives at the target time t, without waiting. If the number of service resources satisfies Z(t) ≥ V(t), then N q (t) = 0. However, unmanned vehicles usually do not require the intervention of service resources, so the service resource configuration method of Z(t) ≥ V(t) will cause serious waste of resources.

[0045] The change of Z(t) is mainly affected by the service staff's scheduling strategy. Compared with N(t), Z(t) is a slow variable and can be regarded as a constant Z const The risk control target can be determined as N(t)≤Z const Based on feedback control theory, the feedback control parameter can be expressed as C(t)=Z const -N(t), C(t) represents the number of service resources available at the target time t, which is used to characterize the safety level of the unmanned vehicle cluster. The risk control target can be expressed as C(t)≥0.

[0046] S240. Determine the service control mode at the next moment based on the feedback control parameters and the service control mode of the unmanned vehicle cluster at the current moment; wherein the service control mode includes a first control mode and a second control mode, the first control mode being a control mode that does not interfere with the task execution of the service task queue, and the second control mode being a control mode that interferes with the task execution of the business tasks in the service task queue and limits the size of the unmanned vehicle cluster.

[0047] It can be understood that N(t) is affected by X(t), Y(t) and V(t). The functional relationship between N(t) and X(t), Y(t) and V(t) can be expressed as N(t) = f[X(t), Y(t), V(t)], and the maximum value of N(t) is V(t). C(t) = Z const -f[X(t),Y(t),V(t)]=g[X(t),Y(t),V(t)]. Since X(t) is affected by the environment and is an uncontrollable factor, the risk control target C(t)≥0 can be met by adjusting Y(t) and V(t).

[0048] In this solution, determining the service control mode at the next moment according to the feedback control parameter and the service control mode of the unmanned vehicle cluster at the current moment includes:

[0049] If the feedback control parameter is greater than the first parameter threshold, and the service control mode of the unmanned vehicle cluster at the current moment is the first control mode, the service control mode at the next moment remains the first control mode;

[0050] If the feedback control parameter is less than or equal to the first parameter threshold, and the service control mode of the unmanned vehicle cluster at the current moment is the first control mode, switching the service control mode at the next moment to the second control mode;

[0051] If the feedback control parameter is greater than or equal to the second parameter threshold, and the service control mode of the unmanned vehicle cluster at the current moment is the second control mode, the service control mode at the next moment is switched to the first control mode.

[0052] It can be understood that the control platform can pre-set a first parameter threshold C1 greater than 0. If C(t)>C1, the control platform can control the unmanned vehicle cluster based on the first control mode; if C(t)≤C1, the control platform can control the unmanned vehicle cluster based on the second control mode.

[0053] In a feasible solution, the control process of the second control mode includes:

[0054] Determine a preset number of target business tasks according to the priority of the business tasks in the service task queue, suspend each target business task, and save each target business task to a pre-established business task queue;

[0055] Maintain the size of the unmanned vehicle cluster and do not issue business tasks to unmanned vehicles that are stationary.

[0056] Among them, the first control mode is not to interfere with the service task queue and the intervention task queue. The second control mode is to sort the service tasks according to the service task priority, and preferentially suspend the service tasks with low priority, and save a preset number of target service tasks that are suspended to a pre-established service task queue. At the same time, the control platform no longer increases the number of driverless vehicles in the driverless vehicle cluster, that is, V(t)=V const , V const is a constant, and the control platform does not issue service tasks to the driverless vehicles in a stationary state, that is, no new service tasks are added.

[0057] Based on the above solution, the suspension processing includes:

[0058] Control the driverless vehicle in a driving state to stop safely;

[0059] If the driverless vehicle has both service tasks and intervention tasks, the intervention tasks are completed after the driverless vehicle is in a stationary state.

[0060] The specific method of suspending the service tasks is: control the driverless vehicle that is driving to stop safely; if the driverless vehicle has both service tasks and intervention tasks, the intervention tasks are ended after the driverless vehicle is in a stationary state, so that the service resources for processing the intervention tasks can be released; if the driverless vehicle has service tasks but no intervention tasks, the probability of generating intervention tasks after the service tasks are suspended is 0.

[0061] In a preferred solution, the saving of each target service task to the pre-established service task queue includes:

[0062] Save each target service task to the pre-established service task queue according to the priority, so as to execute the service tasks in the service task queue in a last-in-first-out manner at the target time; wherein, the target time is the time when the service control mode switches from the second control mode to the first control mode.

[0063] The expected value of the service duration of the intervention tasks in the second control mode is much smaller than the expected value of the service duration of the intervention tasks in the first control mode. At the same time, the expected value of the time interval for the intervention tasks to leave the intervention task queue is much smaller than the expected value of the time interval for entering the service task queue, that is, E[Y2(t)] << E[Y1(t)], and E[Y2(t)] << E[X(t)]. Therefore, in the second control mode, C(t) continues to increase to meet the risk control target C(t)≥0.

[0064] Specifically, the scale of the driverless vehicle cluster is V const, all unmanned vehicles in the unmanned vehicle cluster are stationary, and the business tasks of the unmanned vehicles are suspended, C(t) increases to the upper limit Z const , the number of intervention tasks N in the unmanned vehicle cluster q (t)=0, satisfying the condition N(t≤Z) const Therefore, in the second control mode, the control platform prioritizes the safety of the unmanned vehicle cluster at the expense of the timeliness of business tasks.

[0065] The control platform can also pre-set a second parameter threshold C2 that is greater than or equal to the first parameter threshold C1. If C(t) ≥ C2, the control platform can switch from the second control mode to the first control mode. C2-C1 represents a differential gap, restarts the suspended business tasks, and cancels the quantity limit on V(t). The specific process of resuming the execution of business tasks in the business task queue is: according to the priority of the business tasks, resume the business tasks in turn, and consume the business tasks in the business task queue in a first-in-last-out (FILO) manner.

[0066] The embodiment of the present invention combines the random service system theory with the feedback control theory, defines the risk control target from the perspective of the unmanned vehicle cluster, and provides a service control mode switching method to achieve the risk control target. This solution adjusts the service control mode by setting the threshold of the feedback control parameter, and can meet the safety requirements of the unmanned vehicle cluster operation when the number of service resources is less than the number of unmanned vehicles, and optimize the use of service resources while reducing the risk of the unmanned vehicle cluster.

[0067] Embodiment 3

[0068] Figure 3 This is a schematic diagram of the structure of a device for determining a service control mode provided by Embodiment 3 of the present invention. Figure 3 As shown, the device comprises:

[0069] The information acquisition module 310 is used to obtain the number of service resources and the service task queue of the unmanned vehicle cluster at the current moment; wherein the service task queue is used to store the service tasks to be completed; the service tasks include intervention tasks and business tasks;

[0070] A parameter determination module 320, configured to determine a feedback control parameter according to the number of service resources and the service task queue;

[0071] The mode determination module 330 is used to determine the service control mode at the next moment according to the feedback control parameters and the service control mode of the unmanned vehicle cluster at the current moment; wherein the service control mode includes a first control mode and a second control mode, the first control mode is a control mode that does not interfere with the task execution of the service task queue, and the second control mode is a control mode that interferes with the task execution of the business tasks in the service task queue and limits the size of the unmanned vehicle cluster.

[0072] In this solution, the parameter determination module 320 is specifically used to:

[0073] Determining the number of service tasks in the service task queue;

[0074] The difference between the number of service resources and the number of service tasks is used as a feedback control parameter.

[0075] In a feasible solution, the mode determination module 330 includes:

[0076] If the feedback control parameter is greater than the first parameter threshold, and the service control mode of the unmanned vehicle cluster at the current moment is the first control mode, the service control mode at the next moment remains the first control mode;

[0077] If the feedback control parameter is less than or equal to the first parameter threshold, and the service control mode of the unmanned vehicle cluster at the current moment is the first control mode, switching the service control mode at the next moment to the second control mode;

[0078] If the feedback control parameter is greater than or equal to the second parameter threshold, and the service control mode of the unmanned vehicle cluster at the current moment is the second control mode, the service control mode at the next moment is switched to the first control mode.

[0079] In an embodiment, the control process of the second control mode includes:

[0080] Determine a preset number of target business tasks according to the priority of the business tasks in the service task queue, suspend each target business task, and save each target business task to a pre-established business task queue;

[0081] Maintain the size of the unmanned vehicle cluster and do not issue business tasks to unmanned vehicles that are stationary.

[0082] On the basis of the above scheme, the suspension process includes:

[0083] Control the unmanned vehicle in motion to park safely;

[0084] If the unmanned vehicle has both a business task and an intervention task, the intervention task shall be completed after the unmanned vehicle is stationary.

[0085] In a preferred solution, the step of saving each target business task to a pre-established business task queue includes:

[0086] Each target business task is saved in a pre-established business task queue according to priority, so that the business tasks in the business task queue are executed in a first-in-last-out manner at a target time; wherein the target time is the time when the service control mode switches from the second control mode to the first control mode.

[0087] The device for determining the service control mode provided in the embodiment of the present invention can execute the method for determining the service control mode provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0088] Embodiment 4

[0089] Figure 4 A schematic diagram of an electronic device 410 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0090] like Figure 4 As shown, the electronic device 410 includes at least one processor 411, and a memory connected to the at least one processor 411 in communication, such as a read-only memory (ROM) 412, a random access memory (RAM) 413, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 411 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 412 or the computer program loaded from the storage unit 418 to the random access memory (RAM) 413. In the RAM 413, various programs and data required for the operation of the electronic device 410 can also be stored. The processor 411, the ROM 412, and the RAM 413 are connected to each other via a bus 414. An input / output (I / O) interface 415 is also connected to the bus 414.

[0091] Multiple components in the electronic device 410 are connected to the I / O interface 415, including: an input unit 416, such as a keyboard, a mouse, etc.; an output unit 417, such as various types of displays, speakers, etc.; a storage unit 418, such as a disk, an optical disk, etc.; and a communication unit 419, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 419 allows the electronic device 410 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0092] The processor 411 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 411 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 411 executes the various methods and processes described above, such as a method for determining a service control mode.

[0093] In some embodiments, the method for determining the service control mode may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 418. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 410 via the ROM 412 and / or the communication unit 419. When the computer program is loaded into the RAM 413 and executed by the processor 411, one or more steps of the method for determining the service control mode described above may be performed. Alternatively, in other embodiments, the processor 411 may be configured to perform the method for determining the service control mode in any other appropriate manner (e.g., by means of firmware).

[0094] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0095] The computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable service control mode determination device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0096] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0097] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0098] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0099] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0100] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0101] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for determining a service control mode, characterized in that: The method comprises: Obtaining the number of service resources and service task queues of the unmanned vehicle cluster at the current moment; wherein the service task queue is used to store service tasks to be completed; the service tasks include intervention tasks and business tasks; Determining feedback control parameters according to the number of service resources and the service task queue; The service control mode at the next moment is determined according to the feedback control parameters and the service control mode of the unmanned vehicle cluster at the current moment; wherein the service control mode includes a first control mode and a second control mode, the first control mode is a control mode that does not interfere with the task execution of the service task queue, and the second control mode is a control mode that interferes with the task execution of the business tasks in the service task queue and limits the size of the unmanned vehicle cluster.

2. The method according to claim 1, characterized in that The determining of feedback control parameters according to the number of service resources and the service task queue includes: Determining the number of service tasks in the service task queue; The difference between the number of service resources and the number of service tasks is used as a feedback control parameter.

3. The method according to claim 2, characterized in that The determining the service control mode at the next moment according to the feedback control parameter and the service control mode of the unmanned vehicle cluster at the current moment includes: If the feedback control parameter is greater than the first parameter threshold, and the service control mode of the unmanned vehicle cluster at the current moment is the first control mode, the service control mode at the next moment remains the first control mode; If the feedback control parameter is less than or equal to the first parameter threshold, and the service control mode of the unmanned vehicle cluster at the current moment is the first control mode, switching the service control mode at the next moment to the second control mode; If the feedback control parameter is greater than or equal to the second parameter threshold, and the service control mode of the unmanned vehicle cluster at the current moment is the second control mode, the service control mode at the next moment is switched to the first control mode.

4. The method according to claim 3, characterized in that The control process of the second control mode includes: Determine a preset number of target business tasks according to the priority of the business tasks in the service task queue, suspend each target business task, and save each target business task to a pre-established business task queue; Maintain the size of the unmanned vehicle cluster and do not issue business tasks to unmanned vehicles that are stationary.

5. The method according to claim 4, characterized in that The suspension process includes: Control the unmanned vehicle in motion to park safely; If the unmanned vehicle has both a business task and an intervention task, the intervention task shall be completed after the unmanned vehicle is stationary.

6. The method according to claim 1, characterized in that The step of saving each target business task to a pre-established business task queue includes: Each target business task is saved in a pre-established business task queue according to priority, so that the business tasks in the business task queue are executed in a first-in-last-out manner at a target time; wherein the target time is the time when the service control mode switches from the second control mode to the first control mode.

7. A device for determining a service control mode, characterized in that: The device comprises: An information acquisition module, used to obtain the number of service resources and service task queues of the unmanned vehicle cluster at the current moment; wherein the service task queue is used to store service tasks to be completed; the service tasks include intervention tasks and business tasks; A parameter determination module, used to determine feedback control parameters according to the number of service resources and the service task queue; A mode determination module is used to determine the service control mode at the next moment according to the feedback control parameters and the service control mode of the unmanned vehicle cluster at the current moment; wherein the service control mode includes a first control mode and a second control mode, the first control mode is a control mode that does not interfere with the task execution of the service task queue, and the second control mode is a control mode that interferes with the task execution of the business tasks in the service task queue and limits the size of the unmanned vehicle cluster.

8. An electronic device, characterized in that: The electronic device comprises: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for determining the service control mode described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for determining the service control mode according to any one of claims 1 to 6 when executed.

10. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the method for determining a service control mode according to any one of claims 1 to 6.

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