Vehicle operation maintenance method and device and electronic equipment

Abstract

The invention provides a vehicle operation maintenance method, a vehicle operation maintenance device and electronic equipment, which are used for carrying out operation maintenance on an unmanned taxi by cooperating a driver so as to reduce the employment cost of a safety officer and improve the operation maintenance efficiency. The method comprises the steps of determining a maintenance type and a vehicle position of a to-be-maintained vehicle in response to an operation maintenance instruction of an unmanned taxi; and if the maintenance type is a specified type in which the driver has the processing capability, determining candidate drivers arriving at the vehicle position in the first time period based on the vehicle operation information of each driver in the platform. Based on the total number of vehicles to be maintained in the platform, a driver order receiving income mean value in the current time period and the relative distance between the candidate driver and the vehicle position, a maintenance reward value of the candidate driver and a parking order loss value generated by executing vehicle maintenance are determined; and issuing a maintenance task of the to-be-maintained vehicle to the target driver to indicate the target driver to obtain a corresponding maintenance reward value after maintaining the vehicle.

Description

Technical Field

[0001] The present application relates to the field of vehicle control technology, and in particular to a vehicle operation and maintenance method, device, and electronic equipment. Background Art

[0002] Robotaxi taxis are self-driving taxis that don't require a driver. They rely on sensors, artificial intelligence, and high-precision maps for autonomous driving, navigation, and decision-making. Compared to traditional ride-hailing services, robotaxi taxis offer numerous advantages, including easing traffic congestion, reducing travel costs, reducing vehicle usage, and redistributing public space.

[0003] During actual operation, driverless taxis may require manual maintenance due to passenger misoperation, traffic accidents, and other factors to ensure continued operation. Traditional maintenance strategies typically involve online ride-hailing platforms employing dedicated ground safety officers. Upon receiving maintenance instructions, the platform dispatches a safety officer to the nearest site to perform on-site maintenance.

[0004] However, the high cost of hiring safety officers is a major bottleneck hindering the large-scale expansion of autonomous taxi platforms. Optimizing the operational and maintenance strategies of autonomous taxis to reduce safety officer costs is a pressing issue for ride-hailing platforms. Summary of the Invention

[0005] The present application provides a vehicle operation and maintenance method, device and electronic equipment for cooperating with drivers to maintain driverless taxis, so as to reduce the cost of hiring safety officers and improve the operation and maintenance efficiency of driverless taxis.

[0006] In a first aspect, an embodiment of the present application provides a vehicle operation and maintenance method, comprising:

[0007] In response to an operation maintenance instruction of the driverless taxi, determining the maintenance type and vehicle location of the vehicle to be maintained;

[0008] If the maintenance type is a specified type that indicates the driver has the ability to handle it, then determining a candidate driver who arrives at the vehicle location in the first time period based on the vehicle operation information of each driver in the platform;

[0009] For each candidate driver, the following steps are performed: based on the total number of vehicles to be maintained on the platform, the average driver's order income during the current period, and the relative distance between the candidate driver and the vehicle location, determine the candidate driver's maintenance reward value and the loss value of the order suspension caused by performing vehicle maintenance;

[0010] The maintenance task of the vehicle to be maintained is issued to a target driver to instruct the target driver to obtain a corresponding maintenance reward value after performing vehicle maintenance; wherein the target driver is a candidate driver whose maintenance reward value is higher than the suspension loss value.

[0011] In a second aspect, an embodiment of the present application provides a vehicle operation and maintenance device, comprising:

[0012] A data acquisition unit is configured to: determine the maintenance type and vehicle location of a vehicle to be maintained in response to an operation maintenance instruction of the driverless taxi;

[0013] The candidate driver unit is configured to: if the maintenance type is a specified type indicating that the driver has processing capabilities, determine a candidate driver who arrives at the vehicle location in a first time period based on vehicle operation information of each driver in the platform;

[0014] A cost analysis unit is configured to determine a maintenance reward value for the candidate driver and a loss value of lost orders caused by performing vehicle maintenance based on the total number of vehicles to be maintained on the platform, the average driver's order income during the current period, and the relative distance between the candidate driver and the vehicle location;

[0015] The task dispatching unit is configured to: issue the maintenance task of the vehicle to be maintained to the target driver, so as to instruct the target driver to obtain a corresponding maintenance reward value after performing the vehicle maintenance; wherein, the target driver is a candidate driver whose maintenance reward value is higher than the suspension loss value.

[0016] In some embodiments, the cancellation loss value of the candidate driver is determined by:

[0017] Determining a loss coefficient based on the number of orders currently placed by the platform within a target area; wherein the target area is determined based on the current location of the candidate driver;

[0018] Determining an estimated downtime for the candidate driver based on the maintenance type and the relative distance;

[0019] The loss value of order suspension for the candidate driver is determined based on the average driver's income from accepting orders, the expected order suspension duration, and the loss coefficient.

[0020] In some embodiments, the maintenance reward value of the candidate driver is determined by:

[0021] determining a fixed reward coefficient based on the total number of vehicles to be maintained and the maintenance type;

[0022] Determining a floating reward coefficient based on the growth rate of the total number of vehicles to be maintained in the first historical period;

[0023] The maintenance reward value of the candidate driver is determined based on a preset basic reward value, the fixed reward coefficient and the floating reward coefficient.

[0024] In some embodiments, before determining the candidate driver who arrives at the vehicle location in the first time period based on the vehicle operation information of each driver in the platform, the candidate driver unit is further configured to:

[0025] It is determined that the total number of vehicles to be maintained is greater than a preset number threshold, and / or that the platform currently does not have a safety officer who can arrive at the vehicle location in the second time period.

[0026] In some embodiments, the candidate driver unit is further configured to:

[0027] If the total number of vehicles to be maintained is not greater than the preset number threshold, or the platform has a safety officer who arrives at the vehicle location during the second time period, the maintenance task of the vehicles to be maintained will be handed over to the safety officer.

[0028] In some embodiments, to issue the maintenance task of the vehicle to be maintained to the target driver, the task dispatching unit is specifically configured to:

[0029] For each target driver, respectively performing: determining a task benefit value of the target driver within a unit distance based on the maintenance reward value, the stop order loss value, and the relative distance;

[0030] issuing the maintenance tasks to the target drivers in sequence during the third period according to the order of the task benefits from high to low;

[0031] If no receipt instruction of the maintenance task is received during the third time period, the maintenance task of the vehicle to be maintained is handed over to the platform's safety officer for processing.

[0032] In some embodiments, the task dispatching unit is further configured to:

[0033] If the maintenance type is not the specified type, the maintenance task of the vehicle to be maintained will be handed over to the platform's safety officer for processing; wherein, the number of safety officers in the platform is determined by the following method:

[0034] Determining a first cost range for the driver based on driver maintenance task data from the second historical period, wherein the driver maintenance task data includes: a preset range of maintenance task percentages that the platform requires drivers to handle, and maintenance reward values ​​and order cancellation reward values ​​corresponding to drivers handling maintenance tasks;

[0035] Based on the range of security officers required by the platform and the preset duty cost of each security officer, the platform determines the second cost range for security officers;

[0036] Under the constraint that the first cost range and the second cost range are minimum, the number of safety officers required by the platform is determined based on the range of the number of safety officers; wherein the number of safety officers is positively correlated with the first cost range and negatively correlated with the second cost range.

[0037] In some embodiments, the range of the number of security personnel is determined by:

[0038] Determine the minimum task capacity for a single safety officer based on the safety officer's duty time in the second historical period and a preset time threshold for the safety officer to handle a single maintenance task;

[0039] The range of the number of safety officers is determined based on the number of maintenance tasks handled by the safety officer in the second historical period, the minimum task acceptance quantity, and the preset proportion range.

[0040] In a third aspect, an embodiment of the present application provides an electronic device, including:

[0041] a memory for storing program instructions;

[0042] The processor is configured to call the program instructions stored in the memory and execute the method according to the first aspect based on the obtained program instructions.

[0043] In a fourth aspect, an embodiment of the present application provides a computer program product, including a computer program, which implements the method described in the first aspect when executed by a processor.

[0044] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is used to enable a computer to execute the method described in the first aspect.

[0045] In this embodiment of the present application, the maintenance type and location of a vehicle requiring maintenance are determined by responding to an operational maintenance instruction from a driverless taxi. If the maintenance type is a specified type that indicates the driver's ability to handle it, candidate drivers who can reach the vehicle's location within the first time period are identified based on the vehicle operation information of each driver on the platform. Furthermore, based on the total number of vehicles requiring maintenance on the platform, the average driver's order revenue during the current time period, and the relative distance between the candidate driver and the vehicle's location, a corresponding maintenance reward value is determined for each candidate driver, as well as the loss of lost orders resulting from performing vehicle maintenance.

[0046] Then, by issuing maintenance tasks for vehicles to be maintained to target drivers whose maintenance rewards are higher than the loss of lost orders, drivers are more motivated to accept these tasks. This process reduces the cost of hiring safety officers and improves the operational and maintenance efficiency of autonomous taxis by coordinating driver maintenance and rewarding them accordingly. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments of the present application. Obviously, the drawings introduced below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0048] Figure 1 A schematic diagram of an application scenario of a vehicle operation and maintenance method provided in an embodiment of the present application;

[0049] Figure 2 A flowchart of a vehicle operation and maintenance method provided in an embodiment of the present application;

[0050] Figure 3 A schematic diagram of a process for determining whether the platform performs candidate driver screening according to an embodiment of the present application;

[0051] Figure 4 A schematic diagram of the process of the platform provided in an embodiment of the present application dispatching maintenance tasks to target drivers;

[0052] Figure 5 A schematic diagram of a process for determining the number of security personnel employed by a platform provided in an embodiment of the present application;

[0053] Figure 6 A schematic diagram of the structure of a vehicle operation and maintenance device provided in an embodiment of the present application;

[0054] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0055] The following will clearly and thoroughly describe the technical solutions in the embodiments of the present application in conjunction with the accompanying drawings. In the description of the embodiments of the present application, unless otherwise specified, " / " will mean or, for example, A / B can mean A or B; "and / or" in the text is only a description of the association relationship of associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, "multiple" means two or more than two.

[0056] In the description of the embodiments of the present application, unless otherwise specified, the term "multiple" refers to two or more, and other quantifiers should be understood similarly. The preferred embodiments described herein are only used to illustrate and explain the present application and are not used to limit the present application. In addition, the embodiments of the present application and the features in the embodiments may be combined with each other if there is no conflict.

[0057] To further illustrate the technical solutions provided by the embodiments of the present application, this is described in detail below in conjunction with the accompanying drawings and specific implementation methods. Although the embodiments of the present application provide the method operation steps as shown in the following embodiments or drawings, more or fewer operation steps may be included in the method based on routine or no creative labor. In steps where there is no necessary causal relationship logically, the execution order of these steps is not limited to the execution order provided by the embodiments of the present application. During the actual processing process or when the control device is executed, the method can be executed in the order of the methods shown in the embodiments or drawings or in parallel.

[0058] As mentioned earlier, during the actual operation of driverless taxis, manual maintenance may be required due to passenger misoperation, traffic accidents, and other reasons. Traditional maintenance strategies primarily rely on ride-hailing platforms employing dedicated ground safety officers. Upon receiving maintenance instructions, the platform dispatches a safety officer to the nearest site to perform on-site maintenance.

[0059] However, with the large-scale expansion of driverless taxis, the platforms' demand for safety officers is gradually increasing. Currently, for major ride-hailing platforms, the safety officer recruitment market is relatively transparent, and the cost of hiring safety officers is the main bottleneck currently restricting the platforms' large-scale expansion of driverless taxis.

[0060] Our investigation revealed that a significant portion of the maintenance tasks handled by safety officers can be resolved without specialized maintenance knowledge. Examples include: a previous passenger leaving a door unlocked, rendering the vehicle inoperable; a vehicle requiring temporary parking due to traffic restrictions; and passenger complaints of a dirty, messy, or odorous interior. These issues simply don't require specialized maintenance expertise.

[0061] Furthermore, given that online ride-hailing drivers are often idle during off-peak hours and are geographically dispersed, there's room for flexible scheduling. If drivers can be properly dispatched to handle these incidents and given maintenance incentives, this could not only increase driver income and improve the operational efficiency of driverless taxis, but also significantly reduce the platform's safety officer costs.

[0062] In light of this, the inventive concept of the embodiments of this application is to determine the maintenance type and location of a vehicle to be maintained in response to an operational maintenance instruction from a driverless taxi. If the maintenance type is a specified type that indicates a driver's ability to handle it, candidate drivers who can reach the vehicle's location within the first time period are identified based on the vehicle operation information of each driver on the platform.

[0063] Therefore, under the premise that the vehicle can be maintained by the driver, candidate drivers who can go to the location of the vehicle to be maintained in time can be prioritized. Then, based on the total number of vehicles to be maintained on the platform, the average driver's order income in the current period, and the relative distance between the candidate driver and the vehicle location, the maintenance reward value corresponding to each candidate driver and the loss value of the suspension of orders generated during the execution of the vehicle maintenance task can be determined.

[0064] The maintenance reward is the platform's reward for completing maintenance tasks, while the suspension loss is the loss incurred by drivers operating unoccupied vehicles while they are maintaining them, preventing them from accepting orders. Therefore, issuing maintenance tasks for vehicles requiring maintenance to target drivers whose maintenance reward is higher than the suspension loss can effectively increase their motivation to accept tasks. This process, by coordinating driver maintenance operations and providing them with corresponding maintenance rewards, reduces the cost of hiring safety officers and improves the operational efficiency of autonomous taxis.

[0065] The following describes the application scenarios of the embodiments of this application. Figure 1 , is a schematic diagram of an application scenario of the vehicle operation and maintenance method provided in an embodiment of the present application. The application scenario may include a server 101 and a vehicle-mounted terminal 102.

[0066] The server end 101 refers to the main control terminal of the online car-hailing platform. The server end 101 and the vehicle-mounted end 102 can communicate with each other. The communication method can be to use wired communication technology, for example, by connecting a network cable or a serial port cable; or to use wireless communication technology, for example, through Bluetooth or wireless fidelity (WIFI) and other technologies. There is no specific restriction.

[0067] Vehicle-mounted terminal 102 generally refers to the onboard terminal of driverless taxis and regular online ride-hailing vehicles. When a driverless taxi becomes unable to carry passengers during operation and requires vehicle maintenance to support subsequent operations, the vehicle-mounted terminal 102 transmits the current vehicle location and the type of maintenance required to the service terminal 101.

[0068] In some embodiments, upon determining that the current maintenance type is a specified type that a driver is capable of handling, the server 101 selects candidate drivers from the vicinity of the vehicle to be maintained who are able to arrive promptly at the vehicle to perform maintenance. The server 101 then determines the maintenance reward value for the candidate driver, as well as the loss of lost orders resulting from performing the vehicle maintenance, based on the total number of vehicles to be maintained on the platform, the average driver's earnings for accepting orders during the current time period, and the relative distance between the candidate driver and the vehicle.

[0069] In some embodiments, the service end 101 selects a target driver whose maintenance reward value is higher than the loss value of the suspension order from each candidate driver, and sends the maintenance task of the vehicle to be maintained to the target driver's vehicle-mounted terminal 102 to instruct the target driver to obtain the corresponding maintenance reward value after maintaining the vehicle.

[0070] Next, the vehicle operation and maintenance method provided in the embodiment of the present application is introduced in detail. Figure 2 A flow chart of a vehicle operation and maintenance method provided in an embodiment of the present application is shown in FIG. Figure 2 As shown, the following steps are included:

[0071] Step 201: In response to an operation maintenance instruction of a driverless taxi, determining the maintenance type and vehicle location of a vehicle to be maintained;

[0072] In some embodiments, historical maintenance requirements for autonomous taxis can be statistically categorized to identify various types of maintenance that may be required during vehicle operation. Furthermore, a maintenance complexity analysis can be performed on each of these maintenance types, with corresponding task processing levels assigned to each type. Higher task processing levels indicate greater maintenance complexity.

[0073] In some embodiments, task processing levels may range from 1 to 5. Level 3 and above tasks correspond to maintenance types that require dedicated safety personnel to handle. Examples of such tasks include: vehicle accidents resulting in component damage, vehicle fires, and autonomous driving system failures.

[0074] Accordingly, tasks below Level 3 correspond to maintenance types that can be completed without specialized maintenance knowledge. Examples of such tasks include: a previous passenger leaving the door unlocked, rendering the vehicle inoperable; a vehicle requiring temporary parking due to traffic restrictions; and passenger complaints of a dirty or odorous interior. Therefore, tasks below Level 3 correspond to maintenance types that can be performed by an average driver. For ease of distinction, this application will refer to these maintenance types as designated types.

[0075] Therefore, when an unmanned taxi encounters an abnormality during operation and requires maintenance, it can publish its own vehicle location and the type of maintenance required to the platform's service end through the vehicle-mounted terminal.

[0076] Step 202: If the maintenance type is a specified type that indicates the driver has the processing capability, then based on the vehicle operation information of each driver in the platform, determine a candidate driver who arrives at the vehicle location in the first time period;

[0077] In some embodiments, the vehicle operation drivers of each driver in the platform can be retrieved to screen candidate drivers who can reach the vehicle to be maintained within a first time period (for example, 10 minutes) from the vehicle location of the vehicle to be maintained.

[0078] During specific implementation, vehicle operation information such as the current order acceptance status, real-time location, speed limit during the current period, etc. of the online car-hailing driver near the vehicle to be maintained can be obtained.

[0079] For idle drivers, the time required for the driver to drive to the vehicle to be maintained is predicted based on the driver's current real-time location and speed limit.

[0080] For drivers who have not yet completed their orders, we need to further combine the driver's order destination to predict the time required for the driver to reach the order destination from the current location and then return to the vehicle to be maintained.

[0081] In some embodiments, to conserve computing resources and improve the accuracy of candidate driver screening, only available drivers located near the vehicle to be maintained may be screened, excluding drivers with uncompleted orders from the candidate driver screening process. Whether to include uncompleted drivers in the candidate driver screening process can be determined based on actual business needs and is not a limitation of this application.

[0082] Furthermore, considering that the platform already employs safety officers, meaning they have already incurred the cost of hiring them, assigning all maintenance tasks of a given type to drivers would incur significant additional costs. Therefore, a comprehensive assessment of the current maintenance task backlog and the time required to dispatch safety officers can be used to determine whether the maintenance of the vehicle currently undergoing maintenance should be assigned to the driver.

[0083] In some embodiments, driver dispatch conditions for maintenance can be pre-set: if the total number of vehicles requiring maintenance exceeds a preset threshold, and / or the platform currently lacks a safety officer capable of reaching the vehicle's location during the second time period, a driver can be prioritized for maintenance. In other words, before selecting candidate drivers near the vehicle requiring maintenance through the aforementioned process, the dispatch conditions must be met.

[0084] The total number of vehicles awaiting maintenance on the platform represents the number of maintenance tasks currently pending for safety officers. When the backlog is excessive, drivers should be prioritized to perform maintenance tasks to maximize the operating hours of autonomous taxis. The threshold for the total number of vehicles awaiting maintenance can be set based on actual operational needs, for example, 10 vehicles.

[0085] The second time period required for the safety officer to arrive at the vehicle to be serviced should be less than or equal to the first time period required for the driver to arrive. Because the platform has already paid for the safety officer, the time required for the safety officer to arrive at the vehicle to be serviced should not exceed the time required for the driver to arrive at the vehicle to be serviced. For example, the first time period is set to 10 minutes, and the second time period is set to 8 minutes.

[0086] To facilitate understanding of the above process, Figure 3 The following shows the process of determining whether the platform should screen candidate drivers: Figure 3 As shown, the following steps may be included:

[0087] Step 301: Determine whether the maintenance type of the vehicle to be maintained is a specified type;

[0088] Step 302: If it is not a specified type, the maintenance task of the vehicle to be maintained is handed over to the platform's safety officer for processing;

[0089] Step 303: If it is a specified type, determine whether the total number of vehicles currently waiting for maintenance is greater than a preset threshold;

[0090] Step 304: If the number is greater than a preset threshold, then based on the vehicle operation information of each driver in the platform, determine the candidate driver who arrives at the vehicle to be maintained in the first time period;

[0091] Step 305: If the number is not greater than the preset threshold, determine whether the safety officer can arrive at the vehicle to be maintained in the second time period;

[0092] If there is no safety officer arriving in the second time period, the aforementioned step 304 is executed to dispatch a driver to perform maintenance on the vehicle to be maintained. If there is a safety officer arriving in the second time period, the aforementioned step 302 is executed to hand over the vehicle to be maintained to the safety officer, thereby reducing the platform's additional expenses for the driver to maintain the vehicle to be maintained.

[0093] Step 203: For each candidate driver, the following steps are performed: based on the total number of vehicles to be maintained on the platform, the average driver's order income during the current period, and the relative distance between the candidate driver and the vehicle location, determine the candidate driver's maintenance reward value and the order suspension loss value incurred by performing vehicle maintenance;

[0094] In some embodiments, the loss coefficient can be determined based on the number of orders currently placed by the platform in the target area; wherein, the target area is determined based on the current location of the candidate driver. The target area can be a circular area covered in the road network map with the current location of the candidate driver as the center and a preset distance as the radius, or it can be a block, urban area, etc. corresponding to the current location of the candidate driver in the road network map. This application does not limit this.

[0095] After obtaining the target area corresponding to the candidate driver, the number of orders received by the platform in the target area during the preset time period can be counted, and the number of platform drivers located in the target area during the preset time period can be combined to determine the target area in calculating the loss coefficient caused by the driver being unable to accept orders due to maintaining the vehicle to be maintained.

[0096] In some embodiments, the number of orders received by the platform in the target area during a preset period of time and the average number of drivers located in the target area during the preset period of time may be counted. The loss coefficient is then calculated based on the ratio of the number of orders to the average number of drivers.

[0097] For example, the preset time period can be set to the most recent hour. In this case, the number of orders received by the platform in the target area in the most recent hour can be counted, assuming 80 orders. At the same time, the number of drivers located in the target area per unit time in the hour can be counted. For example, the number of drivers located in the target area per minute can be counted, from which the average number of drivers located in the target area per minute can be calculated, assuming 20 people / minute. The ratio of the number of orders received by the platform in the preset time period to the average number of drivers (80 / 20=4) can be used as the loss coefficient.

[0098] It should be understood that the specific implementation can also be based on the actual business scenario. On the basis of the above parameters, the loss coefficient can be calculated in combination with weight parameters such as the vehicle congestion rate of the target area during the preset time period and whether the preset time period is a night time period. This application does not limit this.

[0099] After determining the loss coefficient through the above process, the estimated downtime of the candidate driver is determined based on the maintenance type of the vehicle to be maintained and the relative distance between the vehicle to be maintained and the candidate driver. Finally, the downtime loss value of the candidate driver is determined based on the average driver's income from accepting orders, the estimated downtime, and the loss coefficient.

[0100] Specifically, the candidate driver's loss value of suspension can be calculated by the following formula (1):

[0101]

[0102] Among them, L i is the loss value of the order suspension of candidate driver i; d ij is the relative distance between candidate driver i and vehicle j to be maintained; t0 is the estimated maintenance time, which can be set based on the maintenance type; P(t) is the driver's order income per unit time t, which is calculated based on the number of orders received by the platform in the target area; v(t) is the driver's average speed per unit time t; λ(t) is the loss coefficient per unit time t, for example, it is set to 1.5 during peak order hours and 1.2 during non-peak hours; β is the vehicle's operating cost per unit distance, for example, 0.5 yuan / km.

[0103] In some embodiments, a fixed reward coefficient can be determined based on the total number of vehicles requiring maintenance and the type of maintenance. A floating reward coefficient can then be determined based on the percentage increase in the total number of vehicles requiring maintenance during the first historical period. For example, the percentage increase in the total number of vehicles requiring maintenance on a given day compared to the previous day can be determined using a daily basis. Finally, the candidate driver's maintenance reward value is determined based on a preset base reward value, the fixed reward coefficient, and the floating reward coefficient.

[0104] Specifically, the maintenance reward value of the candidate driver can be calculated using the following formula (2):

[0105]

[0106] Where Bi is the maintenance reward value of candidate driver i; B base (t) is the fixed reward coefficient per unit time t; R j is the task processing level mentioned above, which is determined based on the maintenance type of the vehicle j to be maintained; θ is the highest task processing level (for example, the task processing level is 1 to 5, θ = 5), R j The larger / θ is, the more difficult the current maintenance task is to handle, and the larger the maintenance reward the driver receives. △B is the floating reward coefficient. For example, for every 10% increase in the total number of vehicles to be maintained on the platform, △B will increase by 20% accordingly. N c is the total number of vehicles currently waiting for maintenance on the platform; K is the aforementioned preset quantity threshold, which represents the upper limit of the maintenance task backlog.

[0107] Step 204: Issue the maintenance task of the vehicle to be maintained to the target driver, instructing the target driver to obtain a corresponding maintenance reward value after performing vehicle maintenance; wherein, the target driver is a candidate driver whose maintenance reward value is higher than the suspension loss value.

[0108] Through the above step 203, the corresponding loss value L of each candidate driver can be calculated. i and maintenance reward value B i Stop order loss value L i This is the loss caused by the driver operating an empty vehicle during the maintenance period and being unable to accept orders. Maintenance reward value B i It is the reward given by the platform to the driver for handling maintenance tasks, so the maintenance reward value B i Higher than the stop order loss value L i The target drivers publish maintenance tasks for vehicles to be maintained, which can effectively improve the enthusiasm of drivers to accept tasks.

[0109] In some embodiments, the maintenance task of the vehicle to be maintained may be issued to the target driver in the following manner:

[0110] For each target driver, execute: based on the maintenance reward value Bi , stop order loss value L i , and the relative distance d ij , determine the target driver's mission benefit value within unit distance (B i -L i ) / d ij The task benefit value represents the net benefit per unit distance for the driver to stop the order to maintain the vehicle to be maintained.

[0111] Then, in descending order of task profit, maintenance tasks for the vehicle are issued to each target driver during the third time period. This third time period can be set based on actual needs, such as 30 minutes. This allows maintenance tasks to be assigned first to drivers with the highest net profit, increasing their enthusiasm for accepting tasks.

[0112] If, in the third period, no driver indicates they've accepted the maintenance task—for example, no driver is willing to service the vehicle within 30 minutes—then the vehicle's operation has been significantly delayed. Since the safety officer has already been paid, the platform doesn't need to incur the additional expense of dispatching a driver. Therefore, the maintenance task can be assigned directly to the platform's safety officer, eliminating the need to continuously broadcast maintenance orders to each target driver.

[0113] In some embodiments, if the maintenance reward values ​​of all candidate drivers are not higher than their loss values ​​for stopping orders, it may be considered to motivate the candidate drivers to accept maintenance tasks as soon as possible by providing additional rewards to them.

[0114] During specific implementation, the cost of hiring a single safety officer (e.g., 8,000 yuan / month) and the average number of maintenance tasks handled by a single safety officer (e.g., 40 tasks / month) can be combined to calculate the average cost per maintenance task handled by the safety officer (8,000 / 40 = 200 yuan / time). Then, a preset proportion of the per-time cost (e.g., 10%) is added to the candidate driver's maintenance reward value. For example, if a candidate driver's original maintenance reward value is 60 yuan and the loss value of a suspended order is 72 yuan, 10% of the per-time cost (20 yuan) can be added to the maintenance reward value, and the updated maintenance reward value is 80 yuan, thereby incentivizing the driver to accept maintenance tasks as soon as possible.

[0115] For ease of understanding, Figure 4 The overall process of the platform dispatching maintenance tasks to target drivers is shown as follows: Figure 4 As shown, the following steps may be included:

[0116] Step 401: Determine whether the maintenance type of the vehicle to be maintained is a specified type;

[0117] Step 402: If it is not a specified type, the maintenance task of the vehicle to be maintained is handed over to the platform's safety officer for processing;

[0118] Step 403: If it is a specified type, determine whether the total number of vehicles currently waiting for maintenance is greater than a preset threshold;

[0119] Step 404: If the number is greater than a preset threshold, then based on the vehicle operation information of each driver in the platform, determine the candidate driver who arrives at the vehicle to be maintained in the first time period;

[0120] Step 405: If the number is not greater than the preset threshold, determine whether the safety officer can arrive at the vehicle to be maintained in the second time period;

[0121] If there is no safety officer arriving in the second period, then execute aforementioned step 404 to dispatch a driver to maintain the vehicle to be maintained. If there is a safety officer arriving in the second period, then execute aforementioned step 402 to hand over the safety officer to maintain the vehicle to be maintained.

[0122] Step 406: Determine the maintenance reward value for the candidate driver and the loss value of the vehicle suspension caused by performing maintenance based on the total number of vehicles to be maintained on the platform, the average driver's income from accepting orders, and the relative distance between the candidate driver and the vehicle location;

[0123] Step 407: Determine whether there is a target driver among the candidate drivers whose maintenance reward value is higher than the loss value of the suspension order;

[0124] Step 408: If the target driver does not exist, the maintenance reward value of the candidate driver is added based on the average single processing cost of the maintenance task handled by the safety officer to generate the target driver;

[0125] Step 409: If a target driver exists, the target driver's mission profit per unit distance is determined based on the maintenance reward value, the loss value of the suspended order, and the relative distance.

[0126] Step 410: issuing the maintenance task of the vehicle to be maintained to each target driver in sequence during the third period in descending order of task benefit value;

[0127] Step 411: Determine whether there is a driver to accept the maintenance task during the third period;

[0128] Step 412: If a driver accepts the maintenance task, the maintenance task will be assigned to the corresponding driver; if no driver accepts the maintenance task, the aforementioned step 402 will be executed to hand over the maintenance to the safety officer to reduce the platform's additional expenses for the driver to maintain the vehicle.

[0129] In the above process, the operational efficiency of autonomous taxis is improved by collaborating with drivers to handle less complex maintenance tasks. In this model, the platform can balance the number of safety officers employed by the platform based on historical data on drivers handling maintenance tasks, thereby reducing the platform's safety officer costs. Figure 5 The following shows the process of determining the number of safety officers to be hired based on the historical data of maintenance tasks handled by drivers. Figure 5 As shown, the following steps may be included:

[0130] Step 501: Determine a first cost range of the platform for the driver based on the driver maintenance task data of the second historical period;

[0131] In some embodiments, every second historical period (e.g., one month), the platform can obtain the driver maintenance task data of the previous month. The driver maintenance task data includes: the preset proportion range Y of maintenance tasks that the platform requires drivers to handle, and the drivers who actually handled maintenance tasks in the previous month, and the corresponding stop order reward value L i And the maintenance reward value B obtained when the task is settled i .

[0132] The preset proportion range Υ can be set based on actual needs. For example, for a specified type of maintenance task that a driver can handle, it is expected that more than 70% will be accepted by the driver. In this case, Υ∈[70%,100%].

[0133] In specific implementation, the first cost range C1 can be calculated by the following formula (3):

[0134]

[0135] Among them, M low is the average number of maintenance tasks handled by drivers who handled maintenance tasks in the second historical period; α is the platform's allocation coefficient for the loss value of suspended orders. Since drivers suspend orders to maintain their vehicles, the revenue brought to the platform during the driver's operation period will be reduced.

[0136] Step 502: Based on the range of the number of security officers required by the platform and the preset duty cost of a single security officer, determine the second cost range of the platform for security officers;

[0137] In some embodiments, the range of the number of security officers required by the platform can be determined by:

[0138] Based on the security officer's duty time T in the second historical period month , and the preset time threshold t for the safety officer to handle a single maintenance task process , determine the minimum task capacity Cap of a single safety officer = T month / t processAmong them, taking the second historical period as one month as an example, the duty time T month The daily working hours for a safety officer is 8 hours * number of working days.

[0139] Then, based on the number of maintenance tasks handled by the safety officer in the second historical period, the minimum task capacity Cap, and the aforementioned preset proportion range Y, the safety officer number range N is determined. w In specific implementation, the range of the number of safety officers N can be determined by the following formula (4): w :

[0140]

[0141] Among them, M low M is the average number of maintenance tasks handled by each driver who handled maintenance tasks in the second historical period; high is the average number of maintenance tasks handled by the security officers hired by the platform in the second historical period for vehicles of non-specified types to be maintained; where “M high +(1-Y)M low " indicates the number of maintenance tasks handled by a single platform safety officer in the second historical period, assuming that a preset ratio of Y maintenance tasks is handled by drivers.

[0142] Next, the number of safety officers can be set to N. w With the preset duty cost C0 of a single security officer, the second cost range C2 = N is determined w *C0; taking the second historical period as one month as an example, the preset duty cost C0 can be calculated based on the monthly salary of the security officer.

[0143] Step 503: Under the constraint that the first cost range and the second cost range are minimum, determine the number of safety officers required by the platform based on the range of the number of safety officers; wherein the number of safety officers is positively correlated with the first cost range and negatively correlated with the second cost range.

[0144] It should be understood that the first cost range C1 represents the additional expenses incurred by the platform for drivers to handle maintenance tasks in the second historical period, namely driver costs. The second cost range C2 represents the cost of the platform to hire safety officers in the second historical period, namely safety officer costs.

[0145] Therefore, the total cost C of the platform's operation and maintenance of driverless taxis can be expressed as C = C1 + C2. Specifically, it is shown in the following formula (5):

[0146]

[0147] The part on the left side of the plus sign in formula (5) corresponds to the calculation formula of the first cost range C1; the part on the right side of the plus sign corresponds to the calculation formula of the second cost range C2.

[0148] From formula (5), we can see that the larger the preset proportion range Y, the higher the first cost range C1, and the smaller the second cost range C2. Therefore, we can use the minimum total cost C as a constraint and traverse the expected proportion value γ' that can minimize the total cost C from the preset proportion range Y. Then substitute the expected proportion value γ' into the aforementioned solution for the range of safety personnel number N. w In formula (4), the number of safety officers required by the platform can be determined.

[0149] By incorporating real-time cost-competition between safety officers and drivers into the aforementioned process, the platform reduces its overall operating and maintenance costs for autonomous taxis. This ensures maximum utilization of both types of human resources, providing a refined operational, risk-stratified, and shared-economy scheduling system for autonomous driving operations, balancing platform costs, driver benefits, and safety responsibilities.

[0150] Based on the same inventive concept, the embodiment of the present application also provides a vehicle operation and maintenance device, specifically Figure 6 As shown, the device may include:

[0151] The data acquisition unit 601 is configured to: determine the maintenance type and vehicle location of the vehicle to be maintained in response to the operation maintenance instruction of the driverless taxi;

[0152] The candidate driver unit 602 is configured to: if the maintenance type is a specified type indicating that the driver has processing capabilities, determine a candidate driver who arrives at the vehicle location in the first time period based on the vehicle operation information of each driver in the platform;

[0153] The cost analysis unit 603 is configured to: for each candidate driver, determine the maintenance reward value for the candidate driver and the loss value of the order suspension caused by performing vehicle maintenance based on the total number of vehicles to be maintained in the platform, the average driver's order income in the current period, and the relative distance between the candidate driver and the vehicle location;

[0154] The task dispatching unit 604 is configured to: issue the maintenance task of the vehicle to be maintained to the target driver, so as to instruct the target driver to obtain a corresponding maintenance reward value after performing vehicle maintenance; wherein, the target driver is a candidate driver whose maintenance reward value is higher than the suspension loss value.

[0155] In some embodiments, the cancellation loss value of the candidate driver is determined by:

[0156] Determining a loss coefficient based on the number of orders currently placed by the platform within a target area; wherein the target area is determined based on the current location of the candidate driver;

[0157] Determining an estimated downtime for the candidate driver based on the maintenance type and the relative distance;

[0158] The loss value of order suspension for the candidate driver is determined based on the average driver's income from accepting orders, the expected order suspension duration, and the loss coefficient.

[0159] In some embodiments, the maintenance reward value of the candidate driver is determined by:

[0160] determining a fixed reward coefficient based on the total number of vehicles to be maintained and the maintenance type;

[0161] Determining a floating reward coefficient based on the growth rate of the total number of vehicles to be maintained in the first historical period;

[0162] The maintenance reward value of the candidate driver is determined based on a preset basic reward value, the fixed reward coefficient and the floating reward coefficient.

[0163] In some embodiments, before determining the candidate driver who arrives at the vehicle location in the first time period based on the vehicle operation information of each driver in the platform, the candidate driver unit 602 is further configured to:

[0164] It is determined that the total number of vehicles to be maintained is greater than a preset number threshold, and / or that the platform currently does not have a safety officer who can arrive at the vehicle location in the second time period.

[0165] In some embodiments, the candidate driver unit 602 is further configured to:

[0166] If the total number of vehicles to be maintained is not greater than the preset number threshold, or the platform has a safety officer who arrives at the vehicle location during the second time period, the maintenance task of the vehicles to be maintained will be handed over to the safety officer.

[0167] In some embodiments, to issue the maintenance task of the vehicle to be maintained to the target driver, the task dispatching unit 604 is specifically configured to:

[0168] For each target driver, respectively performing: determining a task benefit value of the target driver within a unit distance based on the maintenance reward value, the stop order loss value, and the relative distance;

[0169] issuing the maintenance tasks to the target drivers in sequence during the third period according to the order of the task benefits from high to low;

[0170] If no receipt instruction of the maintenance task is received during the third time period, the maintenance task of the vehicle to be maintained is handed over to the platform's safety officer for processing.

[0171] In some embodiments, the task dispatching unit 604 is further configured to:

[0172] If the maintenance type is not the specified type, the maintenance task of the vehicle to be maintained will be handed over to the platform's safety officer for processing; wherein, the number of safety officers in the platform is determined by the following method:

[0173] Determining a first cost range for the driver based on driver maintenance task data from the second historical period, wherein the driver maintenance task data includes: a preset range of maintenance task percentages that the platform requires drivers to handle, and maintenance reward values ​​and order cancellation reward values ​​corresponding to drivers handling maintenance tasks;

[0174] Based on the range of security officers required by the platform and the preset duty cost of each security officer, the platform determines the second cost range for security officers;

[0175] Under the constraint that the first cost range and the second cost range are minimum, the number of safety officers required by the platform is determined based on the range of the number of safety officers; wherein the number of safety officers is positively correlated with the first cost range and negatively correlated with the second cost range.

[0176] In some embodiments, the range of the number of security personnel is determined by:

[0177] Determine the minimum task capacity for a single safety officer based on the safety officer's duty time in the second historical period and a preset time threshold for the safety officer to handle a single maintenance task;

[0178] The range of the number of safety officers is determined based on the number of maintenance tasks handled by the safety officer in the second historical period, the minimum task acceptance quantity, and the preset proportion range.

[0179] Please refer to Figure 7 , is an electronic device 700 provided in an embodiment of the present application, and the electronic device 700 may be, for example, the aforementioned Figure 1 The electronic device 700 includes a processor 780 and a memory 720. In some embodiments, the electronic device 700 may include a display unit 740, which includes a display panel 741 for displaying a user interface. The memory 720 may store the aforementioned maintenance types at various task processing levels. Platform staff can use the display panel 741 to query the platform's currently unprocessed vehicles awaiting maintenance and vehicle operation information for each driver on the platform.

[0180] In some embodiments, the display panel 741 may be configured in the form of a liquid crystal display (LCD) or an organic light emitting diode (OLED).

[0181] In some embodiments, the processor 780 is configured to read a computer program and then execute the method defined by the computer program. For example, the processor 780 reads a data storage program or file, thereby running the data storage program on the electronic device 700 and displaying a corresponding interface on the display unit 740. The processor 780 may include one or more general-purpose processors and may also include one or more DSPs (Digital Signal Processors) to perform related operations to implement the technical solutions provided in the embodiments of the present application.

[0182] The memory 720 generally includes internal memory and external memory. The internal memory may be random access memory (RAM), read-only memory (ROM), and cache (CACHE), etc. The external memory may be a hard disk, an optical disk, a USB disk, a floppy disk or a tape drive, etc. The memory 720 is used to store computer programs and other data. The computer program includes the application corresponding to each vehicle-mounted terminal, etc. Other data may include data generated after the operating system or application is run, and the data includes system data (such as configuration parameters of the operating system) and user data. In the embodiment of the present application, the computer program is stored in the memory 720, and the processor 780 executes the computer program in the memory 720 to implement any of the methods discussed in the previous figure.

[0183] The aforementioned display unit 740 is used to receive input digital information, character information, or contact touch operations / contactless gestures, and generate signal inputs related to user settings and function control of the electronic device 700. Specifically, in an embodiment of the present application, the display unit 740 may include a display panel 741. The display panel 741, such as a touch screen, can collect user touch operations on or near it (such as operations performed by the user using a finger, stylus, or any other suitable object or accessory on or on the display panel 741) and drive corresponding connection devices based on a pre-set program.

[0184] In some embodiments, the display panel 741 may include a touch detection device and a touch controller. The touch detection device detects the user's touch position and the signal generated by the touch operation, and transmits the signal to the touch controller. The touch controller receives the touch information from the touch detection device, converts it into touch point coordinates, and transmits it to the processor 780. The touch controller can also receive and execute commands from the processor 780.

[0185] The display panel 741 can be implemented using various types such as resistive, capacitive, infrared, and surface acoustic wave. In addition to the display unit 740, in some embodiments, the electronic device 700 may further include an input unit 730. The input unit 730 may include an image input device 731 and other input devices 732. The other input devices may include, but are not limited to, one or more of a physical keyboard, function keys (such as volume control keys, power keys, etc.), a trackball, a mouse, and a joystick.

[0186] In addition to the above, the electronic device 700 may also include a power supply 790 for powering other modules, an audio circuit 760, a near-field communication module 770, and an RF circuit 77. The electronic device 700 may also include one or more sensors 750, such as an accelerometer, a light sensor, a pressure sensor, etc. The audio circuit 760 specifically includes a speaker 761 and a microphone 762. For example, the electronic device 700 can collect the user's voice through the microphone 762 to perform corresponding operations.

[0187] In some embodiments, the number of processors 780 may be one or more, and the processor 780 and the memory 720 may be coupled or relatively independent.

[0188] In some embodiments, Figure 7 The processor 780 in the embodiment can be used to implement the following Figure 6 The functions of the various units shown in FIG are, as an example, Figure 7 The processor 780 in can be used to implement the corresponding functions of the server or vehicle-mounted end discussed above.

[0189] For example, when the processor 780 is used as a vehicle-mounted terminal, it can monitor the vehicle's condition in real time during operation and, when it detects that the vehicle requires maintenance, send an operation and maintenance instruction to the server. When the processor 780 is used as a server, it can execute the steps of the vehicle operation and maintenance method provided in the embodiments of the present application to coordinate with the driver to operate and maintain the driverless taxi, thereby reducing the cost of hiring safety officers.

[0190] Those skilled in the art will appreciate that all or part of the steps of implementing the aforementioned method embodiments may be accomplished by a computer program. The aforementioned computer program may be stored in a computer-readable storage medium. When the computer program is executed, it executes the steps of the aforementioned method embodiments. The aforementioned storage medium includes various media that can store program codes, such as mobile storage devices, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0191] Alternatively, if the aforementioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, for example, through a computer program product, which is stored in a storage medium and includes a computer program for enabling a computer device to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0192] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A vehicle operation and maintenance method, characterized in that: include: In response to an operation maintenance instruction of the driverless taxi, determining the maintenance type and vehicle location of the vehicle to be maintained; If the maintenance type is a specified type that indicates the driver has the ability to handle it, then determining a candidate driver who arrives at the vehicle location in the first time period based on the vehicle operation information of each driver in the platform; For each candidate driver, the following steps are performed: based on the total number of vehicles to be maintained on the platform, the average driver's order income during the current period, and the relative distance between the candidate driver and the vehicle location, determine the candidate driver's maintenance reward value and the loss value of the order suspension caused by performing vehicle maintenance; The maintenance task of the vehicle to be maintained is issued to a target driver to instruct the target driver to obtain a corresponding maintenance reward value after performing vehicle maintenance; wherein the target driver is a candidate driver whose maintenance reward value is higher than the suspension loss value.

2. The method according to claim 1, characterized in that The loss value of the candidate driver's suspension order is determined by the following method: Determining a loss coefficient based on the number of orders currently placed by the platform within a target area; wherein the target area is determined based on the current location of the candidate driver; Determining an estimated downtime for the candidate driver based on the maintenance type and the relative distance; The loss value of order suspension for the candidate driver is determined based on the average driver's income from accepting orders, the expected order suspension duration, and the loss coefficient.

3. The method according to claim 1, characterized in that The maintenance reward value of the candidate driver is determined by: determining a fixed reward coefficient based on the total number of vehicles to be maintained and the maintenance type; Determining a floating reward coefficient based on the growth rate of the total number of vehicles to be maintained in the first historical period; The maintenance reward value of the candidate driver is determined based on a preset basic reward value, the fixed reward coefficient and the floating reward coefficient.

4. The method according to claim 1, wherein Before determining the candidate driver who arrives at the vehicle location in the first time period based on the vehicle operation information of each driver in the platform, the method further includes: It is determined that the total number of vehicles to be maintained is greater than a preset number threshold, and / or that the platform currently does not have a safety officer who can arrive at the vehicle location in the second time period.

5. The method according to claim 4, characterized in that The method further comprises: If the total number of vehicles to be maintained is not greater than the preset number threshold, or the platform has a safety officer who arrives at the vehicle location during the second time period, the maintenance task of the vehicles to be maintained will be handed over to the safety officer.

6. The method according to claim 1, characterized in that The issuing of the maintenance task of the vehicle to be maintained to the target driver includes: For each target driver, respectively performing: determining a task benefit value of the target driver within a unit distance based on the maintenance reward value, the stop order loss value, and the relative distance; issuing the maintenance tasks to the target drivers in sequence during the third period according to the order of the task benefits from high to low; If no receipt instruction of the maintenance task is received during the third time period, the maintenance task of the vehicle to be maintained is handed over to the platform's safety officer for processing.

7. The method according to any one of claims 1 to 6, characterized in that: The method further comprises: If the maintenance type is not the specified type, the maintenance task of the vehicle to be maintained will be handed over to the platform's safety officer for processing; wherein, the number of safety officers in the platform is determined by the following method: Determining a first cost range for the driver based on driver maintenance task data from the second historical period, wherein the driver maintenance task data includes: a preset range of maintenance task percentages that the platform requires drivers to handle, and maintenance reward values ​​and order cancellation reward values ​​corresponding to drivers handling maintenance tasks; Based on the range of security officers required by the platform and the preset duty cost of each security officer, the platform determines the second cost range for security officers; Under the constraint that the first cost range and the second cost range are minimum, the number of safety officers required by the platform is determined based on the range of the number of safety officers; wherein the number of safety officers is positively correlated with the first cost range and negatively correlated with the second cost range.

8. The method according to claim 7, characterized in that The range of the number of safety officers is determined by the following method: Determine the minimum task capacity for a single safety officer based on the safety officer's duty time in the second historical period and a preset time threshold for the safety officer to handle a single maintenance task; The range of the number of safety officers is determined based on the number of maintenance tasks handled by the safety officer in the second historical period, the minimum task acceptance quantity, and the preset proportion range.

9. A vehicle operation and maintenance device, characterized in that: include: A data acquisition unit is configured to: determine the maintenance type and vehicle location of a vehicle to be maintained in response to an operation maintenance instruction of the driverless taxi; The candidate driver unit is configured to: if the maintenance type is a specified type indicating that the driver has processing capabilities, determine a candidate driver who arrives at the vehicle location in a first time period based on vehicle operation information of each driver in the platform; The cost analysis unit is configured to: for each candidate driver, determine the maintenance reward value of the candidate driver and the loss value of the suspension of orders caused by performing vehicle maintenance based on the total number of vehicles to be maintained in the platform, the average driver's order income in the current period, and the relative distance between the candidate driver and the vehicle location; The task dispatching unit is configured to: issue the maintenance task of the vehicle to be maintained to the target driver, so as to instruct the target driver to obtain a corresponding maintenance reward value after performing the vehicle maintenance; wherein, the target driver is a candidate driver whose maintenance reward value is higher than the suspension loss value.

10. An electronic device, characterized in that: include: a memory for storing program instructions; The processor is configured to call the program instructions stored in the memory, and execute the method according to any one of claims 1 to 8 based on the obtained program instructions.

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