JP7775591B2 - Vehicle computing device, vehicle participation estimation method and estimation system - Google Patents

Description

The technology disclosed herein belongs to the technical field of vehicle computing devices, as well as vehicle participation estimation methods and estimation systems.

In recent years, vehicles have been equipped with computing devices with relatively high computing power for electronic control. However, these computing devices have not been effectively utilized when the vehicle is not in use, such as when the vehicle is parked. In response to this situation, grid computing using computing devices installed in multiple vehicles is being considered as a way to effectively utilize the computing devices installed in the vehicles.

For example, Patent Document 1 discloses a grid computing management server that uses a communication device mounted on a vehicle. This management server includes a signal receiving unit that receives a signal from the communication device indicating that it is possible to participate in grid computing, a status determining unit that determines whether the processing capacity of the processing device is insufficient, and a response transmitting unit that sends an instruction to the communication device to participate in grid computing if the processing capacity of the processing device is insufficient.

Patent document 2 also discloses a method for a vehicle rental support system that estimates periods of vehicle non-use based on the vehicle provider's schedule information, and sets the vehicle rental period based on the vehicle non-use periods.

Japanese Patent Application Laid-Open No. 2020-160661 Japanese Patent Application Laid-Open No. 2019-160209

When performing grid computing using a computing device installed in a vehicle, it is desirable to have the vehicle participate in grid computing during periods when the vehicle is not in use, particularly while the vehicle is stopped, in order to improve the stability of communications between the vehicle and a server and between vehicles. Patent Document 1 identifies periods when the vehicle is not in use based on the vehicle's usage history, and generates schedule information that specifies these periods as periods during which the vehicle's computing device can participate in grid computing. Furthermore, the method of Patent Document 2 can be used to obtain schedule information for the vehicle user and, based on that schedule, identify periods during which the vehicle's computing device can participate in grid computing.

However, even if a period of time during which the vehicle will not be used is estimated based on the vehicle's usage history and the user's schedule information, the user may suddenly use the vehicle, such as to go shopping. If the vehicle is currently performing job processing, that processing will be stopped.

The technology disclosed here was developed in light of these issues, and its purpose is to stabilize job processing in grid computing using vehicle computing devices.

In order to solve the above problem, the technology disclosed herein is configured so that a computing device of a vehicle that can participate in grid computing in which multiple vehicles act as computing nodes to perform job computation processing when the vehicle is stopped is equipped with a communication unit and a control unit, the communication unit acquires facility information of a facility where a user of the vehicle is staying and exit information indicating the time when the user exited the facility, the control unit executes a participation time estimation process to estimate a participation time, which is the remaining time during which the vehicle can participate in grid computing, based on the facility information and the exit information , and when it is difficult to complete the computation processing of a job currently being executed within the estimated participation time, the control unit transfers job data of the job being computed to other vehicles participating in the same grid computing .

In other words, when a user exits a facility, the user is more likely to use a vehicle. However, the distance from the facility to the vehicle's location varies depending on the facility. Therefore, by acquiring facility information in addition to exit information, it is possible to estimate the time it will take for the user to reach the vehicle's parking location based on the facility information and exit information, i.e., the time during which the user can participate in grid computing. If the time during which participation in grid computing can be estimated, it is possible to estimate the time during which job computation processing can be performed. This allows the computing device to estimate whether it is possible to complete the computation processing of the currently executing job within the participation time. If the computing device cannot complete the job computation processing within the participation time, it can perform processing such as handing over the computation processing to another vehicle participating in the same grid computing. As a result, job computation processing can be stabilized.

In one embodiment of the vehicle's computing device, the communication unit is capable of communicating with a key device that the user can carry and that is used to operate the vehicle, and when the control unit acquires the exit information, if it is estimated that the user is carrying the key device, it executes the participation time estimation process, but if it is estimated that the user is not carrying the key device, it does not execute the participation time estimation process.

In other words, even if a user leaves a facility, the likelihood that the user will use the vehicle for driving is quite low if they do not have the key device. Therefore, if the participation time estimation process is not executed when the user leaves the facility without the key device, the computing device will not need to allocate resources to estimating the available participation time. As a result, job calculation processing can be made more stable.

In another embodiment of the vehicle's computing device, the communication unit is capable of communicating with a mobile device owned by the user, and when the exit information is acquired, the control unit executes the participation time estimation process if it is estimated that the mobile device is approaching the vehicle, but does not execute the participation time estimation process if it is estimated that the mobile device is not moving or is moving away from the vehicle.

In other words, since the mobile device is owned by the user, the current location of the mobile device is equal to the user's current location. Furthermore, when the user moves away from the vehicle, it is highly unlikely that the user will use the vehicle for traveling. Therefore, after the user leaves the facility, if the mobile device is not moving or is moving away from the vehicle, the participation time estimation process is not executed. This eliminates the need for the computing device to allocate resources to estimating the available participation time. As a result, job calculation processing can be made more stable.

In the vehicle's calculation device, the control unit may acquire the user's schedule information via the communication unit and estimate a planned stopping time during which the user will not be driving the vehicle based on the schedule information. The control unit may also be configured to execute the participation time estimation process when the current time falls within the estimated planned stopping time, but not execute the participation time estimation process when the current time does not fall within the estimated planned stopping time.

With this configuration, the participation time is estimated only when there is a possibility that the user will unexpectedly drive the vehicle. This allows the computing device to minimize the period of time that resources are allocated to estimating the participation time. As a result, job computation processing can be made more stable.

Another aspect of the technology disclosed herein also relates to a participation estimation method for estimating, by a computer, the participation of vehicles in grid computing in which, when a plurality of vehicles are stopped, each of the plurality of vehicles serves as a computation node. This participation estimation method includes a facility information acquisition step of acquiring facility information that is information about a facility where a user of a specific vehicle among the plurality of vehicles is staying, an exit information acquisition step of acquiring exit information that indicates a time when the user exited the facility, and a participation time estimation step of estimating a remaining time during which the specific vehicle can participate in the grid computing based on the facility information and the exit information, and when it is difficult for the computer to complete the calculation processing of a currently executing job within the estimated participation time, the computer transfers job data of the currently executing job to another vehicle participating in the same grid computing .

Even with this configuration, the available time for a specific vehicle to participate in grid computing can be estimated, and the available time for the specific vehicle to execute job computation processing can be estimated. This allows the specific vehicle to estimate whether it will be able to complete the computation processing of the job currently being executed within the available participation time, and measures can be taken to ensure stable completion of job computation processing. As a result, job computation processing can be stabilized.

Another aspect of the technology disclosed herein relates to a system for estimating vehicle participation in grid computing, in which a plurality of vehicles act as computation nodes when the plurality of vehicles are stopped. The participation estimation system includes a communication unit, an estimation unit that estimates a remaining time during which a specific vehicle among the plurality of vehicles can participate in the grid computing, and a computing unit of the vehicle that constitutes the grid computing , wherein the communication unit acquires facility information of a facility where a user of the vehicle is staying and exit information that indicates a time when the user exited the facility, the estimation unit estimates a participation time that is the remaining time during which the vehicle can participate in the grid computing based on the facility information and the exit information, and a control unit of the vehicle, when it is difficult to complete computation processing of a currently executing job within the estimated participation time, transfers job data of the job being computed to another vehicle participating in the same grid computing .

Even with this configuration, the available time for a specific vehicle to participate in grid computing can be estimated, and the available time for the specific vehicle to execute job computation processing can be estimated. This allows the specific vehicle to estimate whether it will be able to complete the computation processing of the job currently being executed within the available participation time, and measures can be taken to ensure stable completion of job computation processing. As a result, job computation processing can be stabilized.

As described above, the technology disclosed herein makes it possible to estimate the time a vehicle can participate in grid computing based on information about the facility where the user is staying and information indicating the user's departure time from the facility, and to take action according to the time of participation, thereby stabilizing job calculation processing.

FIG. 1 is a schematic diagram illustrating a configuration of a system including a vehicle having a computing device according to a first exemplary embodiment. FIG. 2 is a conceptual diagram for explaining grid computing. FIG. 3 is a block diagram illustrating the configuration of a vehicle. FIG. 4 is a block diagram illustrating the configuration of a user terminal. FIG. 5 is a block diagram showing the configuration of a client server. FIG. 6 is a block diagram illustrating the configuration of the facility server. FIG. 7 is a block diagram showing the configuration of the management server. FIG. 8 is a flowchart illustrating a grid computing process performed by the system. FIG. 9 is a schematic diagram showing the destinations of information transmission and reception when a vehicle performs participation time estimation processing. FIG. 10 is a block diagram showing functional blocks for the control unit of the vehicle to perform the participation time estimation process. FIG. 11 is a flowchart illustrating the participation time estimation process performed by the control unit. FIG. 12 is a schematic diagram showing the destinations of transmission and reception of information when a vehicle performs a participation time estimation process in a computing device according to the second embodiment. FIG. 13 is a flowchart illustrating a participation time estimation process performed by the control unit in the arithmetic device according to the second embodiment. FIG. 14 is a schematic diagram showing the destinations of information transmission and reception when the management server performs the participation time estimation process.

An exemplary embodiment will be described in detail below with reference to the drawings.

(System configuration)
1 illustrates the configuration of a system 1 including a vehicle 10 having a computing device according to an embodiment. The system 1 includes a plurality of vehicles 10, a plurality of user terminals 20, a client server 30, a facility server 40, and a management server 50. These components can communicate with each other via a communication network 5. Each of the plurality of vehicles 10 is equipped with a computing unit 105.

(Grid Computing)
2, in the system 1 of the embodiment, grid computing is configured by the computing units 105 mounted on each vehicle 10. In grid computing, grid computing processing is performed in which job data is processed by an available computing unit 105 among the multiple computing units 105. In other words, the computing unit 105 corresponds to a computing resource of grid computing that performs job computation processing using each of the multiple vehicles 10 as a computation node.

When the computing power of the computing unit 105 is required in the vehicle 10, the computing unit 105 enters an operating state and the computing power of the computing unit 105 is used. For example, when the vehicle 10 is traveling, the computing power of the computing unit 105 is required to control the traveling of the vehicle 10, and the computing unit 105 enters an operating state.

On the other hand, when the computing power of the computing unit 105 is no longer needed in the vehicle 10, the computing unit 105 enters a stopped state, and the computing power of the computing unit 105 is no longer used. For example, when the vehicle 10 is stopped and the ignition is turned off or the power is turned off, the computing power of the computing unit 105 is no longer needed, and the computing unit 105 enters a stopped state.

Here, when the computing power of the computing unit 105 is not required in the vehicle 10, the computing power of the computing unit 105 can be provided for grid computing processing, thereby making effective use of the computing power of the computing unit 105. The computing unit 105 is basically used as a computing resource for grid computing when the vehicle 10 is stopped, i.e., when the computing power of the computing unit 105 is not being used for driving control.

(Vehicle configuration)
The vehicle 10 is a vehicle owned by a user. The user drives the vehicle 10. In this example, the vehicle 10 is a four-wheeled automobile. The vehicle 10 is also equipped with a battery (not shown). Power from the battery is supplied to on-board devices such as the computing unit 105. Examples of such vehicles 10 include electric vehicles and plug-in hybrid vehicles.

As shown in FIG. 3, the vehicle 10 includes an actuator 11, a sensor 12, an input unit 101, an output unit 102, a communication unit 103, a memory unit 104, and a computing unit 105. At least the communication unit 103 and the computing unit 105 are included in the computing device of the vehicle 10.

Actuators 11 include drive system actuators, steering system actuators, braking system actuators, etc. Examples of drive system actuators include the engine, transmission, and motor. Examples of braking system actuators include brakes. Examples of steering system actuators include steering.

The sensor 12 acquires various types of information used to control the vehicle 10. Examples of the sensor 12 include an exterior camera 121 (see Figure 8) that captures images outside the vehicle, an interior camera that captures images inside the vehicle, radar that detects objects outside the vehicle, a vehicle speed sensor, an acceleration sensor, a yaw rate sensor, an accelerator position sensor, a steering sensor, a key detection sensor 122 (see Figure 9), and a position sensor 124 (see Figure 9).

The input unit 101 inputs information and data. Examples of the input unit 101 include a navigation system that inputs information according to an operation when operated, a camera that inputs an image showing information, and a microphone that inputs audio showing information. The information and data input to the input unit 101 is sent to the calculator 105.

The output unit 102 outputs information and data. Examples of the output unit 102 include a display unit that outputs an image representing information, and a speaker that outputs audio representing information.

The communication unit 103 transmits and receives information and data. Information and data received by the communication unit 103 is sent to the computing unit 105. The communication unit 103 is composed of, for example, a wireless communication device.

The memory unit 104 stores information and data.

The computing unit 105 has a control unit 106 that controls each part of the vehicle 10. In this example, the control unit 106 controls the actuator 11 in accordance with various information obtained by the sensor 12.

The control unit 106 includes a processor, memory, etc. Examples of processors include a CPU (Central Processing Unit) and a GPU (Graphics Processing Unit). The memory stores programs for operating the processor, as well as information and data indicating the results of the processor's processing. The processing of the control unit 106, which will be described later, is performed by the processor using the programs and data stored in the memory.

The number of processors constituting the control unit 106 may be one or more. Furthermore, the processor constituting the control unit 106 may be either a CPU or a GPU, or both a CPU and a GPU. In this example, the control unit 106 has both a CPU and a GPU. For example, the control unit 106 is composed of one or more ECUs (Electronic Control Units).

In this example, the memory unit 104 stores vehicle information D11, vehicle status information D12, driving history information D13, calculator information D14, and driving schedule information D15.

<Vehicle Information>
The vehicle information D11 is information related to the vehicle 10. For example, the vehicle information D11 includes a vehicle ID set for the vehicle 10, a user ID set for the user who owns the vehicle 10, vehicle performance information indicating the performance of the vehicle, etc. The vehicle ID is an example of vehicle identification information that identifies the vehicle 10. The user ID is an example of user identification information that identifies the user.

<Vehicle status information>
The vehicle status information D12 indicates the status of the vehicle 10. For example, the vehicle status information D12 includes vehicle position information, vehicle communication information, vehicle power source information, vehicle battery remaining capacity information, vehicle charging information, etc. The vehicle position information indicates the position (latitude and longitude) of the vehicle 10. The vehicle position information can be acquired, for example, by a GPS (Global Positioning System). The vehicle communication information indicates the communication status of the vehicle 10. The vehicle power source information indicates the power source status of the vehicle 10. For example, the vehicle power source information indicates whether the ignition power is on or off, whether the accessory power is on or off, etc. The vehicle battery remaining capacity information indicates the remaining capacity of a battery (not shown) installed in the vehicle 10. The vehicle charging information indicates whether the vehicle 10 is being charged at a charging facility (not shown).

<Driving history information>
The driving history information D13 is information that indicates the driving history of the vehicle 10. For example, the driving history information D13 indicates the position of the vehicle 10 in association with the date and time.

<Computer unit information>
The calculator information D14 is information related to the calculator 105. For example, the calculator information D14 includes a calculator ID set in the calculator 105, a vehicle ID set in the vehicle 10 on which the calculator 105 is mounted, calculator performance information indicating the performance of the calculator 105, and the like. The calculator ID is an example of calculator identification information for identifying the calculator 105. The performance of the calculator 105 indicated in the calculator performance information includes a calculation capacity indicating the calculation capacity (specifically, the maximum calculation capacity) of the calculator 105, a ratio of the CPU to the GPU in the calculator 105, and the like. The calculation capacity of the calculator 105 is the amount of data that the calculator 105 can calculate per unit time.

<Schedule Information>
The driving schedule information D15 is information indicating a usage schedule of the computing unit 105. For example, the schedule information indicates the date and time when the computing unit 105 is used for driving control. The schedule information may also indicate the date and time when the computing unit 105 is not used for driving control. The schedule information may be input from the input unit 101 or may be input from the user terminal 20. In addition, the schedule information may indicate a driving schedule estimated based on the driving history information D13.

(Configuration of user terminal)
The user terminal 20 is a terminal device owned by a user. The user operates the user terminal 20 to use various functions. The user can also carry the user terminal 20. Examples of such user terminals 20 include smartphones, tablets, and laptop-type personal computers.

As shown in FIG. 4, the user terminal 20 includes an input unit 201, an output unit 202, a communication unit 203, a memory unit 204, and a control unit 205.

The input unit 201 inputs information and data. Examples of the input unit 201 include an operation unit that is operated to input information corresponding to the operation, a camera that inputs images showing information, and a microphone that inputs audio showing information. For example, a user can operate the operation unit to access the navigation system of the vehicle 10 and thereby register a destination. The information input to the input unit 101 is sent to the calculator 105.

The output unit 202 outputs information and data. Examples of the output unit 202 include a display unit that outputs an image representing information, and a speaker that outputs audio representing information.

The communication unit 203 sends and receives information and data. Information and data received by the communication unit 303 is sent to the control unit 205.

The memory unit 204 stores information and data.

The control unit 205 controls each unit of the user terminal 20. The control unit 205 has a processor, memory, etc. The memory stores programs for operating the processor, information and data indicating the processing results of the processor, etc.

In this example, the storage unit 204 stores terminal information D21, terminal status information D22, and schedule information D23.

<Device Information>
The terminal information D21 is information related to the user terminal 20. For example, the terminal information D21 includes a user terminal ID set in the user terminal 20, user terminal performance information indicating the performance of the user terminal 20, etc. The user terminal ID is an example of user terminal identification information that identifies the user terminal 20.

<Device status information>
The terminal status information D22 is information indicating the status of the user terminal 20. The terminal status information D22 includes user terminal position information indicating the position of the user terminal 20, user terminal communication status information indicating the communication status of the user terminal 20, and the like.

<Schedule Information>
The schedule information D23 indicates the behavior history and behavior schedule of the user who owns the user terminal 20. For example, the schedule information D23 indicates the user's location and the length of stay (or the planned length of stay) in association with each other. The schedule information D23 can be acquired by a schedule function installed in the user terminal 20. Specifically, the user inputs their own behavior history and behavior schedule into the user terminal 20 using the schedule function, thereby obtaining the schedule information D23 indicating the user's behavior history and behavior schedule. The schedule information D23 includes a schedule for driving the vehicle 10.

(Client-server configuration)
The client server 30 is owned by a client, who requests the calculation of job data. Examples of such clients include companies, research institutes, and educational institutions.

As shown in FIG. 5, the client server 30 includes an input unit 301, an output unit 302, a communication unit 303, a memory unit 304, and a control unit 305.

The input unit 301 inputs information and data. Examples of the input unit 301 include an operation unit that is operated to input information corresponding to the operation, a camera that inputs an image representing information, and a microphone that inputs audio representing information. The information and data input to the input unit 301 is sent to the control unit 305.

The output unit 302 outputs information and data. Examples of the output unit 302 include a display unit that outputs an image representing information, and a speaker that outputs audio representing information.

The communication unit 303 sends and receives information and data. Information and data received by the communication unit 303 is sent to the control unit 305.

The memory unit 304 stores information and data.

The control unit 305 controls each part of the client server 30. The control unit 305 has a processor, memory, etc. The memory stores programs for operating the processor, information and data indicating the processing results of the processor, etc.

In this example, the storage unit 304 stores client information D31 and job data D1.

<Client Information>
The client information D31 is information about the client. The client information D31 includes a client ID set for the client, a client server ID set for the client server 30 owned by the client, a person in charge's name, address, telephone number, etc. The client ID is an example of client identification information that identifies the client. The client server ID is an example of client server identification information that identifies the client server 30.

<Job Data>
The job data D1 is data corresponding to a job and is processed to execute the job.

Job data D1 can be classified by calculation type. Examples of calculation types include CPU-based calculation types and GPU-based calculation types. Job data D1 of the CPU-based calculation type tends to require complex calculations with many conditional branches, such as simulation calculations. Job data D1 of the GPU-based calculation type tends to require a huge amount of simple calculations, such as image processing and machine learning.

Job data D1 can also be classified by the job's processing conditions. Examples of processing conditions include processing conditions that require constant communication and processing conditions that do not require constant communication. Job data D1 with processing conditions that require constant communication requires that the computing resources (i.e., the computing unit 105) be able to communicate at all times in grid computing processing. Job data D1 with processing conditions that do not require constant communication does not require that the computing resources be able to communicate at all times in grid computing processing.

The storage unit 304 may also store job information related to jobs. The job information includes job name information indicating the name of the job, job content information explaining the content of the job, job data information related to the job data corresponding to the job, and job delivery date information indicating the delivery date of the job. The job data information indicates the calculation type, processing conditions, required calculation capacity, etc. of the job data.

(Configuration of facility server)
The facility server 40 is owned by a facility. Examples of facilities include a user's workplace, a stadium, a theater, a movie theater, a supermarket, a restaurant, an accommodation facility, a ticket sales facility, etc. For facilities that require a reservation for a visit, the user can make a reservation for a visit to the facility via the user terminal 20.

As shown in FIG. 6, the facility server 40 includes an input unit 401, an output unit 402, a communication unit 403, a memory unit 404, and a control unit 405. The configurations of the input unit 401, output unit 402, communication unit 403, memory unit 404, and control unit 405 of the facility server 40 are the same as the configurations of the input unit 301, output unit 302, communication unit 303, memory unit 304, and control unit 305 of the client server 30.

In this example, the storage unit 404 stores facility information D41 and facility usage information D42.

Facility Information
The facility information D41 is information related to a facility. The facility information D41 includes a facility ID set for the facility, a facility server ID set for the facility server 40 owned by the facility, facility location information indicating the location (latitude and longitude) of the facility, the name of the person in charge, the address, the telephone number, the business content of the facility, the location of the entrances and exits at the facility, and the location of the parking lot. The facility ID is an example of facility identification information that identifies the facility. The facility server ID is an example of facility server identification information that identifies the facility server 40.

<Facility Usage Information>
The facility usage information D42 indicates the usage status (usage history and planned usage) of the facility. Specifically, the facility usage information D42 indicates users who use the facility and their stay period (or planned stay period) in association with each other.

(Management Server Configuration)
The management server 50 manages the operation of the system 1, which is configured as a grid computing system. The management server 50 is owned by the operator who operates the system 1.

As shown in FIG. 7, the management server 50 includes an input unit 501, an output unit 502, a communication unit 503, a memory unit 504, and a control unit 505. The configurations of the input unit 501, output unit 502, communication unit 503, memory unit 504, and control unit 505 of the management server 50 are the same as the configurations of the input unit 301, output unit 302, communication unit 303, memory unit 304, and control unit 305 of the client server 30.

In this example, the storage unit 504 stores a user table D51, an arithmetic unit table D52, a client table D53, a job table D54, a resource table D55, a matching table D56, job data D1, and calculation result data D2.

<User table>
The user table D51 is a table for managing users. For each user, the user table D51 registers a user ID set for the user, a vehicle ID set for the vehicle 10 owned by the user, a computing unit ID set for the computing unit 105 owned by the user, a user terminal ID set for the user terminal 20 owned by the user, and the like.

<Calculator Table>
The computing unit table D52 is a table for managing the computing units 105. In the computing unit table D52, for each computing unit 105, a computing unit ID set in the computing unit 105, a user ID set for the user who owns the computing unit 105, a vehicle ID set for the vehicle 10 in which the computing unit 105 is installed, etc. are registered.

Furthermore, the computing unit table D52 registers, for each computing unit 105, the performance of that computing unit 105 (such as computing capacity and CPU/GPU ratio), the operating status of that computing unit 105 (operating history and operating schedule), and the like. In other words, the computing unit table D52 includes operating status information D5 indicating the operating status of each of the multiple computing units 105, and performance information D6 indicating the performance of each of the multiple computing units 105. The performance information D6 includes computing capacity information D7 indicating the computing capacity of each of the multiple computing units 105.

<Client Table>
The client table D53 is a table for managing clients. For each client, the client table D53 registers a client ID set for that client, a client server ID set for the client server 30 owned by the client, the name, address, telephone number, etc. of the person in charge of the client. The client table D53 records the usage history of grid computing for each client.

<Job Table>
The job table D54 is a table for managing jobs requested by clients. For each job, the job table D54 registers the reception number set for that job, the client ID set for the client that requested the job, the name and content of the job, etc. The job table D54 also registers for each job the calculation type and processing conditions of the job data corresponding to that job, the required calculation capacity that is the calculation capacity required to calculate the job data, the delivery date set for that job, etc.

<Resource Table>
The resource table D55 is a table for managing the computing capacity in grid computing processing. Specifically, the resource table D55 is a table for managing computing capacity information related to the estimated computing capacity of the computing resource. The resource table D55 registers, for each computing unit 105, the computing unit ID set for that computing unit 105.

Matching Table
The matching table D56 is a table for managing the results of a matching process that matches jobs with grid computing. For each job, the matching table D56 registers the reception number set for the job, the job data corresponding to the job, the computing unit ID set for each computing unit 105 that constitutes the computing resource allocated to the job data by the matching process, and the like.

<Job Data>
The job data D1 stored in the storage unit 504 is the accepted job data D1.

<Calculation result data>
The calculation result data D2 stored in the storage unit 504 is calculation result information calculated by grid computing processing, and indicates the results of the calculation.

(Grid computing processing)
Next, the grid computing process will be described with reference to Fig. 8. In the grid computing process, the job data D1 is processed by an available computing unit 105 among the plurality of computing units 105. After the matching process is completed, the control unit 505 performs the following process.

First, in step S11, the control unit 505 references the matching table D56 and distributes the job data D1 to be subjected to grid computing processing to the computing units 105 assigned to that job data D1 in the matching process. Specifically, the control unit 505 transmits a portion of the job data D1 to each of the computing units 105 assigned to that job data D1. As a result, the job data D1 is processed in parallel by the computing units 105 assigned to that job data D1.

Next, in step S12, when each computing unit 105 completes the calculation of the data (part of job data D1) sent to that computing unit 105, it sends the partial calculation result data obtained by that calculation to the management server 50. The control unit 505 of the management server 50 receives the partial calculation result data sent from the computing unit 105 and stores the partial calculation result data in the memory unit 504.

Next, in step S13, the control unit 505 determines whether all of the computing units 105 to which the job data D1 was distributed in step S11 have completed calculations. If all of the computing units 105 have completed calculations, the control unit 505 proceeds to step S14; if at least some of the computing units 105 have not completed calculations, the control unit 505 performs the processing of step S12.

In step S14, the control unit 505 combines the partial calculation result data stored in the storage unit 504 to generate calculation result data D2 (calculation result data D2 indicating the results of the calculation of job data D1) corresponding to job data D1 that is the target of grid computing processing. The control unit 505 then transmits the calculation result data D2 corresponding to job data D1 that is the target of grid computing processing to the client server 30 of the client that requested the calculation of job data D1.

Then, in step S15, the operator of system 1 awards a reward to the user who provided the computing power of the computing unit 105 for the grid computing process. Examples of rewards awarded to users include points that can be used in system 1, virtual currency, and product discounts. For example, the control unit 505 of the management server 50 performs processing to award a reward to the user who provided the computing power of the computing unit 105 for the grid computing process. Examples of processing to award a reward include processing to associate the "user ID" set for the user with "points" (or virtual currency) that can be used in system 1 and register them in user table D51, and processing to send information indicating product discounts to the user terminal 20 owned by the user.

Furthermore, a reward may be granted by the client to a user who provides the computing power of the computing unit 105 to a grid computing process. For example, the control unit 305 of the client server 30 may execute processing to grant a reward to a user who provides the computing power of the computing unit 105 to a grid computing process.

(Vehicle processing with grid computing)
To successfully complete the grid computing process described above, it is necessary that the computing unit 105 of the vehicle 10 is stably supplied as a computing resource, that is, that each vehicle 10 is able to stably execute the computational process of the job. The computing unit 105 can estimate the time that the vehicle 10 will be stopped (hereinafter referred to as the estimated stopping time) based on the driving schedule information D15 stored in the storage unit 104 and the schedule information D23 acquired from the user terminal 20. In other words, the computing unit 105 can schedule in advance the time period during which it can supply itself as a computing resource for grid computing (the time period during which it can participate in grid computing).

However, even during a time period that the computing unit 105 estimates as a time period during which the vehicle 10 can participate in grid computing, the user may suddenly need to drive the vehicle 10, such as to go shopping or travel to work. As a result, the computing unit 105 must use itself for driving control while it is performing the computational processing of a job assigned to it in grid computing. In this case, the computing unit 105 is forced to abort the job, which may result in the grid computing processing not being completed successfully.

Therefore, in the first embodiment, the control unit 106 of the computing unit 105 executes a participation time estimation process to estimate the remaining time during which the vehicle 10 can participate in grid computing when the user leaves the facility where the vehicle 10 is staying. More specifically, in the first embodiment, the control unit 106 executes the participation time estimation process when the user leaves the facility while the control unit 106 is executing job processing by grid computing within a previously estimated planned stopping time. This participation time _tj corresponds to the time it takes for the user to reach the vehicle 10.

In particular, in the first embodiment, the control unit 106 estimates the available participation time _tj when it detects that the user has left the facility with the key device 122a (see FIG. 10 ) for operating the vehicle 10. That is, the control unit 106 executes the participation time estimation process when it is estimated that the user has the key device 122a, but does not execute the participation time estimation process when it is estimated that the user does not have the key device 122a. In other words, even if the user has left the facility, if the user does not have the key device 122a, the user is unlikely to use the vehicle 10 for driving. Therefore, when the user has left the facility without the key device 122a, the control unit 106 does not execute the participation time estimation process, so that the control unit 106 does not need to allocate resources to estimating the available participation time. Note that "operating the vehicle 10" here includes not only turning on the ignition of the vehicle 10 but also unlocking the doors of the vehicle 10.

Next, the flow up to when the control unit 106 estimates the participation available time _tj will be described with reference to Fig. 10. Here, the vehicle 10 is participating in grid computing and is executing the calculation processing of a job.

First, when a user exits a facility, the facility server 40 transmits exit information D43 indicating the user's exit time to the management server 50. At this time, the facility server 40 also transmits facility information D41 to the management server 50. After acquiring the exit information D43, the management server 50 transmits the exit information D43 and facility information D41 to the vehicle 10 owned by the user (strictly speaking, to the control unit 106 of the vehicle 10). When the control unit 106 of the vehicle 10 acquires the facility information D41 and the exit information D43, it estimates whether the user is carrying the key device 122a. When the control unit 106 estimates that the key device 122a is moving based on the detection result of the key detection sensor 122, it estimates that the user is carrying the key device 122a. When it is estimated that the user is carrying the key device 122a, it estimates the available participation time _tj .

After estimating the participation time _tj , if the control unit 106 determines that it is difficult to complete the calculation processing of the currently executing job within the estimated participation time _tj , the control unit 106 executes a specific process to continue the calculation of the job. The specific process includes, for example, a process of packaging job data of the job being calculated (hereinafter referred to as partial job data D1a) and transferring it to other vehicles participating in the same grid computing, a process of requesting that the vehicle not be used for driving until the calculation processing of the job is completed, a process of partially restricting the functions of the vehicle while driving until the calculation processing of the job is completed, and the like.

Figure 10 shows the functional blocks that make up the functions of the computing device of each vehicle 10 that execute the participation time estimation process and the specific process. This function is installed in each vehicle 10 participating in grid computing.

The vehicle 10 has a participation time estimation module 161 that estimates a participation time _tj , which is the remaining time during which the vehicle 10 can participate in grid computing. Information from the exterior camera 121, the key detection sensor 122, and the position sensor 124 is input to the participation time estimation module 161. Schedule information D23 is input to the participation time estimation module 161 from the user terminal 20. Driving schedule information D15 is input to the participation time estimation module 161 from the storage unit 14. Facility information D41 and exit information D43 are input to the participation time estimation module 161 from the facility server 40 via the management server 50.

Multiple exterior cameras 121 are installed on the vehicle 10 so that they can capture 360-degree images around the vehicle 10.

The key detection sensor 122 communicates with a key device 122a (see Figure 10), such as a keyless key or smart key (registered trademark) owned by the user of the vehicle 10, to detect the location of the keyless key or the like. This key device 122a is a key required to operate the vehicle 10, and includes not only the keyless key or the like described above, but also devices in which an electronic key for operating the vehicle 10 is registered. For example, when an electronic key is registered to the user's mobile terminal 20, the user's mobile terminal 20 corresponds to the key device 122a.

The position sensor 124 uses the Global Positioning System (GPS) to detect the vehicle's current location.

The position detection module 162 is a module that communicates with the user terminal 20 owned by the user of the vehicle 10 and detects the position of the user terminal 20. The position detection module 162 detects the position of the user terminal 20, for example, using a GPS sensor installed in the user terminal 20.

When estimating the participation time _tj , first, the participation time estimation module 161 estimates the current stopping position of the vehicle 10 based on the detection results of the exterior camera 121 and the position sensor 124. Next, the participation time estimation module 161 estimates the distance from the location of the facility to the stopping position of the vehicle based on the facility information D41. Next, the participation time estimation module 161 estimates the travel time required for the user to travel from the location of the facility to the stopping position of the vehicle. At this time, the participation time estimation module 161 basically assumes that the user is walking and calculates the travel time by assuming the user's walking speed as the user's travel speed. Next, the participation time estimation module 161 calculates the elapsed time from the exit time by subtracting the current time from the user's exit time included in the exit information D43. Then, the participation time estimation module 161 estimates the participation time _tj by subtracting the elapsed time from the travel time. Furthermore, the participation time estimation module 161 may calculate the user's travel time by assuming the travel speed of the key device 122a to be the user's travel speed, or may calculate the travel speed of the user terminal 20 from the detection result of the position detection module 162 and assume that the travel speed of the user terminal 20 is the user's travel speed.

The possible participation time t _j estimated by the possible participation time estimation module 161 is input to the process execution management module 167 .

The control unit 106 has a calculation time estimation module 169 that estimates the job completion time, which is the time it takes for the vehicle (or more precisely, the vehicle's computing unit) to complete the job calculation. The calculation time estimation module 169 receives information from the partial job data D1a and information from the computational resource management module 166.

The computational resource management module 166 is a module that manages the current computational resources, in other words, the current computational capacity, of the computing unit of the host vehicle. Information regarding the current computational capacity of the computing unit is input from the computational resource management module 166 to the computation time estimation module 169.

The calculation time estimation module 169 estimates the job completion time when the partial job data Da1 is processed using the current calculation capacity of the calculation unit obtained from the calculation resource management module 166. The estimated job completion time is input to the processing execution management module 167.

The process execution management module 167 is a module that manages various processes in the computing unit 105. The process execution management module 167 compares the possible participation time _tj obtained from the possible participation time estimation module 161 with the job completion time obtained from the calculation time estimation module 169, and when the possible participation time _tj is equal to or greater than the job completion time, continues the calculation, and when the possible participation time _tj is less than the job completion time, performs the above-mentioned specific process. The process execution management module 167 determines the content of the specific process to be executed based on the status of other vehicles in the vicinity, information about the facility where the user is staying, etc.

The process execution management module 167 sends a control signal to the communication control module 168 depending on the content of the determined specific process. For example, when transferring partial job data D1a to another vehicle participating in the same grid computing, the process execution management module 167 sends a control signal to the communication control module 168 to transfer the partial job data D1a. Furthermore, for example, when requesting the user to delay use of the vehicle or when restricting some of the vehicle's functions while driving, the process execution management module 167 sends a control signal to the communication control module 168 to send a message to the user's user terminal 20 to that effect.

Note that the participation time estimation module 161, computational resource management module 166, processing execution management module 167, communication control module 168, and computation time estimation module 169 are examples of modules that make up the control unit 106.

As described above, by estimating the possible participation time _tj , it is possible to estimate, based on the user's current behavior, whether the job calculation processing will be completed before the user uses the vehicle for driving. As a result, when the job calculation processing is difficult to complete, the above-mentioned specific processing can be executed, thereby stabilizing the job calculation processing.

<Flowchart of participation time estimation process>
11 is a flowchart illustrating the participation time estimation process executed by the control unit 106. The control unit 106 estimates the planned stopping time in advance based on the traveling schedule information D15 and the schedule information D23 of the user terminal 20.

First, in step S21, the control unit 106 acquires facility information and exit information from the management server 50 via the communication unit 103.

Next, in step S22, the control unit 106 determines whether the current time belongs to the scheduled stopping time. If the result is YES, meaning that the current time belongs to the scheduled stopping time, the control unit 106 proceeds to step S23. On the other hand, if the result is NO, meaning that the current time does not belong to the scheduled stopping time, the control unit 106 returns.

In step S23, the control unit 106 determines whether or not job calculation processing is currently being executed. If the answer is YES, meaning that job calculation processing is currently being executed, the control unit 106 proceeds to step S24. On the other hand, if the answer is NO, meaning that job calculation processing is not currently being executed, the control unit 106 returns. Note that even if the vehicle 10 is participating in grid computing, the control unit 106 determines that job calculation processing is not currently being executed if the job assigned to it has been completed.

In step S24, the control unit 106 estimates whether the user possesses the key device 122a. If the result is YES, meaning that the user possesses the key device 122a, the control unit 106 proceeds to step S25. On the other hand, if the result is NO, meaning that the user does not possess the key device 122a, the control unit 106 returns.

In step S25, the control unit 106 estimates the current parked position of the vehicle 10. When the vehicle 10 is parked in a multi-story parking garage, not only the two-dimensional position but also the vertical position, i.e., the three-dimensional position, is estimated.

Next, in step S26, the control unit 106 identifies the location of the facility entrance/exit from the facility information D41 and estimates the distance between the facility entrance/exit and the vehicle's stopping position.

Next, in step S27, the control unit 106 estimates the user's travel time. The control unit 106 estimates the user's travel time based on the estimated distance calculated in step S26 and the user's travel speed. As mentioned above, the user's travel speed may be assumed to be walking speed, or the travel speed of the key device 122a.

Next, in step S28, the control unit 106 calculates the time that has elapsed since the user's exit time included in the exit information D43. The control unit 106 calculates the time that has elapsed since the user's exit time by subtracting the current time from the user's exit time.

Then, in step S29, the control unit 106 estimates the available participation time _tj by subtracting the elapsed time calculated in step S28 from the travel time calculated in step S27. After step S29, the control unit 106 returns.

In this way, when there is a possibility that the user will suddenly use the vehicle 10 for traveling, such as when the user leaves the facility with the key device 122a, the participation possible time _tj is estimated. Then, when the participation possible time _tj is shorter than the job completion time, the control unit 106 executes the above-mentioned specific process to complete the job calculation process. This makes it possible to stabilize the job calculation process.

Therefore, in the first embodiment, the computing device of the vehicle 10 includes a communication unit 103 and a control unit 106. The communication unit 103 acquires facility information D41 of a facility where a user of the vehicle 10 is staying and exit information D43 indicating the time when the user exited the facility. The control unit 106 executes a participation time estimation process to estimate a participation time _tj , which is the remaining time during which the vehicle 10 can participate in grid computing, based on the facility information D41 and the exit information D43. In this manner, the computing device can estimate the time during which the computing device can execute the job's computational processing by estimating the participation time _tj in grid computing. This allows the computing device of the vehicle 10 to estimate whether the computing process of the currently executing job can be completed within the participation time tj. When the computing device cannot complete the job's computational processing within the participation time _tj , the computing device can perform the specific processing described above. As a result, the job's computational processing can be stabilized.

In particular, in the first embodiment, the communication unit 103 is capable of communicating with a key device 122a that the user can carry and that can be used to operate the vehicle 10. When the control unit 106 acquires the exit information D43 and it is estimated that the user is carrying the key device 122a, it executes the participation time estimation process, but when it is estimated that the user is not carrying the key device 122a, it does not execute the participation time estimation process. As a result, when it is unlikely that the user will use the vehicle 10 for driving, the control unit 106 does not need to execute the participation time estimation process, and therefore does not need to allocate resources to estimating the possible participation time _tj . As a result, the job calculation process can be more stable.

Furthermore, in the first embodiment, the control unit 106 acquires the user's schedule information D23 via the communication unit 103, estimates a planned stop time during which the user will not be driving the vehicle 10 based on the schedule information D23, and executes the participation time estimation process when the current time falls within the estimated planned stop time, but does not execute the participation time estimation process when the current time does not fall within the estimated planned stop time. As a result, the possible participation time _tj is estimated only when there is a possibility that the user will unexpectedly drive the vehicle 10, so the control unit 106 can minimize the period during which resources are allocated to estimating the possible participation time _tj . As a result, the job calculation process can be more stable.

[Embodiment 2]
Hereinafter, the second embodiment will be described in detail with reference to the drawings. In the following description, parts common to the first embodiment will be denoted by the same reference numerals, and detailed description thereof will be omitted.

In this second embodiment, the conditions for executing the participation time estimation process differ from those in the first embodiment. Specifically, in this second embodiment, when the control unit 106 acquires exit information D43 from the management server 50 and it is estimated that the user terminal 20 is approaching the vehicle 10, it executes the participation time estimation process. However, when it is estimated that the user terminal 20 is not moving or is moving away from the vehicle 10, it does not execute the participation time estimation process. Because the user terminal 20 is owned by the user, the location of the user terminal 20 can be considered to be the user's location. Even if the user exits the facility, if the user terminal 20 is not moving or is moving away from the vehicle 10, the user is likely not to operate the vehicle 10. For this reason, if the user is not moving or is moving away from the vehicle 10 after exiting the facility, the control unit 106 does not execute the participation time estimation process, thereby eliminating the need for the control unit 106 to allocate resources to estimating the available participation time. A situation in which the user exits the facility and the user terminal 20 is not moving can be assumed to be, for example, when the user is taking a break outside the facility or waiting for someone.

12 schematically shows a flow up to when the control unit 106 estimates the participation available time _tj in the present embodiment 2. Here, the vehicle 10 is participating in grid computing and is executing the calculation processing of a job.

As shown in FIG. 12 , when a user exits a facility, facility server 40 transmits exit information D43 indicating the user's exit time to management server 50. At this time, facility server 40 also transmits facility information D41 to management server 50. After acquiring facility information D41 and exit information D43, management server 50 transmits exit information D43 and facility information D41 to vehicle 10 owned by the user (strictly speaking, to control unit 106 of vehicle 10). Upon acquiring facility information D41 and exit information D43, control unit 106 of vehicle 10 detects the position of user terminal 20 and estimates whether or not user terminal 20 is approaching vehicle 10. When it is estimated that user terminal 20 is approaching vehicle 10, control unit 106 estimates available participation time _tj .

<Flowchart of participation time estimation process>
13 is a flowchart illustrating the participation time estimation process executed by the control unit 106. The control unit 106 estimates the planned stopping time in advance based on the traveling schedule information D15 and the schedule information D23 of the user terminal 20.

First, in step S31, the control unit 106 acquires facility information and exit information from the management server 50 via the communication unit 103.

Next, in step S32, the control unit 106 determines whether the current time belongs to the scheduled stopping time. If the result is YES, meaning that the current time belongs to the scheduled stopping time, the control unit 106 proceeds to step S33. On the other hand, if the result is NO, meaning that the current time does not belong to the scheduled stopping time, the control unit 106 returns.

In step S33, the control unit 106 determines whether or not the job calculation process is currently being executed. If the result is YES, meaning that the job calculation process is currently being executed, the control unit 106 proceeds to step S34. On the other hand, if the result is NO, meaning that the job calculation process is not currently being executed, the control unit 106 returns.

In step S34, the control unit 106 estimates whether the user terminal 20 is approaching the vehicle 10. If the result is YES, meaning that the control unit 106 estimates that the user terminal 20 is approaching the vehicle 10, the control unit 106 proceeds to step S35. On the other hand, if the result is NO, meaning that the user terminal 20 is not moving or is moving away from the vehicle 10, the control unit 106 returns.

In step S35, the control unit 106 estimates the current parked position of the vehicle 10. When the vehicle 10 is parked in a multi-story parking garage, not only the two-dimensional position but also the vertical position, i.e., the three-dimensional position, is estimated.

Next, in step S36, the control unit 106 identifies the location of the facility entrance/exit from the facility information D41 and estimates the distance between the facility entrance/exit and the vehicle's stopping position.

Next, in step S37, the control unit 106 estimates the user's travel time. The control unit 106 estimates the user's travel time based on the estimated distance calculated in step S36 and the user's travel speed. The user's travel speed may be assumed to be the user's walking speed or the travel speed of the user terminal 20.

Next, in step S38, the control unit 106 calculates the time that has elapsed since the user's exit time included in the exit information D43. The control unit 106 calculates the time that has elapsed since the user's exit time by subtracting the current time from the user's exit time.

Then, in step S39, the control unit 106 estimates the participation time _tj by subtracting the elapsed time calculated in step S38 from the travel time calculated in step S37. After step S39, the control unit 106 returns.

Then, as in the first embodiment, when the participation time _tj is shorter than the job completion time, the control unit 106 executes the above-described specific process to complete the job calculation process, thereby stabilizing the job calculation process.

Therefore, even in the configuration of the second embodiment, the calculation device of the vehicle 10 can estimate whether or not the calculation processing of the currently executing job can be completed within the participation time _tj . If the calculation processing of the job cannot be completed within the participation time _tj , the calculation device of the vehicle 10 can perform the specific processing described above. As a result, the calculation processing of the job can be stabilized.

In particular, in the second embodiment, the communication unit 103 of the vehicle 10 is capable of communicating with the user terminal 20 owned by the user, and when the control unit 106 of the vehicle 10 acquires the exit information D43, it executes the participation time estimation process if it is estimated that the user terminal 20 is approaching the vehicle 10, but does not execute the participation time estimation process if it is estimated that the user terminal 20 is not moving or is moving away from the vehicle 10. As a result, when the user is unlikely to operate the vehicle 10, the control unit 106 does not need to allocate resources to estimating the available participation time _tj . As a result, the job calculation process can be made more stable.

Other Embodiments
The technology disclosed herein is not limited to the above-described embodiments, and can be substituted within the scope of the claims.

For example, in the first and second embodiments described above, the control unit 106 of the vehicle 10 estimates the available participation time _tj by estimating the parked location of the vehicle 10 and whether or not the user's portable devices, such as the key device 122a and the user terminal 20, have moved. Alternatively, the control unit 505 of the management server 50 may estimate the available participation time _tj by estimating the parked location of the vehicle 10 and whether or not the user's portable devices have moved. The control unit 505 of the management server 50 may also determine whether the job's calculation processing will be completed within the available participation time _tj . In this case, as shown in FIG. 14 , the management server 50 does not need to transmit facility information D41 and exit information D43 to the control unit 106 of the vehicle 10. Furthermore, the vehicle 10 transmits parked location information indicating the parked location of the vehicle 10 and key location information indicating the location of the key device 122a to the management server 50. In this case, the control unit 505 of the management server 50 corresponds to the estimation unit.

In the first embodiment, the control unit 106 estimates the possible participation time _tj when the user has the key device 122a. However, as in the second embodiment, the control unit 106 may execute the participation time estimation process when it is estimated that the key device 122a is approaching the vehicle 10, but may not execute the participation time estimation process when it is estimated that the key device 122a is not moving or is moving away from the vehicle 10.

Furthermore, in the first and second embodiments described above, the participation time _tj is estimated only when the calculation processing of a job is being executed. However, this is not limiting, and the participation time _tj may be estimated even if the calculation processing of a job is not being executed, as long as it is during the scheduled stop time. In this way, by transmitting information about the participation time _tj to the management server 50, the management server 50 can assign to the vehicle 10 a job that can be processed within the participation time _tj . This makes it possible to further stabilize the calculation processing of jobs in the vehicle 10.

In addition, in the above-described first and second embodiments, the control unit 106 estimated the position of the vehicle 10 from the detection results of the position sensor 124. However, this is not limited to this, and the control unit 106 may estimate the position of the vehicle 10 based on facility information D41. That is, since facility information D41 includes the location of parking lots at facilities, the vehicle 10 can estimate its own location as the location of the parking lot at the facility where the user is staying.

The above-described embodiments are merely examples and should not be interpreted as limiting the scope of the present disclosure. The scope of the present disclosure is defined by the claims, and all modifications and variations that fall within the equivalent range of the claims are within the scope of the present disclosure.

The technology disclosed here is useful when multiple vehicles are parked and job calculations are performed using grid computing, with each vehicle acting as a computing node.

10 Vehicle 103 Communication unit 106 Control unit 503 Communication unit 505 Control unit (estimation unit)
D23 Schedule information D41 Facility information D43 Exit information t _j Available participation time

Claims (6)

A computing device of a vehicle that can participate in grid computing in which each of a plurality of vehicles performs job computation processing as a computation node while the vehicle is stopped,
The Communications Department and
a control unit;
the communication unit acquires facility information of a facility where a user of the vehicle is staying and exit information indicating a time when the user exited the facility;
the control unit executes a participation time estimation process to estimate a remaining time during which the vehicle can participate in grid computing, based on the facility information and the exit information;
The control unit is also configured to transfer job data of the job being calculated to other vehicles participating in the same grid computing when it is difficult to complete the calculation processing of the job currently being executed within the estimated participation time . 2. The vehicle computing device according to claim 1,
the communication unit is capable of communicating with a key device that can be carried by the user and that operates the vehicle;
A vehicle computing device characterized in that, when the control unit obtains the exit information, it executes the participation time estimation process if it is estimated that the user is in possession of the key device, but does not execute the participation time estimation process if it is estimated that the user is not in possession of the key device. 2. The vehicle computing device according to claim 1,
the communication unit is capable of communicating with a mobile device owned by the user,
A vehicle calculation device characterized in that, when the control unit acquires the exit information, it executes the participation time estimation process if it is estimated that the mobile device is approaching the vehicle, but does not execute the participation time estimation process if it is estimated that the mobile device is not moving or is moving away from the vehicle. 2. The vehicle computing device according to claim 1 ,
the control unit acquires schedule information of the user via the communication unit, and estimates a planned stopping time during which the user will not be driving the vehicle based on the schedule information;
Furthermore, the control unit executes the participation time estimation process when the current time belongs to the estimated planned stopping time, but does not execute the participation time estimation process when the current time does not belong to the estimated planned stopping time. A participation estimation method for estimating participation of vehicles in grid computing, in which each of a plurality of vehicles serves as a calculation node when the plurality of vehicles are stopped, by a computer, the method comprising:
a facility information acquisition step of acquiring facility information that is information about a facility where a user of a specific vehicle among the plurality of vehicles is staying;
an exit information acquisition step of acquiring exit information indicating the time when the user exited the facility;
a participation time estimation step of estimating a remaining time during which the specific vehicle can participate in the grid computing based on the facility information and the exit information ,
and when it is difficult for the computer to complete the calculation processing of the job currently being executed within the estimated participation time, the computer transfers job data of the job being calculated to other vehicles participating in the same grid computing . A system for estimating participation of vehicles in grid computing, in which each of a plurality of vehicles serves as a calculation node when the plurality of vehicles are stopped, comprising:
The Communications Department and
an estimation unit that estimates a remaining time during which a specific vehicle among the plurality of vehicles can participate in the grid computing;
a computing unit of the vehicle that configures the grid computing ,
the communication unit acquires facility information of a facility where a user of the vehicle is staying and exit information indicating a time when the user exited the facility;
the estimation unit estimates a participation time, which is a remaining time during which the vehicle can participate in grid computing, based on the facility information and the exit information ;
When it is difficult to complete the calculation processing of the job currently being executed within the estimated participation time, the calculation unit transfers job data of the job being calculated to other vehicles participating in the same grid computing .